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d4f9288be4cdc6f074a13d49e7f617af269bca21a03de5e2812fefa3fe31feff | from sympy.ntheory.generate import Sieve, sieve
from sympy.ntheory.primetest import (mr, is_lucas_prp, is_square,
is_strong_lucas_prp, is_extra_strong_lucas_prp, isprime, is_euler_pseudoprime,
is_gaussian_prime)
from sympy.testing.pytest import slow
from sympy.core.numbers import I
def test_euler_pseudoprimes():
assert is_euler_pseudoprime(9, 1) == True
assert is_euler_pseudoprime(341, 2) == False
assert is_euler_pseudoprime(121, 3) == True
assert is_euler_pseudoprime(341, 4) == True
assert is_euler_pseudoprime(217, 5) == False
assert is_euler_pseudoprime(185, 6) == False
assert is_euler_pseudoprime(55, 111) == True
assert is_euler_pseudoprime(115, 114) == True
assert is_euler_pseudoprime(49, 117) == True
assert is_euler_pseudoprime(85, 84) == True
assert is_euler_pseudoprime(87, 88) == True
assert is_euler_pseudoprime(49, 128) == True
assert is_euler_pseudoprime(39, 77) == True
assert is_euler_pseudoprime(9881, 30) == True
assert is_euler_pseudoprime(8841, 29) == False
assert is_euler_pseudoprime(8421, 29) == False
assert is_euler_pseudoprime(9997, 19) == True
def test_is_extra_strong_lucas_prp():
assert is_extra_strong_lucas_prp(4) == False
assert is_extra_strong_lucas_prp(989) == True
assert is_extra_strong_lucas_prp(10877) == True
assert is_extra_strong_lucas_prp(9) == False
assert is_extra_strong_lucas_prp(16) == False
assert is_extra_strong_lucas_prp(169) == False
@slow
def test_prps():
oddcomposites = [n for n in range(1, 10**5) if
n % 2 and not isprime(n)]
# A checksum would be better.
assert sum(oddcomposites) == 2045603465
assert [n for n in oddcomposites if mr(n, [2])] == [
2047, 3277, 4033, 4681, 8321, 15841, 29341, 42799, 49141,
52633, 65281, 74665, 80581, 85489, 88357, 90751]
assert [n for n in oddcomposites if mr(n, [3])] == [
121, 703, 1891, 3281, 8401, 8911, 10585, 12403, 16531,
18721, 19345, 23521, 31621, 44287, 47197, 55969, 63139,
74593, 79003, 82513, 87913, 88573, 97567]
assert [n for n in oddcomposites if mr(n, [325])] == [
9, 25, 27, 49, 65, 81, 325, 341, 343, 697, 1141, 2059,
2149, 3097, 3537, 4033, 4681, 4941, 5833, 6517, 7987, 8911,
12403, 12913, 15043, 16021, 20017, 22261, 23221, 24649,
24929, 31841, 35371, 38503, 43213, 44173, 47197, 50041,
55909, 56033, 58969, 59089, 61337, 65441, 68823, 72641,
76793, 78409, 85879]
assert not any(mr(n, [9345883071009581737]) for n in oddcomposites)
assert [n for n in oddcomposites if is_lucas_prp(n)] == [
323, 377, 1159, 1829, 3827, 5459, 5777, 9071, 9179, 10877,
11419, 11663, 13919, 14839, 16109, 16211, 18407, 18971,
19043, 22499, 23407, 24569, 25199, 25877, 26069, 27323,
32759, 34943, 35207, 39059, 39203, 39689, 40309, 44099,
46979, 47879, 50183, 51983, 53663, 56279, 58519, 60377,
63881, 69509, 72389, 73919, 75077, 77219, 79547, 79799,
82983, 84419, 86063, 90287, 94667, 97019, 97439]
assert [n for n in oddcomposites if is_strong_lucas_prp(n)] == [
5459, 5777, 10877, 16109, 18971, 22499, 24569, 25199, 40309,
58519, 75077, 97439]
assert [n for n in oddcomposites if is_extra_strong_lucas_prp(n)
] == [
989, 3239, 5777, 10877, 27971, 29681, 30739, 31631, 39059,
72389, 73919, 75077]
def test_isprime():
s = Sieve()
s.extend(100000)
ps = set(s.primerange(2, 100001))
for n in range(100001):
# if (n in ps) != isprime(n): print n
assert (n in ps) == isprime(n)
assert isprime(179424673)
assert isprime(20678048681)
assert isprime(1968188556461)
assert isprime(2614941710599)
assert isprime(65635624165761929287)
assert isprime(1162566711635022452267983)
assert isprime(77123077103005189615466924501)
assert isprime(3991617775553178702574451996736229)
assert isprime(273952953553395851092382714516720001799)
assert isprime(int('''
531137992816767098689588206552468627329593117727031923199444138200403\
559860852242739162502265229285668889329486246501015346579337652707239\
409519978766587351943831270835393219031728127'''))
# Some Mersenne primes
assert isprime(2**61 - 1)
assert isprime(2**89 - 1)
assert isprime(2**607 - 1)
# (but not all Mersenne's are primes
assert not isprime(2**601 - 1)
# pseudoprimes
#-------------
# to some small bases
assert not isprime(2152302898747)
assert not isprime(3474749660383)
assert not isprime(341550071728321)
assert not isprime(3825123056546413051)
# passes the base set [2, 3, 7, 61, 24251]
assert not isprime(9188353522314541)
# large examples
assert not isprime(877777777777777777777777)
# conjectured psi_12 given at http://mathworld.wolfram.com/StrongPseudoprime.html
assert not isprime(318665857834031151167461)
# conjectured psi_17 given at http://mathworld.wolfram.com/StrongPseudoprime.html
assert not isprime(564132928021909221014087501701)
# Arnault's 1993 number; a factor of it is
# 400958216639499605418306452084546853005188166041132508774506\
# 204738003217070119624271622319159721973358216316508535816696\
# 9145233813917169287527980445796800452592031836601
assert not isprime(int('''
803837457453639491257079614341942108138837688287558145837488917522297\
427376533365218650233616396004545791504202360320876656996676098728404\
396540823292873879185086916685732826776177102938969773947016708230428\
687109997439976544144845341155872450633409279022275296229414984230688\
1685404326457534018329786111298960644845216191652872597534901'''))
# Arnault's 1995 number; can be factored as
# p1*(313*(p1 - 1) + 1)*(353*(p1 - 1) + 1) where p1 is
# 296744956686855105501541746429053327307719917998530433509950\
# 755312768387531717701995942385964281211880336647542183455624\
# 93168782883
assert not isprime(int('''
288714823805077121267142959713039399197760945927972270092651602419743\
230379915273311632898314463922594197780311092934965557841894944174093\
380561511397999942154241693397290542371100275104208013496673175515285\
922696291677532547504444585610194940420003990443211677661994962953925\
045269871932907037356403227370127845389912612030924484149472897688540\
6024976768122077071687938121709811322297802059565867'''))
sieve.extend(3000)
assert isprime(2819)
assert not isprime(2931)
assert not isprime(2.0)
def test_is_square():
assert [i for i in range(25) if is_square(i)] == [0, 1, 4, 9, 16]
# issue #17044
assert not is_square(60 ** 3)
assert not is_square(60 ** 5)
assert not is_square(84 ** 7)
assert not is_square(105 ** 9)
assert not is_square(120 ** 3)
def test_is_gaussianprime():
assert is_gaussian_prime(7*I)
assert is_gaussian_prime(7)
assert is_gaussian_prime(2 + 3*I)
assert not is_gaussian_prime(2 + 2*I)
|
e9cc79adb50a57bbb613254b071baa5fde066cb5e6518029059807ec2eb41056 | from sympy.concrete.summations import summation
from sympy.core.containers import Dict
from sympy.core.mul import Mul
from sympy.core.power import Pow
from sympy.core.singleton import S
from sympy.core.symbol import Symbol
from sympy.functions.combinatorial.factorials import factorial as fac
from sympy.core.evalf import bitcount
from sympy.core.numbers import Integer, Rational
from sympy.ntheory import (totient,
factorint, primefactors, divisors, nextprime,
primerange, pollard_rho, perfect_power, multiplicity, multiplicity_in_factorial,
trailing, divisor_count, primorial, pollard_pm1, divisor_sigma,
factorrat, reduced_totient)
from sympy.ntheory.factor_ import (smoothness, smoothness_p, proper_divisors,
antidivisors, antidivisor_count, core, udivisors, udivisor_sigma,
udivisor_count, proper_divisor_count, primenu, primeomega, small_trailing,
mersenne_prime_exponent, is_perfect, is_mersenne_prime, is_abundant,
is_deficient, is_amicable, dra, drm)
from sympy.testing.pytest import raises, slow
from sympy.utilities.iterables import capture
def fac_multiplicity(n, p):
"""Return the power of the prime number p in the
factorization of n!"""
if p > n:
return 0
if p > n//2:
return 1
q, m = n, 0
while q >= p:
q //= p
m += q
return m
def multiproduct(seq=(), start=1):
"""
Return the product of a sequence of factors with multiplicities,
times the value of the parameter ``start``. The input may be a
sequence of (factor, exponent) pairs or a dict of such pairs.
>>> multiproduct({3:7, 2:5}, 4) # = 3**7 * 2**5 * 4
279936
"""
if not seq:
return start
if isinstance(seq, dict):
seq = iter(seq.items())
units = start
multi = []
for base, exp in seq:
if not exp:
continue
elif exp == 1:
units *= base
else:
if exp % 2:
units *= base
multi.append((base, exp//2))
return units * multiproduct(multi)**2
def test_trailing_bitcount():
assert trailing(0) == 0
assert trailing(1) == 0
assert trailing(-1) == 0
assert trailing(2) == 1
assert trailing(7) == 0
assert trailing(-7) == 0
for i in range(100):
assert trailing(1 << i) == i
assert trailing((1 << i) * 31337) == i
assert trailing(1 << 1000001) == 1000001
assert trailing((1 << 273956)*7**37) == 273956
# issue 12709
big = small_trailing[-1]*2
assert trailing(-big) == trailing(big)
assert bitcount(-big) == bitcount(big)
def test_multiplicity():
for b in range(2, 20):
for i in range(100):
assert multiplicity(b, b**i) == i
assert multiplicity(b, (b**i) * 23) == i
assert multiplicity(b, (b**i) * 1000249) == i
# Should be fast
assert multiplicity(10, 10**10023) == 10023
# Should exit quickly
assert multiplicity(10**10, 10**10) == 1
# Should raise errors for bad input
raises(ValueError, lambda: multiplicity(1, 1))
raises(ValueError, lambda: multiplicity(1, 2))
raises(ValueError, lambda: multiplicity(1.3, 2))
raises(ValueError, lambda: multiplicity(2, 0))
raises(ValueError, lambda: multiplicity(1.3, 0))
# handles Rationals
assert multiplicity(10, Rational(30, 7)) == 1
assert multiplicity(Rational(2, 7), Rational(4, 7)) == 1
assert multiplicity(Rational(1, 7), Rational(3, 49)) == 2
assert multiplicity(Rational(2, 7), Rational(7, 2)) == -1
assert multiplicity(3, Rational(1, 9)) == -2
def test_multiplicity_in_factorial():
n = fac(1000)
for i in (2, 4, 6, 12, 30, 36, 48, 60, 72, 96):
assert multiplicity(i, n) == multiplicity_in_factorial(i, 1000)
def test_perfect_power():
raises(ValueError, lambda: perfect_power(0))
raises(ValueError, lambda: perfect_power(Rational(25, 4)))
assert perfect_power(1) is False
assert perfect_power(2) is False
assert perfect_power(3) is False
assert perfect_power(4) == (2, 2)
assert perfect_power(14) is False
assert perfect_power(25) == (5, 2)
assert perfect_power(22) is False
assert perfect_power(22, [2]) is False
assert perfect_power(137**(3*5*13)) == (137, 3*5*13)
assert perfect_power(137**(3*5*13) + 1) is False
assert perfect_power(137**(3*5*13) - 1) is False
assert perfect_power(103005006004**7) == (103005006004, 7)
assert perfect_power(103005006004**7 + 1) is False
assert perfect_power(103005006004**7 - 1) is False
assert perfect_power(103005006004**12) == (103005006004, 12)
assert perfect_power(103005006004**12 + 1) is False
assert perfect_power(103005006004**12 - 1) is False
assert perfect_power(2**10007) == (2, 10007)
assert perfect_power(2**10007 + 1) is False
assert perfect_power(2**10007 - 1) is False
assert perfect_power((9**99 + 1)**60) == (9**99 + 1, 60)
assert perfect_power((9**99 + 1)**60 + 1) is False
assert perfect_power((9**99 + 1)**60 - 1) is False
assert perfect_power((10**40000)**2, big=False) == (10**40000, 2)
assert perfect_power(10**100000) == (10, 100000)
assert perfect_power(10**100001) == (10, 100001)
assert perfect_power(13**4, [3, 5]) is False
assert perfect_power(3**4, [3, 10], factor=0) is False
assert perfect_power(3**3*5**3) == (15, 3)
assert perfect_power(2**3*5**5) is False
assert perfect_power(2*13**4) is False
assert perfect_power(2**5*3**3) is False
t = 2**24
for d in divisors(24):
m = perfect_power(t*3**d)
assert m and m[1] == d or d == 1
m = perfect_power(t*3**d, big=False)
assert m and m[1] == 2 or d == 1 or d == 3, (d, m)
@slow
def test_factorint():
assert primefactors(123456) == [2, 3, 643]
assert factorint(0) == {0: 1}
assert factorint(1) == {}
assert factorint(-1) == {-1: 1}
assert factorint(-2) == {-1: 1, 2: 1}
assert factorint(-16) == {-1: 1, 2: 4}
assert factorint(2) == {2: 1}
assert factorint(126) == {2: 1, 3: 2, 7: 1}
assert factorint(123456) == {2: 6, 3: 1, 643: 1}
assert factorint(5951757) == {3: 1, 7: 1, 29: 2, 337: 1}
assert factorint(64015937) == {7993: 1, 8009: 1}
assert factorint(2**(2**6) + 1) == {274177: 1, 67280421310721: 1}
#issue 19683
assert factorint(10**38 - 1) == {3: 2, 11: 1, 909090909090909091: 1, 1111111111111111111: 1}
#issue 17676
assert factorint(28300421052393658575) == {3: 1, 5: 2, 11: 2, 43: 1, 2063: 2, 4127: 1, 4129: 1}
assert factorint(2063**2 * 4127**1 * 4129**1) == {2063: 2, 4127: 1, 4129: 1}
assert factorint(2347**2 * 7039**1 * 7043**1) == {2347: 2, 7039: 1, 7043: 1}
assert factorint(0, multiple=True) == [0]
assert factorint(1, multiple=True) == []
assert factorint(-1, multiple=True) == [-1]
assert factorint(-2, multiple=True) == [-1, 2]
assert factorint(-16, multiple=True) == [-1, 2, 2, 2, 2]
assert factorint(2, multiple=True) == [2]
assert factorint(24, multiple=True) == [2, 2, 2, 3]
assert factorint(126, multiple=True) == [2, 3, 3, 7]
assert factorint(123456, multiple=True) == [2, 2, 2, 2, 2, 2, 3, 643]
assert factorint(5951757, multiple=True) == [3, 7, 29, 29, 337]
assert factorint(64015937, multiple=True) == [7993, 8009]
assert factorint(2**(2**6) + 1, multiple=True) == [274177, 67280421310721]
assert factorint(fac(1, evaluate=False)) == {}
assert factorint(fac(7, evaluate=False)) == {2: 4, 3: 2, 5: 1, 7: 1}
assert factorint(fac(15, evaluate=False)) == \
{2: 11, 3: 6, 5: 3, 7: 2, 11: 1, 13: 1}
assert factorint(fac(20, evaluate=False)) == \
{2: 18, 3: 8, 5: 4, 7: 2, 11: 1, 13: 1, 17: 1, 19: 1}
assert factorint(fac(23, evaluate=False)) == \
{2: 19, 3: 9, 5: 4, 7: 3, 11: 2, 13: 1, 17: 1, 19: 1, 23: 1}
assert multiproduct(factorint(fac(200))) == fac(200)
assert multiproduct(factorint(fac(200, evaluate=False))) == fac(200)
for b, e in factorint(fac(150)).items():
assert e == fac_multiplicity(150, b)
for b, e in factorint(fac(150, evaluate=False)).items():
assert e == fac_multiplicity(150, b)
assert factorint(103005006059**7) == {103005006059: 7}
assert factorint(31337**191) == {31337: 191}
assert factorint(2**1000 * 3**500 * 257**127 * 383**60) == \
{2: 1000, 3: 500, 257: 127, 383: 60}
assert len(factorint(fac(10000))) == 1229
assert len(factorint(fac(10000, evaluate=False))) == 1229
assert factorint(12932983746293756928584532764589230) == \
{2: 1, 5: 1, 73: 1, 727719592270351: 1, 63564265087747: 1, 383: 1}
assert factorint(727719592270351) == {727719592270351: 1}
assert factorint(2**64 + 1, use_trial=False) == factorint(2**64 + 1)
for n in range(60000):
assert multiproduct(factorint(n)) == n
assert pollard_rho(2**64 + 1, seed=1) == 274177
assert pollard_rho(19, seed=1) is None
assert factorint(3, limit=2) == {3: 1}
assert factorint(12345) == {3: 1, 5: 1, 823: 1}
assert factorint(
12345, limit=3) == {4115: 1, 3: 1} # the 5 is greater than the limit
assert factorint(1, limit=1) == {}
assert factorint(0, 3) == {0: 1}
assert factorint(12, limit=1) == {12: 1}
assert factorint(30, limit=2) == {2: 1, 15: 1}
assert factorint(16, limit=2) == {2: 4}
assert factorint(124, limit=3) == {2: 2, 31: 1}
assert factorint(4*31**2, limit=3) == {2: 2, 31: 2}
p1 = nextprime(2**32)
p2 = nextprime(2**16)
p3 = nextprime(p2)
assert factorint(p1*p2*p3) == {p1: 1, p2: 1, p3: 1}
assert factorint(13*17*19, limit=15) == {13: 1, 17*19: 1}
assert factorint(1951*15013*15053, limit=2000) == {225990689: 1, 1951: 1}
assert factorint(primorial(17) + 1, use_pm1=0) == \
{int(19026377261): 1, 3467: 1, 277: 1, 105229: 1}
# when prime b is closer than approx sqrt(8*p) to prime p then they are
# "close" and have a trivial factorization
a = nextprime(2**2**8) # 78 digits
b = nextprime(a + 2**2**4)
assert 'Fermat' in capture(lambda: factorint(a*b, verbose=1))
raises(ValueError, lambda: pollard_rho(4))
raises(ValueError, lambda: pollard_pm1(3))
raises(ValueError, lambda: pollard_pm1(10, B=2))
# verbose coverage
n = nextprime(2**16)*nextprime(2**17)*nextprime(1901)
assert 'with primes' in capture(lambda: factorint(n, verbose=1))
capture(lambda: factorint(nextprime(2**16)*1012, verbose=1))
n = nextprime(2**17)
capture(lambda: factorint(n**3, verbose=1)) # perfect power termination
capture(lambda: factorint(2*n, verbose=1)) # factoring complete msg
# exceed 1st
n = nextprime(2**17)
n *= nextprime(n)
assert '1000' in capture(lambda: factorint(n, limit=1000, verbose=1))
n *= nextprime(n)
assert len(factorint(n)) == 3
assert len(factorint(n, limit=p1)) == 3
n *= nextprime(2*n)
# exceed 2nd
assert '2001' in capture(lambda: factorint(n, limit=2000, verbose=1))
assert capture(
lambda: factorint(n, limit=4000, verbose=1)).count('Pollard') == 2
# non-prime pm1 result
n = nextprime(8069)
n *= nextprime(2*n)*nextprime(2*n, 2)
capture(lambda: factorint(n, verbose=1)) # non-prime pm1 result
# factor fermat composite
p1 = nextprime(2**17)
p2 = nextprime(2*p1)
assert factorint((p1*p2**2)**3) == {p1: 3, p2: 6}
# Test for non integer input
raises(ValueError, lambda: factorint(4.5))
# test dict/Dict input
sans = '2**10*3**3'
n = {4: 2, 12: 3}
assert str(factorint(n)) == sans
assert str(factorint(Dict(n))) == sans
def test_divisors_and_divisor_count():
assert divisors(-1) == [1]
assert divisors(0) == []
assert divisors(1) == [1]
assert divisors(2) == [1, 2]
assert divisors(3) == [1, 3]
assert divisors(17) == [1, 17]
assert divisors(10) == [1, 2, 5, 10]
assert divisors(100) == [1, 2, 4, 5, 10, 20, 25, 50, 100]
assert divisors(101) == [1, 101]
assert divisor_count(0) == 0
assert divisor_count(-1) == 1
assert divisor_count(1) == 1
assert divisor_count(6) == 4
assert divisor_count(12) == 6
assert divisor_count(180, 3) == divisor_count(180//3)
assert divisor_count(2*3*5, 7) == 0
def test_proper_divisors_and_proper_divisor_count():
assert proper_divisors(-1) == []
assert proper_divisors(0) == []
assert proper_divisors(1) == []
assert proper_divisors(2) == [1]
assert proper_divisors(3) == [1]
assert proper_divisors(17) == [1]
assert proper_divisors(10) == [1, 2, 5]
assert proper_divisors(100) == [1, 2, 4, 5, 10, 20, 25, 50]
assert proper_divisors(1000000007) == [1]
assert proper_divisor_count(0) == 0
assert proper_divisor_count(-1) == 0
assert proper_divisor_count(1) == 0
assert proper_divisor_count(36) == 8
assert proper_divisor_count(2*3*5) == 7
def test_udivisors_and_udivisor_count():
assert udivisors(-1) == [1]
assert udivisors(0) == []
assert udivisors(1) == [1]
assert udivisors(2) == [1, 2]
assert udivisors(3) == [1, 3]
assert udivisors(17) == [1, 17]
assert udivisors(10) == [1, 2, 5, 10]
assert udivisors(100) == [1, 4, 25, 100]
assert udivisors(101) == [1, 101]
assert udivisors(1000) == [1, 8, 125, 1000]
assert udivisor_count(0) == 0
assert udivisor_count(-1) == 1
assert udivisor_count(1) == 1
assert udivisor_count(6) == 4
assert udivisor_count(12) == 4
assert udivisor_count(180) == 8
assert udivisor_count(2*3*5*7) == 16
def test_issue_6981():
S = set(divisors(4)).union(set(divisors(Integer(2))))
assert S == {1,2,4}
def test_totient():
assert [totient(k) for k in range(1, 12)] == \
[1, 1, 2, 2, 4, 2, 6, 4, 6, 4, 10]
assert totient(5005) == 2880
assert totient(5006) == 2502
assert totient(5009) == 5008
assert totient(2**100) == 2**99
raises(ValueError, lambda: totient(30.1))
raises(ValueError, lambda: totient(20.001))
m = Symbol("m", integer=True)
assert totient(m)
assert totient(m).subs(m, 3**10) == 3**10 - 3**9
assert summation(totient(m), (m, 1, 11)) == 42
n = Symbol("n", integer=True, positive=True)
assert totient(n).is_integer
x=Symbol("x", integer=False)
raises(ValueError, lambda: totient(x))
y=Symbol("y", positive=False)
raises(ValueError, lambda: totient(y))
z=Symbol("z", positive=True, integer=True)
raises(ValueError, lambda: totient(2**(-z)))
def test_reduced_totient():
assert [reduced_totient(k) for k in range(1, 16)] == \
[1, 1, 2, 2, 4, 2, 6, 2, 6, 4, 10, 2, 12, 6, 4]
assert reduced_totient(5005) == 60
assert reduced_totient(5006) == 2502
assert reduced_totient(5009) == 5008
assert reduced_totient(2**100) == 2**98
m = Symbol("m", integer=True)
assert reduced_totient(m)
assert reduced_totient(m).subs(m, 2**3*3**10) == 3**10 - 3**9
assert summation(reduced_totient(m), (m, 1, 16)) == 68
n = Symbol("n", integer=True, positive=True)
assert reduced_totient(n).is_integer
def test_divisor_sigma():
assert [divisor_sigma(k) for k in range(1, 12)] == \
[1, 3, 4, 7, 6, 12, 8, 15, 13, 18, 12]
assert [divisor_sigma(k, 2) for k in range(1, 12)] == \
[1, 5, 10, 21, 26, 50, 50, 85, 91, 130, 122]
assert divisor_sigma(23450) == 50592
assert divisor_sigma(23450, 0) == 24
assert divisor_sigma(23450, 1) == 50592
assert divisor_sigma(23450, 2) == 730747500
assert divisor_sigma(23450, 3) == 14666785333344
a = Symbol("a", prime=True)
b = Symbol("b", prime=True)
j = Symbol("j", integer=True, positive=True)
k = Symbol("k", integer=True, positive=True)
assert divisor_sigma(a**j*b**k) == (a**(j + 1) - 1)*(b**(k + 1) - 1)/((a - 1)*(b - 1))
assert divisor_sigma(a**j*b**k, 2) == (a**(2*j + 2) - 1)*(b**(2*k + 2) - 1)/((a**2 - 1)*(b**2 - 1))
assert divisor_sigma(a**j*b**k, 0) == (j + 1)*(k + 1)
m = Symbol("m", integer=True)
k = Symbol("k", integer=True)
assert divisor_sigma(m)
assert divisor_sigma(m, k)
assert divisor_sigma(m).subs(m, 3**10) == 88573
assert divisor_sigma(m, k).subs([(m, 3**10), (k, 3)]) == 213810021790597
assert summation(divisor_sigma(m), (m, 1, 11)) == 99
def test_udivisor_sigma():
assert [udivisor_sigma(k) for k in range(1, 12)] == \
[1, 3, 4, 5, 6, 12, 8, 9, 10, 18, 12]
assert [udivisor_sigma(k, 3) for k in range(1, 12)] == \
[1, 9, 28, 65, 126, 252, 344, 513, 730, 1134, 1332]
assert udivisor_sigma(23450) == 42432
assert udivisor_sigma(23450, 0) == 16
assert udivisor_sigma(23450, 1) == 42432
assert udivisor_sigma(23450, 2) == 702685000
assert udivisor_sigma(23450, 4) == 321426961814978248
m = Symbol("m", integer=True)
k = Symbol("k", integer=True)
assert udivisor_sigma(m)
assert udivisor_sigma(m, k)
assert udivisor_sigma(m).subs(m, 4**9) == 262145
assert udivisor_sigma(m, k).subs([(m, 4**9), (k, 2)]) == 68719476737
assert summation(udivisor_sigma(m), (m, 2, 15)) == 169
def test_issue_4356():
assert factorint(1030903) == {53: 2, 367: 1}
def test_divisors():
assert divisors(28) == [1, 2, 4, 7, 14, 28]
assert [x for x in divisors(3*5*7, 1)] == [1, 3, 5, 15, 7, 21, 35, 105]
assert divisors(0) == []
def test_divisor_count():
assert divisor_count(0) == 0
assert divisor_count(6) == 4
def test_proper_divisors():
assert proper_divisors(-1) == []
assert proper_divisors(28) == [1, 2, 4, 7, 14]
assert [x for x in proper_divisors(3*5*7, True)] == [1, 3, 5, 15, 7, 21, 35]
def test_proper_divisor_count():
assert proper_divisor_count(6) == 3
assert proper_divisor_count(108) == 11
def test_antidivisors():
assert antidivisors(-1) == []
assert antidivisors(-3) == [2]
assert antidivisors(14) == [3, 4, 9]
assert antidivisors(237) == [2, 5, 6, 11, 19, 25, 43, 95, 158]
assert antidivisors(12345) == [2, 6, 7, 10, 30, 1646, 3527, 4938, 8230]
assert antidivisors(393216) == [262144]
assert sorted(x for x in antidivisors(3*5*7, 1)) == \
[2, 6, 10, 11, 14, 19, 30, 42, 70]
assert antidivisors(1) == []
def test_antidivisor_count():
assert antidivisor_count(0) == 0
assert antidivisor_count(-1) == 0
assert antidivisor_count(-4) == 1
assert antidivisor_count(20) == 3
assert antidivisor_count(25) == 5
assert antidivisor_count(38) == 7
assert antidivisor_count(180) == 6
assert antidivisor_count(2*3*5) == 3
def test_smoothness_and_smoothness_p():
assert smoothness(1) == (1, 1)
assert smoothness(2**4*3**2) == (3, 16)
assert smoothness_p(10431, m=1) == \
(1, [(3, (2, 2, 4)), (19, (1, 5, 5)), (61, (1, 31, 31))])
assert smoothness_p(10431) == \
(-1, [(3, (2, 2, 2)), (19, (1, 3, 9)), (61, (1, 5, 5))])
assert smoothness_p(10431, power=1) == \
(-1, [(3, (2, 2, 2)), (61, (1, 5, 5)), (19, (1, 3, 9))])
assert smoothness_p(21477639576571, visual=1) == \
'p**i=4410317**1 has p-1 B=1787, B-pow=1787\n' + \
'p**i=4869863**1 has p-1 B=2434931, B-pow=2434931'
def test_visual_factorint():
assert factorint(1, visual=1) == 1
forty2 = factorint(42, visual=True)
assert type(forty2) == Mul
assert str(forty2) == '2**1*3**1*7**1'
assert factorint(1, visual=True) is S.One
no = dict(evaluate=False)
assert factorint(42**2, visual=True) == Mul(Pow(2, 2, **no),
Pow(3, 2, **no),
Pow(7, 2, **no), **no)
assert -1 in factorint(-42, visual=True).args
def test_factorrat():
assert str(factorrat(S(12)/1, visual=True)) == '2**2*3**1'
assert str(factorrat(Rational(1, 1), visual=True)) == '1'
assert str(factorrat(S(25)/14, visual=True)) == '5**2/(2*7)'
assert str(factorrat(Rational(25, 14), visual=True)) == '5**2/(2*7)'
assert str(factorrat(S(-25)/14/9, visual=True)) == '-1*5**2/(2*3**2*7)'
assert factorrat(S(12)/1, multiple=True) == [2, 2, 3]
assert factorrat(Rational(1, 1), multiple=True) == []
assert factorrat(S(25)/14, multiple=True) == [Rational(1, 7), S.Half, 5, 5]
assert factorrat(Rational(25, 14), multiple=True) == [Rational(1, 7), S.Half, 5, 5]
assert factorrat(Rational(12, 1), multiple=True) == [2, 2, 3]
assert factorrat(S(-25)/14/9, multiple=True) == \
[-1, Rational(1, 7), Rational(1, 3), Rational(1, 3), S.Half, 5, 5]
def test_visual_io():
sm = smoothness_p
fi = factorint
# with smoothness_p
n = 124
d = fi(n)
m = fi(d, visual=True)
t = sm(n)
s = sm(t)
for th in [d, s, t, n, m]:
assert sm(th, visual=True) == s
assert sm(th, visual=1) == s
for th in [d, s, t, n, m]:
assert sm(th, visual=False) == t
assert [sm(th, visual=None) for th in [d, s, t, n, m]] == [s, d, s, t, t]
assert [sm(th, visual=2) for th in [d, s, t, n, m]] == [s, d, s, t, t]
# with factorint
for th in [d, m, n]:
assert fi(th, visual=True) == m
assert fi(th, visual=1) == m
for th in [d, m, n]:
assert fi(th, visual=False) == d
assert [fi(th, visual=None) for th in [d, m, n]] == [m, d, d]
assert [fi(th, visual=0) for th in [d, m, n]] == [m, d, d]
# test reevaluation
no = dict(evaluate=False)
assert sm({4: 2}, visual=False) == sm(16)
assert sm(Mul(*[Pow(k, v, **no) for k, v in {4: 2, 2: 6}.items()], **no),
visual=False) == sm(2**10)
assert fi({4: 2}, visual=False) == fi(16)
assert fi(Mul(*[Pow(k, v, **no) for k, v in {4: 2, 2: 6}.items()], **no),
visual=False) == fi(2**10)
def test_core():
assert core(35**13, 10) == 42875
assert core(210**2) == 1
assert core(7776, 3) == 36
assert core(10**27, 22) == 10**5
assert core(537824) == 14
assert core(1, 6) == 1
def test_primenu():
assert primenu(2) == 1
assert primenu(2 * 3) == 2
assert primenu(2 * 3 * 5) == 3
assert primenu(3 * 25) == primenu(3) + primenu(25)
assert [primenu(p) for p in primerange(1, 10)] == [1, 1, 1, 1]
assert primenu(fac(50)) == 15
assert primenu(2 ** 9941 - 1) == 1
n = Symbol('n', integer=True)
assert primenu(n)
assert primenu(n).subs(n, 2 ** 31 - 1) == 1
assert summation(primenu(n), (n, 2, 30)) == 43
def test_primeomega():
assert primeomega(2) == 1
assert primeomega(2 * 2) == 2
assert primeomega(2 * 2 * 3) == 3
assert primeomega(3 * 25) == primeomega(3) + primeomega(25)
assert [primeomega(p) for p in primerange(1, 10)] == [1, 1, 1, 1]
assert primeomega(fac(50)) == 108
assert primeomega(2 ** 9941 - 1) == 1
n = Symbol('n', integer=True)
assert primeomega(n)
assert primeomega(n).subs(n, 2 ** 31 - 1) == 1
assert summation(primeomega(n), (n, 2, 30)) == 59
def test_mersenne_prime_exponent():
assert mersenne_prime_exponent(1) == 2
assert mersenne_prime_exponent(4) == 7
assert mersenne_prime_exponent(10) == 89
assert mersenne_prime_exponent(25) == 21701
raises(ValueError, lambda: mersenne_prime_exponent(52))
raises(ValueError, lambda: mersenne_prime_exponent(0))
def test_is_perfect():
assert is_perfect(6) is True
assert is_perfect(15) is False
assert is_perfect(28) is True
assert is_perfect(400) is False
assert is_perfect(496) is True
assert is_perfect(8128) is True
assert is_perfect(10000) is False
def test_is_mersenne_prime():
assert is_mersenne_prime(10) is False
assert is_mersenne_prime(127) is True
assert is_mersenne_prime(511) is False
assert is_mersenne_prime(131071) is True
assert is_mersenne_prime(2147483647) is True
def test_is_abundant():
assert is_abundant(10) is False
assert is_abundant(12) is True
assert is_abundant(18) is True
assert is_abundant(21) is False
assert is_abundant(945) is True
def test_is_deficient():
assert is_deficient(10) is True
assert is_deficient(22) is True
assert is_deficient(56) is False
assert is_deficient(20) is False
assert is_deficient(36) is False
def test_is_amicable():
assert is_amicable(173, 129) is False
assert is_amicable(220, 284) is True
assert is_amicable(8756, 8756) is False
def test_dra():
assert dra(19, 12) == 8
assert dra(2718, 10) == 9
assert dra(0, 22) == 0
assert dra(23456789, 10) == 8
raises(ValueError, lambda: dra(24, -2))
raises(ValueError, lambda: dra(24.2, 5))
def test_drm():
assert drm(19, 12) == 7
assert drm(2718, 10) == 2
assert drm(0, 15) == 0
assert drm(234161, 10) == 6
raises(ValueError, lambda: drm(24, -2))
raises(ValueError, lambda: drm(11.6, 9))
|
1f2f6961164fb859bbcab19546cda86ffc37618ddb30410d1ff8640e1f78ed41 | from sympy.ntheory.ecm import ecm, Point
from sympy.testing.pytest import slow
@slow
def test_ecm():
assert ecm(3146531246531241245132451321) == {3, 100327907731, 10454157497791297}
assert ecm(46167045131415113) == {43, 2634823, 407485517}
assert ecm(631211032315670776841) == {9312934919, 67777885039}
assert ecm(398883434337287) == {99476569, 4009823}
assert ecm(64211816600515193) == {281719, 359641, 633767}
assert ecm(4269021180054189416198169786894227) == {184039, 241603, 333331, 477973, 618619, 974123}
assert ecm(4516511326451341281684513) == {3, 39869, 131743543, 95542348571}
assert ecm(4132846513818654136451) == {47, 160343, 2802377, 195692803}
assert ecm(168541512131094651323) == {79, 113, 11011069, 1714635721}
#This takes ~10secs while factorint is not able to factorize this even in ~10mins
assert ecm(7060005655815754299976961394452809, B1=100000, B2=1000000) == {6988699669998001, 1010203040506070809}
def test_Point():
from sympy.core.numbers import mod_inverse
#The curve is of the form y**2 = x**3 + a*x**2 + x
mod = 101
a = 10
a_24 = (a + 2)*mod_inverse(4, mod)
p1 = Point(10, 17, a_24, mod)
p2 = p1.double()
assert p2 == Point(68, 56, a_24, mod)
p4 = p2.double()
assert p4 == Point(22, 64, a_24, mod)
p8 = p4.double()
assert p8 == Point(71, 95, a_24, mod)
p16 = p8.double()
assert p16 == Point(5, 16, a_24, mod)
p32 = p16.double()
assert p32 == Point(33, 96, a_24, mod)
# p3 = p2 + p1
p3 = p2.add(p1, p1)
assert p3 == Point(1, 61, a_24, mod)
# p5 = p3 + p2 or p4 + p1
p5 = p3.add(p2, p1)
assert p5 == Point(49, 90, a_24, mod)
assert p5 == p4.add(p1, p3)
# p6 = 2*p3
p6 = p3.double()
assert p6 == Point(87, 43, a_24, mod)
assert p6 == p4.add(p2, p2)
# p7 = p5 + p2
p7 = p5.add(p2, p3)
assert p7 == Point(69, 23, a_24, mod)
assert p7 == p4.add(p3, p1)
assert p7 == p6.add(p1, p5)
# p9 = p5 + p4
p9 = p5.add(p4, p1)
assert p9 == Point(56, 99, a_24, mod)
assert p9 == p6.add(p3, p3)
assert p9 == p7.add(p2, p5)
assert p9 == p8.add(p1, p7)
assert p5 == p1.mont_ladder(5)
assert p9 == p1.mont_ladder(9)
assert p16 == p1.mont_ladder(16)
assert p9 == p3.mont_ladder(3)
|
f2eba3e9795ab4dc8820b3a98c96a9d7708c6660f0ac2c862a7f4b8885222d5d | from sympy.ntheory.multinomial import (binomial_coefficients, binomial_coefficients_list, multinomial_coefficients)
from sympy.ntheory.multinomial import multinomial_coefficients_iterator
def test_binomial_coefficients_list():
assert binomial_coefficients_list(0) == [1]
assert binomial_coefficients_list(1) == [1, 1]
assert binomial_coefficients_list(2) == [1, 2, 1]
assert binomial_coefficients_list(3) == [1, 3, 3, 1]
assert binomial_coefficients_list(4) == [1, 4, 6, 4, 1]
assert binomial_coefficients_list(5) == [1, 5, 10, 10, 5, 1]
assert binomial_coefficients_list(6) == [1, 6, 15, 20, 15, 6, 1]
def test_binomial_coefficients():
for n in range(15):
c = binomial_coefficients(n)
l = [c[k] for k in sorted(c)]
assert l == binomial_coefficients_list(n)
def test_multinomial_coefficients():
assert multinomial_coefficients(1, 1) == {(1,): 1}
assert multinomial_coefficients(1, 2) == {(2,): 1}
assert multinomial_coefficients(1, 3) == {(3,): 1}
assert multinomial_coefficients(2, 0) == {(0, 0): 1}
assert multinomial_coefficients(2, 1) == {(0, 1): 1, (1, 0): 1}
assert multinomial_coefficients(2, 2) == {(2, 0): 1, (0, 2): 1, (1, 1): 2}
assert multinomial_coefficients(2, 3) == {(3, 0): 1, (1, 2): 3, (0, 3): 1,
(2, 1): 3}
assert multinomial_coefficients(3, 1) == {(1, 0, 0): 1, (0, 1, 0): 1,
(0, 0, 1): 1}
assert multinomial_coefficients(3, 2) == {(0, 1, 1): 2, (0, 0, 2): 1,
(1, 1, 0): 2, (0, 2, 0): 1, (1, 0, 1): 2, (2, 0, 0): 1}
mc = multinomial_coefficients(3, 3)
assert mc == {(2, 1, 0): 3, (0, 3, 0): 1,
(1, 0, 2): 3, (0, 2, 1): 3, (0, 1, 2): 3, (3, 0, 0): 1,
(2, 0, 1): 3, (1, 2, 0): 3, (1, 1, 1): 6, (0, 0, 3): 1}
assert dict(multinomial_coefficients_iterator(2, 0)) == {(0, 0): 1}
assert dict(
multinomial_coefficients_iterator(2, 1)) == {(0, 1): 1, (1, 0): 1}
assert dict(multinomial_coefficients_iterator(2, 2)) == \
{(2, 0): 1, (0, 2): 1, (1, 1): 2}
assert dict(multinomial_coefficients_iterator(3, 3)) == mc
it = multinomial_coefficients_iterator(7, 2)
assert [next(it) for i in range(4)] == \
[((2, 0, 0, 0, 0, 0, 0), 1), ((1, 1, 0, 0, 0, 0, 0), 2),
((0, 2, 0, 0, 0, 0, 0), 1), ((1, 0, 1, 0, 0, 0, 0), 2)]
|
985def6528c4196ae7726a92469c5dbd10d0b9f3e5738a328b7ab15fcb8b8025 | from collections import defaultdict
from sympy.core.containers import Tuple
from sympy.core.singleton import S
from sympy.core.symbol import (Dummy, Symbol)
from sympy.ntheory import n_order, is_primitive_root, is_quad_residue, \
legendre_symbol, jacobi_symbol, totient, primerange, sqrt_mod, \
primitive_root, quadratic_residues, is_nthpow_residue, nthroot_mod, \
sqrt_mod_iter, mobius, discrete_log, quadratic_congruence, \
polynomial_congruence
from sympy.ntheory.residue_ntheory import _primitive_root_prime_iter, \
_discrete_log_trial_mul, _discrete_log_shanks_steps, \
_discrete_log_pollard_rho, _discrete_log_pohlig_hellman
from sympy.polys.domains import ZZ
from sympy.testing.pytest import raises
def test_residue():
assert n_order(2, 13) == 12
assert [n_order(a, 7) for a in range(1, 7)] == \
[1, 3, 6, 3, 6, 2]
assert n_order(5, 17) == 16
assert n_order(17, 11) == n_order(6, 11)
assert n_order(101, 119) == 6
assert n_order(11, (10**50 + 151)**2) == 10000000000000000000000000000000000000000000000030100000000000000000000000000000000000000000000022650
raises(ValueError, lambda: n_order(6, 9))
assert is_primitive_root(2, 7) is False
assert is_primitive_root(3, 8) is False
assert is_primitive_root(11, 14) is False
assert is_primitive_root(12, 17) == is_primitive_root(29, 17)
raises(ValueError, lambda: is_primitive_root(3, 6))
for p in primerange(3, 100):
it = _primitive_root_prime_iter(p)
assert len(list(it)) == totient(totient(p))
assert primitive_root(97) == 5
assert primitive_root(97**2) == 5
assert primitive_root(40487) == 5
# note that primitive_root(40487) + 40487 = 40492 is a primitive root
# of 40487**2, but it is not the smallest
assert primitive_root(40487**2) == 10
assert primitive_root(82) == 7
p = 10**50 + 151
assert primitive_root(p) == 11
assert primitive_root(2*p) == 11
assert primitive_root(p**2) == 11
raises(ValueError, lambda: primitive_root(-3))
assert is_quad_residue(3, 7) is False
assert is_quad_residue(10, 13) is True
assert is_quad_residue(12364, 139) == is_quad_residue(12364 % 139, 139)
assert is_quad_residue(207, 251) is True
assert is_quad_residue(0, 1) is True
assert is_quad_residue(1, 1) is True
assert is_quad_residue(0, 2) == is_quad_residue(1, 2) is True
assert is_quad_residue(1, 4) is True
assert is_quad_residue(2, 27) is False
assert is_quad_residue(13122380800, 13604889600) is True
assert [j for j in range(14) if is_quad_residue(j, 14)] == \
[0, 1, 2, 4, 7, 8, 9, 11]
raises(ValueError, lambda: is_quad_residue(1.1, 2))
raises(ValueError, lambda: is_quad_residue(2, 0))
assert quadratic_residues(S.One) == [0]
assert quadratic_residues(1) == [0]
assert quadratic_residues(12) == [0, 1, 4, 9]
assert quadratic_residues(12) == [0, 1, 4, 9]
assert quadratic_residues(13) == [0, 1, 3, 4, 9, 10, 12]
assert [len(quadratic_residues(i)) for i in range(1, 20)] == \
[1, 2, 2, 2, 3, 4, 4, 3, 4, 6, 6, 4, 7, 8, 6, 4, 9, 8, 10]
assert list(sqrt_mod_iter(6, 2)) == [0]
assert sqrt_mod(3, 13) == 4
assert sqrt_mod(3, -13) == 4
assert sqrt_mod(6, 23) == 11
assert sqrt_mod(345, 690) == 345
assert sqrt_mod(67, 101) == None
assert sqrt_mod(1020, 104729) == None
for p in range(3, 100):
d = defaultdict(list)
for i in range(p):
d[pow(i, 2, p)].append(i)
for i in range(1, p):
it = sqrt_mod_iter(i, p)
v = sqrt_mod(i, p, True)
if v:
v = sorted(v)
assert d[i] == v
else:
assert not d[i]
assert sqrt_mod(9, 27, True) == [3, 6, 12, 15, 21, 24]
assert sqrt_mod(9, 81, True) == [3, 24, 30, 51, 57, 78]
assert sqrt_mod(9, 3**5, True) == [3, 78, 84, 159, 165, 240]
assert sqrt_mod(81, 3**4, True) == [0, 9, 18, 27, 36, 45, 54, 63, 72]
assert sqrt_mod(81, 3**5, True) == [9, 18, 36, 45, 63, 72, 90, 99, 117,\
126, 144, 153, 171, 180, 198, 207, 225, 234]
assert sqrt_mod(81, 3**6, True) == [9, 72, 90, 153, 171, 234, 252, 315,\
333, 396, 414, 477, 495, 558, 576, 639, 657, 720]
assert sqrt_mod(81, 3**7, True) == [9, 234, 252, 477, 495, 720, 738, 963,\
981, 1206, 1224, 1449, 1467, 1692, 1710, 1935, 1953, 2178]
for a, p in [(26214400, 32768000000), (26214400, 16384000000),
(262144, 1048576), (87169610025, 163443018796875),
(22315420166400, 167365651248000000)]:
assert pow(sqrt_mod(a, p), 2, p) == a
n = 70
a, p = 5**2*3**n*2**n, 5**6*3**(n+1)*2**(n+2)
it = sqrt_mod_iter(a, p)
for i in range(10):
assert pow(next(it), 2, p) == a
a, p = 5**2*3**n*2**n, 5**6*3**(n+1)*2**(n+3)
it = sqrt_mod_iter(a, p)
for i in range(2):
assert pow(next(it), 2, p) == a
n = 100
a, p = 5**2*3**n*2**n, 5**6*3**(n+1)*2**(n+1)
it = sqrt_mod_iter(a, p)
for i in range(2):
assert pow(next(it), 2, p) == a
assert type(next(sqrt_mod_iter(9, 27))) is int
assert type(next(sqrt_mod_iter(9, 27, ZZ))) is type(ZZ(1))
assert type(next(sqrt_mod_iter(1, 7, ZZ))) is type(ZZ(1))
assert is_nthpow_residue(2, 1, 5)
#issue 10816
assert is_nthpow_residue(1, 0, 1) is False
assert is_nthpow_residue(1, 0, 2) is True
assert is_nthpow_residue(3, 0, 2) is True
assert is_nthpow_residue(0, 1, 8) is True
assert is_nthpow_residue(2, 3, 2) is True
assert is_nthpow_residue(2, 3, 9) is False
assert is_nthpow_residue(3, 5, 30) is True
assert is_nthpow_residue(21, 11, 20) is True
assert is_nthpow_residue(7, 10, 20) is False
assert is_nthpow_residue(5, 10, 20) is True
assert is_nthpow_residue(3, 10, 48) is False
assert is_nthpow_residue(1, 10, 40) is True
assert is_nthpow_residue(3, 10, 24) is False
assert is_nthpow_residue(1, 10, 24) is True
assert is_nthpow_residue(3, 10, 24) is False
assert is_nthpow_residue(2, 10, 48) is False
assert is_nthpow_residue(81, 3, 972) is False
assert is_nthpow_residue(243, 5, 5103) is True
assert is_nthpow_residue(243, 3, 1240029) is False
assert is_nthpow_residue(36010, 8, 87382) is True
assert is_nthpow_residue(28552, 6, 2218) is True
assert is_nthpow_residue(92712, 9, 50026) is True
x = {pow(i, 56, 1024) for i in range(1024)}
assert {a for a in range(1024) if is_nthpow_residue(a, 56, 1024)} == x
x = { pow(i, 256, 2048) for i in range(2048)}
assert {a for a in range(2048) if is_nthpow_residue(a, 256, 2048)} == x
x = { pow(i, 11, 324000) for i in range(1000)}
assert [ is_nthpow_residue(a, 11, 324000) for a in x]
x = { pow(i, 17, 22217575536) for i in range(1000)}
assert [ is_nthpow_residue(a, 17, 22217575536) for a in x]
assert is_nthpow_residue(676, 3, 5364)
assert is_nthpow_residue(9, 12, 36)
assert is_nthpow_residue(32, 10, 41)
assert is_nthpow_residue(4, 2, 64)
assert is_nthpow_residue(31, 4, 41)
assert not is_nthpow_residue(2, 2, 5)
assert is_nthpow_residue(8547, 12, 10007)
assert is_nthpow_residue(Dummy(even=True) + 3, 3, 2) == True
assert nthroot_mod(Dummy(odd=True), 3, 2) == 1
assert nthroot_mod(29, 31, 74) == [45]
assert nthroot_mod(1801, 11, 2663) == 44
for a, q, p in [(51922, 2, 203017), (43, 3, 109), (1801, 11, 2663),
(26118163, 1303, 33333347), (1499, 7, 2663), (595, 6, 2663),
(1714, 12, 2663), (28477, 9, 33343)]:
r = nthroot_mod(a, q, p)
assert pow(r, q, p) == a
assert nthroot_mod(11, 3, 109) is None
assert nthroot_mod(16, 5, 36, True) == [4, 22]
assert nthroot_mod(9, 16, 36, True) == [3, 9, 15, 21, 27, 33]
assert nthroot_mod(4, 3, 3249000) == []
assert nthroot_mod(36010, 8, 87382, True) == [40208, 47174]
assert nthroot_mod(0, 12, 37, True) == [0]
assert nthroot_mod(0, 7, 100, True) == [0, 10, 20, 30, 40, 50, 60, 70, 80, 90]
assert nthroot_mod(4, 4, 27, True) == [5, 22]
assert nthroot_mod(4, 4, 121, True) == [19, 102]
assert nthroot_mod(2, 3, 7, True) == []
for p in range(5, 100):
qv = range(3, p, 4)
for q in qv:
d = defaultdict(list)
for i in range(p):
d[pow(i, q, p)].append(i)
for a in range(1, p - 1):
res = nthroot_mod(a, q, p, True)
if d[a]:
assert d[a] == res
else:
assert res == []
assert legendre_symbol(5, 11) == 1
assert legendre_symbol(25, 41) == 1
assert legendre_symbol(67, 101) == -1
assert legendre_symbol(0, 13) == 0
assert legendre_symbol(9, 3) == 0
raises(ValueError, lambda: legendre_symbol(2, 4))
assert jacobi_symbol(25, 41) == 1
assert jacobi_symbol(-23, 83) == -1
assert jacobi_symbol(3, 9) == 0
assert jacobi_symbol(42, 97) == -1
assert jacobi_symbol(3, 5) == -1
assert jacobi_symbol(7, 9) == 1
assert jacobi_symbol(0, 3) == 0
assert jacobi_symbol(0, 1) == 1
assert jacobi_symbol(2, 1) == 1
assert jacobi_symbol(1, 3) == 1
raises(ValueError, lambda: jacobi_symbol(3, 8))
assert mobius(13*7) == 1
assert mobius(1) == 1
assert mobius(13*7*5) == -1
assert mobius(13**2) == 0
raises(ValueError, lambda: mobius(-3))
p = Symbol('p', integer=True, positive=True, prime=True)
x = Symbol('x', positive=True)
i = Symbol('i', integer=True)
assert mobius(p) == -1
raises(TypeError, lambda: mobius(x))
raises(ValueError, lambda: mobius(i))
assert _discrete_log_trial_mul(587, 2**7, 2) == 7
assert _discrete_log_trial_mul(941, 7**18, 7) == 18
assert _discrete_log_trial_mul(389, 3**81, 3) == 81
assert _discrete_log_trial_mul(191, 19**123, 19) == 123
assert _discrete_log_shanks_steps(442879, 7**2, 7) == 2
assert _discrete_log_shanks_steps(874323, 5**19, 5) == 19
assert _discrete_log_shanks_steps(6876342, 7**71, 7) == 71
assert _discrete_log_shanks_steps(2456747, 3**321, 3) == 321
assert _discrete_log_pollard_rho(6013199, 2**6, 2, rseed=0) == 6
assert _discrete_log_pollard_rho(6138719, 2**19, 2, rseed=0) == 19
assert _discrete_log_pollard_rho(36721943, 2**40, 2, rseed=0) == 40
assert _discrete_log_pollard_rho(24567899, 3**333, 3, rseed=0) == 333
raises(ValueError, lambda: _discrete_log_pollard_rho(11, 7, 31, rseed=0))
raises(ValueError, lambda: _discrete_log_pollard_rho(227, 3**7, 5, rseed=0))
assert _discrete_log_pohlig_hellman(98376431, 11**9, 11) == 9
assert _discrete_log_pohlig_hellman(78723213, 11**31, 11) == 31
assert _discrete_log_pohlig_hellman(32942478, 11**98, 11) == 98
assert _discrete_log_pohlig_hellman(14789363, 11**444, 11) == 444
assert discrete_log(587, 2**9, 2) == 9
assert discrete_log(2456747, 3**51, 3) == 51
assert discrete_log(32942478, 11**127, 11) == 127
assert discrete_log(432751500361, 7**324, 7) == 324
args = 5779, 3528, 6215
assert discrete_log(*args) == 687
assert discrete_log(*Tuple(*args)) == 687
assert quadratic_congruence(400, 85, 125, 1600) == [295, 615, 935, 1255, 1575]
assert quadratic_congruence(3, 6, 5, 25) == [3, 20]
assert quadratic_congruence(120, 80, 175, 500) == []
assert quadratic_congruence(15, 14, 7, 2) == [1]
assert quadratic_congruence(8, 15, 7, 29) == [10, 28]
assert quadratic_congruence(160, 200, 300, 461) == [144, 431]
assert quadratic_congruence(100000, 123456, 7415263, 48112959837082048697) == [30417843635344493501, 36001135160550533083]
assert quadratic_congruence(65, 121, 72, 277) == [249, 252]
assert quadratic_congruence(5, 10, 14, 2) == [0]
assert quadratic_congruence(10, 17, 19, 2) == [1]
assert quadratic_congruence(10, 14, 20, 2) == [0, 1]
assert polynomial_congruence(6*x**5 + 10*x**4 + 5*x**3 + x**2 + x + 1,
972000) == [220999, 242999, 463999, 485999, 706999, 728999, 949999, 971999]
assert polynomial_congruence(x**3 - 10*x**2 + 12*x - 82, 33075) == [30287]
assert polynomial_congruence(x**2 + x + 47, 2401) == [785, 1615]
assert polynomial_congruence(10*x**2 + 14*x + 20, 2) == [0, 1]
assert polynomial_congruence(x**3 + 3, 16) == [5]
assert polynomial_congruence(65*x**2 + 121*x + 72, 277) == [249, 252]
assert polynomial_congruence(x**4 - 4, 27) == [5, 22]
assert polynomial_congruence(35*x**3 - 6*x**2 - 567*x + 2308, 148225) == [86957,
111157, 122531, 146731]
assert polynomial_congruence(x**16 - 9, 36) == [3, 9, 15, 21, 27, 33]
assert polynomial_congruence(x**6 - 2*x**5 - 35, 6125) == [3257]
raises(ValueError, lambda: polynomial_congruence(x**x, 6125))
raises(ValueError, lambda: polynomial_congruence(x**i, 6125))
raises(ValueError, lambda: polynomial_congruence(0.1*x**2 + 6, 100))
|
00b2b32c07023c8313af7242e91247b8e61deb3d1a155685e7e7b8f3589c61ef | from sympy.core.numbers import (I, Rational, nan, zoo)
from sympy.core.singleton import S
from sympy.core.symbol import Symbol
from sympy.ntheory.generate import (sieve, Sieve)
from sympy.series.limits import limit
from sympy.ntheory import isprime, totient, mobius, randprime, nextprime, prevprime, \
primerange, primepi, prime, primorial, composite, compositepi, reduced_totient
from sympy.ntheory.generate import cycle_length
from sympy.ntheory.primetest import mr
from sympy.testing.pytest import raises
def test_prime():
assert prime(1) == 2
assert prime(2) == 3
assert prime(5) == 11
assert prime(11) == 31
assert prime(57) == 269
assert prime(296) == 1949
assert prime(559) == 4051
assert prime(3000) == 27449
assert prime(4096) == 38873
assert prime(9096) == 94321
assert prime(25023) == 287341
assert prime(10000000) == 179424673 # issue #20951
assert prime(99999999) == 2038074739
raises(ValueError, lambda: prime(0))
sieve.extend(3000)
assert prime(401) == 2749
raises(ValueError, lambda: prime(-1))
def test_primepi():
assert primepi(-1) == 0
assert primepi(1) == 0
assert primepi(2) == 1
assert primepi(Rational(7, 2)) == 2
assert primepi(3.5) == 2
assert primepi(5) == 3
assert primepi(11) == 5
assert primepi(57) == 16
assert primepi(296) == 62
assert primepi(559) == 102
assert primepi(3000) == 430
assert primepi(4096) == 564
assert primepi(9096) == 1128
assert primepi(25023) == 2763
assert primepi(10**8) == 5761455
assert primepi(253425253) == 13856396
assert primepi(8769575643) == 401464322
sieve.extend(3000)
assert primepi(2000) == 303
n = Symbol('n')
assert primepi(n).subs(n, 2) == 1
r = Symbol('r', real=True)
assert primepi(r).subs(r, 2) == 1
assert primepi(S.Infinity) is S.Infinity
assert primepi(S.NegativeInfinity) == 0
assert limit(primepi(n), n, 100) == 25
raises(ValueError, lambda: primepi(I))
raises(ValueError, lambda: primepi(1 + I))
raises(ValueError, lambda: primepi(zoo))
raises(ValueError, lambda: primepi(nan))
def test_composite():
from sympy.ntheory.generate import sieve
sieve._reset()
assert composite(1) == 4
assert composite(2) == 6
assert composite(5) == 10
assert composite(11) == 20
assert composite(41) == 58
assert composite(57) == 80
assert composite(296) == 370
assert composite(559) == 684
assert composite(3000) == 3488
assert composite(4096) == 4736
assert composite(9096) == 10368
assert composite(25023) == 28088
sieve.extend(3000)
assert composite(1957) == 2300
assert composite(2568) == 2998
raises(ValueError, lambda: composite(0))
def test_compositepi():
assert compositepi(1) == 0
assert compositepi(2) == 0
assert compositepi(5) == 1
assert compositepi(11) == 5
assert compositepi(57) == 40
assert compositepi(296) == 233
assert compositepi(559) == 456
assert compositepi(3000) == 2569
assert compositepi(4096) == 3531
assert compositepi(9096) == 7967
assert compositepi(25023) == 22259
assert compositepi(10**8) == 94238544
assert compositepi(253425253) == 239568856
assert compositepi(8769575643) == 8368111320
sieve.extend(3000)
assert compositepi(2321) == 1976
def test_generate():
from sympy.ntheory.generate import sieve
sieve._reset()
assert nextprime(-4) == 2
assert nextprime(2) == 3
assert nextprime(5) == 7
assert nextprime(12) == 13
assert prevprime(3) == 2
assert prevprime(7) == 5
assert prevprime(13) == 11
assert prevprime(19) == 17
assert prevprime(20) == 19
sieve.extend_to_no(9)
assert sieve._list[-1] == 23
assert sieve._list[-1] < 31
assert 31 in sieve
assert nextprime(90) == 97
assert nextprime(10**40) == (10**40 + 121)
assert prevprime(97) == 89
assert prevprime(10**40) == (10**40 - 17)
assert list(sieve.primerange(10, 1)) == []
assert list(sieve.primerange(5, 9)) == [5, 7]
sieve._reset(prime=True)
assert list(sieve.primerange(2, 13)) == [2, 3, 5, 7, 11]
assert list(sieve.primerange(13)) == [2, 3, 5, 7, 11]
assert list(sieve.primerange(8)) == [2, 3, 5, 7]
assert list(sieve.primerange(-2)) == []
assert list(sieve.primerange(29)) == [2, 3, 5, 7, 11, 13, 17, 19, 23]
assert list(sieve.primerange(34)) == [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31]
assert list(sieve.totientrange(5, 15)) == [4, 2, 6, 4, 6, 4, 10, 4, 12, 6]
sieve._reset(totient=True)
assert list(sieve.totientrange(3, 13)) == [2, 2, 4, 2, 6, 4, 6, 4, 10, 4]
assert list(sieve.totientrange(900, 1000)) == [totient(x) for x in range(900, 1000)]
assert list(sieve.totientrange(0, 1)) == []
assert list(sieve.totientrange(1, 2)) == [1]
assert list(sieve.mobiusrange(5, 15)) == [-1, 1, -1, 0, 0, 1, -1, 0, -1, 1]
sieve._reset(mobius=True)
assert list(sieve.mobiusrange(3, 13)) == [-1, 0, -1, 1, -1, 0, 0, 1, -1, 0]
assert list(sieve.mobiusrange(1050, 1100)) == [mobius(x) for x in range(1050, 1100)]
assert list(sieve.mobiusrange(0, 1)) == []
assert list(sieve.mobiusrange(1, 2)) == [1]
assert list(primerange(10, 1)) == []
assert list(primerange(2, 7)) == [2, 3, 5]
assert list(primerange(2, 10)) == [2, 3, 5, 7]
assert list(primerange(1050, 1100)) == [1051, 1061,
1063, 1069, 1087, 1091, 1093, 1097]
s = Sieve()
for i in range(30, 2350, 376):
for j in range(2, 5096, 1139):
A = list(s.primerange(i, i + j))
B = list(primerange(i, i + j))
assert A == B
s = Sieve()
assert s[10] == 29
assert nextprime(2, 2) == 5
raises(ValueError, lambda: totient(0))
raises(ValueError, lambda: reduced_totient(0))
raises(ValueError, lambda: primorial(0))
assert mr(1, [2]) is False
func = lambda i: (i**2 + 1) % 51
assert next(cycle_length(func, 4)) == (6, 2)
assert list(cycle_length(func, 4, values=True)) == \
[17, 35, 2, 5, 26, 14, 44, 50, 2, 5, 26, 14]
assert next(cycle_length(func, 4, nmax=5)) == (5, None)
assert list(cycle_length(func, 4, nmax=5, values=True)) == \
[17, 35, 2, 5, 26]
sieve.extend(3000)
assert nextprime(2968) == 2969
assert prevprime(2930) == 2927
raises(ValueError, lambda: prevprime(1))
raises(ValueError, lambda: prevprime(-4))
def test_randprime():
assert randprime(10, 1) is None
assert randprime(3, -3) is None
assert randprime(2, 3) == 2
assert randprime(1, 3) == 2
assert randprime(3, 5) == 3
raises(ValueError, lambda: randprime(-12, -2))
raises(ValueError, lambda: randprime(-10, 0))
raises(ValueError, lambda: randprime(20, 22))
raises(ValueError, lambda: randprime(0, 2))
raises(ValueError, lambda: randprime(1, 2))
for a in [100, 300, 500, 250000]:
for b in [100, 300, 500, 250000]:
p = randprime(a, a + b)
assert a <= p < (a + b) and isprime(p)
def test_primorial():
assert primorial(1) == 2
assert primorial(1, nth=0) == 1
assert primorial(2) == 6
assert primorial(2, nth=0) == 2
assert primorial(4, nth=0) == 6
def test_search():
assert 2 in sieve
assert 2.1 not in sieve
assert 1 not in sieve
assert 2**1000 not in sieve
raises(ValueError, lambda: sieve.search(1))
def test_sieve_slice():
assert sieve[5] == 11
assert list(sieve[5:10]) == [sieve[x] for x in range(5, 10)]
assert list(sieve[5:10:2]) == [sieve[x] for x in range(5, 10, 2)]
assert list(sieve[1:5]) == [2, 3, 5, 7]
raises(IndexError, lambda: sieve[:5])
raises(IndexError, lambda: sieve[0])
raises(IndexError, lambda: sieve[0:5])
def test_sieve_iter():
values = []
for value in sieve:
if value > 7:
break
values.append(value)
assert values == list(sieve[1:5])
def test_sieve_repr():
assert "sieve" in repr(sieve)
assert "prime" in repr(sieve)
|
d98c95a17df1e2c3923f1c5edb2ca856686afbe93c4fee4a90f2eea4f348c44e | from typing import Dict as tDict, Tuple as tTuple
from sympy.ntheory import qs
from sympy.ntheory.qs import SievePolynomial, \
_generate_factor_base, _initialize_first_polynomial, _initialize_ith_poly, \
_gen_sieve_array, _check_smoothness, _trial_division_stage, _gauss_mod_2, \
_build_matrix, _find_factor
assert qs(10009202107, 100, 10000) == {100043, 100049}
assert qs(211107295182713951054568361, 1000, 10000) == {13791315212531, 15307263442931}
assert qs(980835832582657*990377764891511, 3000, 50000) == {980835832582657, 990377764891511}
assert qs(18640889198609*20991129234731, 1000, 50000) == {18640889198609, 20991129234731}
n = 10009202107
M = 50
#a = 10, b = 15, modified_coeff = [a**2, 2*a*b, b**2 - N]
sieve_poly = SievePolynomial([100, 1600, -10009195707], 10, 80)
assert sieve_poly.eval(10) == -10009169707
assert sieve_poly.eval(5) == -10009185207
idx_1000, idx_5000, factor_base = _generate_factor_base(2000, n)
assert idx_1000 == 82
assert [factor_base[i].prime for i in range(15)] == [2, 3, 7, 11, 17, 19, 29, 31,\
43, 59, 61, 67, 71, 73, 79]
assert [factor_base[i].tmem_p for i in range(15)] == [1, 1, 3, 5, 3, 6, 6, 14, 1,\
16, 24, 22, 18, 22, 15]
assert [factor_base[i].log_p for i in range(5)] == [710, 1125, 1993, 2455, 2901]
g, B = _initialize_first_polynomial(n, M, factor_base, idx_1000, idx_5000, seed=0)
assert g.a == 1133107
assert g.b == 682543
assert B == [272889, 409654]
assert [factor_base[i].soln1 for i in range(15)] == [0, 0, 3, 7, 13, 0, 8, 19,\
9, 43, 27, 25, 63, 29, 19]
assert [factor_base[i].soln2 for i in range(15)] == [0, 1, 1, 3, 12, 16, 15, 6,\
15, 1, 56, 55, 61, 58, 16]
assert [factor_base[i].a_inv for i in range(15)] == [1, 1, 5, 7, 3, 5, 26, 6,\
40, 5, 21, 45, 4, 1, 8]
assert [factor_base[i].b_ainv for i in range(5)] == [[0, 0], [0, 2], [3, 0],\
[3, 9], [13, 13]]
g_1 = _initialize_ith_poly(n, factor_base, 1, g, B)
assert g_1.a == 1133107
assert g_1.b == 136765
sieve_array = _gen_sieve_array(M, factor_base)
assert sieve_array[0:5] == [8424, 13603, 1835, 5335, 710]
assert _check_smoothness(9645, factor_base) == (5, False)
assert _check_smoothness(210313, factor_base)[0][0:15] == [0, 0, 0, 0, 0, 0, 0,\
0, 0, 1, 0, 0, 1, 0, 1]
assert _check_smoothness(210313, factor_base)[1] == True
partial_relations = {} # type: tDict[int, tTuple[int, int]]
smooth_relation, partial_relation = _trial_division_stage(n, M, factor_base,\
sieve_array, sieve_poly,\
partial_relations, ERROR_TERM=25*2**10)
assert partial_relations == {8699: (440, -10009008507),
166741: (490, -10008962007),
131449: (530, -10008921207),
6653: (550, -10008899607)}
assert [smooth_relation[i][0] for i in range(5)] == [-250, -670615476700,\
-45211565844500, -231723037747200, -1811665537200]
assert [smooth_relation[i][1] for i in range(5)] == [-10009139607, 1133094251961,\
5302606761, 53804049849, 1950723889]
assert smooth_relation[0][2][0:15] == [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
assert _gauss_mod_2([[0, 0, 1], [1, 0, 1], [0, 1, 0], [0, 1, 1], [0, 1, 1]]) ==\
([[[0, 1, 1], 3], [[0, 1, 1], 4]], [True, True, True, False, False], [[0, 0, 1],\
[1, 0, 0], [0, 1, 0], [0, 1, 1], [0, 1, 1]])
N=1817
smooth_relations = [(2455024, 637, [0, 0, 0, 1]),
(-27993000, 81536, [0, 1, 0, 1]),
(11461840, 12544, [0, 0, 0, 0]),
(149, 20384, [0, 1, 0, 1]),
(-31138074, 19208, [0, 1, 0, 0])]
matrix = _build_matrix(smooth_relations)
assert matrix == [[0, 0, 0, 1], [0, 1, 0, 1], [0, 0, 0, 0], [0, 1, 0, 1], [0, 1, 0, 0]]
dependent_row, mark, gauss_matrix = _gauss_mod_2(matrix)
assert dependent_row == [[[0, 0, 0, 0], 2], [[0, 1, 0, 0], 3]]
assert mark == [True, True, False, False, True]
assert gauss_matrix == [[0, 0, 0, 1], [0, 1, 0, 0], [0, 0, 0, 0], [0, 1, 0, 0], [0, 1, 0, 1]]
factor = _find_factor(dependent_row, mark, gauss_matrix, 0, smooth_relations, N)
assert factor == 23
|
dd25a415029e17ea754163f822ef4d200d684f1005a3504b46bacb7ab045021c | from sympy.core.symbol import symbols
from sympy.sets.sets import FiniteSet
from sympy.combinatorics.polyhedron import (Polyhedron,
tetrahedron, cube as square, octahedron, dodecahedron, icosahedron,
cube_faces)
from sympy.combinatorics.permutations import Permutation
from sympy.combinatorics.perm_groups import PermutationGroup
from sympy.testing.pytest import raises
rmul = Permutation.rmul
def test_polyhedron():
raises(ValueError, lambda: Polyhedron(list('ab'),
pgroup=[Permutation([0])]))
pgroup = [Permutation([[0, 7, 2, 5], [6, 1, 4, 3]]),
Permutation([[0, 7, 1, 6], [5, 2, 4, 3]]),
Permutation([[3, 6, 0, 5], [4, 1, 7, 2]]),
Permutation([[7, 4, 5], [1, 3, 0], [2], [6]]),
Permutation([[1, 3, 2], [7, 6, 5], [4], [0]]),
Permutation([[4, 7, 6], [2, 0, 3], [1], [5]]),
Permutation([[1, 2, 0], [4, 5, 6], [3], [7]]),
Permutation([[4, 2], [0, 6], [3, 7], [1, 5]]),
Permutation([[3, 5], [7, 1], [2, 6], [0, 4]]),
Permutation([[2, 5], [1, 6], [0, 4], [3, 7]]),
Permutation([[4, 3], [7, 0], [5, 1], [6, 2]]),
Permutation([[4, 1], [0, 5], [6, 2], [7, 3]]),
Permutation([[7, 2], [3, 6], [0, 4], [1, 5]]),
Permutation([0, 1, 2, 3, 4, 5, 6, 7])]
corners = tuple(symbols('A:H'))
faces = cube_faces
cube = Polyhedron(corners, faces, pgroup)
assert cube.edges == FiniteSet(*(
(0, 1), (6, 7), (1, 2), (5, 6), (0, 3), (2, 3),
(4, 7), (4, 5), (3, 7), (1, 5), (0, 4), (2, 6)))
for i in range(3): # add 180 degree face rotations
cube.rotate(cube.pgroup[i]**2)
assert cube.corners == corners
for i in range(3, 7): # add 240 degree axial corner rotations
cube.rotate(cube.pgroup[i]**2)
assert cube.corners == corners
cube.rotate(1)
raises(ValueError, lambda: cube.rotate(Permutation([0, 1])))
assert cube.corners != corners
assert cube.array_form == [7, 6, 4, 5, 3, 2, 0, 1]
assert cube.cyclic_form == [[0, 7, 1, 6], [2, 4, 3, 5]]
cube.reset()
assert cube.corners == corners
def check(h, size, rpt, target):
assert len(h.faces) + len(h.vertices) - len(h.edges) == 2
assert h.size == size
got = set()
for p in h.pgroup:
# make sure it restores original
P = h.copy()
hit = P.corners
for i in range(rpt):
P.rotate(p)
if P.corners == hit:
break
else:
print('error in permutation', p.array_form)
for i in range(rpt):
P.rotate(p)
got.add(tuple(P.corners))
c = P.corners
f = [[c[i] for i in f] for f in P.faces]
assert h.faces == Polyhedron(c, f).faces
assert len(got) == target
assert PermutationGroup([Permutation(g) for g in got]).is_group
for h, size, rpt, target in zip(
(tetrahedron, square, octahedron, dodecahedron, icosahedron),
(4, 8, 6, 20, 12),
(3, 4, 4, 5, 5),
(12, 24, 24, 60, 60)):
check(h, size, rpt, target)
def test_pgroups():
from sympy.combinatorics.polyhedron import (cube, tetrahedron_faces,
octahedron_faces, dodecahedron_faces, icosahedron_faces)
from sympy.combinatorics.polyhedron import _pgroup_calcs
(tetrahedron2, cube2, octahedron2, dodecahedron2, icosahedron2,
tetrahedron_faces2, cube_faces2, octahedron_faces2,
dodecahedron_faces2, icosahedron_faces2) = _pgroup_calcs()
assert tetrahedron == tetrahedron2
assert cube == cube2
assert octahedron == octahedron2
assert dodecahedron == dodecahedron2
assert icosahedron == icosahedron2
assert sorted(map(sorted, tetrahedron_faces)) == sorted(map(sorted, tetrahedron_faces2))
assert sorted(cube_faces) == sorted(cube_faces2)
assert sorted(octahedron_faces) == sorted(octahedron_faces2)
assert sorted(dodecahedron_faces) == sorted(dodecahedron_faces2)
assert sorted(icosahedron_faces) == sorted(icosahedron_faces2)
|
ec04ccc333ef0285a21fb09ec7e0fade79a539adb487bd333b94d61958ac1703 | from sympy.core.singleton import S
from sympy.combinatorics.fp_groups import (FpGroup, low_index_subgroups,
reidemeister_presentation, FpSubgroup,
simplify_presentation)
from sympy.combinatorics.free_groups import (free_group, FreeGroup)
from sympy.testing.pytest import slow
"""
References
==========
[1] Holt, D., Eick, B., O'Brien, E.
"Handbook of Computational Group Theory"
[2] John J. Cannon; Lucien A. Dimino; George Havas; Jane M. Watson
Mathematics of Computation, Vol. 27, No. 123. (Jul., 1973), pp. 463-490.
"Implementation and Analysis of the Todd-Coxeter Algorithm"
[3] PROC. SECOND INTERNAT. CONF. THEORY OF GROUPS, CANBERRA 1973,
pp. 347-356. "A Reidemeister-Schreier program" by George Havas.
http://staff.itee.uq.edu.au/havas/1973cdhw.pdf
"""
def test_low_index_subgroups():
F, x, y = free_group("x, y")
# Example 5.10 from [1] Pg. 194
f = FpGroup(F, [x**2, y**3, (x*y)**4])
L = low_index_subgroups(f, 4)
t1 = [[[0, 0, 0, 0]],
[[0, 0, 1, 2], [1, 1, 2, 0], [3, 3, 0, 1], [2, 2, 3, 3]],
[[0, 0, 1, 2], [2, 2, 2, 0], [1, 1, 0, 1]],
[[1, 1, 0, 0], [0, 0, 1, 1]]]
for i in range(len(t1)):
assert L[i].table == t1[i]
f = FpGroup(F, [x**2, y**3, (x*y)**7])
L = low_index_subgroups(f, 15)
t2 = [[[0, 0, 0, 0]],
[[0, 0, 1, 2], [1, 1, 2, 0], [3, 3, 0, 1], [2, 2, 4, 5],
[4, 4, 5, 3], [6, 6, 3, 4], [5, 5, 6, 6]],
[[0, 0, 1, 2], [1, 1, 2, 0], [3, 3, 0, 1], [2, 2, 4, 5],
[6, 6, 5, 3], [5, 5, 3, 4], [4, 4, 6, 6]],
[[0, 0, 1, 2], [1, 1, 2, 0], [3, 3, 0, 1], [2, 2, 4, 5],
[6, 6, 5, 3], [7, 7, 3, 4], [4, 4, 8, 9], [5, 5, 10, 11],
[11, 11, 9, 6], [9, 9, 6, 8], [12, 12, 11, 7], [8, 8, 7, 10],
[10, 10, 13, 14], [14, 14, 14, 12], [13, 13, 12, 13]],
[[0, 0, 1, 2], [1, 1, 2, 0], [3, 3, 0, 1], [2, 2, 4, 5],
[6, 6, 5, 3], [7, 7, 3, 4], [4, 4, 8, 9], [5, 5, 10, 11],
[11, 11, 9, 6], [12, 12, 6, 8], [10, 10, 11, 7], [8, 8, 7, 10],
[9, 9, 13, 14], [14, 14, 14, 12], [13, 13, 12, 13]],
[[0, 0, 1, 2], [1, 1, 2, 0], [3, 3, 0, 1], [2, 2, 4, 5],
[6, 6, 5, 3], [7, 7, 3, 4], [4, 4, 8, 9], [5, 5, 10, 11],
[11, 11, 9, 6], [12, 12, 6, 8], [13, 13, 11, 7], [8, 8, 7, 10],
[9, 9, 12, 12], [10, 10, 13, 13]],
[[0, 0, 1, 2], [3, 3, 2, 0], [4, 4, 0, 1], [1, 1, 3, 3], [2, 2, 5, 6]
, [7, 7, 6, 4], [8, 8, 4, 5], [5, 5, 8, 9], [6, 6, 9, 7],
[10, 10, 7, 8], [9, 9, 11, 12], [11, 11, 12, 10], [13, 13, 10, 11],
[12, 12, 13, 13]],
[[0, 0, 1, 2], [3, 3, 2, 0], [4, 4, 0, 1], [1, 1, 3, 3], [2, 2, 5, 6]
, [7, 7, 6, 4], [8, 8, 4, 5], [5, 5, 8, 9], [6, 6, 9, 7],
[10, 10, 7, 8], [9, 9, 11, 12], [13, 13, 12, 10], [12, 12, 10, 11],
[11, 11, 13, 13]],
[[0, 0, 1, 2], [3, 3, 2, 0], [4, 4, 0, 1], [1, 1, 5, 6], [2, 2, 4, 4]
, [7, 7, 6, 3], [8, 8, 3, 5], [5, 5, 8, 9], [6, 6, 9, 7],
[10, 10, 7, 8], [9, 9, 11, 12], [13, 13, 12, 10], [12, 12, 10, 11],
[11, 11, 13, 13]],
[[0, 0, 1, 2], [3, 3, 2, 0], [4, 4, 0, 1], [1, 1, 5, 6], [2, 2, 7, 8]
, [5, 5, 6, 3], [9, 9, 3, 5], [10, 10, 8, 4], [8, 8, 4, 7],
[6, 6, 10, 11], [7, 7, 11, 9], [12, 12, 9, 10], [11, 11, 13, 14],
[14, 14, 14, 12], [13, 13, 12, 13]],
[[0, 0, 1, 2], [3, 3, 2, 0], [4, 4, 0, 1], [1, 1, 5, 6], [2, 2, 7, 8]
, [6, 6, 6, 3], [5, 5, 3, 5], [8, 8, 8, 4], [7, 7, 4, 7]],
[[0, 0, 1, 2], [3, 3, 2, 0], [4, 4, 0, 1], [1, 1, 5, 6], [2, 2, 7, 8]
, [9, 9, 6, 3], [6, 6, 3, 5], [10, 10, 8, 4], [11, 11, 4, 7],
[5, 5, 10, 12], [7, 7, 12, 9], [8, 8, 11, 11], [13, 13, 9, 10],
[12, 12, 13, 13]],
[[0, 0, 1, 2], [3, 3, 2, 0], [4, 4, 0, 1], [1, 1, 5, 6], [2, 2, 7, 8]
, [9, 9, 6, 3], [6, 6, 3, 5], [10, 10, 8, 4], [11, 11, 4, 7],
[5, 5, 12, 11], [7, 7, 10, 10], [8, 8, 9, 12], [13, 13, 11, 9],
[12, 12, 13, 13]],
[[0, 0, 1, 2], [3, 3, 2, 0], [4, 4, 0, 1], [1, 1, 5, 6], [2, 2, 7, 8]
, [9, 9, 6, 3], [10, 10, 3, 5], [7, 7, 8, 4], [11, 11, 4, 7],
[5, 5, 9, 9], [6, 6, 11, 12], [8, 8, 12, 10], [13, 13, 10, 11],
[12, 12, 13, 13]],
[[0, 0, 1, 2], [3, 3, 2, 0], [4, 4, 0, 1], [1, 1, 5, 6], [2, 2, 7, 8]
, [9, 9, 6, 3], [10, 10, 3, 5], [7, 7, 8, 4], [11, 11, 4, 7],
[5, 5, 12, 11], [6, 6, 10, 10], [8, 8, 9, 12], [13, 13, 11, 9],
[12, 12, 13, 13]],
[[0, 0, 1, 2], [3, 3, 2, 0], [4, 4, 0, 1], [1, 1, 5, 6], [2, 2, 7, 8]
, [9, 9, 6, 3], [10, 10, 3, 5], [11, 11, 8, 4], [12, 12, 4, 7],
[5, 5, 9, 9], [6, 6, 12, 13], [7, 7, 11, 11], [8, 8, 13, 10],
[13, 13, 10, 12]],
[[1, 1, 0, 0], [0, 0, 2, 3], [4, 4, 3, 1], [5, 5, 1, 2], [2, 2, 4, 4]
, [3, 3, 6, 7], [7, 7, 7, 5], [6, 6, 5, 6]]]
for i in range(len(t2)):
assert L[i].table == t2[i]
f = FpGroup(F, [x**2, y**3, (x*y)**7])
L = low_index_subgroups(f, 10, [x])
t3 = [[[0, 0, 0, 0]],
[[0, 0, 1, 2], [1, 1, 2, 0], [3, 3, 0, 1], [2, 2, 4, 5], [4, 4, 5, 3],
[6, 6, 3, 4], [5, 5, 6, 6]],
[[0, 0, 1, 2], [1, 1, 2, 0], [3, 3, 0, 1], [2, 2, 4, 5], [6, 6, 5, 3],
[5, 5, 3, 4], [4, 4, 6, 6]],
[[0, 0, 1, 2], [3, 3, 2, 0], [4, 4, 0, 1], [1, 1, 5, 6], [2, 2, 7, 8],
[6, 6, 6, 3], [5, 5, 3, 5], [8, 8, 8, 4], [7, 7, 4, 7]]]
for i in range(len(t3)):
assert L[i].table == t3[i]
def test_subgroup_presentations():
F, x, y = free_group("x, y")
f = FpGroup(F, [x**3, y**5, (x*y)**2])
H = [x*y, x**-1*y**-1*x*y*x]
p1 = reidemeister_presentation(f, H)
assert str(p1) == "((y_1, y_2), (y_1**2, y_2**3, y_2*y_1*y_2*y_1*y_2*y_1))"
H = f.subgroup(H)
assert (H.generators, H.relators) == p1
f = FpGroup(F, [x**3, y**3, (x*y)**3])
H = [x*y, x*y**-1]
p2 = reidemeister_presentation(f, H)
assert str(p2) == "((x_0, y_0), (x_0**3, y_0**3, x_0*y_0*x_0*y_0*x_0*y_0))"
f = FpGroup(F, [x**2*y**2, y**-1*x*y*x**-3])
H = [x]
p3 = reidemeister_presentation(f, H)
assert str(p3) == "((x_0,), (x_0**4,))"
f = FpGroup(F, [x**3*y**-3, (x*y)**3, (x*y**-1)**2])
H = [x]
p4 = reidemeister_presentation(f, H)
assert str(p4) == "((x_0,), (x_0**6,))"
# this presentation can be improved, the most simplified form
# of presentation is <a, b | a^11, b^2, (a*b)^3, (a^4*b*a^-5*b)^2>
# See [2] Pg 474 group PSL_2(11)
# This is the group PSL_2(11)
F, a, b, c = free_group("a, b, c")
f = FpGroup(F, [a**11, b**5, c**4, (b*c**2)**2, (a*b*c)**3, (a**4*c**2)**3, b**2*c**-1*b**-1*c, a**4*b**-1*a**-1*b])
H = [a, b, c**2]
gens, rels = reidemeister_presentation(f, H)
assert str(gens) == "(b_1, c_3)"
assert len(rels) == 18
@slow
def test_order():
F, x, y = free_group("x, y")
f = FpGroup(F, [x**4, y**2, x*y*x**-1*y])
assert f.order() == 8
f = FpGroup(F, [x*y*x**-1*y**-1, y**2])
assert f.order() is S.Infinity
F, a, b, c = free_group("a, b, c")
f = FpGroup(F, [a**250, b**2, c*b*c**-1*b, c**4, c**-1*a**-1*c*a, a**-1*b**-1*a*b])
assert f.order() == 2000
F, x = free_group("x")
f = FpGroup(F, [])
assert f.order() is S.Infinity
f = FpGroup(free_group('')[0], [])
assert f.order() == 1
def test_fp_subgroup():
def _test_subgroup(K, T, S):
_gens = T(K.generators)
assert all(elem in S for elem in _gens)
assert T.is_injective()
assert T.image().order() == S.order()
F, x, y = free_group("x, y")
f = FpGroup(F, [x**4, y**2, x*y*x**-1*y])
S = FpSubgroup(f, [x*y])
assert (x*y)**-3 in S
K, T = f.subgroup([x*y], homomorphism=True)
assert T(K.generators) == [y*x**-1]
_test_subgroup(K, T, S)
S = FpSubgroup(f, [x**-1*y*x])
assert x**-1*y**4*x in S
assert x**-1*y**4*x**2 not in S
K, T = f.subgroup([x**-1*y*x], homomorphism=True)
assert T(K.generators[0]**3) == y**3
_test_subgroup(K, T, S)
f = FpGroup(F, [x**3, y**5, (x*y)**2])
H = [x*y, x**-1*y**-1*x*y*x]
K, T = f.subgroup(H, homomorphism=True)
S = FpSubgroup(f, H)
_test_subgroup(K, T, S)
def test_permutation_methods():
F, x, y = free_group("x, y")
# DihedralGroup(8)
G = FpGroup(F, [x**2, y**8, x*y*x**-1*y])
T = G._to_perm_group()[1]
assert T.is_isomorphism()
assert G.center() == [y**4]
# DiheadralGroup(4)
G = FpGroup(F, [x**2, y**4, x*y*x**-1*y])
S = FpSubgroup(G, G.normal_closure([x]))
assert x in S
assert y**-1*x*y in S
# Z_5xZ_4
G = FpGroup(F, [x*y*x**-1*y**-1, y**5, x**4])
assert G.is_abelian
assert G.is_solvable
# AlternatingGroup(5)
G = FpGroup(F, [x**3, y**2, (x*y)**5])
assert not G.is_solvable
# AlternatingGroup(4)
G = FpGroup(F, [x**3, y**2, (x*y)**3])
assert len(G.derived_series()) == 3
S = FpSubgroup(G, G.derived_subgroup())
assert S.order() == 4
def test_simplify_presentation():
# ref #16083
G = simplify_presentation(FpGroup(FreeGroup([]), []))
assert not G.generators
assert not G.relators
def test_cyclic():
F, x, y = free_group("x, y")
f = FpGroup(F, [x*y, x**-1*y**-1*x*y*x])
assert f.is_cyclic
f = FpGroup(F, [x*y, x*y**-1])
assert f.is_cyclic
f = FpGroup(F, [x**4, y**2, x*y*x**-1*y])
assert not f.is_cyclic
def test_abelian_invariants():
F, x, y = free_group("x, y")
f = FpGroup(F, [x*y, x**-1*y**-1*x*y*x])
assert f.abelian_invariants() == []
f = FpGroup(F, [x*y, x*y**-1])
assert f.abelian_invariants() == [2]
f = FpGroup(F, [x**4, y**2, x*y*x**-1*y])
assert f.abelian_invariants() == [2, 4]
|
a29a6ccca24b2d2a5c1331e07aca48bde4a6102ddf0d9d2a92eb3593b301b781 | from sympy.core.sorting import ordered, default_sort_key
from sympy.combinatorics.partitions import (Partition, IntegerPartition,
RGS_enum, RGS_unrank, RGS_rank,
random_integer_partition)
from sympy.testing.pytest import raises
from sympy.utilities.iterables import partitions
from sympy.sets.sets import Set, FiniteSet
def test_partition_constructor():
raises(ValueError, lambda: Partition([1, 1, 2]))
raises(ValueError, lambda: Partition([1, 2, 3], [2, 3, 4]))
raises(ValueError, lambda: Partition(1, 2, 3))
raises(ValueError, lambda: Partition(*list(range(3))))
assert Partition([1, 2, 3], [4, 5]) == Partition([4, 5], [1, 2, 3])
assert Partition({1, 2, 3}, {4, 5}) == Partition([1, 2, 3], [4, 5])
a = FiniteSet(1, 2, 3)
b = FiniteSet(4, 5)
assert Partition(a, b) == Partition([1, 2, 3], [4, 5])
assert Partition({a, b}) == Partition(FiniteSet(a, b))
assert Partition({a, b}) != Partition(a, b)
def test_partition():
from sympy.abc import x
a = Partition([1, 2, 3], [4])
b = Partition([1, 2], [3, 4])
c = Partition([x])
l = [a, b, c]
l.sort(key=default_sort_key)
assert l == [c, a, b]
l.sort(key=lambda w: default_sort_key(w, order='rev-lex'))
assert l == [c, a, b]
assert (a == b) is False
assert a <= b
assert (a > b) is False
assert a != b
assert a < b
assert (a + 2).partition == [[1, 2], [3, 4]]
assert (b - 1).partition == [[1, 2, 4], [3]]
assert (a - 1).partition == [[1, 2, 3, 4]]
assert (a + 1).partition == [[1, 2, 4], [3]]
assert (b + 1).partition == [[1, 2], [3], [4]]
assert a.rank == 1
assert b.rank == 3
assert a.RGS == (0, 0, 0, 1)
assert b.RGS == (0, 0, 1, 1)
def test_integer_partition():
# no zeros in partition
raises(ValueError, lambda: IntegerPartition(list(range(3))))
# check fails since 1 + 2 != 100
raises(ValueError, lambda: IntegerPartition(100, list(range(1, 3))))
a = IntegerPartition(8, [1, 3, 4])
b = a.next_lex()
c = IntegerPartition([1, 3, 4])
d = IntegerPartition(8, {1: 3, 3: 1, 2: 1})
assert a == c
assert a.integer == d.integer
assert a.conjugate == [3, 2, 2, 1]
assert (a == b) is False
assert a <= b
assert (a > b) is False
assert a != b
for i in range(1, 11):
next = set()
prev = set()
a = IntegerPartition([i])
ans = {IntegerPartition(p) for p in partitions(i)}
n = len(ans)
for j in range(n):
next.add(a)
a = a.next_lex()
IntegerPartition(i, a.partition) # check it by giving i
for j in range(n):
prev.add(a)
a = a.prev_lex()
IntegerPartition(i, a.partition) # check it by giving i
assert next == ans
assert prev == ans
assert IntegerPartition([1, 2, 3]).as_ferrers() == '###\n##\n#'
assert IntegerPartition([1, 1, 3]).as_ferrers('o') == 'ooo\no\no'
assert str(IntegerPartition([1, 1, 3])) == '[3, 1, 1]'
assert IntegerPartition([1, 1, 3]).partition == [3, 1, 1]
raises(ValueError, lambda: random_integer_partition(-1))
assert random_integer_partition(1) == [1]
assert random_integer_partition(10, seed=[1, 3, 2, 1, 5, 1]
) == [5, 2, 1, 1, 1]
def test_rgs():
raises(ValueError, lambda: RGS_unrank(-1, 3))
raises(ValueError, lambda: RGS_unrank(3, 0))
raises(ValueError, lambda: RGS_unrank(10, 1))
raises(ValueError, lambda: Partition.from_rgs(list(range(3)), list(range(2))))
raises(ValueError, lambda: Partition.from_rgs(list(range(1, 3)), list(range(2))))
assert RGS_enum(-1) == 0
assert RGS_enum(1) == 1
assert RGS_unrank(7, 5) == [0, 0, 1, 0, 2]
assert RGS_unrank(23, 14) == [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 2, 2]
assert RGS_rank(RGS_unrank(40, 100)) == 40
def test_ordered_partition_9608():
a = Partition([1, 2, 3], [4])
b = Partition([1, 2], [3, 4])
assert list(ordered([a,b], Set._infimum_key))
|
84c10ac017b15044291783cdc2b76c1014ecacd12b7798aec24607bb872dfb16 | from sympy.core import S, Rational
from sympy.combinatorics.schur_number import schur_partition, SchurNumber
from sympy.testing.randtest import _randint
from sympy.testing.pytest import raises
from sympy.core.symbol import symbols
def _sum_free_test(subset):
"""
Checks if subset is sum-free(There are no x,y,z in the subset such that
x + y = z)
"""
for i in subset:
for j in subset:
assert (i + j in subset) is False
def test_schur_partition():
raises(ValueError, lambda: schur_partition(S.Infinity))
raises(ValueError, lambda: schur_partition(-1))
raises(ValueError, lambda: schur_partition(0))
assert schur_partition(2) == [[1, 2]]
random_number_generator = _randint(1000)
for _ in range(5):
n = random_number_generator(1, 1000)
result = schur_partition(n)
t = 0
numbers = []
for item in result:
_sum_free_test(item)
"""
Checks if the occurance of all numbers is exactly one
"""
t += len(item)
for l in item:
assert (l in numbers) is False
numbers.append(l)
assert n == t
x = symbols("x")
raises(ValueError, lambda: schur_partition(x))
def test_schur_number():
first_known_schur_numbers = {1: 1, 2: 4, 3: 13, 4: 44, 5: 160}
for k in first_known_schur_numbers:
assert SchurNumber(k) == first_known_schur_numbers[k]
assert SchurNumber(S.Infinity) == S.Infinity
assert SchurNumber(0) == 0
raises(ValueError, lambda: SchurNumber(0.5))
n = symbols("n")
assert SchurNumber(n).lower_bound() == 3**n/2 - Rational(1, 2)
assert SchurNumber(8).lower_bound() == 5039
|
ad3bc6758470d99c3398145e0586befdd4a9906006bc8c83fb9f43e940c10169 | from itertools import permutations
from sympy.core.expr import unchanged
from sympy.core.numbers import Integer
from sympy.core.relational import Eq
from sympy.core.symbol import Symbol
from sympy.core.singleton import S
from sympy.combinatorics.permutations import \
Permutation, _af_parity, _af_rmul, _af_rmuln, AppliedPermutation, Cycle
from sympy.printing import sstr, srepr, pretty, latex
from sympy.testing.pytest import raises, warns_deprecated_sympy
rmul = Permutation.rmul
a = Symbol('a', integer=True)
def test_Permutation():
# don't auto fill 0
raises(ValueError, lambda: Permutation([1]))
p = Permutation([0, 1, 2, 3])
# call as bijective
assert [p(i) for i in range(p.size)] == list(p)
# call as operator
assert p(list(range(p.size))) == list(p)
# call as function
assert list(p(1, 2)) == [0, 2, 1, 3]
raises(TypeError, lambda: p(-1))
raises(TypeError, lambda: p(5))
# conversion to list
assert list(p) == list(range(4))
assert Permutation(size=4) == Permutation(3)
assert Permutation(Permutation(3), size=5) == Permutation(4)
# cycle form with size
assert Permutation([[1, 2]], size=4) == Permutation([[1, 2], [0], [3]])
# random generation
assert Permutation.random(2) in (Permutation([1, 0]), Permutation([0, 1]))
p = Permutation([2, 5, 1, 6, 3, 0, 4])
q = Permutation([[1], [0, 3, 5, 6, 2, 4]])
assert len({p, p}) == 1
r = Permutation([1, 3, 2, 0, 4, 6, 5])
ans = Permutation(_af_rmuln(*[w.array_form for w in (p, q, r)])).array_form
assert rmul(p, q, r).array_form == ans
# make sure no other permutation of p, q, r could have given
# that answer
for a, b, c in permutations((p, q, r)):
if (a, b, c) == (p, q, r):
continue
assert rmul(a, b, c).array_form != ans
assert p.support() == list(range(7))
assert q.support() == [0, 2, 3, 4, 5, 6]
assert Permutation(p.cyclic_form).array_form == p.array_form
assert p.cardinality == 5040
assert q.cardinality == 5040
assert q.cycles == 2
assert rmul(q, p) == Permutation([4, 6, 1, 2, 5, 3, 0])
assert rmul(p, q) == Permutation([6, 5, 3, 0, 2, 4, 1])
assert _af_rmul(p.array_form, q.array_form) == \
[6, 5, 3, 0, 2, 4, 1]
assert rmul(Permutation([[1, 2, 3], [0, 4]]),
Permutation([[1, 2, 4], [0], [3]])).cyclic_form == \
[[0, 4, 2], [1, 3]]
assert q.array_form == [3, 1, 4, 5, 0, 6, 2]
assert q.cyclic_form == [[0, 3, 5, 6, 2, 4]]
assert q.full_cyclic_form == [[0, 3, 5, 6, 2, 4], [1]]
assert p.cyclic_form == [[0, 2, 1, 5], [3, 6, 4]]
t = p.transpositions()
assert t == [(0, 5), (0, 1), (0, 2), (3, 4), (3, 6)]
assert Permutation.rmul(*[Permutation(Cycle(*ti)) for ti in (t)])
assert Permutation([1, 0]).transpositions() == [(0, 1)]
assert p**13 == p
assert q**0 == Permutation(list(range(q.size)))
assert q**-2 == ~q**2
assert q**2 == Permutation([5, 1, 0, 6, 3, 2, 4])
assert q**3 == q**2*q
assert q**4 == q**2*q**2
a = Permutation(1, 3)
b = Permutation(2, 0, 3)
I = Permutation(3)
assert ~a == a**-1
assert a*~a == I
assert a*b**-1 == a*~b
ans = Permutation(0, 5, 3, 1, 6)(2, 4)
assert (p + q.rank()).rank() == ans.rank()
assert (p + q.rank())._rank == ans.rank()
assert (q + p.rank()).rank() == ans.rank()
raises(TypeError, lambda: p + Permutation(list(range(10))))
assert (p - q.rank()).rank() == Permutation(0, 6, 3, 1, 2, 5, 4).rank()
assert p.rank() - q.rank() < 0 # for coverage: make sure mod is used
assert (q - p.rank()).rank() == Permutation(1, 4, 6, 2)(3, 5).rank()
assert p*q == Permutation(_af_rmuln(*[list(w) for w in (q, p)]))
assert p*Permutation([]) == p
assert Permutation([])*p == p
assert p*Permutation([[0, 1]]) == Permutation([2, 5, 0, 6, 3, 1, 4])
assert Permutation([[0, 1]])*p == Permutation([5, 2, 1, 6, 3, 0, 4])
pq = p ^ q
assert pq == Permutation([5, 6, 0, 4, 1, 2, 3])
assert pq == rmul(q, p, ~q)
qp = q ^ p
assert qp == Permutation([4, 3, 6, 2, 1, 5, 0])
assert qp == rmul(p, q, ~p)
raises(ValueError, lambda: p ^ Permutation([]))
assert p.commutator(q) == Permutation(0, 1, 3, 4, 6, 5, 2)
assert q.commutator(p) == Permutation(0, 2, 5, 6, 4, 3, 1)
assert p.commutator(q) == ~q.commutator(p)
raises(ValueError, lambda: p.commutator(Permutation([])))
assert len(p.atoms()) == 7
assert q.atoms() == {0, 1, 2, 3, 4, 5, 6}
assert p.inversion_vector() == [2, 4, 1, 3, 1, 0]
assert q.inversion_vector() == [3, 1, 2, 2, 0, 1]
assert Permutation.from_inversion_vector(p.inversion_vector()) == p
assert Permutation.from_inversion_vector(q.inversion_vector()).array_form\
== q.array_form
raises(ValueError, lambda: Permutation.from_inversion_vector([0, 2]))
assert Permutation([i for i in range(500, -1, -1)]).inversions() == 125250
s = Permutation([0, 4, 1, 3, 2])
assert s.parity() == 0
_ = s.cyclic_form # needed to create a value for _cyclic_form
assert len(s._cyclic_form) != s.size and s.parity() == 0
assert not s.is_odd
assert s.is_even
assert Permutation([0, 1, 4, 3, 2]).parity() == 1
assert _af_parity([0, 4, 1, 3, 2]) == 0
assert _af_parity([0, 1, 4, 3, 2]) == 1
s = Permutation([0])
assert s.is_Singleton
assert Permutation([]).is_Empty
r = Permutation([3, 2, 1, 0])
assert (r**2).is_Identity
assert rmul(~p, p).is_Identity
assert (~p)**13 == Permutation([5, 2, 0, 4, 6, 1, 3])
assert ~(r**2).is_Identity
assert p.max() == 6
assert p.min() == 0
q = Permutation([[6], [5], [0, 1, 2, 3, 4]])
assert q.max() == 4
assert q.min() == 0
p = Permutation([1, 5, 2, 0, 3, 6, 4])
q = Permutation([[1, 2, 3, 5, 6], [0, 4]])
assert p.ascents() == [0, 3, 4]
assert q.ascents() == [1, 2, 4]
assert r.ascents() == []
assert p.descents() == [1, 2, 5]
assert q.descents() == [0, 3, 5]
assert Permutation(r.descents()).is_Identity
assert p.inversions() == 7
# test the merge-sort with a longer permutation
big = list(p) + list(range(p.max() + 1, p.max() + 130))
assert Permutation(big).inversions() == 7
assert p.signature() == -1
assert q.inversions() == 11
assert q.signature() == -1
assert rmul(p, ~p).inversions() == 0
assert rmul(p, ~p).signature() == 1
assert p.order() == 6
assert q.order() == 10
assert (p**(p.order())).is_Identity
assert p.length() == 6
assert q.length() == 7
assert r.length() == 4
assert p.runs() == [[1, 5], [2], [0, 3, 6], [4]]
assert q.runs() == [[4], [2, 3, 5], [0, 6], [1]]
assert r.runs() == [[3], [2], [1], [0]]
assert p.index() == 8
assert q.index() == 8
assert r.index() == 3
assert p.get_precedence_distance(q) == q.get_precedence_distance(p)
assert p.get_adjacency_distance(q) == p.get_adjacency_distance(q)
assert p.get_positional_distance(q) == p.get_positional_distance(q)
p = Permutation([0, 1, 2, 3])
q = Permutation([3, 2, 1, 0])
assert p.get_precedence_distance(q) == 6
assert p.get_adjacency_distance(q) == 3
assert p.get_positional_distance(q) == 8
p = Permutation([0, 3, 1, 2, 4])
q = Permutation.josephus(4, 5, 2)
assert p.get_adjacency_distance(q) == 3
raises(ValueError, lambda: p.get_adjacency_distance(Permutation([])))
raises(ValueError, lambda: p.get_positional_distance(Permutation([])))
raises(ValueError, lambda: p.get_precedence_distance(Permutation([])))
a = [Permutation.unrank_nonlex(4, i) for i in range(5)]
iden = Permutation([0, 1, 2, 3])
for i in range(5):
for j in range(i + 1, 5):
assert a[i].commutes_with(a[j]) == \
(rmul(a[i], a[j]) == rmul(a[j], a[i]))
if a[i].commutes_with(a[j]):
assert a[i].commutator(a[j]) == iden
assert a[j].commutator(a[i]) == iden
a = Permutation(3)
b = Permutation(0, 6, 3)(1, 2)
assert a.cycle_structure == {1: 4}
assert b.cycle_structure == {2: 1, 3: 1, 1: 2}
# issue 11130
raises(ValueError, lambda: Permutation(3, size=3))
raises(ValueError, lambda: Permutation([1, 2, 0, 3], size=3))
def test_Permutation_subclassing():
# Subclass that adds permutation application on iterables
class CustomPermutation(Permutation):
def __call__(self, *i):
try:
return super().__call__(*i)
except TypeError:
pass
try:
perm_obj = i[0]
return [self._array_form[j] for j in perm_obj]
except TypeError:
raise TypeError('unrecognized argument')
def __eq__(self, other):
if isinstance(other, Permutation):
return self._hashable_content() == other._hashable_content()
else:
return super().__eq__(other)
def __hash__(self):
return super().__hash__()
p = CustomPermutation([1, 2, 3, 0])
q = Permutation([1, 2, 3, 0])
assert p == q
raises(TypeError, lambda: q([1, 2]))
assert [2, 3] == p([1, 2])
assert type(p * q) == CustomPermutation
assert type(q * p) == Permutation # True because q.__mul__(p) is called!
# Run all tests for the Permutation class also on the subclass
def wrapped_test_Permutation():
# Monkeypatch the class definition in the globals
globals()['__Perm'] = globals()['Permutation']
globals()['Permutation'] = CustomPermutation
test_Permutation()
globals()['Permutation'] = globals()['__Perm'] # Restore
del globals()['__Perm']
wrapped_test_Permutation()
def test_josephus():
assert Permutation.josephus(4, 6, 1) == Permutation([3, 1, 0, 2, 5, 4])
assert Permutation.josephus(1, 5, 1).is_Identity
def test_ranking():
assert Permutation.unrank_lex(5, 10).rank() == 10
p = Permutation.unrank_lex(15, 225)
assert p.rank() == 225
p1 = p.next_lex()
assert p1.rank() == 226
assert Permutation.unrank_lex(15, 225).rank() == 225
assert Permutation.unrank_lex(10, 0).is_Identity
p = Permutation.unrank_lex(4, 23)
assert p.rank() == 23
assert p.array_form == [3, 2, 1, 0]
assert p.next_lex() is None
p = Permutation([1, 5, 2, 0, 3, 6, 4])
q = Permutation([[1, 2, 3, 5, 6], [0, 4]])
a = [Permutation.unrank_trotterjohnson(4, i).array_form for i in range(5)]
assert a == [[0, 1, 2, 3], [0, 1, 3, 2], [0, 3, 1, 2], [3, 0, 1,
2], [3, 0, 2, 1] ]
assert [Permutation(pa).rank_trotterjohnson() for pa in a] == list(range(5))
assert Permutation([0, 1, 2, 3]).next_trotterjohnson() == \
Permutation([0, 1, 3, 2])
assert q.rank_trotterjohnson() == 2283
assert p.rank_trotterjohnson() == 3389
assert Permutation([1, 0]).rank_trotterjohnson() == 1
a = Permutation(list(range(3)))
b = a
l = []
tj = []
for i in range(6):
l.append(a)
tj.append(b)
a = a.next_lex()
b = b.next_trotterjohnson()
assert a == b is None
assert {tuple(a) for a in l} == {tuple(a) for a in tj}
p = Permutation([2, 5, 1, 6, 3, 0, 4])
q = Permutation([[6], [5], [0, 1, 2, 3, 4]])
assert p.rank() == 1964
assert q.rank() == 870
assert Permutation([]).rank_nonlex() == 0
prank = p.rank_nonlex()
assert prank == 1600
assert Permutation.unrank_nonlex(7, 1600) == p
qrank = q.rank_nonlex()
assert qrank == 41
assert Permutation.unrank_nonlex(7, 41) == Permutation(q.array_form)
a = [Permutation.unrank_nonlex(4, i).array_form for i in range(24)]
assert a == [
[1, 2, 3, 0], [3, 2, 0, 1], [1, 3, 0, 2], [1, 2, 0, 3], [2, 3, 1, 0],
[2, 0, 3, 1], [3, 0, 1, 2], [2, 0, 1, 3], [1, 3, 2, 0], [3, 0, 2, 1],
[1, 0, 3, 2], [1, 0, 2, 3], [2, 1, 3, 0], [2, 3, 0, 1], [3, 1, 0, 2],
[2, 1, 0, 3], [3, 2, 1, 0], [0, 2, 3, 1], [0, 3, 1, 2], [0, 2, 1, 3],
[3, 1, 2, 0], [0, 3, 2, 1], [0, 1, 3, 2], [0, 1, 2, 3]]
N = 10
p1 = Permutation(a[0])
for i in range(1, N+1):
p1 = p1*Permutation(a[i])
p2 = Permutation.rmul_with_af(*[Permutation(h) for h in a[N::-1]])
assert p1 == p2
ok = []
p = Permutation([1, 0])
for i in range(3):
ok.append(p.array_form)
p = p.next_nonlex()
if p is None:
ok.append(None)
break
assert ok == [[1, 0], [0, 1], None]
assert Permutation([3, 2, 0, 1]).next_nonlex() == Permutation([1, 3, 0, 2])
assert [Permutation(pa).rank_nonlex() for pa in a] == list(range(24))
def test_mul():
a, b = [0, 2, 1, 3], [0, 1, 3, 2]
assert _af_rmul(a, b) == [0, 2, 3, 1]
assert _af_rmuln(a, b, list(range(4))) == [0, 2, 3, 1]
assert rmul(Permutation(a), Permutation(b)).array_form == [0, 2, 3, 1]
a = Permutation([0, 2, 1, 3])
b = (0, 1, 3, 2)
c = (3, 1, 2, 0)
assert Permutation.rmul(a, b, c) == Permutation([1, 2, 3, 0])
assert Permutation.rmul(a, c) == Permutation([3, 2, 1, 0])
raises(TypeError, lambda: Permutation.rmul(b, c))
n = 6
m = 8
a = [Permutation.unrank_nonlex(n, i).array_form for i in range(m)]
h = list(range(n))
for i in range(m):
h = _af_rmul(h, a[i])
h2 = _af_rmuln(*a[:i + 1])
assert h == h2
def test_args():
p = Permutation([(0, 3, 1, 2), (4, 5)])
assert p._cyclic_form is None
assert Permutation(p) == p
assert p.cyclic_form == [[0, 3, 1, 2], [4, 5]]
assert p._array_form == [3, 2, 0, 1, 5, 4]
p = Permutation((0, 3, 1, 2))
assert p._cyclic_form is None
assert p._array_form == [0, 3, 1, 2]
assert Permutation([0]) == Permutation((0, ))
assert Permutation([[0], [1]]) == Permutation(((0, ), (1, ))) == \
Permutation(((0, ), [1]))
assert Permutation([[1, 2]]) == Permutation([0, 2, 1])
assert Permutation([[1], [4, 2]]) == Permutation([0, 1, 4, 3, 2])
assert Permutation([[1], [4, 2]], size=1) == Permutation([0, 1, 4, 3, 2])
assert Permutation(
[[1], [4, 2]], size=6) == Permutation([0, 1, 4, 3, 2, 5])
assert Permutation([[0, 1], [0, 2]]) == Permutation(0, 1, 2)
assert Permutation([], size=3) == Permutation([0, 1, 2])
assert Permutation(3).list(5) == [0, 1, 2, 3, 4]
assert Permutation(3).list(-1) == []
assert Permutation(5)(1, 2).list(-1) == [0, 2, 1]
assert Permutation(5)(1, 2).list() == [0, 2, 1, 3, 4, 5]
raises(ValueError, lambda: Permutation([1, 2], [0]))
# enclosing brackets needed
raises(ValueError, lambda: Permutation([[1, 2], 0]))
# enclosing brackets needed on 0
raises(ValueError, lambda: Permutation([1, 1, 0]))
raises(ValueError, lambda: Permutation([4, 5], size=10)) # where are 0-3?
# but this is ok because cycles imply that only those listed moved
assert Permutation(4, 5) == Permutation([0, 1, 2, 3, 5, 4])
def test_Cycle():
assert str(Cycle()) == '()'
assert Cycle(Cycle(1,2)) == Cycle(1, 2)
assert Cycle(1,2).copy() == Cycle(1,2)
assert list(Cycle(1, 3, 2)) == [0, 3, 1, 2]
assert Cycle(1, 2)(2, 3) == Cycle(1, 3, 2)
assert Cycle(1, 2)(2, 3)(4, 5) == Cycle(1, 3, 2)(4, 5)
assert Permutation(Cycle(1, 2)(2, 1, 0, 3)).cyclic_form, Cycle(0, 2, 1)
raises(ValueError, lambda: Cycle().list())
assert Cycle(1, 2).list() == [0, 2, 1]
assert Cycle(1, 2).list(4) == [0, 2, 1, 3]
assert Cycle(3).list(2) == [0, 1]
assert Cycle(3).list(6) == [0, 1, 2, 3, 4, 5]
assert Permutation(Cycle(1, 2), size=4) == \
Permutation([0, 2, 1, 3])
assert str(Cycle(1, 2)(4, 5)) == '(1 2)(4 5)'
assert str(Cycle(1, 2)) == '(1 2)'
assert Cycle(Permutation(list(range(3)))) == Cycle()
assert Cycle(1, 2).list() == [0, 2, 1]
assert Cycle(1, 2).list(4) == [0, 2, 1, 3]
assert Cycle().size == 0
raises(ValueError, lambda: Cycle((1, 2)))
raises(ValueError, lambda: Cycle(1, 2, 1))
raises(TypeError, lambda: Cycle(1, 2)*{})
raises(ValueError, lambda: Cycle(4)[a])
raises(ValueError, lambda: Cycle(2, -4, 3))
# check round-trip
p = Permutation([[1, 2], [4, 3]], size=5)
assert Permutation(Cycle(p)) == p
def test_from_sequence():
assert Permutation.from_sequence('SymPy') == Permutation(4)(0, 1, 3)
assert Permutation.from_sequence('SymPy', key=lambda x: x.lower()) == \
Permutation(4)(0, 2)(1, 3)
def test_resize():
p = Permutation(0, 1, 2)
assert p.resize(5) == Permutation(0, 1, 2, size=5)
assert p.resize(4) == Permutation(0, 1, 2, size=4)
assert p.resize(3) == p
raises(ValueError, lambda: p.resize(2))
p = Permutation(0, 1, 2)(3, 4)(5, 6)
assert p.resize(3) == Permutation(0, 1, 2)
raises(ValueError, lambda: p.resize(4))
def test_printing_cyclic():
p1 = Permutation([0, 2, 1])
assert repr(p1) == 'Permutation(1, 2)'
assert str(p1) == '(1 2)'
p2 = Permutation()
assert repr(p2) == 'Permutation()'
assert str(p2) == '()'
p3 = Permutation([1, 2, 0, 3])
assert repr(p3) == 'Permutation(3)(0, 1, 2)'
def test_printing_non_cyclic():
p1 = Permutation([0, 1, 2, 3, 4, 5])
assert srepr(p1, perm_cyclic=False) == 'Permutation([], size=6)'
assert sstr(p1, perm_cyclic=False) == 'Permutation([], size=6)'
p2 = Permutation([0, 1, 2])
assert srepr(p2, perm_cyclic=False) == 'Permutation([0, 1, 2])'
assert sstr(p2, perm_cyclic=False) == 'Permutation([0, 1, 2])'
p3 = Permutation([0, 2, 1])
assert srepr(p3, perm_cyclic=False) == 'Permutation([0, 2, 1])'
assert sstr(p3, perm_cyclic=False) == 'Permutation([0, 2, 1])'
p4 = Permutation([0, 1, 3, 2, 4, 5, 6, 7])
assert srepr(p4, perm_cyclic=False) == 'Permutation([0, 1, 3, 2], size=8)'
def test_deprecated_print_cyclic():
p = Permutation(0, 1, 2)
try:
Permutation.print_cyclic = True
with warns_deprecated_sympy():
assert sstr(p) == '(0 1 2)'
with warns_deprecated_sympy():
assert srepr(p) == 'Permutation(0, 1, 2)'
with warns_deprecated_sympy():
assert pretty(p) == '(0 1 2)'
with warns_deprecated_sympy():
assert latex(p) == r'\left( 0\; 1\; 2\right)'
Permutation.print_cyclic = False
with warns_deprecated_sympy():
assert sstr(p) == 'Permutation([1, 2, 0])'
with warns_deprecated_sympy():
assert srepr(p) == 'Permutation([1, 2, 0])'
with warns_deprecated_sympy():
assert pretty(p, use_unicode=False) == '/0 1 2\\\n\\1 2 0/'
with warns_deprecated_sympy():
assert latex(p) == \
r'\begin{pmatrix} 0 & 1 & 2 \\ 1 & 2 & 0 \end{pmatrix}'
finally:
Permutation.print_cyclic = None
def test_permutation_equality():
a = Permutation(0, 1, 2)
b = Permutation(0, 1, 2)
assert Eq(a, b) is S.true
c = Permutation(0, 2, 1)
assert Eq(a, c) is S.false
d = Permutation(0, 1, 2, size=4)
assert unchanged(Eq, a, d)
e = Permutation(0, 2, 1, size=4)
assert unchanged(Eq, a, e)
i = Permutation()
assert unchanged(Eq, i, 0)
assert unchanged(Eq, 0, i)
def test_issue_17661():
c1 = Cycle(1,2)
c2 = Cycle(1,2)
assert c1 == c2
assert repr(c1) == 'Cycle(1, 2)'
assert c1 == c2
def test_permutation_apply():
x = Symbol('x')
p = Permutation(0, 1, 2)
assert p.apply(0) == 1
assert isinstance(p.apply(0), Integer)
assert p.apply(x) == AppliedPermutation(p, x)
assert AppliedPermutation(p, x).subs(x, 0) == 1
x = Symbol('x', integer=False)
raises(NotImplementedError, lambda: p.apply(x))
x = Symbol('x', negative=True)
raises(NotImplementedError, lambda: p.apply(x))
def test_AppliedPermutation():
x = Symbol('x')
p = Permutation(0, 1, 2)
raises(ValueError, lambda: AppliedPermutation((0, 1, 2), x))
assert AppliedPermutation(p, 1, evaluate=True) == 2
assert AppliedPermutation(p, 1, evaluate=False).__class__ == \
AppliedPermutation
|
ea9ca12d85791ee5efc7adebfa01951ebf0b4ab1915dca43b9d8459fd7c1a97f | from sympy.combinatorics.subsets import Subset, ksubsets
from sympy.testing.pytest import raises
def test_subset():
a = Subset(['c', 'd'], ['a', 'b', 'c', 'd'])
assert a.next_binary() == Subset(['b'], ['a', 'b', 'c', 'd'])
assert a.prev_binary() == Subset(['c'], ['a', 'b', 'c', 'd'])
assert a.next_lexicographic() == Subset(['d'], ['a', 'b', 'c', 'd'])
assert a.prev_lexicographic() == Subset(['c'], ['a', 'b', 'c', 'd'])
assert a.next_gray() == Subset(['c'], ['a', 'b', 'c', 'd'])
assert a.prev_gray() == Subset(['d'], ['a', 'b', 'c', 'd'])
assert a.rank_binary == 3
assert a.rank_lexicographic == 14
assert a.rank_gray == 2
assert a.cardinality == 16
assert a.size == 2
assert Subset.bitlist_from_subset(a, ['a', 'b', 'c', 'd']) == '0011'
a = Subset([2, 5, 7], [1, 2, 3, 4, 5, 6, 7])
assert a.next_binary() == Subset([2, 5, 6], [1, 2, 3, 4, 5, 6, 7])
assert a.prev_binary() == Subset([2, 5], [1, 2, 3, 4, 5, 6, 7])
assert a.next_lexicographic() == Subset([2, 6], [1, 2, 3, 4, 5, 6, 7])
assert a.prev_lexicographic() == Subset([2, 5, 6, 7], [1, 2, 3, 4, 5, 6, 7])
assert a.next_gray() == Subset([2, 5, 6, 7], [1, 2, 3, 4, 5, 6, 7])
assert a.prev_gray() == Subset([2, 5], [1, 2, 3, 4, 5, 6, 7])
assert a.rank_binary == 37
assert a.rank_lexicographic == 93
assert a.rank_gray == 57
assert a.cardinality == 128
superset = ['a', 'b', 'c', 'd']
assert Subset.unrank_binary(4, superset).rank_binary == 4
assert Subset.unrank_gray(10, superset).rank_gray == 10
superset = [1, 2, 3, 4, 5, 6, 7, 8, 9]
assert Subset.unrank_binary(33, superset).rank_binary == 33
assert Subset.unrank_gray(25, superset).rank_gray == 25
a = Subset([], ['a', 'b', 'c', 'd'])
i = 1
while a.subset != Subset(['d'], ['a', 'b', 'c', 'd']).subset:
a = a.next_lexicographic()
i = i + 1
assert i == 16
i = 1
while a.subset != Subset([], ['a', 'b', 'c', 'd']).subset:
a = a.prev_lexicographic()
i = i + 1
assert i == 16
raises(ValueError, lambda: Subset(['a', 'b'], ['a']))
raises(ValueError, lambda: Subset(['a'], ['b', 'c']))
raises(ValueError, lambda: Subset.subset_from_bitlist(['a', 'b'], '010'))
assert Subset(['a'], ['a', 'b']) != Subset(['b'], ['a', 'b'])
assert Subset(['a'], ['a', 'b']) != Subset(['a'], ['a', 'c'])
def test_ksubsets():
assert list(ksubsets([1, 2, 3], 2)) == [(1, 2), (1, 3), (2, 3)]
assert list(ksubsets([1, 2, 3, 4, 5], 2)) == [(1, 2), (1, 3), (1, 4),
(1, 5), (2, 3), (2, 4), (2, 5), (3, 4), (3, 5), (4, 5)]
|
877b4fca3300efd33d40c734ace960557537d65674b3fc6863f60856c573d058 | from sympy.combinatorics.free_groups import free_group, FreeGroup
from sympy.core import Symbol
from sympy.testing.pytest import raises
from sympy.core.numbers import oo
F, x, y, z = free_group("x, y, z")
def test_FreeGroup__init__():
x, y, z = map(Symbol, "xyz")
assert len(FreeGroup("x, y, z").generators) == 3
assert len(FreeGroup(x).generators) == 1
assert len(FreeGroup(("x", "y", "z"))) == 3
assert len(FreeGroup((x, y, z)).generators) == 3
def test_free_group():
G, a, b, c = free_group("a, b, c")
assert F.generators == (x, y, z)
assert x*z**2 in F
assert x in F
assert y*z**-1 in F
assert (y*z)**0 in F
assert a not in F
assert a**0 not in F
assert len(F) == 3
assert str(F) == '<free group on the generators (x, y, z)>'
assert not F == G
assert F.order() is oo
assert F.is_abelian == False
assert F.center() == {F.identity}
(e,) = free_group("")
assert e.order() == 1
assert e.generators == ()
assert e.elements == {e.identity}
assert e.is_abelian == True
def test_FreeGroup__hash__():
assert hash(F)
def test_FreeGroup__eq__():
assert free_group("x, y, z")[0] == free_group("x, y, z")[0]
assert free_group("x, y, z")[0] is free_group("x, y, z")[0]
assert free_group("x, y, z")[0] != free_group("a, x, y")[0]
assert free_group("x, y, z")[0] is not free_group("a, x, y")[0]
assert free_group("x, y")[0] != free_group("x, y, z")[0]
assert free_group("x, y")[0] is not free_group("x, y, z")[0]
assert free_group("x, y, z")[0] != free_group("x, y")[0]
assert free_group("x, y, z")[0] is not free_group("x, y")[0]
def test_FreeGroup__getitem__():
assert F[0:] == FreeGroup("x, y, z")
assert F[1:] == FreeGroup("y, z")
assert F[2:] == FreeGroup("z")
def test_FreeGroupElm__hash__():
assert hash(x*y*z)
def test_FreeGroupElm_copy():
f = x*y*z**3
g = f.copy()
h = x*y*z**7
assert f == g
assert f != h
def test_FreeGroupElm_inverse():
assert x.inverse() == x**-1
assert (x*y).inverse() == y**-1*x**-1
assert (y*x*y**-1).inverse() == y*x**-1*y**-1
assert (y**2*x**-1).inverse() == x*y**-2
def test_FreeGroupElm_type_error():
raises(TypeError, lambda: 2/x)
raises(TypeError, lambda: x**2 + y**2)
raises(TypeError, lambda: x/2)
def test_FreeGroupElm_methods():
assert (x**0).order() == 1
assert (y**2).order() is oo
assert (x**-1*y).commutator(x) == y**-1*x**-1*y*x
assert len(x**2*y**-1) == 3
assert len(x**-1*y**3*z) == 5
def test_FreeGroupElm_eliminate_word():
w = x**5*y*x**2*y**-4*x
assert w.eliminate_word( x, x**2 ) == x**10*y*x**4*y**-4*x**2
w3 = x**2*y**3*x**-1*y
assert w3.eliminate_word(x, x**2) == x**4*y**3*x**-2*y
assert w3.eliminate_word(x, y) == y**5
assert w3.eliminate_word(x, y**4) == y**8
assert w3.eliminate_word(y, x**-1) == x**-3
assert w3.eliminate_word(x, y*z) == y*z*y*z*y**3*z**-1
assert (y**-3).eliminate_word(y, x**-1*z**-1) == z*x*z*x*z*x
#assert w3.eliminate_word(x, y*x) == y*x*y*x**2*y*x*y*x*y*x*z**3
#assert w3.eliminate_word(x, x*y) == x*y*x**2*y*x*y*x*y*x*y*z**3
def test_FreeGroupElm_array_form():
assert (x*z).array_form == ((Symbol('x'), 1), (Symbol('z'), 1))
assert (x**2*z*y*x**-2).array_form == \
((Symbol('x'), 2), (Symbol('z'), 1), (Symbol('y'), 1), (Symbol('x'), -2))
assert (x**-2*y**-1).array_form == ((Symbol('x'), -2), (Symbol('y'), -1))
def test_FreeGroupElm_letter_form():
assert (x**3).letter_form == (Symbol('x'), Symbol('x'), Symbol('x'))
assert (x**2*z**-2*x).letter_form == \
(Symbol('x'), Symbol('x'), -Symbol('z'), -Symbol('z'), Symbol('x'))
def test_FreeGroupElm_ext_rep():
assert (x**2*z**-2*x).ext_rep == \
(Symbol('x'), 2, Symbol('z'), -2, Symbol('x'), 1)
assert (x**-2*y**-1).ext_rep == (Symbol('x'), -2, Symbol('y'), -1)
assert (x*z).ext_rep == (Symbol('x'), 1, Symbol('z'), 1)
def test_FreeGroupElm__mul__pow__():
x1 = x.group.dtype(((Symbol('x'), 1),))
assert x**2 == x1*x
assert (x**2*y*x**-2)**4 == x**2*y**4*x**-2
assert (x**2)**2 == x**4
assert (x**-1)**-1 == x
assert (x**-1)**0 == F.identity
assert (y**2)**-2 == y**-4
assert x**2*x**-1 == x
assert x**2*y**2*y**-1 == x**2*y
assert x*x**-1 == F.identity
assert x/x == F.identity
assert x/x**2 == x**-1
assert (x**2*y)/(x**2*y**-1) == x**2*y**2*x**-2
assert (x**2*y)/(y**-1*x**2) == x**2*y*x**-2*y
assert x*(x**-1*y*z*y**-1) == y*z*y**-1
assert x**2*(x**-2*y**-1*z**2*y) == y**-1*z**2*y
def test_FreeGroupElm__len__():
assert len(x**5*y*x**2*y**-4*x) == 13
assert len(x**17) == 17
assert len(y**0) == 0
def test_FreeGroupElm_comparison():
assert not (x*y == y*x)
assert x**0 == y**0
assert x**2 < y**3
assert not x**3 < y**2
assert x*y < x**2*y
assert x**2*y**2 < y**4
assert not y**4 < y**-4
assert not y**4 < x**-4
assert y**-2 < y**2
assert x**2 <= y**2
assert x**2 <= x**2
assert not y*z > z*y
assert x > x**-1
assert not x**2 >= y**2
def test_FreeGroupElm_syllables():
w = x**5*y*x**2*y**-4*x
assert w.number_syllables() == 5
assert w.exponent_syllable(2) == 2
assert w.generator_syllable(3) == Symbol('y')
assert w.sub_syllables(1, 2) == y
assert w.sub_syllables(3, 3) == F.identity
def test_FreeGroup_exponents():
w1 = x**2*y**3
assert w1.exponent_sum(x) == 2
assert w1.exponent_sum(x**-1) == -2
assert w1.generator_count(x) == 2
w2 = x**2*y**4*x**-3
assert w2.exponent_sum(x) == -1
assert w2.generator_count(x) == 5
def test_FreeGroup_generators():
assert (x**2*y**4*z**-1).contains_generators() == {x, y, z}
assert (x**-1*y**3).contains_generators() == {x, y}
def test_FreeGroupElm_words():
w = x**5*y*x**2*y**-4*x
assert w.subword(2, 6) == x**3*y
assert w.subword(3, 2) == F.identity
assert w.subword(6, 10) == x**2*y**-2
assert w.substituted_word(0, 7, y**-1) == y**-1*x*y**-4*x
assert w.substituted_word(0, 7, y**2*x) == y**2*x**2*y**-4*x
|
e6946cc39e44432af7d66529deec1c6b0ffea6eb57709203ce603b912edc5d43 | from sympy.concrete.products import (Product, product)
from sympy.concrete.summations import Sum
from sympy.core.function import (Derivative, Function, diff)
from sympy.core.numbers import (Rational, oo, pi)
from sympy.core.singleton import S
from sympy.core.symbol import (Dummy, Symbol, symbols)
from sympy.functions.combinatorial.factorials import (rf, factorial)
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.trigonometric import (cos, sin)
from sympy.functions.special.tensor_functions import KroneckerDelta
from sympy.simplify.combsimp import combsimp
from sympy.simplify.simplify import simplify
from sympy.testing.pytest import raises
a, k, n, m, x = symbols('a,k,n,m,x', integer=True)
f = Function('f')
def test_karr_convention():
# Test the Karr product convention that we want to hold.
# See his paper "Summation in Finite Terms" for a detailed
# reasoning why we really want exactly this definition.
# The convention is described for sums on page 309 and
# essentially in section 1.4, definition 3. For products
# we can find in analogy:
#
# \prod_{m <= i < n} f(i) 'has the obvious meaning' for m < n
# \prod_{m <= i < n} f(i) = 0 for m = n
# \prod_{m <= i < n} f(i) = 1 / \prod_{n <= i < m} f(i) for m > n
#
# It is important to note that he defines all products with
# the upper limit being *exclusive*.
# In contrast, SymPy and the usual mathematical notation has:
#
# prod_{i = a}^b f(i) = f(a) * f(a+1) * ... * f(b-1) * f(b)
#
# with the upper limit *inclusive*. So translating between
# the two we find that:
#
# \prod_{m <= i < n} f(i) = \prod_{i = m}^{n-1} f(i)
#
# where we intentionally used two different ways to typeset the
# products and its limits.
i = Symbol("i", integer=True)
k = Symbol("k", integer=True)
j = Symbol("j", integer=True, positive=True)
# A simple example with a concrete factors and symbolic limits.
# The normal product: m = k and n = k + j and therefore m < n:
m = k
n = k + j
a = m
b = n - 1
S1 = Product(i**2, (i, a, b)).doit()
# The reversed product: m = k + j and n = k and therefore m > n:
m = k + j
n = k
a = m
b = n - 1
S2 = Product(i**2, (i, a, b)).doit()
assert S1 * S2 == 1
# Test the empty product: m = k and n = k and therefore m = n:
m = k
n = k
a = m
b = n - 1
Sz = Product(i**2, (i, a, b)).doit()
assert Sz == 1
# Another example this time with an unspecified factor and
# numeric limits. (We can not do both tests in the same example.)
f = Function("f")
# The normal product with m < n:
m = 2
n = 11
a = m
b = n - 1
S1 = Product(f(i), (i, a, b)).doit()
# The reversed product with m > n:
m = 11
n = 2
a = m
b = n - 1
S2 = Product(f(i), (i, a, b)).doit()
assert simplify(S1 * S2) == 1
# Test the empty product with m = n:
m = 5
n = 5
a = m
b = n - 1
Sz = Product(f(i), (i, a, b)).doit()
assert Sz == 1
def test_karr_proposition_2a():
# Test Karr, page 309, proposition 2, part a
i, u, v = symbols('i u v', integer=True)
def test_the_product(m, n):
# g
g = i**3 + 2*i**2 - 3*i
# f = Delta g
f = simplify(g.subs(i, i+1) / g)
# The product
a = m
b = n - 1
P = Product(f, (i, a, b)).doit()
# Test if Product_{m <= i < n} f(i) = g(n) / g(m)
assert combsimp(P / (g.subs(i, n) / g.subs(i, m))) == 1
# m < n
test_the_product(u, u + v)
# m = n
test_the_product(u, u)
# m > n
test_the_product(u + v, u)
def test_karr_proposition_2b():
# Test Karr, page 309, proposition 2, part b
i, u, v, w = symbols('i u v w', integer=True)
def test_the_product(l, n, m):
# Productmand
s = i**3
# First product
a = l
b = n - 1
S1 = Product(s, (i, a, b)).doit()
# Second product
a = l
b = m - 1
S2 = Product(s, (i, a, b)).doit()
# Third product
a = m
b = n - 1
S3 = Product(s, (i, a, b)).doit()
# Test if S1 = S2 * S3 as required
assert combsimp(S1 / (S2 * S3)) == 1
# l < m < n
test_the_product(u, u + v, u + v + w)
# l < m = n
test_the_product(u, u + v, u + v)
# l < m > n
test_the_product(u, u + v + w, v)
# l = m < n
test_the_product(u, u, u + v)
# l = m = n
test_the_product(u, u, u)
# l = m > n
test_the_product(u + v, u + v, u)
# l > m < n
test_the_product(u + v, u, u + w)
# l > m = n
test_the_product(u + v, u, u)
# l > m > n
test_the_product(u + v + w, u + v, u)
def test_simple_products():
assert product(2, (k, a, n)) == 2**(n - a + 1)
assert product(k, (k, 1, n)) == factorial(n)
assert product(k**3, (k, 1, n)) == factorial(n)**3
assert product(k + 1, (k, 0, n - 1)) == factorial(n)
assert product(k + 1, (k, a, n - 1)) == rf(1 + a, n - a)
assert product(cos(k), (k, 0, 5)) == cos(1)*cos(2)*cos(3)*cos(4)*cos(5)
assert product(cos(k), (k, 3, 5)) == cos(3)*cos(4)*cos(5)
assert product(cos(k), (k, 1, Rational(5, 2))) != cos(1)*cos(2)
assert isinstance(product(k**k, (k, 1, n)), Product)
assert Product(x**k, (k, 1, n)).variables == [k]
raises(ValueError, lambda: Product(n))
raises(ValueError, lambda: Product(n, k))
raises(ValueError, lambda: Product(n, k, 1))
raises(ValueError, lambda: Product(n, k, 1, 10))
raises(ValueError, lambda: Product(n, (k, 1)))
assert product(1, (n, 1, oo)) == 1 # issue 8301
assert product(2, (n, 1, oo)) is oo
assert product(-1, (n, 1, oo)).func is Product
def test_multiple_products():
assert product(x, (n, 1, k), (k, 1, m)) == x**(m**2/2 + m/2)
assert product(f(n), (
n, 1, m), (m, 1, k)) == Product(f(n), (n, 1, m), (m, 1, k)).doit()
assert Product(f(n), (m, 1, k), (n, 1, k)).doit() == \
Product(Product(f(n), (m, 1, k)), (n, 1, k)).doit() == \
product(f(n), (m, 1, k), (n, 1, k)) == \
product(product(f(n), (m, 1, k)), (n, 1, k)) == \
Product(f(n)**k, (n, 1, k))
assert Product(
x, (x, 1, k), (k, 1, n)).doit() == Product(factorial(k), (k, 1, n))
assert Product(x**k, (n, 1, k), (k, 1, m)).variables == [n, k]
def test_rational_products():
assert product(1 + 1/k, (k, 1, n)) == rf(2, n)/factorial(n)
def test_special_products():
# Wallis product
assert product((4*k)**2 / (4*k**2 - 1), (k, 1, n)) == \
4**n*factorial(n)**2/rf(S.Half, n)/rf(Rational(3, 2), n)
# Euler's product formula for sin
assert product(1 + a/k**2, (k, 1, n)) == \
rf(1 - sqrt(-a), n)*rf(1 + sqrt(-a), n)/factorial(n)**2
def test__eval_product():
from sympy.abc import i, n
# issue 4809
a = Function('a')
assert product(2*a(i), (i, 1, n)) == 2**n * Product(a(i), (i, 1, n))
# issue 4810
assert product(2**i, (i, 1, n)) == 2**(n/2 + n**2/2)
k, m = symbols('k m', integer=True)
assert product(2**i, (i, k, m)) == 2**(-k**2/2 + k/2 + m**2/2 + m/2)
n = Symbol('n', negative=True, integer=True)
p = Symbol('p', positive=True, integer=True)
assert product(2**i, (i, n, p)) == 2**(-n**2/2 + n/2 + p**2/2 + p/2)
assert product(2**i, (i, p, n)) == 2**(n**2/2 + n/2 - p**2/2 + p/2)
def test_product_pow():
# issue 4817
assert product(2**f(k), (k, 1, n)) == 2**Sum(f(k), (k, 1, n))
assert product(2**(2*f(k)), (k, 1, n)) == 2**Sum(2*f(k), (k, 1, n))
def test_infinite_product():
# issue 5737
assert isinstance(Product(2**(1/factorial(n)), (n, 0, oo)), Product)
def test_conjugate_transpose():
p = Product(x**k, (k, 1, 3))
assert p.adjoint().doit() == p.doit().adjoint()
assert p.conjugate().doit() == p.doit().conjugate()
assert p.transpose().doit() == p.doit().transpose()
A, B = symbols("A B", commutative=False)
p = Product(A*B**k, (k, 1, 3))
assert p.adjoint().doit() == p.doit().adjoint()
assert p.conjugate().doit() == p.doit().conjugate()
assert p.transpose().doit() == p.doit().transpose()
p = Product(B**k*A, (k, 1, 3))
assert p.adjoint().doit() == p.doit().adjoint()
assert p.conjugate().doit() == p.doit().conjugate()
assert p.transpose().doit() == p.doit().transpose()
def test_simplify_prod():
y, t, b, c = symbols('y, t, b, c', integer = True)
_simplify = lambda e: simplify(e, doit=False)
assert _simplify(Product(x*y, (x, n, m), (y, a, k)) * \
Product(y, (x, n, m), (y, a, k))) == \
Product(x*y**2, (x, n, m), (y, a, k))
assert _simplify(3 * y* Product(x, (x, n, m)) * Product(x, (x, m + 1, a))) \
== 3 * y * Product(x, (x, n, a))
assert _simplify(Product(x, (x, k + 1, a)) * Product(x, (x, n, k))) == \
Product(x, (x, n, a))
assert _simplify(Product(x, (x, k + 1, a)) * Product(x + 1, (x, n, k))) == \
Product(x, (x, k + 1, a)) * Product(x + 1, (x, n, k))
assert _simplify(Product(x, (t, a, b)) * Product(y, (t, a, b)) * \
Product(x, (t, b+1, c))) == Product(x*y, (t, a, b)) * \
Product(x, (t, b+1, c))
assert _simplify(Product(x, (t, a, b)) * Product(x, (t, b+1, c)) * \
Product(y, (t, a, b))) == Product(x*y, (t, a, b)) * \
Product(x, (t, b+1, c))
def test_change_index():
b, y, c, d, z = symbols('b, y, c, d, z', integer = True)
assert Product(x, (x, a, b)).change_index(x, x + 1, y) == \
Product(y - 1, (y, a + 1, b + 1))
assert Product(x**2, (x, a, b)).change_index(x, x - 1) == \
Product((x + 1)**2, (x, a - 1, b - 1))
assert Product(x**2, (x, a, b)).change_index(x, -x, y) == \
Product((-y)**2, (y, -b, -a))
assert Product(x, (x, a, b)).change_index(x, -x - 1) == \
Product(-x - 1, (x, - b - 1, -a - 1))
assert Product(x*y, (x, a, b), (y, c, d)).change_index(x, x - 1, z) == \
Product((z + 1)*y, (z, a - 1, b - 1), (y, c, d))
def test_reorder():
b, y, c, d, z = symbols('b, y, c, d, z', integer = True)
assert Product(x*y, (x, a, b), (y, c, d)).reorder((0, 1)) == \
Product(x*y, (y, c, d), (x, a, b))
assert Product(x, (x, a, b), (x, c, d)).reorder((0, 1)) == \
Product(x, (x, c, d), (x, a, b))
assert Product(x*y + z, (x, a, b), (z, m, n), (y, c, d)).reorder(\
(2, 0), (0, 1)) == Product(x*y + z, (z, m, n), (y, c, d), (x, a, b))
assert Product(x*y*z, (x, a, b), (y, c, d), (z, m, n)).reorder(\
(0, 1), (1, 2), (0, 2)) == \
Product(x*y*z, (x, a, b), (z, m, n), (y, c, d))
assert Product(x*y*z, (x, a, b), (y, c, d), (z, m, n)).reorder(\
(x, y), (y, z), (x, z)) == \
Product(x*y*z, (x, a, b), (z, m, n), (y, c, d))
assert Product(x*y, (x, a, b), (y, c, d)).reorder((x, 1)) == \
Product(x*y, (y, c, d), (x, a, b))
assert Product(x*y, (x, a, b), (y, c, d)).reorder((y, x)) == \
Product(x*y, (y, c, d), (x, a, b))
def test_Product_is_convergent():
assert Product(1/n**2, (n, 1, oo)).is_convergent() is S.false
assert Product(exp(1/n**2), (n, 1, oo)).is_convergent() is S.true
assert Product(1/n, (n, 1, oo)).is_convergent() is S.false
assert Product(1 + 1/n, (n, 1, oo)).is_convergent() is S.false
assert Product(1 + 1/n**2, (n, 1, oo)).is_convergent() is S.true
def test_reverse_order():
x, y, a, b, c, d= symbols('x, y, a, b, c, d', integer = True)
assert Product(x, (x, 0, 3)).reverse_order(0) == Product(1/x, (x, 4, -1))
assert Product(x*y, (x, 1, 5), (y, 0, 6)).reverse_order(0, 1) == \
Product(x*y, (x, 6, 0), (y, 7, -1))
assert Product(x, (x, 1, 2)).reverse_order(0) == Product(1/x, (x, 3, 0))
assert Product(x, (x, 1, 3)).reverse_order(0) == Product(1/x, (x, 4, 0))
assert Product(x, (x, 1, a)).reverse_order(0) == Product(1/x, (x, a + 1, 0))
assert Product(x, (x, a, 5)).reverse_order(0) == Product(1/x, (x, 6, a - 1))
assert Product(x, (x, a + 1, a + 5)).reverse_order(0) == \
Product(1/x, (x, a + 6, a))
assert Product(x, (x, a + 1, a + 2)).reverse_order(0) == \
Product(1/x, (x, a + 3, a))
assert Product(x, (x, a + 1, a + 1)).reverse_order(0) == \
Product(1/x, (x, a + 2, a))
assert Product(x, (x, a, b)).reverse_order(0) == Product(1/x, (x, b + 1, a - 1))
assert Product(x, (x, a, b)).reverse_order(x) == Product(1/x, (x, b + 1, a - 1))
assert Product(x*y, (x, a, b), (y, 2, 5)).reverse_order(x, 1) == \
Product(x*y, (x, b + 1, a - 1), (y, 6, 1))
assert Product(x*y, (x, a, b), (y, 2, 5)).reverse_order(y, x) == \
Product(x*y, (x, b + 1, a - 1), (y, 6, 1))
def test_issue_9983():
n = Symbol('n', integer=True, positive=True)
p = Product(1 + 1/n**Rational(2, 3), (n, 1, oo))
assert p.is_convergent() is S.false
assert product(1 + 1/n**Rational(2, 3), (n, 1, oo)) == p.doit()
def test_issue_13546():
n = Symbol('n')
k = Symbol('k')
p = Product(n + 1 / 2**k, (k, 0, n-1)).doit()
assert p.subs(n, 2).doit() == Rational(15, 2)
def test_issue_14036():
a, n = symbols('a n')
assert product(1 - a**2 / (n*pi)**2, [n, 1, oo]) != 0
def test_rewrite_Sum():
assert Product(1 - S.Half**2/k**2, (k, 1, oo)).rewrite(Sum) == \
exp(Sum(log(1 - 1/(4*k**2)), (k, 1, oo)))
def test_KroneckerDelta_Product():
y = Symbol('y')
assert Product(x*KroneckerDelta(x, y), (x, 0, 1)).doit() == 0
def test_issue_20848():
_i = Dummy('i')
t, y, z = symbols('t y z')
assert diff(Product(x, (y, 1, z)), x).as_dummy() == Sum(Product(x, (y, 1, _i - 1))*Product(x, (y, _i + 1, z)), (_i, 1, z)).as_dummy()
assert diff(Product(x, (y, 1, z)), x).doit() == x**z*z/x
assert diff(Product(x, (y, x, z)), x) == Derivative(Product(x, (y, x, z)), x)
assert diff(Product(t, (x, 1, z)), x) == S(0)
assert Product(sin(n*x), (n, -1, 1)).diff(x).doit() == S(0)
|
fe2dd6180c67bcb7754eebf31ab22f43b624f88e85de65fae3049d136a772c42 | from sympy.concrete.guess import (
find_simple_recurrence_vector,
find_simple_recurrence,
rationalize,
guess_generating_function_rational,
guess_generating_function,
guess
)
from sympy.concrete.products import Product
from sympy.core.function import Function
from sympy.core.numbers import Rational
from sympy.core.singleton import S
from sympy.core.symbol import (Symbol, symbols)
from sympy.core.sympify import sympify
from sympy.functions.combinatorial.factorials import (RisingFactorial, factorial)
from sympy.functions.combinatorial.numbers import fibonacci
from sympy.functions.elementary.exponential import exp
def test_find_simple_recurrence_vector():
assert find_simple_recurrence_vector(
[fibonacci(k) for k in range(12)]) == [1, -1, -1]
def test_find_simple_recurrence():
a = Function('a')
n = Symbol('n')
assert find_simple_recurrence([fibonacci(k) for k in range(12)]) == (
-a(n) - a(n + 1) + a(n + 2))
f = Function('a')
i = Symbol('n')
a = [1, 1, 1]
for k in range(15): a.append(5*a[-1]-3*a[-2]+8*a[-3])
assert find_simple_recurrence(a, A=f, N=i) == (
-8*f(i) + 3*f(i + 1) - 5*f(i + 2) + f(i + 3))
assert find_simple_recurrence([0, 2, 15, 74, 12, 3, 0,
1, 2, 85, 4, 5, 63]) == 0
def test_rationalize():
from mpmath import cos, pi, mpf
assert rationalize(cos(pi/3)) == S.Half
assert rationalize(mpf("0.333333333333333")) == Rational(1, 3)
assert rationalize(mpf("-0.333333333333333")) == Rational(-1, 3)
assert rationalize(pi, maxcoeff = 250) == Rational(355, 113)
def test_guess_generating_function_rational():
x = Symbol('x')
assert guess_generating_function_rational([fibonacci(k)
for k in range(5, 15)]) == ((3*x + 5)/(-x**2 - x + 1))
def test_guess_generating_function():
x = Symbol('x')
assert guess_generating_function([fibonacci(k)
for k in range(5, 15)])['ogf'] == ((3*x + 5)/(-x**2 - x + 1))
assert guess_generating_function(
[1, 2, 5, 14, 41, 124, 383, 1200, 3799, 12122, 38919])['ogf'] == (
(1/(x**4 + 2*x**2 - 4*x + 1))**S.Half)
assert guess_generating_function(sympify(
"[3/2, 11/2, 0, -121/2, -363/2, 121, 4719/2, 11495/2, -8712, -178717/2]")
)['ogf'] == (x + Rational(3, 2))/(11*x**2 - 3*x + 1)
assert guess_generating_function([factorial(k) for k in range(12)],
types=['egf'])['egf'] == 1/(-x + 1)
assert guess_generating_function([k+1 for k in range(12)],
types=['egf']) == {'egf': (x + 1)*exp(x), 'lgdegf': (x + 2)/(x + 1)}
def test_guess():
i0, i1 = symbols('i0 i1')
assert guess([1, 2, 6, 24, 120], evaluate=False) == [Product(i1 + 1, (i1, 1, i0 - 1))]
assert guess([1, 2, 6, 24, 120]) == [RisingFactorial(2, i0 - 1)]
assert guess([1, 2, 7, 42, 429, 7436, 218348, 10850216], niter=4) == [
2**(i0 - 1)*(Rational(27, 16))**(i0**2/2 - 3*i0/2 +
1)*Product(RisingFactorial(Rational(5, 3), i1 - 1)*RisingFactorial(Rational(7, 3), i1
- 1)/(RisingFactorial(Rational(3, 2), i1 - 1)*RisingFactorial(Rational(5, 2), i1 -
1)), (i1, 1, i0 - 1))]
assert guess([1, 0, 2]) == []
x, y = symbols('x y')
guess([1, 2, 6, 24, 120], variables=[x, y]) == [RisingFactorial(2, x - 1)]
|
fb1f42cad5cf484f9e75572a871694765d23d7f015be09577955716ca6a95cfd | """Tests for Gosper's algorithm for hypergeometric summation. """
from sympy.core.numbers import (Rational, pi)
from sympy.core.singleton import S
from sympy.core.symbol import Symbol
from sympy.functions.combinatorial.factorials import (binomial, factorial)
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.special.gamma_functions import gamma
from sympy.polys.polytools import Poly
from sympy.simplify.simplify import simplify
from sympy.abc import a, b, j, k, m, n, r, x
from sympy.concrete.gosper import gosper_normal, gosper_sum, gosper_term
def test_gosper_normal():
eq = 4*n + 5, 2*(4*n + 1)*(2*n + 3), n
assert gosper_normal(*eq) == \
(Poly(Rational(1, 4), n), Poly(n + Rational(3, 2)), Poly(n + Rational(1, 4)))
assert gosper_normal(*eq, polys=False) == \
(Rational(1, 4), n + Rational(3, 2), n + Rational(1, 4))
def test_gosper_term():
assert gosper_term((4*k + 1)*factorial(
k)/factorial(2*k + 1), k) == (-k - S.Half)/(k + Rational(1, 4))
def test_gosper_sum():
assert gosper_sum(1, (k, 0, n)) == 1 + n
assert gosper_sum(k, (k, 0, n)) == n*(1 + n)/2
assert gosper_sum(k**2, (k, 0, n)) == n*(1 + n)*(1 + 2*n)/6
assert gosper_sum(k**3, (k, 0, n)) == n**2*(1 + n)**2/4
assert gosper_sum(2**k, (k, 0, n)) == 2*2**n - 1
assert gosper_sum(factorial(k), (k, 0, n)) is None
assert gosper_sum(binomial(n, k), (k, 0, n)) is None
assert gosper_sum(factorial(k)/k**2, (k, 0, n)) is None
assert gosper_sum((k - 3)*factorial(k), (k, 0, n)) is None
assert gosper_sum(k*factorial(k), k) == factorial(k)
assert gosper_sum(
k*factorial(k), (k, 0, n)) == n*factorial(n) + factorial(n) - 1
assert gosper_sum((-1)**k*binomial(n, k), (k, 0, n)) == 0
assert gosper_sum((
-1)**k*binomial(n, k), (k, 0, m)) == -(-1)**m*(m - n)*binomial(n, m)/n
assert gosper_sum((4*k + 1)*factorial(k)/factorial(2*k + 1), (k, 0, n)) == \
(2*factorial(2*n + 1) - factorial(n))/factorial(2*n + 1)
# issue 6033:
assert gosper_sum(
n*(n + a + b)*a**n*b**n/(factorial(n + a)*factorial(n + b)), \
(n, 0, m)).simplify() == -exp(m*log(a) + m*log(b))*gamma(a + 1) \
*gamma(b + 1)/(gamma(a)*gamma(b)*gamma(a + m + 1)*gamma(b + m + 1)) \
+ 1/(gamma(a)*gamma(b))
def test_gosper_sum_indefinite():
assert gosper_sum(k, k) == k*(k - 1)/2
assert gosper_sum(k**2, k) == k*(k - 1)*(2*k - 1)/6
assert gosper_sum(1/(k*(k + 1)), k) == -1/k
assert gosper_sum(-(27*k**4 + 158*k**3 + 430*k**2 + 678*k + 445)*gamma(2*k
+ 4)/(3*(3*k + 7)*gamma(3*k + 6)), k) == \
(3*k + 5)*(k**2 + 2*k + 5)*gamma(2*k + 4)/gamma(3*k + 6)
def test_gosper_sum_parametric():
assert gosper_sum(binomial(S.Half, m - j + 1)*binomial(S.Half, m + j), (j, 1, n)) == \
n*(1 + m - n)*(-1 + 2*m + 2*n)*binomial(S.Half, 1 + m - n)* \
binomial(S.Half, m + n)/(m*(1 + 2*m))
def test_gosper_sum_algebraic():
assert gosper_sum(
n**2 + sqrt(2), (n, 0, m)) == (m + 1)*(2*m**2 + m + 6*sqrt(2))/6
def test_gosper_sum_iterated():
f1 = binomial(2*k, k)/4**k
f2 = (1 + 2*n)*binomial(2*n, n)/4**n
f3 = (1 + 2*n)*(3 + 2*n)*binomial(2*n, n)/(3*4**n)
f4 = (1 + 2*n)*(3 + 2*n)*(5 + 2*n)*binomial(2*n, n)/(15*4**n)
f5 = (1 + 2*n)*(3 + 2*n)*(5 + 2*n)*(7 + 2*n)*binomial(2*n, n)/(105*4**n)
assert gosper_sum(f1, (k, 0, n)) == f2
assert gosper_sum(f2, (n, 0, n)) == f3
assert gosper_sum(f3, (n, 0, n)) == f4
assert gosper_sum(f4, (n, 0, n)) == f5
# the AeqB tests test expressions given in
# www.math.upenn.edu/~wilf/AeqB.pdf
def test_gosper_sum_AeqB_part1():
f1a = n**4
f1b = n**3*2**n
f1c = 1/(n**2 + sqrt(5)*n - 1)
f1d = n**4*4**n/binomial(2*n, n)
f1e = factorial(3*n)/(factorial(n)*factorial(n + 1)*factorial(n + 2)*27**n)
f1f = binomial(2*n, n)**2/((n + 1)*4**(2*n))
f1g = (4*n - 1)*binomial(2*n, n)**2/((2*n - 1)**2*4**(2*n))
f1h = n*factorial(n - S.Half)**2/factorial(n + 1)**2
g1a = m*(m + 1)*(2*m + 1)*(3*m**2 + 3*m - 1)/30
g1b = 26 + 2**(m + 1)*(m**3 - 3*m**2 + 9*m - 13)
g1c = (m + 1)*(m*(m**2 - 7*m + 3)*sqrt(5) - (
3*m**3 - 7*m**2 + 19*m - 6))/(2*m**3*sqrt(5) + m**4 + 5*m**2 - 1)/6
g1d = Rational(-2, 231) + 2*4**m*(m + 1)*(63*m**4 + 112*m**3 + 18*m**2 -
22*m + 3)/(693*binomial(2*m, m))
g1e = Rational(-9, 2) + (81*m**2 + 261*m + 200)*factorial(
3*m + 2)/(40*27**m*factorial(m)*factorial(m + 1)*factorial(m + 2))
g1f = (2*m + 1)**2*binomial(2*m, m)**2/(4**(2*m)*(m + 1))
g1g = -binomial(2*m, m)**2/4**(2*m)
g1h = 4*pi -(2*m + 1)**2*(3*m + 4)*factorial(m - S.Half)**2/factorial(m + 1)**2
g = gosper_sum(f1a, (n, 0, m))
assert g is not None and simplify(g - g1a) == 0
g = gosper_sum(f1b, (n, 0, m))
assert g is not None and simplify(g - g1b) == 0
g = gosper_sum(f1c, (n, 0, m))
assert g is not None and simplify(g - g1c) == 0
g = gosper_sum(f1d, (n, 0, m))
assert g is not None and simplify(g - g1d) == 0
g = gosper_sum(f1e, (n, 0, m))
assert g is not None and simplify(g - g1e) == 0
g = gosper_sum(f1f, (n, 0, m))
assert g is not None and simplify(g - g1f) == 0
g = gosper_sum(f1g, (n, 0, m))
assert g is not None and simplify(g - g1g) == 0
g = gosper_sum(f1h, (n, 0, m))
# need to call rewrite(gamma) here because we have terms involving
# factorial(1/2)
assert g is not None and simplify(g - g1h).rewrite(gamma) == 0
def test_gosper_sum_AeqB_part2():
f2a = n**2*a**n
f2b = (n - r/2)*binomial(r, n)
f2c = factorial(n - 1)**2/(factorial(n - x)*factorial(n + x))
g2a = -a*(a + 1)/(a - 1)**3 + a**(
m + 1)*(a**2*m**2 - 2*a*m**2 + m**2 - 2*a*m + 2*m + a + 1)/(a - 1)**3
g2b = (m - r)*binomial(r, m)/2
ff = factorial(1 - x)*factorial(1 + x)
g2c = 1/ff*(
1 - 1/x**2) + factorial(m)**2/(x**2*factorial(m - x)*factorial(m + x))
g = gosper_sum(f2a, (n, 0, m))
assert g is not None and simplify(g - g2a) == 0
g = gosper_sum(f2b, (n, 0, m))
assert g is not None and simplify(g - g2b) == 0
g = gosper_sum(f2c, (n, 1, m))
assert g is not None and simplify(g - g2c) == 0
def test_gosper_nan():
a = Symbol('a', positive=True)
b = Symbol('b', positive=True)
n = Symbol('n', integer=True)
m = Symbol('m', integer=True)
f2d = n*(n + a + b)*a**n*b**n/(factorial(n + a)*factorial(n + b))
g2d = 1/(factorial(a - 1)*factorial(
b - 1)) - a**(m + 1)*b**(m + 1)/(factorial(a + m)*factorial(b + m))
g = gosper_sum(f2d, (n, 0, m))
assert simplify(g - g2d) == 0
def test_gosper_sum_AeqB_part3():
f3a = 1/n**4
f3b = (6*n + 3)/(4*n**4 + 8*n**3 + 8*n**2 + 4*n + 3)
f3c = 2**n*(n**2 - 2*n - 1)/(n**2*(n + 1)**2)
f3d = n**2*4**n/((n + 1)*(n + 2))
f3e = 2**n/(n + 1)
f3f = 4*(n - 1)*(n**2 - 2*n - 1)/(n**2*(n + 1)**2*(n - 2)**2*(n - 3)**2)
f3g = (n**4 - 14*n**2 - 24*n - 9)*2**n/(n**2*(n + 1)**2*(n + 2)**2*
(n + 3)**2)
# g3a -> no closed form
g3b = m*(m + 2)/(2*m**2 + 4*m + 3)
g3c = 2**m/m**2 - 2
g3d = Rational(2, 3) + 4**(m + 1)*(m - 1)/(m + 2)/3
# g3e -> no closed form
g3f = -(Rational(-1, 16) + 1/((m - 2)**2*(m + 1)**2)) # the AeqB key is wrong
g3g = Rational(-2, 9) + 2**(m + 1)/((m + 1)**2*(m + 3)**2)
g = gosper_sum(f3a, (n, 1, m))
assert g is None
g = gosper_sum(f3b, (n, 1, m))
assert g is not None and simplify(g - g3b) == 0
g = gosper_sum(f3c, (n, 1, m - 1))
assert g is not None and simplify(g - g3c) == 0
g = gosper_sum(f3d, (n, 1, m))
assert g is not None and simplify(g - g3d) == 0
g = gosper_sum(f3e, (n, 0, m - 1))
assert g is None
g = gosper_sum(f3f, (n, 4, m))
assert g is not None and simplify(g - g3f) == 0
g = gosper_sum(f3g, (n, 1, m))
assert g is not None and simplify(g - g3g) == 0
|
baf4ebb1e85cb12d29b469c90f61f9b60814177ef904846a499822bc2ac8454b | from sympy.concrete.products import (Product, product)
from sympy.concrete.summations import (Sum, summation)
from sympy.core.function import (Derivative, Function)
from sympy.core.mul import prod
from sympy.core import (Catalan, EulerGamma)
from sympy.core.numbers import (E, I, Rational, nan, oo, pi)
from sympy.core.relational import Eq
from sympy.core.singleton import S
from sympy.core.symbol import (Dummy, Symbol, symbols)
from sympy.core.sympify import sympify
from sympy.functions.combinatorial.factorials import (rf, binomial, factorial)
from sympy.functions.combinatorial.numbers import harmonic
from sympy.functions.elementary.complexes import Abs
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.hyperbolic import (sinh, tanh)
from sympy.functions.elementary.integers import floor
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.piecewise import Piecewise
from sympy.functions.elementary.trigonometric import (cos, sin)
from sympy.functions.special.gamma_functions import (gamma, lowergamma)
from sympy.functions.special.tensor_functions import KroneckerDelta
from sympy.functions.special.zeta_functions import zeta
from sympy.integrals.integrals import Integral
from sympy.logic.boolalg import And, Or
from sympy.matrices.expressions.matexpr import MatrixSymbol
from sympy.matrices.expressions.special import Identity
from sympy.sets.fancysets import Range
from sympy.sets.sets import Interval
from sympy.simplify.combsimp import combsimp
from sympy.simplify.simplify import simplify
from sympy.tensor.indexed import (Idx, Indexed, IndexedBase)
from sympy.abc import a, b, c, d, k, m, x, y, z
from sympy.concrete.summations import (
telescopic, _dummy_with_inherited_properties_concrete, eval_sum_residue)
from sympy.concrete.expr_with_intlimits import ReorderError
from sympy.core.facts import InconsistentAssumptions
from sympy.testing.pytest import XFAIL, raises, slow
from sympy.matrices import (Matrix, SparseMatrix,
ImmutableDenseMatrix, ImmutableSparseMatrix)
from sympy.core.mod import Mod
n = Symbol('n', integer=True)
def test_karr_convention():
# Test the Karr summation convention that we want to hold.
# See his paper "Summation in Finite Terms" for a detailed
# reasoning why we really want exactly this definition.
# The convention is described on page 309 and essentially
# in section 1.4, definition 3:
#
# \sum_{m <= i < n} f(i) 'has the obvious meaning' for m < n
# \sum_{m <= i < n} f(i) = 0 for m = n
# \sum_{m <= i < n} f(i) = - \sum_{n <= i < m} f(i) for m > n
#
# It is important to note that he defines all sums with
# the upper limit being *exclusive*.
# In contrast, SymPy and the usual mathematical notation has:
#
# sum_{i = a}^b f(i) = f(a) + f(a+1) + ... + f(b-1) + f(b)
#
# with the upper limit *inclusive*. So translating between
# the two we find that:
#
# \sum_{m <= i < n} f(i) = \sum_{i = m}^{n-1} f(i)
#
# where we intentionally used two different ways to typeset the
# sum and its limits.
i = Symbol("i", integer=True)
k = Symbol("k", integer=True)
j = Symbol("j", integer=True)
# A simple example with a concrete summand and symbolic limits.
# The normal sum: m = k and n = k + j and therefore m < n:
m = k
n = k + j
a = m
b = n - 1
S1 = Sum(i**2, (i, a, b)).doit()
# The reversed sum: m = k + j and n = k and therefore m > n:
m = k + j
n = k
a = m
b = n - 1
S2 = Sum(i**2, (i, a, b)).doit()
assert simplify(S1 + S2) == 0
# Test the empty sum: m = k and n = k and therefore m = n:
m = k
n = k
a = m
b = n - 1
Sz = Sum(i**2, (i, a, b)).doit()
assert Sz == 0
# Another example this time with an unspecified summand and
# numeric limits. (We can not do both tests in the same example.)
f = Function("f")
# The normal sum with m < n:
m = 2
n = 11
a = m
b = n - 1
S1 = Sum(f(i), (i, a, b)).doit()
# The reversed sum with m > n:
m = 11
n = 2
a = m
b = n - 1
S2 = Sum(f(i), (i, a, b)).doit()
assert simplify(S1 + S2) == 0
# Test the empty sum with m = n:
m = 5
n = 5
a = m
b = n - 1
Sz = Sum(f(i), (i, a, b)).doit()
assert Sz == 0
e = Piecewise((exp(-i), Mod(i, 2) > 0), (0, True))
s = Sum(e, (i, 0, 11))
assert s.n(3) == s.doit().n(3)
def test_karr_proposition_2a():
# Test Karr, page 309, proposition 2, part a
i = Symbol("i", integer=True)
u = Symbol("u", integer=True)
v = Symbol("v", integer=True)
def test_the_sum(m, n):
# g
g = i**3 + 2*i**2 - 3*i
# f = Delta g
f = simplify(g.subs(i, i+1) - g)
# The sum
a = m
b = n - 1
S = Sum(f, (i, a, b)).doit()
# Test if Sum_{m <= i < n} f(i) = g(n) - g(m)
assert simplify(S - (g.subs(i, n) - g.subs(i, m))) == 0
# m < n
test_the_sum(u, u+v)
# m = n
test_the_sum(u, u )
# m > n
test_the_sum(u+v, u )
def test_karr_proposition_2b():
# Test Karr, page 309, proposition 2, part b
i = Symbol("i", integer=True)
u = Symbol("u", integer=True)
v = Symbol("v", integer=True)
w = Symbol("w", integer=True)
def test_the_sum(l, n, m):
# Summand
s = i**3
# First sum
a = l
b = n - 1
S1 = Sum(s, (i, a, b)).doit()
# Second sum
a = l
b = m - 1
S2 = Sum(s, (i, a, b)).doit()
# Third sum
a = m
b = n - 1
S3 = Sum(s, (i, a, b)).doit()
# Test if S1 = S2 + S3 as required
assert S1 - (S2 + S3) == 0
# l < m < n
test_the_sum(u, u+v, u+v+w)
# l < m = n
test_the_sum(u, u+v, u+v )
# l < m > n
test_the_sum(u, u+v+w, v )
# l = m < n
test_the_sum(u, u, u+v )
# l = m = n
test_the_sum(u, u, u )
# l = m > n
test_the_sum(u+v, u+v, u )
# l > m < n
test_the_sum(u+v, u, u+w )
# l > m = n
test_the_sum(u+v, u, u )
# l > m > n
test_the_sum(u+v+w, u+v, u )
def test_arithmetic_sums():
assert summation(1, (n, a, b)) == b - a + 1
assert Sum(S.NaN, (n, a, b)) is S.NaN
assert Sum(x, (n, a, a)).doit() == x
assert Sum(x, (x, a, a)).doit() == a
assert Sum(x, (n, 1, a)).doit() == a*x
assert Sum(x, (x, Range(1, 11))).doit() == 55
assert Sum(x, (x, Range(1, 11, 2))).doit() == 25
assert Sum(x, (x, Range(1, 10, 2))) == Sum(x, (x, Range(9, 0, -2)))
lo, hi = 1, 2
s1 = Sum(n, (n, lo, hi))
s2 = Sum(n, (n, hi, lo))
assert s1 != s2
assert s1.doit() == 3 and s2.doit() == 0
lo, hi = x, x + 1
s1 = Sum(n, (n, lo, hi))
s2 = Sum(n, (n, hi, lo))
assert s1 != s2
assert s1.doit() == 2*x + 1 and s2.doit() == 0
assert Sum(Integral(x, (x, 1, y)) + x, (x, 1, 2)).doit() == \
y**2 + 2
assert summation(1, (n, 1, 10)) == 10
assert summation(2*n, (n, 0, 10**10)) == 100000000010000000000
assert summation(4*n*m, (n, a, 1), (m, 1, d)).expand() == \
2*d + 2*d**2 + a*d + a*d**2 - d*a**2 - a**2*d**2
assert summation(cos(n), (n, -2, 1)) == cos(-2) + cos(-1) + cos(0) + cos(1)
assert summation(cos(n), (n, x, x + 2)) == cos(x) + cos(x + 1) + cos(x + 2)
assert isinstance(summation(cos(n), (n, x, x + S.Half)), Sum)
assert summation(k, (k, 0, oo)) is oo
assert summation(k, (k, Range(1, 11))) == 55
def test_polynomial_sums():
assert summation(n**2, (n, 3, 8)) == 199
assert summation(n, (n, a, b)) == \
((a + b)*(b - a + 1)/2).expand()
assert summation(n**2, (n, 1, b)) == \
((2*b**3 + 3*b**2 + b)/6).expand()
assert summation(n**3, (n, 1, b)) == \
((b**4 + 2*b**3 + b**2)/4).expand()
assert summation(n**6, (n, 1, b)) == \
((6*b**7 + 21*b**6 + 21*b**5 - 7*b**3 + b)/42).expand()
def test_geometric_sums():
assert summation(pi**n, (n, 0, b)) == (1 - pi**(b + 1)) / (1 - pi)
assert summation(2 * 3**n, (n, 0, b)) == 3**(b + 1) - 1
assert summation(S.Half**n, (n, 1, oo)) == 1
assert summation(2**n, (n, 0, b)) == 2**(b + 1) - 1
assert summation(2**n, (n, 1, oo)) is oo
assert summation(2**(-n), (n, 1, oo)) == 1
assert summation(3**(-n), (n, 4, oo)) == Rational(1, 54)
assert summation(2**(-4*n + 3), (n, 1, oo)) == Rational(8, 15)
assert summation(2**(n + 1), (n, 1, b)).expand() == 4*(2**b - 1)
# issue 6664:
assert summation(x**n, (n, 0, oo)) == \
Piecewise((1/(-x + 1), Abs(x) < 1), (Sum(x**n, (n, 0, oo)), True))
assert summation(-2**n, (n, 0, oo)) is -oo
assert summation(I**n, (n, 0, oo)) == Sum(I**n, (n, 0, oo))
# issue 6802:
assert summation((-1)**(2*x + 2), (x, 0, n)) == n + 1
assert summation((-2)**(2*x + 2), (x, 0, n)) == 4*4**(n + 1)/S(3) - Rational(4, 3)
assert summation((-1)**x, (x, 0, n)) == -(-1)**(n + 1)/S(2) + S.Half
assert summation(y**x, (x, a, b)) == \
Piecewise((-a + b + 1, Eq(y, 1)), ((y**a - y**(b + 1))/(-y + 1), True))
assert summation((-2)**(y*x + 2), (x, 0, n)) == \
4*Piecewise((n + 1, Eq((-2)**y, 1)),
((-(-2)**(y*(n + 1)) + 1)/(-(-2)**y + 1), True))
# issue 8251:
assert summation((1/(n + 1)**2)*n**2, (n, 0, oo)) is oo
#issue 9908:
assert Sum(1/(n**3 - 1), (n, -oo, -2)).doit() == summation(1/(n**3 - 1), (n, -oo, -2))
#issue 11642:
result = Sum(0.5**n, (n, 1, oo)).doit()
assert result == 1
assert result.is_Float
result = Sum(0.25**n, (n, 1, oo)).doit()
assert result == 1/3.
assert result.is_Float
result = Sum(0.99999**n, (n, 1, oo)).doit()
assert result == 99999
assert result.is_Float
result = Sum(S.Half**n, (n, 1, oo)).doit()
assert result == 1
assert not result.is_Float
result = Sum(Rational(3, 5)**n, (n, 1, oo)).doit()
assert result == Rational(3, 2)
assert not result.is_Float
assert Sum(1.0**n, (n, 1, oo)).doit() is oo
assert Sum(2.43**n, (n, 1, oo)).doit() is oo
# Issue 13979
i, k, q = symbols('i k q', integer=True)
result = summation(
exp(-2*I*pi*k*i/n) * exp(2*I*pi*q*i/n) / n, (i, 0, n - 1)
)
assert result.simplify() == Piecewise(
(1, Eq(exp(-2*I*pi*(k - q)/n), 1)), (0, True)
)
def test_harmonic_sums():
assert summation(1/k, (k, 0, n)) == Sum(1/k, (k, 0, n))
assert summation(1/k, (k, 1, n)) == harmonic(n)
assert summation(n/k, (k, 1, n)) == n*harmonic(n)
assert summation(1/k, (k, 5, n)) == harmonic(n) - harmonic(4)
def test_composite_sums():
f = S.Half*(7 - 6*n + Rational(1, 7)*n**3)
s = summation(f, (n, a, b))
assert not isinstance(s, Sum)
A = 0
for i in range(-3, 5):
A += f.subs(n, i)
B = s.subs(a, -3).subs(b, 4)
assert A == B
def test_hypergeometric_sums():
assert summation(
binomial(2*k, k)/4**k, (k, 0, n)) == (1 + 2*n)*binomial(2*n, n)/4**n
assert summation(binomial(2*k, k)/5**k, (k, -oo, oo)) == sqrt(5)
def test_other_sums():
f = m**2 + m*exp(m)
g = 3*exp(Rational(3, 2))/2 + exp(S.Half)/2 - exp(Rational(-1, 2))/2 - 3*exp(Rational(-3, 2))/2 + 5
assert summation(f, (m, Rational(-3, 2), Rational(3, 2))) == g
assert summation(f, (m, -1.5, 1.5)).evalf().epsilon_eq(g.evalf(), 1e-10)
fac = factorial
def NS(e, n=15, **options):
return str(sympify(e).evalf(n, **options))
def test_evalf_fast_series():
# Euler transformed series for sqrt(1+x)
assert NS(Sum(
fac(2*n + 1)/fac(n)**2/2**(3*n + 1), (n, 0, oo)), 100) == NS(sqrt(2), 100)
# Some series for exp(1)
estr = NS(E, 100)
assert NS(Sum(1/fac(n), (n, 0, oo)), 100) == estr
assert NS(1/Sum((1 - 2*n)/fac(2*n), (n, 0, oo)), 100) == estr
assert NS(Sum((2*n + 1)/fac(2*n), (n, 0, oo)), 100) == estr
assert NS(Sum((4*n + 3)/2**(2*n + 1)/fac(2*n + 1), (n, 0, oo))**2, 100) == estr
pistr = NS(pi, 100)
# Ramanujan series for pi
assert NS(9801/sqrt(8)/Sum(fac(
4*n)*(1103 + 26390*n)/fac(n)**4/396**(4*n), (n, 0, oo)), 100) == pistr
assert NS(1/Sum(
binomial(2*n, n)**3 * (42*n + 5)/2**(12*n + 4), (n, 0, oo)), 100) == pistr
# Machin's formula for pi
assert NS(16*Sum((-1)**n/(2*n + 1)/5**(2*n + 1), (n, 0, oo)) -
4*Sum((-1)**n/(2*n + 1)/239**(2*n + 1), (n, 0, oo)), 100) == pistr
# Apery's constant
astr = NS(zeta(3), 100)
P = 126392*n**5 + 412708*n**4 + 531578*n**3 + 336367*n**2 + 104000* \
n + 12463
assert NS(Sum((-1)**n * P / 24 * (fac(2*n + 1)*fac(2*n)*fac(
n))**3 / fac(3*n + 2) / fac(4*n + 3)**3, (n, 0, oo)), 100) == astr
assert NS(Sum((-1)**n * (205*n**2 + 250*n + 77)/64 * fac(n)**10 /
fac(2*n + 1)**5, (n, 0, oo)), 100) == astr
def test_evalf_fast_series_issue_4021():
# Catalan's constant
assert NS(Sum((-1)**(n - 1)*2**(8*n)*(40*n**2 - 24*n + 3)*fac(2*n)**3*
fac(n)**2/n**3/(2*n - 1)/fac(4*n)**2, (n, 1, oo))/64, 100) == \
NS(Catalan, 100)
astr = NS(zeta(3), 100)
assert NS(5*Sum(
(-1)**(n - 1)*fac(n)**2 / n**3 / fac(2*n), (n, 1, oo))/2, 100) == astr
assert NS(Sum((-1)**(n - 1)*(56*n**2 - 32*n + 5) / (2*n - 1)**2 * fac(n - 1)
**3 / fac(3*n), (n, 1, oo))/4, 100) == astr
def test_evalf_slow_series():
assert NS(Sum((-1)**n / n, (n, 1, oo)), 15) == NS(-log(2), 15)
assert NS(Sum((-1)**n / n, (n, 1, oo)), 50) == NS(-log(2), 50)
assert NS(Sum(1/n**2, (n, 1, oo)), 15) == NS(pi**2/6, 15)
assert NS(Sum(1/n**2, (n, 1, oo)), 100) == NS(pi**2/6, 100)
assert NS(Sum(1/n**2, (n, 1, oo)), 500) == NS(pi**2/6, 500)
assert NS(Sum((-1)**n / (2*n + 1)**3, (n, 0, oo)), 15) == NS(pi**3/32, 15)
assert NS(Sum((-1)**n / (2*n + 1)**3, (n, 0, oo)), 50) == NS(pi**3/32, 50)
def test_evalf_oo_to_oo():
# There used to be an error in certain cases
# Does not evaluate, but at least do not throw an error
# Evaluates symbolically to 0, which is not correct
assert Sum(1/(n**2+1), (n, -oo, oo)).evalf() == Sum(1/(n**2+1), (n, -oo, oo))
# This evaluates if from 1 to oo and symbolically
assert Sum(1/(factorial(abs(n))), (n, -oo, -1)).evalf() == Sum(1/(factorial(abs(n))), (n, -oo, -1))
def test_euler_maclaurin():
# Exact polynomial sums with E-M
def check_exact(f, a, b, m, n):
A = Sum(f, (k, a, b))
s, e = A.euler_maclaurin(m, n)
assert (e == 0) and (s.expand() == A.doit())
check_exact(k**4, a, b, 0, 2)
check_exact(k**4 + 2*k, a, b, 1, 2)
check_exact(k**4 + k**2, a, b, 1, 5)
check_exact(k**5, 2, 6, 1, 2)
check_exact(k**5, 2, 6, 1, 3)
assert Sum(x-1, (x, 0, 2)).euler_maclaurin(m=30, n=30, eps=2**-15) == (0, 0)
# Not exact
assert Sum(k**6, (k, a, b)).euler_maclaurin(0, 2)[1] != 0
# Numerical test
for mi, ni in [(2, 4), (2, 20), (10, 20), (18, 20)]:
A = Sum(1/k**3, (k, 1, oo))
s, e = A.euler_maclaurin(mi, ni)
assert abs((s - zeta(3)).evalf()) < e.evalf()
raises(ValueError, lambda: Sum(1, (x, 0, 1), (k, 0, 1)).euler_maclaurin())
@slow
def test_evalf_euler_maclaurin():
assert NS(Sum(1/k**k, (k, 1, oo)), 15) == '1.29128599706266'
assert NS(Sum(1/k**k, (k, 1, oo)),
50) == '1.2912859970626635404072825905956005414986193682745'
assert NS(Sum(1/k - log(1 + 1/k), (k, 1, oo)), 15) == NS(EulerGamma, 15)
assert NS(Sum(1/k - log(1 + 1/k), (k, 1, oo)), 50) == NS(EulerGamma, 50)
assert NS(Sum(log(k)/k**2, (k, 1, oo)), 15) == '0.937548254315844'
assert NS(Sum(log(k)/k**2, (k, 1, oo)),
50) == '0.93754825431584375370257409456786497789786028861483'
assert NS(Sum(1/k, (k, 1000000, 2000000)), 15) == '0.693147930560008'
assert NS(Sum(1/k, (k, 1000000, 2000000)),
50) == '0.69314793056000780941723211364567656807940638436025'
def test_evalf_symbolic():
f, g = symbols('f g', cls=Function)
# issue 6328
expr = Sum(f(x), (x, 1, 3)) + Sum(g(x), (x, 1, 3))
assert expr.evalf() == expr
def test_evalf_issue_3273():
assert Sum(0, (k, 1, oo)).evalf() == 0
def test_simple_products():
assert Product(S.NaN, (x, 1, 3)) is S.NaN
assert product(S.NaN, (x, 1, 3)) is S.NaN
assert Product(x, (n, a, a)).doit() == x
assert Product(x, (x, a, a)).doit() == a
assert Product(x, (y, 1, a)).doit() == x**a
lo, hi = 1, 2
s1 = Product(n, (n, lo, hi))
s2 = Product(n, (n, hi, lo))
assert s1 != s2
# This IS correct according to Karr product convention
assert s1.doit() == 2
assert s2.doit() == 1
lo, hi = x, x + 1
s1 = Product(n, (n, lo, hi))
s2 = Product(n, (n, hi, lo))
s3 = 1 / Product(n, (n, hi + 1, lo - 1))
assert s1 != s2
# This IS correct according to Karr product convention
assert s1.doit() == x*(x + 1)
assert s2.doit() == 1
assert s3.doit() == x*(x + 1)
assert Product(Integral(2*x, (x, 1, y)) + 2*x, (x, 1, 2)).doit() == \
(y**2 + 1)*(y**2 + 3)
assert product(2, (n, a, b)) == 2**(b - a + 1)
assert product(n, (n, 1, b)) == factorial(b)
assert product(n**3, (n, 1, b)) == factorial(b)**3
assert product(3**(2 + n), (n, a, b)) \
== 3**(2*(1 - a + b) + b/2 + (b**2)/2 + a/2 - (a**2)/2)
assert product(cos(n), (n, 3, 5)) == cos(3)*cos(4)*cos(5)
assert product(cos(n), (n, x, x + 2)) == cos(x)*cos(x + 1)*cos(x + 2)
assert isinstance(product(cos(n), (n, x, x + S.Half)), Product)
# If Product managed to evaluate this one, it most likely got it wrong!
assert isinstance(Product(n**n, (n, 1, b)), Product)
def test_rational_products():
assert combsimp(product(1 + 1/n, (n, a, b))) == (1 + b)/a
assert combsimp(product(n + 1, (n, a, b))) == gamma(2 + b)/gamma(1 + a)
assert combsimp(product((n + 1)/(n - 1), (n, a, b))) == b*(1 + b)/(a*(a - 1))
assert combsimp(product(n/(n + 1)/(n + 2), (n, a, b))) == \
a*gamma(a + 2)/(b + 1)/gamma(b + 3)
assert combsimp(product(n*(n + 1)/(n - 1)/(n - 2), (n, a, b))) == \
b**2*(b - 1)*(1 + b)/(a - 1)**2/(a*(a - 2))
def test_wallis_product():
# Wallis product, given in two different forms to ensure that Product
# can factor simple rational expressions
A = Product(4*n**2 / (4*n**2 - 1), (n, 1, b))
B = Product((2*n)*(2*n)/(2*n - 1)/(2*n + 1), (n, 1, b))
R = pi*gamma(b + 1)**2/(2*gamma(b + S.Half)*gamma(b + Rational(3, 2)))
assert simplify(A.doit()) == R
assert simplify(B.doit()) == R
# This one should eventually also be doable (Euler's product formula for sin)
# assert Product(1+x/n**2, (n, 1, b)) == ...
def test_telescopic_sums():
#checks also input 2 of comment 1 issue 4127
assert Sum(1/k - 1/(k + 1), (k, 1, n)).doit() == 1 - 1/(1 + n)
f = Function("f")
assert Sum(
f(k) - f(k + 2), (k, m, n)).doit() == -f(1 + n) - f(2 + n) + f(m) + f(1 + m)
assert Sum(cos(k) - cos(k + 3), (k, 1, n)).doit() == -cos(1 + n) - \
cos(2 + n) - cos(3 + n) + cos(1) + cos(2) + cos(3)
# dummy variable shouldn't matter
assert telescopic(1/m, -m/(1 + m), (m, n - 1, n)) == \
telescopic(1/k, -k/(1 + k), (k, n - 1, n))
assert Sum(1/x/(x - 1), (x, a, b)).doit() == -((a - b - 1)/(b*(a - 1)))
def test_sum_reconstruct():
s = Sum(n**2, (n, -1, 1))
assert s == Sum(*s.args)
raises(ValueError, lambda: Sum(x, x))
raises(ValueError, lambda: Sum(x, (x, 1)))
def test_limit_subs():
for F in (Sum, Product, Integral):
assert F(a*exp(a), (a, -2, 2)) == F(a*exp(a), (a, -b, b)).subs(b, 2)
assert F(a, (a, F(b, (b, 1, 2)), 4)).subs(F(b, (b, 1, 2)), c) == \
F(a, (a, c, 4))
assert F(x, (x, 1, x + y)).subs(x, 1) == F(x, (x, 1, y + 1))
def test_function_subs():
f = Function("f")
S = Sum(x*f(y),(x,0,oo),(y,0,oo))
assert S.subs(f(y),y) == Sum(x*y,(x,0,oo),(y,0,oo))
assert S.subs(f(x),x) == S
raises(ValueError, lambda: S.subs(f(y),x+y) )
S = Sum(x*log(y),(x,0,oo),(y,0,oo))
assert S.subs(log(y),y) == S
S = Sum(x*f(y),(x,0,oo),(y,0,oo))
assert S.subs(f(y),y) == Sum(x*y,(x,0,oo),(y,0,oo))
def test_equality():
# if this fails remove special handling below
raises(ValueError, lambda: Sum(x, x))
r = symbols('x', real=True)
for F in (Sum, Product, Integral):
try:
assert F(x, x) != F(y, y)
assert F(x, (x, 1, 2)) != F(x, x)
assert F(x, (x, x)) != F(x, x) # or else they print the same
assert F(1, x) != F(1, y)
except ValueError:
pass
assert F(a, (x, 1, 2)) != F(a, (x, 1, 3)) # diff limit
assert F(a, (x, 1, x)) != F(a, (y, 1, y))
assert F(a, (x, 1, 2)) != F(b, (x, 1, 2)) # diff expression
assert F(x, (x, 1, 2)) != F(r, (r, 1, 2)) # diff assumptions
assert F(1, (x, 1, x)) != F(1, (y, 1, x)) # only dummy is diff
assert F(1, (x, 1, x)).dummy_eq(F(1, (y, 1, x)))
# issue 5265
assert Sum(x, (x, 1, x)).subs(x, a) == Sum(x, (x, 1, a))
def test_Sum_doit():
f = Function('f')
assert Sum(n*Integral(a**2), (n, 0, 2)).doit() == a**3
assert Sum(n*Integral(a**2), (n, 0, 2)).doit(deep=False) == \
3*Integral(a**2)
assert summation(n*Integral(a**2), (n, 0, 2)) == 3*Integral(a**2)
# test nested sum evaluation
s = Sum( Sum( Sum(2,(z,1,n+1)), (y,x+1,n)), (x,1,n))
assert 0 == (s.doit() - n*(n+1)*(n-1)).factor()
# Integer assumes finite
assert Sum(KroneckerDelta(x, y), (x, -oo, oo)).doit() == Piecewise((1, And(-oo < y, y < oo)), (0, True))
assert Sum(KroneckerDelta(m, n), (m, -oo, oo)).doit() == 1
assert Sum(m*KroneckerDelta(x, y), (x, -oo, oo)).doit() == Piecewise((m, And(-oo < y, y < oo)), (0, True))
assert Sum(x*KroneckerDelta(m, n), (m, -oo, oo)).doit() == x
assert Sum(Sum(KroneckerDelta(m, n), (m, 1, 3)), (n, 1, 3)).doit() == 3
assert Sum(Sum(KroneckerDelta(k, m), (m, 1, 3)), (n, 1, 3)).doit() == \
3 * Piecewise((1, And(1 <= k, k <= 3)), (0, True))
assert Sum(f(n) * Sum(KroneckerDelta(m, n), (m, 0, oo)), (n, 1, 3)).doit() == \
f(1) + f(2) + f(3)
assert Sum(f(n) * Sum(KroneckerDelta(m, n), (m, 0, oo)), (n, 1, oo)).doit() == \
Sum(f(n), (n, 1, oo))
# issue 2597
nmax = symbols('N', integer=True, positive=True)
pw = Piecewise((1, And(1 <= n, n <= nmax)), (0, True))
assert Sum(pw, (n, 1, nmax)).doit() == Sum(Piecewise((1, nmax >= n),
(0, True)), (n, 1, nmax))
q, s = symbols('q, s')
assert summation(1/n**(2*s), (n, 1, oo)) == Piecewise((zeta(2*s), 2*s > 1),
(Sum(n**(-2*s), (n, 1, oo)), True))
assert summation(1/(n+1)**s, (n, 0, oo)) == Piecewise((zeta(s), s > 1),
(Sum((n + 1)**(-s), (n, 0, oo)), True))
assert summation(1/(n+q)**s, (n, 0, oo)) == Piecewise(
(zeta(s, q), And(q > 0, s > 1)),
(Sum((n + q)**(-s), (n, 0, oo)), True))
assert summation(1/(n+q)**s, (n, q, oo)) == Piecewise(
(zeta(s, 2*q), And(2*q > 0, s > 1)),
(Sum((n + q)**(-s), (n, q, oo)), True))
assert summation(1/n**2, (n, 1, oo)) == zeta(2)
assert summation(1/n**s, (n, 0, oo)) == Sum(n**(-s), (n, 0, oo))
def test_Product_doit():
assert Product(n*Integral(a**2), (n, 1, 3)).doit() == 2 * a**9 / 9
assert Product(n*Integral(a**2), (n, 1, 3)).doit(deep=False) == \
6*Integral(a**2)**3
assert product(n*Integral(a**2), (n, 1, 3)) == 6*Integral(a**2)**3
def test_Sum_interface():
assert isinstance(Sum(0, (n, 0, 2)), Sum)
assert Sum(nan, (n, 0, 2)) is nan
assert Sum(nan, (n, 0, oo)) is nan
assert Sum(0, (n, 0, 2)).doit() == 0
assert isinstance(Sum(0, (n, 0, oo)), Sum)
assert Sum(0, (n, 0, oo)).doit() == 0
raises(ValueError, lambda: Sum(1))
raises(ValueError, lambda: summation(1))
def test_diff():
assert Sum(x, (x, 1, 2)).diff(x) == 0
assert Sum(x*y, (x, 1, 2)).diff(x) == 0
assert Sum(x*y, (y, 1, 2)).diff(x) == Sum(y, (y, 1, 2))
e = Sum(x*y, (x, 1, a))
assert e.diff(a) == Derivative(e, a)
assert Sum(x*y, (x, 1, 3), (a, 2, 5)).diff(y).doit() == \
Sum(x*y, (x, 1, 3), (a, 2, 5)).doit().diff(y) == 24
assert Sum(x, (x, 1, 2)).diff(y) == 0
def test_hypersum():
assert simplify(summation(x**n/fac(n), (n, 1, oo))) == -1 + exp(x)
assert summation((-1)**n * x**(2*n) / fac(2*n), (n, 0, oo)) == cos(x)
assert simplify(summation((-1)**n*x**(2*n + 1) /
factorial(2*n + 1), (n, 3, oo))) == -x + sin(x) + x**3/6 - x**5/120
assert summation(1/(n + 2)**3, (n, 1, oo)) == Rational(-9, 8) + zeta(3)
assert summation(1/n**4, (n, 1, oo)) == pi**4/90
s = summation(x**n*n, (n, -oo, 0))
assert s.is_Piecewise
assert s.args[0].args[0] == -1/(x*(1 - 1/x)**2)
assert s.args[0].args[1] == (abs(1/x) < 1)
m = Symbol('n', integer=True, positive=True)
assert summation(binomial(m, k), (k, 0, m)) == 2**m
def test_issue_4170():
assert summation(1/factorial(k), (k, 0, oo)) == E
def test_is_commutative():
from sympy.physics.secondquant import NO, F, Fd
m = Symbol('m', commutative=False)
for f in (Sum, Product, Integral):
assert f(z, (z, 1, 1)).is_commutative is True
assert f(z*y, (z, 1, 6)).is_commutative is True
assert f(m*x, (x, 1, 2)).is_commutative is False
assert f(NO(Fd(x)*F(y))*z, (z, 1, 2)).is_commutative is False
def test_is_zero():
for func in [Sum, Product]:
assert func(0, (x, 1, 1)).is_zero is True
assert func(x, (x, 1, 1)).is_zero is None
assert Sum(0, (x, 1, 0)).is_zero is True
assert Product(0, (x, 1, 0)).is_zero is False
def test_is_number():
# is number should not rely on evaluation or assumptions,
# it should be equivalent to `not foo.free_symbols`
assert Sum(1, (x, 1, 1)).is_number is True
assert Sum(1, (x, 1, x)).is_number is False
assert Sum(0, (x, y, z)).is_number is False
assert Sum(x, (y, 1, 2)).is_number is False
assert Sum(x, (y, 1, 1)).is_number is False
assert Sum(x, (x, 1, 2)).is_number is True
assert Sum(x*y, (x, 1, 2), (y, 1, 3)).is_number is True
assert Product(2, (x, 1, 1)).is_number is True
assert Product(2, (x, 1, y)).is_number is False
assert Product(0, (x, y, z)).is_number is False
assert Product(1, (x, y, z)).is_number is False
assert Product(x, (y, 1, x)).is_number is False
assert Product(x, (y, 1, 2)).is_number is False
assert Product(x, (y, 1, 1)).is_number is False
assert Product(x, (x, 1, 2)).is_number is True
def test_free_symbols():
for func in [Sum, Product]:
assert func(1, (x, 1, 2)).free_symbols == set()
assert func(0, (x, 1, y)).free_symbols == {y}
assert func(2, (x, 1, y)).free_symbols == {y}
assert func(x, (x, 1, 2)).free_symbols == set()
assert func(x, (x, 1, y)).free_symbols == {y}
assert func(x, (y, 1, y)).free_symbols == {x, y}
assert func(x, (y, 1, 2)).free_symbols == {x}
assert func(x, (y, 1, 1)).free_symbols == {x}
assert func(x, (y, 1, z)).free_symbols == {x, z}
assert func(x, (x, 1, y), (y, 1, 2)).free_symbols == set()
assert func(x, (x, 1, y), (y, 1, z)).free_symbols == {z}
assert func(x, (x, 1, y), (y, 1, y)).free_symbols == {y}
assert func(x, (y, 1, y), (y, 1, z)).free_symbols == {x, z}
assert Sum(1, (x, 1, y)).free_symbols == {y}
# free_symbols answers whether the object *as written* has free symbols,
# not whether the evaluated expression has free symbols
assert Product(1, (x, 1, y)).free_symbols == {y}
def test_conjugate_transpose():
A, B = symbols("A B", commutative=False)
p = Sum(A*B**n, (n, 1, 3))
assert p.adjoint().doit() == p.doit().adjoint()
assert p.conjugate().doit() == p.doit().conjugate()
assert p.transpose().doit() == p.doit().transpose()
p = Sum(B**n*A, (n, 1, 3))
assert p.adjoint().doit() == p.doit().adjoint()
assert p.conjugate().doit() == p.doit().conjugate()
assert p.transpose().doit() == p.doit().transpose()
def test_noncommutativity_honoured():
A, B = symbols("A B", commutative=False)
M = symbols('M', integer=True, positive=True)
p = Sum(A*B**n, (n, 1, M))
assert p.doit() == A*Piecewise((M, Eq(B, 1)),
((B - B**(M + 1))*(1 - B)**(-1), True))
p = Sum(B**n*A, (n, 1, M))
assert p.doit() == Piecewise((M, Eq(B, 1)),
((B - B**(M + 1))*(1 - B)**(-1), True))*A
p = Sum(B**n*A*B**n, (n, 1, M))
assert p.doit() == p
def test_issue_4171():
assert summation(factorial(2*k + 1)/factorial(2*k), (k, 0, oo)) is oo
assert summation(2*k + 1, (k, 0, oo)) is oo
def test_issue_6273():
assert Sum(x, (x, 1, n)).n(2, subs={n: 1}) == 1
def test_issue_6274():
assert Sum(x, (x, 1, 0)).doit() == 0
assert NS(Sum(x, (x, 1, 0))) == '0'
assert Sum(n, (n, 10, 5)).doit() == -30
assert NS(Sum(n, (n, 10, 5))) == '-30.0000000000000'
def test_simplify_sum():
y, t, v = symbols('y, t, v')
_simplify = lambda e: simplify(e, doit=False)
assert _simplify(Sum(x*y, (x, n, m), (y, a, k)) + \
Sum(y, (x, n, m), (y, a, k))) == Sum(y * (x + 1), (x, n, m), (y, a, k))
assert _simplify(Sum(x, (x, n, m)) + Sum(x, (x, m + 1, a))) == \
Sum(x, (x, n, a))
assert _simplify(Sum(x, (x, k + 1, a)) + Sum(x, (x, n, k))) == \
Sum(x, (x, n, a))
assert _simplify(Sum(x, (x, k + 1, a)) + Sum(x + 1, (x, n, k))) == \
Sum(x, (x, n, a)) + Sum(1, (x, n, k))
assert _simplify(Sum(x, (x, 0, 3)) * 3 + 3 * Sum(x, (x, 4, 6)) + \
4 * Sum(z, (z, 0, 1))) == 4*Sum(z, (z, 0, 1)) + 3*Sum(x, (x, 0, 6))
assert _simplify(3*Sum(x**2, (x, a, b)) + Sum(x, (x, a, b))) == \
Sum(x*(3*x + 1), (x, a, b))
assert _simplify(Sum(x**3, (x, n, k)) * 3 + 3 * Sum(x, (x, n, k)) + \
4 * y * Sum(z, (z, n, k))) + 1 == \
4*y*Sum(z, (z, n, k)) + 3*Sum(x**3 + x, (x, n, k)) + 1
assert _simplify(Sum(x, (x, a, b)) + 1 + Sum(x, (x, b + 1, c))) == \
1 + Sum(x, (x, a, c))
assert _simplify(Sum(x, (t, a, b)) + Sum(y, (t, a, b)) + \
Sum(x, (t, b+1, c))) == x * Sum(1, (t, a, c)) + y * Sum(1, (t, a, b))
assert _simplify(Sum(x, (t, a, b)) + Sum(x, (t, b+1, c)) + \
Sum(y, (t, a, b))) == x * Sum(1, (t, a, c)) + y * Sum(1, (t, a, b))
assert _simplify(Sum(x, (t, a, b)) + 2 * Sum(x, (t, b+1, c))) == \
_simplify(Sum(x, (t, a, b)) + Sum(x, (t, b+1, c)) + Sum(x, (t, b+1, c)))
assert _simplify(Sum(x, (x, a, b))*Sum(x**2, (x, a, b))) == \
Sum(x, (x, a, b)) * Sum(x**2, (x, a, b))
assert _simplify(Sum(x, (t, a, b)) + Sum(y, (t, a, b)) + Sum(z, (t, a, b))) \
== (x + y + z) * Sum(1, (t, a, b)) # issue 8596
assert _simplify(Sum(x, (t, a, b)) + Sum(y, (t, a, b)) + Sum(z, (t, a, b)) + \
Sum(v, (t, a, b))) == (x + y + z + v) * Sum(1, (t, a, b)) # issue 8596
assert _simplify(Sum(x * y, (x, a, b)) / (3 * y)) == \
(Sum(x, (x, a, b)) / 3)
assert _simplify(Sum(Function('f')(x) * y * z, (x, a, b)) / (y * z)) \
== Sum(Function('f')(x), (x, a, b))
assert _simplify(Sum(c * x, (x, a, b)) - c * Sum(x, (x, a, b))) == 0
assert _simplify(c * (Sum(x, (x, a, b)) + y)) == c * (y + Sum(x, (x, a, b)))
assert _simplify(c * (Sum(x, (x, a, b)) + y * Sum(x, (x, a, b)))) == \
c * (y + 1) * Sum(x, (x, a, b))
assert _simplify(Sum(Sum(c * x, (x, a, b)), (y, a, b))) == \
c * Sum(x, (x, a, b), (y, a, b))
assert _simplify(Sum((3 + y) * Sum(c * x, (x, a, b)), (y, a, b))) == \
c * Sum((3 + y), (y, a, b)) * Sum(x, (x, a, b))
assert _simplify(Sum((3 + t) * Sum(c * t, (x, a, b)), (y, a, b))) == \
c*t*(t + 3)*Sum(1, (x, a, b))*Sum(1, (y, a, b))
assert _simplify(Sum(Sum(d * t, (x, a, b - 1)) + \
Sum(d * t, (x, b, c)), (t, a, b))) == \
d * Sum(1, (x, a, c)) * Sum(t, (t, a, b))
def test_change_index():
b, v, w = symbols('b, v, w', integer = True)
assert Sum(x, (x, a, b)).change_index(x, x + 1, y) == \
Sum(y - 1, (y, a + 1, b + 1))
assert Sum(x**2, (x, a, b)).change_index( x, x - 1) == \
Sum((x+1)**2, (x, a - 1, b - 1))
assert Sum(x**2, (x, a, b)).change_index( x, -x, y) == \
Sum((-y)**2, (y, -b, -a))
assert Sum(x, (x, a, b)).change_index( x, -x - 1) == \
Sum(-x - 1, (x, -b - 1, -a - 1))
assert Sum(x*y, (x, a, b), (y, c, d)).change_index( x, x - 1, z) == \
Sum((z + 1)*y, (z, a - 1, b - 1), (y, c, d))
assert Sum(x, (x, a, b)).change_index( x, x + v) == \
Sum(-v + x, (x, a + v, b + v))
assert Sum(x, (x, a, b)).change_index( x, -x - v) == \
Sum(-v - x, (x, -b - v, -a - v))
assert Sum(x, (x, a, b)).change_index(x, w*x, v) == \
Sum(v/w, (v, b*w, a*w))
raises(ValueError, lambda: Sum(x, (x, a, b)).change_index(x, 2*x))
def test_reorder():
b, y, c, d, z = symbols('b, y, c, d, z', integer = True)
assert Sum(x*y, (x, a, b), (y, c, d)).reorder((0, 1)) == \
Sum(x*y, (y, c, d), (x, a, b))
assert Sum(x, (x, a, b), (x, c, d)).reorder((0, 1)) == \
Sum(x, (x, c, d), (x, a, b))
assert Sum(x*y + z, (x, a, b), (z, m, n), (y, c, d)).reorder(\
(2, 0), (0, 1)) == Sum(x*y + z, (z, m, n), (y, c, d), (x, a, b))
assert Sum(x*y*z, (x, a, b), (y, c, d), (z, m, n)).reorder(\
(0, 1), (1, 2), (0, 2)) == Sum(x*y*z, (x, a, b), (z, m, n), (y, c, d))
assert Sum(x*y*z, (x, a, b), (y, c, d), (z, m, n)).reorder(\
(x, y), (y, z), (x, z)) == Sum(x*y*z, (x, a, b), (z, m, n), (y, c, d))
assert Sum(x*y, (x, a, b), (y, c, d)).reorder((x, 1)) == \
Sum(x*y, (y, c, d), (x, a, b))
assert Sum(x*y, (x, a, b), (y, c, d)).reorder((y, x)) == \
Sum(x*y, (y, c, d), (x, a, b))
def test_reverse_order():
assert Sum(x, (x, 0, 3)).reverse_order(0) == Sum(-x, (x, 4, -1))
assert Sum(x*y, (x, 1, 5), (y, 0, 6)).reverse_order(0, 1) == \
Sum(x*y, (x, 6, 0), (y, 7, -1))
assert Sum(x, (x, 1, 2)).reverse_order(0) == Sum(-x, (x, 3, 0))
assert Sum(x, (x, 1, 3)).reverse_order(0) == Sum(-x, (x, 4, 0))
assert Sum(x, (x, 1, a)).reverse_order(0) == Sum(-x, (x, a + 1, 0))
assert Sum(x, (x, a, 5)).reverse_order(0) == Sum(-x, (x, 6, a - 1))
assert Sum(x, (x, a + 1, a + 5)).reverse_order(0) == \
Sum(-x, (x, a + 6, a))
assert Sum(x, (x, a + 1, a + 2)).reverse_order(0) == \
Sum(-x, (x, a + 3, a))
assert Sum(x, (x, a + 1, a + 1)).reverse_order(0) == \
Sum(-x, (x, a + 2, a))
assert Sum(x, (x, a, b)).reverse_order(0) == Sum(-x, (x, b + 1, a - 1))
assert Sum(x, (x, a, b)).reverse_order(x) == Sum(-x, (x, b + 1, a - 1))
assert Sum(x*y, (x, a, b), (y, 2, 5)).reverse_order(x, 1) == \
Sum(x*y, (x, b + 1, a - 1), (y, 6, 1))
assert Sum(x*y, (x, a, b), (y, 2, 5)).reverse_order(y, x) == \
Sum(x*y, (x, b + 1, a - 1), (y, 6, 1))
def test_issue_7097():
assert sum(x**n/n for n in range(1, 401)) == summation(x**n/n, (n, 1, 400))
def test_factor_expand_subs():
# test factoring
assert Sum(4 * x, (x, 1, y)).factor() == 4 * Sum(x, (x, 1, y))
assert Sum(x * a, (x, 1, y)).factor() == a * Sum(x, (x, 1, y))
assert Sum(4 * x * a, (x, 1, y)).factor() == 4 * a * Sum(x, (x, 1, y))
assert Sum(4 * x * y, (x, 1, y)).factor() == 4 * y * Sum(x, (x, 1, y))
# test expand
assert Sum(x+1,(x,1,y)).expand() == Sum(x,(x,1,y)) + Sum(1,(x,1,y))
assert Sum(x+a*x**2,(x,1,y)).expand() == Sum(x,(x,1,y)) + Sum(a*x**2,(x,1,y))
assert Sum(x**(n + 1)*(n + 1), (n, -1, oo)).expand() \
== Sum(x*x**n, (n, -1, oo)) + Sum(n*x*x**n, (n, -1, oo))
assert Sum(x**(n + 1)*(n + 1), (n, -1, oo)).expand(power_exp=False) \
== Sum(n*x**(n+1), (n, -1, oo)) + Sum(x**(n+1), (n, -1, oo))
assert Sum(a*n+a*n**2,(n,0,4)).expand() \
== Sum(a*n,(n,0,4)) + Sum(a*n**2,(n,0,4))
assert Sum(x**a*x**n,(x,0,3)) \
== Sum(x**(a+n),(x,0,3)).expand(power_exp=True)
assert Sum(x**(a+n),(x,0,3)) \
== Sum(x**(a+n),(x,0,3)).expand(power_exp=False)
# test subs
assert Sum(1/(1+a*x**2),(x,0,3)).subs([(a,3)]) == Sum(1/(1+3*x**2),(x,0,3))
assert Sum(x*y,(x,0,y),(y,0,x)).subs([(x,3)]) == Sum(x*y,(x,0,y),(y,0,3))
assert Sum(x,(x,1,10)).subs([(x,y-2)]) == Sum(x,(x,1,10))
assert Sum(1/x,(x,1,10)).subs([(x,(3+n)**3)]) == Sum(1/x,(x,1,10))
assert Sum(1/x,(x,1,10)).subs([(x,3*x-2)]) == Sum(1/x,(x,1,10))
def test_distribution_over_equality():
f = Function('f')
assert Product(Eq(x*2, f(x)), (x, 1, 3)).doit() == Eq(48, f(1)*f(2)*f(3))
assert Sum(Eq(f(x), x**2), (x, 0, y)) == \
Eq(Sum(f(x), (x, 0, y)), Sum(x**2, (x, 0, y)))
def test_issue_2787():
n, k = symbols('n k', positive=True, integer=True)
p = symbols('p', positive=True)
binomial_dist = binomial(n, k)*p**k*(1 - p)**(n - k)
s = Sum(binomial_dist*k, (k, 0, n))
res = s.doit().simplify()
assert res == Piecewise(
(n*p, p/Abs(p - 1) <= 1),
((-p + 1)**n*Sum(k*p**k*binomial(n, k)/(-p + 1)**(k), (k, 0, n)),
True))
# Issue #17165: make sure that another simplify does not complicate
# the result (but why didn't first simplify handle this?)
assert res.simplify() == Piecewise((n*p, p <= S.Half),
((1 - p)**n*Sum(k*p**k*binomial(n, k)/(1 - p)**k,
(k, 0, n)), True))
def test_issue_4668():
assert summation(1/n, (n, 2, oo)) is oo
def test_matrix_sum():
A = Matrix([[0, 1], [n, 0]])
result = Sum(A, (n, 0, 3)).doit()
assert result == Matrix([[0, 4], [6, 0]])
assert result.__class__ == ImmutableDenseMatrix
A = SparseMatrix([[0, 1], [n, 0]])
result = Sum(A, (n, 0, 3)).doit()
assert result.__class__ == ImmutableSparseMatrix
def test_failing_matrix_sum():
n = Symbol('n')
# TODO Implement matrix geometric series summation.
A = Matrix([[0, 1, 0], [-1, 0, 0], [0, 0, 0]])
assert Sum(A ** n, (n, 1, 4)).doit() == \
Matrix([[0, 0, 0], [0, 0, 0], [0, 0, 0]])
# issue sympy/sympy#16989
assert summation(A**n, (n, 1, 1)) == A
def test_indexed_idx_sum():
i = symbols('i', cls=Idx)
r = Indexed('r', i)
assert Sum(r, (i, 0, 3)).doit() == sum([r.xreplace({i: j}) for j in range(4)])
assert Product(r, (i, 0, 3)).doit() == prod([r.xreplace({i: j}) for j in range(4)])
j = symbols('j', integer=True)
assert Sum(r, (i, j, j+2)).doit() == sum([r.xreplace({i: j+k}) for k in range(3)])
assert Product(r, (i, j, j+2)).doit() == prod([r.xreplace({i: j+k}) for k in range(3)])
k = Idx('k', range=(1, 3))
A = IndexedBase('A')
assert Sum(A[k], k).doit() == sum([A[Idx(j, (1, 3))] for j in range(1, 4)])
assert Product(A[k], k).doit() == prod([A[Idx(j, (1, 3))] for j in range(1, 4)])
raises(ValueError, lambda: Sum(A[k], (k, 1, 4)))
raises(ValueError, lambda: Sum(A[k], (k, 0, 3)))
raises(ValueError, lambda: Sum(A[k], (k, 2, oo)))
raises(ValueError, lambda: Product(A[k], (k, 1, 4)))
raises(ValueError, lambda: Product(A[k], (k, 0, 3)))
raises(ValueError, lambda: Product(A[k], (k, 2, oo)))
@slow
def test_is_convergent():
# divergence tests --
assert Sum(n/(2*n + 1), (n, 1, oo)).is_convergent() is S.false
assert Sum(factorial(n)/5**n, (n, 1, oo)).is_convergent() is S.false
assert Sum(3**(-2*n - 1)*n**n, (n, 1, oo)).is_convergent() is S.false
assert Sum((-1)**n*n, (n, 3, oo)).is_convergent() is S.false
assert Sum((-1)**n, (n, 1, oo)).is_convergent() is S.false
assert Sum(log(1/n), (n, 2, oo)).is_convergent() is S.false
# Raabe's test --
assert Sum(Product((3*m),(m,1,n))/Product((3*m+4),(m,1,n)),(n,1,oo)).is_convergent() is S.true
# root test --
assert Sum((-12)**n/n, (n, 1, oo)).is_convergent() is S.false
# integral test --
# p-series test --
assert Sum(1/(n**2 + 1), (n, 1, oo)).is_convergent() is S.true
assert Sum(1/n**Rational(6, 5), (n, 1, oo)).is_convergent() is S.true
assert Sum(2/(n*sqrt(n - 1)), (n, 2, oo)).is_convergent() is S.true
assert Sum(1/(sqrt(n)*sqrt(n)), (n, 2, oo)).is_convergent() is S.false
assert Sum(factorial(n) / factorial(n+2), (n, 1, oo)).is_convergent() is S.true
assert Sum(rf(5,n)/rf(7,n),(n,1,oo)).is_convergent() is S.true
assert Sum((rf(1, n)*rf(2, n))/(rf(3, n)*factorial(n)),(n,1,oo)).is_convergent() is S.false
# comparison test --
assert Sum(1/(n + log(n)), (n, 1, oo)).is_convergent() is S.false
assert Sum(1/(n**2*log(n)), (n, 2, oo)).is_convergent() is S.true
assert Sum(1/(n*log(n)), (n, 2, oo)).is_convergent() is S.false
assert Sum(2/(n*log(n)*log(log(n))**2), (n, 5, oo)).is_convergent() is S.true
assert Sum(2/(n*log(n)**2), (n, 2, oo)).is_convergent() is S.true
assert Sum((n - 1)/(n**2*log(n)**3), (n, 2, oo)).is_convergent() is S.true
assert Sum(1/(n*log(n)*log(log(n))), (n, 5, oo)).is_convergent() is S.false
assert Sum((n - 1)/(n*log(n)**3), (n, 3, oo)).is_convergent() is S.false
assert Sum(2/(n**2*log(n)), (n, 2, oo)).is_convergent() is S.true
assert Sum(1/(n*sqrt(log(n))*log(log(n))), (n, 100, oo)).is_convergent() is S.false
assert Sum(log(log(n))/(n*log(n)**2), (n, 100, oo)).is_convergent() is S.true
assert Sum(log(n)/n**2, (n, 5, oo)).is_convergent() is S.true
# alternating series tests --
assert Sum((-1)**(n - 1)/(n**2 - 1), (n, 3, oo)).is_convergent() is S.true
# with -negativeInfinite Limits
assert Sum(1/(n**2 + 1), (n, -oo, 1)).is_convergent() is S.true
assert Sum(1/(n - 1), (n, -oo, -1)).is_convergent() is S.false
assert Sum(1/(n**2 - 1), (n, -oo, -5)).is_convergent() is S.true
assert Sum(1/(n**2 - 1), (n, -oo, 2)).is_convergent() is S.true
assert Sum(1/(n**2 - 1), (n, -oo, oo)).is_convergent() is S.true
# piecewise functions
f = Piecewise((n**(-2), n <= 1), (n**2, n > 1))
assert Sum(f, (n, 1, oo)).is_convergent() is S.false
assert Sum(f, (n, -oo, oo)).is_convergent() is S.false
assert Sum(f, (n, 1, 100)).is_convergent() is S.true
#assert Sum(f, (n, -oo, 1)).is_convergent() is S.true
# integral test
assert Sum(log(n)/n**3, (n, 1, oo)).is_convergent() is S.true
assert Sum(-log(n)/n**3, (n, 1, oo)).is_convergent() is S.true
# the following function has maxima located at (x, y) =
# (1.2, 0.43), (3.0, -0.25) and (6.8, 0.050)
eq = (x - 2)*(x**2 - 6*x + 4)*exp(-x)
assert Sum(eq, (x, 1, oo)).is_convergent() is S.true
assert Sum(eq, (x, 1, 2)).is_convergent() is S.true
assert Sum(1/(x**3), (x, 1, oo)).is_convergent() is S.true
assert Sum(1/(x**S.Half), (x, 1, oo)).is_convergent() is S.false
# issue 19545
assert Sum(1/n - 3/(3*n +2), (n, 1, oo)).is_convergent() is S.true
# issue 19836
assert Sum(4/(n + 2) - 5/(n + 1) + 1/n,(n, 7, oo)).is_convergent() is S.true
def test_is_absolutely_convergent():
assert Sum((-1)**n, (n, 1, oo)).is_absolutely_convergent() is S.false
assert Sum((-1)**n/n**2, (n, 1, oo)).is_absolutely_convergent() is S.true
@XFAIL
def test_convergent_failing():
# dirichlet tests
assert Sum(sin(n)/n, (n, 1, oo)).is_convergent() is S.true
assert Sum(sin(2*n)/n, (n, 1, oo)).is_convergent() is S.true
def test_issue_6966():
i, k, m = symbols('i k m', integer=True)
z_i, q_i = symbols('z_i q_i')
a_k = Sum(-q_i*z_i/k,(i,1,m))
b_k = a_k.diff(z_i)
assert isinstance(b_k, Sum)
assert b_k == Sum(-q_i/k,(i,1,m))
def test_issue_10156():
cx = Sum(2*y**2*x, (x, 1,3))
e = 2*y*Sum(2*cx*x**2, (x, 1, 9))
assert e.factor() == \
8*y**3*Sum(x, (x, 1, 3))*Sum(x**2, (x, 1, 9))
def test_issue_10973():
assert Sum((-n + (n**3 + 1)**(S(1)/3))/log(n), (n, 1, oo)).is_convergent() is S.true
def test_issue_14129():
assert Sum( k*x**k, (k, 0, n-1)).doit() == \
Piecewise((n**2/2 - n/2, Eq(x, 1)), ((n*x*x**n -
n*x**n - x*x**n + x)/(x - 1)**2, True))
assert Sum( x**k, (k, 0, n-1)).doit() == \
Piecewise((n, Eq(x, 1)), ((-x**n + 1)/(-x + 1), True))
assert Sum( k*(x/y+x)**k, (k, 0, n-1)).doit() == \
Piecewise((n*(n - 1)/2, Eq(x, y/(y + 1))),
(x*(y + 1)*(n*x*y*(x + x/y)**n/(x + x/y)
+ n*x*(x + x/y)**n/(x + x/y) - n*y*(x
+ x/y)**n/(x + x/y) - x*y*(x + x/y)**n/(x
+ x/y) - x*(x + x/y)**n/(x + x/y) + y)/(x*y
+ x - y)**2, True))
def test_issue_14112():
assert Sum((-1)**n/sqrt(n), (n, 1, oo)).is_absolutely_convergent() is S.false
assert Sum((-1)**(2*n)/n, (n, 1, oo)).is_convergent() is S.false
assert Sum((-2)**n + (-3)**n, (n, 1, oo)).is_convergent() is S.false
def test_sin_times_absolutely_convergent():
assert Sum(sin(n) / n**3, (n, 1, oo)).is_convergent() is S.true
assert Sum(sin(n) * log(n) / n**3, (n, 1, oo)).is_convergent() is S.true
def test_issue_14111():
assert Sum(1/log(log(n)), (n, 22, oo)).is_convergent() is S.false
def test_issue_14484():
assert Sum(sin(n)/log(log(n)), (n, 22, oo)).is_convergent() is S.false
def test_issue_14640():
i, n = symbols("i n", integer=True)
a, b, c = symbols("a b c")
assert Sum(a**-i/(a - b), (i, 0, n)).doit() == Sum(
1/(a*a**i - a**i*b), (i, 0, n)).doit() == Piecewise(
(n + 1, Eq(1/a, 1)),
((-a**(-n - 1) + 1)/(1 - 1/a), True))/(a - b)
assert Sum((b*a**i - c*a**i)**-2, (i, 0, n)).doit() == Piecewise(
(n + 1, Eq(a**(-2), 1)),
((-a**(-2*n - 2) + 1)/(1 - 1/a**2), True))/(b - c)**2
s = Sum(i*(a**(n - i) - b**(n - i))/(a - b), (i, 0, n)).doit()
assert not s.has(Sum)
assert s.subs({a: 2, b: 3, n: 5}) == 122
def test_issue_15943():
s = Sum(binomial(n, k)*factorial(n - k), (k, 0, n)).doit().rewrite(gamma)
assert s == -E*(n + 1)*gamma(n + 1)*lowergamma(n + 1, 1)/gamma(n + 2
) + E*gamma(n + 1)
assert s.simplify() == E*(factorial(n) - lowergamma(n + 1, 1))
def test_Sum_dummy_eq():
assert not Sum(x, (x, a, b)).dummy_eq(1)
assert not Sum(x, (x, a, b)).dummy_eq(Sum(x, (x, a, b), (a, 1, 2)))
assert not Sum(x, (x, a, b)).dummy_eq(Sum(x, (x, a, c)))
assert Sum(x, (x, a, b)).dummy_eq(Sum(x, (x, a, b)))
d = Dummy()
assert Sum(x, (x, a, d)).dummy_eq(Sum(x, (x, a, c)), c)
assert not Sum(x, (x, a, d)).dummy_eq(Sum(x, (x, a, c)))
assert Sum(x, (x, a, c)).dummy_eq(Sum(y, (y, a, c)))
assert Sum(x, (x, a, d)).dummy_eq(Sum(y, (y, a, c)), c)
assert not Sum(x, (x, a, d)).dummy_eq(Sum(y, (y, a, c)))
def test_issue_15852():
assert summation(x**y*y, (y, -oo, oo)).doit() == Sum(x**y*y, (y, -oo, oo))
def test_exceptions():
S = Sum(x, (x, a, b))
raises(ValueError, lambda: S.change_index(x, x**2, y))
S = Sum(x, (x, a, b), (x, 1, 4))
raises(ValueError, lambda: S.index(x))
S = Sum(x, (x, a, b), (y, 1, 4))
raises(ValueError, lambda: S.reorder([x]))
S = Sum(x, (x, y, b), (y, 1, 4))
raises(ReorderError, lambda: S.reorder_limit(0, 1))
S = Sum(x*y, (x, a, b), (y, 1, 4))
raises(NotImplementedError, lambda: S.is_convergent())
def test_sumproducts_assumptions():
M = Symbol('M', integer=True, positive=True)
m = Symbol('m', integer=True)
for func in [Sum, Product]:
assert func(m, (m, -M, M)).is_positive is None
assert func(m, (m, -M, M)).is_nonpositive is None
assert func(m, (m, -M, M)).is_negative is None
assert func(m, (m, -M, M)).is_nonnegative is None
assert func(m, (m, -M, M)).is_finite is True
m = Symbol('m', integer=True, nonnegative=True)
for func in [Sum, Product]:
assert func(m, (m, 0, M)).is_positive is None
assert func(m, (m, 0, M)).is_nonpositive is None
assert func(m, (m, 0, M)).is_negative is False
assert func(m, (m, 0, M)).is_nonnegative is True
assert func(m, (m, 0, M)).is_finite is True
m = Symbol('m', integer=True, positive=True)
for func in [Sum, Product]:
assert func(m, (m, 1, M)).is_positive is True
assert func(m, (m, 1, M)).is_nonpositive is False
assert func(m, (m, 1, M)).is_negative is False
assert func(m, (m, 1, M)).is_nonnegative is True
assert func(m, (m, 1, M)).is_finite is True
m = Symbol('m', integer=True, negative=True)
assert Sum(m, (m, -M, -1)).is_positive is False
assert Sum(m, (m, -M, -1)).is_nonpositive is True
assert Sum(m, (m, -M, -1)).is_negative is True
assert Sum(m, (m, -M, -1)).is_nonnegative is False
assert Sum(m, (m, -M, -1)).is_finite is True
assert Product(m, (m, -M, -1)).is_positive is None
assert Product(m, (m, -M, -1)).is_nonpositive is None
assert Product(m, (m, -M, -1)).is_negative is None
assert Product(m, (m, -M, -1)).is_nonnegative is None
assert Product(m, (m, -M, -1)).is_finite is True
m = Symbol('m', integer=True, nonpositive=True)
assert Sum(m, (m, -M, 0)).is_positive is False
assert Sum(m, (m, -M, 0)).is_nonpositive is True
assert Sum(m, (m, -M, 0)).is_negative is None
assert Sum(m, (m, -M, 0)).is_nonnegative is None
assert Sum(m, (m, -M, 0)).is_finite is True
assert Product(m, (m, -M, 0)).is_positive is None
assert Product(m, (m, -M, 0)).is_nonpositive is None
assert Product(m, (m, -M, 0)).is_negative is None
assert Product(m, (m, -M, 0)).is_nonnegative is None
assert Product(m, (m, -M, 0)).is_finite is True
m = Symbol('m', integer=True)
assert Sum(2, (m, 0, oo)).is_positive is None
assert Sum(2, (m, 0, oo)).is_nonpositive is None
assert Sum(2, (m, 0, oo)).is_negative is None
assert Sum(2, (m, 0, oo)).is_nonnegative is None
assert Sum(2, (m, 0, oo)).is_finite is None
assert Product(2, (m, 0, oo)).is_positive is None
assert Product(2, (m, 0, oo)).is_nonpositive is None
assert Product(2, (m, 0, oo)).is_negative is False
assert Product(2, (m, 0, oo)).is_nonnegative is None
assert Product(2, (m, 0, oo)).is_finite is None
assert Product(0, (x, M, M-1)).is_positive is True
assert Product(0, (x, M, M-1)).is_finite is True
def test_expand_with_assumptions():
M = Symbol('M', integer=True, positive=True)
x = Symbol('x', positive=True)
m = Symbol('m', nonnegative=True)
assert log(Product(x**m, (m, 0, M))).expand() == Sum(m*log(x), (m, 0, M))
assert log(Product(exp(x**m), (m, 0, M))).expand() == Sum(x**m, (m, 0, M))
assert log(Product(x**m, (m, 0, M))).rewrite(Sum).expand() == Sum(m*log(x), (m, 0, M))
assert log(Product(exp(x**m), (m, 0, M))).rewrite(Sum).expand() == Sum(x**m, (m, 0, M))
n = Symbol('n', nonnegative=True)
i, j = symbols('i,j', positive=True, integer=True)
x, y = symbols('x,y', positive=True)
assert log(Product(x**i*y**j, (i, 1, n), (j, 1, m))).expand() \
== Sum(i*log(x) + j*log(y), (i, 1, n), (j, 1, m))
def test_has_finite_limits():
x = Symbol('x')
assert Sum(1, (x, 1, 9)).has_finite_limits is True
assert Sum(1, (x, 1, oo)).has_finite_limits is False
M = Symbol('M')
assert Sum(1, (x, 1, M)).has_finite_limits is None
M = Symbol('M', positive=True)
assert Sum(1, (x, 1, M)).has_finite_limits is True
x = Symbol('x', positive=True)
M = Symbol('M')
assert Sum(1, (x, 1, M)).has_finite_limits is True
assert Sum(1, (x, 1, M), (y, -oo, oo)).has_finite_limits is False
def test_has_reversed_limits():
assert Sum(1, (x, 1, 1)).has_reversed_limits is False
assert Sum(1, (x, 1, 9)).has_reversed_limits is False
assert Sum(1, (x, 1, -9)).has_reversed_limits is True
assert Sum(1, (x, 1, 0)).has_reversed_limits is True
assert Sum(1, (x, 1, oo)).has_reversed_limits is False
M = Symbol('M')
assert Sum(1, (x, 1, M)).has_reversed_limits is None
M = Symbol('M', positive=True, integer=True)
assert Sum(1, (x, 1, M)).has_reversed_limits is False
assert Sum(1, (x, 1, M), (y, -oo, oo)).has_reversed_limits is False
M = Symbol('M', negative=True)
assert Sum(1, (x, 1, M)).has_reversed_limits is True
assert Sum(1, (x, 1, M), (y, -oo, oo)).has_reversed_limits is True
assert Sum(1, (x, oo, oo)).has_reversed_limits is None
def test_has_empty_sequence():
assert Sum(1, (x, 1, 1)).has_empty_sequence is False
assert Sum(1, (x, 1, 9)).has_empty_sequence is False
assert Sum(1, (x, 1, -9)).has_empty_sequence is False
assert Sum(1, (x, 1, 0)).has_empty_sequence is True
assert Sum(1, (x, y, y - 1)).has_empty_sequence is True
assert Sum(1, (x, 3, 2), (y, -oo, oo)).has_empty_sequence is True
assert Sum(1, (y, -oo, oo), (x, 3, 2)).has_empty_sequence is True
assert Sum(1, (x, oo, oo)).has_empty_sequence is False
def test_empty_sequence():
assert Product(x*y, (x, -oo, oo), (y, 1, 0)).doit() == 1
assert Product(x*y, (y, 1, 0), (x, -oo, oo)).doit() == 1
assert Sum(x, (x, -oo, oo), (y, 1, 0)).doit() == 0
assert Sum(x, (y, 1, 0), (x, -oo, oo)).doit() == 0
def test_issue_8016():
k = Symbol('k', integer=True)
n, m = symbols('n, m', integer=True, positive=True)
s = Sum(binomial(m, k)*binomial(m, n - k)*(-1)**k, (k, 0, n))
assert s.doit().simplify() == \
cos(pi*n/2)*gamma(m + 1)/gamma(n/2 + 1)/gamma(m - n/2 + 1)
def test_issue_14313():
assert Sum(S.Half**floor(n/2), (n, 1, oo)).is_convergent()
def test_issue_14563():
# The assertion was failing due to no assumptions methods in Sums and Product
assert 1 % Sum(1, (x, 0, 1)) == 1
def test_issue_16735():
assert Sum(5**n/gamma(n+1), (n, 1, oo)).is_convergent() is S.true
def test_issue_14871():
assert Sum((Rational(1, 10))**n*rf(0, n)/factorial(n), (n, 0, oo)).rewrite(factorial).doit() == 1
def test_issue_17165():
n = symbols("n", integer=True)
x = symbols('x')
s = (x*Sum(x**n, (n, -1, oo)))
ssimp = s.doit().simplify()
assert ssimp == Piecewise((-1/(x - 1), (x > -1) & (x < 1)),
(x*Sum(x**n, (n, -1, oo)), True)), ssimp
assert ssimp.simplify() == ssimp
def test_issue_19379():
assert Sum(factorial(n)/factorial(n + 2), (n, 1, oo)).is_convergent() is S.true
def test_issue_20777():
assert Sum(exp(x*sin(n/m)), (n, 1, m)).doit() == Sum(exp(x*sin(n/m)), (n, 1, m))
def test__dummy_with_inherited_properties_concrete():
x = Symbol('x')
from sympy.core.containers import Tuple
d = _dummy_with_inherited_properties_concrete(Tuple(x, 0, 5))
assert d.is_real
assert d.is_integer
assert d.is_nonnegative
assert d.is_extended_nonnegative
d = _dummy_with_inherited_properties_concrete(Tuple(x, 1, 9))
assert d.is_real
assert d.is_integer
assert d.is_positive
assert d.is_odd is None
d = _dummy_with_inherited_properties_concrete(Tuple(x, -5, 5))
assert d.is_real
assert d.is_integer
assert d.is_positive is None
assert d.is_extended_nonnegative is None
assert d.is_odd is None
d = _dummy_with_inherited_properties_concrete(Tuple(x, -1.5, 1.5))
assert d.is_real
assert d.is_integer is None
assert d.is_positive is None
assert d.is_extended_nonnegative is None
N = Symbol('N', integer=True, positive=True)
d = _dummy_with_inherited_properties_concrete(Tuple(x, 2, N))
assert d.is_real
assert d.is_positive
assert d.is_integer
# Return None if no assumptions are added
N = Symbol('N', integer=True, positive=True)
d = _dummy_with_inherited_properties_concrete(Tuple(N, 2, 4))
assert d is None
x = Symbol('x', negative=True)
raises(InconsistentAssumptions,
lambda: _dummy_with_inherited_properties_concrete(Tuple(x, 1, 5)))
def test_matrixsymbol_summation_numerical_limits():
A = MatrixSymbol('A', 3, 3)
n = Symbol('n', integer=True)
assert Sum(A**n, (n, 0, 2)).doit() == Identity(3) + A + A**2
assert Sum(A, (n, 0, 2)).doit() == 3*A
assert Sum(n*A, (n, 0, 2)).doit() == 3*A
B = Matrix([[0, n, 0], [-1, 0, 0], [0, 0, 2]])
ans = Matrix([[0, 6, 0], [-4, 0, 0], [0, 0, 8]]) + 4*A
assert Sum(A+B, (n, 0, 3)).doit() == ans
ans = A*Matrix([[0, 6, 0], [-4, 0, 0], [0, 0, 8]])
assert Sum(A*B, (n, 0, 3)).doit() == ans
ans = (A**2*Matrix([[-2, 0, 0], [0,-2, 0], [0, 0, 4]]) +
A**3*Matrix([[0, -9, 0], [3, 0, 0], [0, 0, 8]]) +
A*Matrix([[0, 1, 0], [-1, 0, 0], [0, 0, 2]]))
assert Sum(A**n*B**n, (n, 1, 3)).doit() == ans
def test_issue_21651():
i = Symbol('i')
a = Sum(floor(2*2**(-i)), (i, S.One, 2))
assert a.doit() == S.One
@XFAIL
def test_matrixsymbol_summation_symbolic_limits():
N = Symbol('N', integer=True, positive=True)
A = MatrixSymbol('A', 3, 3)
n = Symbol('n', integer=True)
assert Sum(A, (n, 0, N)).doit() == (N+1)*A
assert Sum(n*A, (n, 0, N)).doit() == (N**2/2+N/2)*A
def test_summation_by_residues():
x = Symbol('x')
# Examples from Nakhle H. Asmar, Loukas Grafakos,
# Complex Analysis with Applications
assert eval_sum_residue(1 / (x**2 + 1), (x, -oo, oo)) == pi/tanh(pi)
assert eval_sum_residue(1 / x**6, (x, S(1), oo)) == pi**6/945
assert eval_sum_residue(1 / (x**2 + 9), (x, -oo, oo)) == pi/(3*tanh(3*pi))
assert eval_sum_residue(1 / (x**2 + 1)**2, (x, -oo, oo)).cancel() == \
(-pi**2*tanh(pi)**2 + pi*tanh(pi) + pi**2)/(2*tanh(pi)**2)
assert eval_sum_residue(x**2 / (x**2 + 1)**2, (x, -oo, oo)).cancel() == \
(-pi**2 + pi*tanh(pi) + pi**2*tanh(pi)**2)/(2*tanh(pi)**2)
assert eval_sum_residue(1 / (4*x**2 - 1), (x, -oo, oo)) == 0
assert eval_sum_residue(x**2 / (x**2 - S(1)/4)**2, (x, -oo, oo)) == pi**2/2
assert eval_sum_residue(1 / (4*x**2 - 1)**2, (x, -oo, oo)) == pi**2/8
assert eval_sum_residue(1 / ((x - S(1)/2)**2 + 1), (x, -oo, oo)) == pi*tanh(pi)
assert eval_sum_residue(1 / x**2, (x, S(1), oo)) == pi**2/6
assert eval_sum_residue(1 / x**4, (x, S(1), oo)) == pi**4/90
assert eval_sum_residue(1 / x**2 / (x**2 + 4), (x, S(1), oo)) == \
-pi*(-pi/12 - 1/(16*pi) + 1/(8*tanh(2*pi)))/2
# Some examples made from 1 / (x**2 + 1)
assert eval_sum_residue(1 / (x**2 + 1), (x, S(0), oo)) == \
S(1)/2 + pi/(2*tanh(pi))
assert eval_sum_residue(1 / (x**2 + 1), (x, S(1), oo)) == \
-S(1)/2 + pi/(2*tanh(pi))
assert eval_sum_residue(1 / (x**2 + 1), (x, S(-1), oo)) == \
1 + pi/(2*tanh(pi))
assert eval_sum_residue((-1)**x / (x**2 + 1), (x, -oo, oo)) == \
pi/sinh(pi)
assert eval_sum_residue((-1)**x / (x**2 + 1), (x, S(0), oo)) == \
pi/(2*sinh(pi)) + S(1)/2
assert eval_sum_residue((-1)**x / (x**2 + 1), (x, S(1), oo)) == \
-S(1)/2 + pi/(2*sinh(pi))
assert eval_sum_residue((-1)**x / (x**2 + 1), (x, S(-1), oo)) == \
pi/(2*sinh(pi))
# Some examples made from shifting of 1 / (x**2 + 1)
assert eval_sum_residue(1 / (x**2 + 2*x + 2), (x, S(-1), oo)) == S(1)/2 + pi/(2*tanh(pi))
assert eval_sum_residue(1 / (x**2 + 4*x + 5), (x, S(-2), oo)) == S(1)/2 + pi/(2*tanh(pi))
assert eval_sum_residue(1 / (x**2 - 2*x + 2), (x, S(1), oo)) == S(1)/2 + pi/(2*tanh(pi))
assert eval_sum_residue(1 / (x**2 - 4*x + 5), (x, S(2), oo)) == S(1)/2 + pi/(2*tanh(pi))
assert eval_sum_residue((-1)**x * -1 / (x**2 + 2*x + 2), (x, S(-1), oo)) == S(1)/2 + pi/(2*sinh(pi))
assert eval_sum_residue((-1)**x * -1 / (x**2 -2*x + 2), (x, S(1), oo)) == S(1)/2 + pi/(2*sinh(pi))
# Some examples made from 1 / x**2
assert eval_sum_residue(1 / x**2, (x, S(2), oo)) == -1 + pi**2/6
assert eval_sum_residue(1 / x**2, (x, S(3), oo)) == -S(5)/4 + pi**2/6
assert eval_sum_residue((-1)**x / x**2, (x, S(1), oo)) == -pi**2/12
assert eval_sum_residue((-1)**x / x**2, (x, S(2), oo)) == 1 - pi**2/12
@slow
def test_summation_by_residues_failing():
x = Symbol('x')
# Failing because of the bug in residue computation
assert eval_sum_residue(x**2 / (x**4 + 1), (x, S(1), oo))
assert eval_sum_residue(1 / ((x - 1)*(x - 2) + 1), (x, -oo, oo)) != 0
def test_process_limits():
from sympy.concrete.expr_with_limits import _process_limits
# these should be (x, Range(3)) not Range(3)
raises(ValueError, lambda: _process_limits(
Range(3), discrete=True))
raises(ValueError, lambda: _process_limits(
Range(3), discrete=False))
# these should be (x, union) not union
# (but then we would get a TypeError because we don't
# handle non-contiguous sets: see below use of `union`)
union = Or(x < 1, x > 3).as_set()
raises(ValueError, lambda: _process_limits(
union, discrete=True))
raises(ValueError, lambda: _process_limits(
union, discrete=False))
# error not triggered if not needed
assert _process_limits((x, 1, 2)) == ([(x, 1, 2)], 1)
# this equivalence is used to detect Reals in _process_limits
assert isinstance(S.Reals, Interval)
C = Integral # continuous limits
assert C(x, x >= 5) == C(x, (x, 5, oo))
assert C(x, x < 3) == C(x, (x, -oo, 3))
ans = C(x, (x, 0, 3))
assert C(x, And(x >= 0, x < 3)) == ans
assert C(x, (x, Interval.Ropen(0, 3))) == ans
raises(TypeError, lambda: C(x, (x, Range(3))))
# discrete limits
for D in (Sum, Product):
r, ans = Range(3, 10, 2), D(2*x + 3, (x, 0, 3))
assert D(x, (x, r)) == ans
assert D(x, (x, r.reversed)) == ans
r, ans = Range(3, oo, 2), D(2*x + 3, (x, 0, oo))
assert D(x, (x, r)) == ans
assert D(x, (x, r.reversed)) == ans
r, ans = Range(-oo, 5, 2), D(3 - 2*x, (x, 0, oo))
assert D(x, (x, r)) == ans
assert D(x, (x, r.reversed)) == ans
raises(TypeError, lambda: D(x, x > 0))
raises(ValueError, lambda: D(x, Interval(1, 3)))
raises(NotImplementedError, lambda: D(x, (x, union)))
|
c825fc9a78cf57404005aae02720d4412f2aeaab2c27753bbe75d2b686fd6cde | import sympy
import tempfile
import os
from sympy.core.mod import Mod
from sympy.core.relational import Eq
from sympy.core.symbol import symbols
from sympy.external import import_module
from sympy.tensor import IndexedBase, Idx
from sympy.utilities.autowrap import autowrap, ufuncify, CodeWrapError
from sympy.testing.pytest import skip
numpy = import_module('numpy', min_module_version='1.6.1')
Cython = import_module('Cython', min_module_version='0.15.1')
f2py = import_module('numpy.f2py', import_kwargs={'fromlist': ['f2py']})
f2pyworks = False
if f2py:
try:
autowrap(symbols('x'), 'f95', 'f2py')
except (CodeWrapError, ImportError, OSError):
f2pyworks = False
else:
f2pyworks = True
a, b, c = symbols('a b c')
n, m, d = symbols('n m d', integer=True)
A, B, C = symbols('A B C', cls=IndexedBase)
i = Idx('i', m)
j = Idx('j', n)
k = Idx('k', d)
def has_module(module):
"""
Return True if module exists, otherwise run skip().
module should be a string.
"""
# To give a string of the module name to skip(), this function takes a
# string. So we don't waste time running import_module() more than once,
# just map the three modules tested here in this dict.
modnames = {'numpy': numpy, 'Cython': Cython, 'f2py': f2py}
if modnames[module]:
if module == 'f2py' and not f2pyworks:
skip("Couldn't run f2py.")
return True
skip("Couldn't import %s." % module)
#
# test runners used by several language-backend combinations
#
def runtest_autowrap_twice(language, backend):
f = autowrap((((a + b)/c)**5).expand(), language, backend)
g = autowrap((((a + b)/c)**4).expand(), language, backend)
# check that autowrap updates the module name. Else, g gives the same as f
assert f(1, -2, 1) == -1.0
assert g(1, -2, 1) == 1.0
def runtest_autowrap_trace(language, backend):
has_module('numpy')
trace = autowrap(A[i, i], language, backend)
assert trace(numpy.eye(100)) == 100
def runtest_autowrap_matrix_vector(language, backend):
has_module('numpy')
x, y = symbols('x y', cls=IndexedBase)
expr = Eq(y[i], A[i, j]*x[j])
mv = autowrap(expr, language, backend)
# compare with numpy's dot product
M = numpy.random.rand(10, 20)
x = numpy.random.rand(20)
y = numpy.dot(M, x)
assert numpy.sum(numpy.abs(y - mv(M, x))) < 1e-13
def runtest_autowrap_matrix_matrix(language, backend):
has_module('numpy')
expr = Eq(C[i, j], A[i, k]*B[k, j])
matmat = autowrap(expr, language, backend)
# compare with numpy's dot product
M1 = numpy.random.rand(10, 20)
M2 = numpy.random.rand(20, 15)
M3 = numpy.dot(M1, M2)
assert numpy.sum(numpy.abs(M3 - matmat(M1, M2))) < 1e-13
def runtest_ufuncify(language, backend):
has_module('numpy')
a, b, c = symbols('a b c')
fabc = ufuncify([a, b, c], a*b + c, backend=backend)
facb = ufuncify([a, c, b], a*b + c, backend=backend)
grid = numpy.linspace(-2, 2, 50)
b = numpy.linspace(-5, 4, 50)
c = numpy.linspace(-1, 1, 50)
expected = grid*b + c
numpy.testing.assert_allclose(fabc(grid, b, c), expected)
numpy.testing.assert_allclose(facb(grid, c, b), expected)
def runtest_issue_10274(language, backend):
expr = (a - b + c)**(13)
tmp = tempfile.mkdtemp()
f = autowrap(expr, language, backend, tempdir=tmp,
helpers=('helper', a - b + c, (a, b, c)))
assert f(1, 1, 1) == 1
for file in os.listdir(tmp):
if file.startswith("wrapped_code_") and file.endswith(".c"):
fil = open(tmp + '/' + file)
lines = fil.readlines()
assert lines[0] == "/******************************************************************************\n"
assert "Code generated with SymPy " + sympy.__version__ in lines[1]
assert lines[2:] == [
" * *\n",
" * See http://www.sympy.org/ for more information. *\n",
" * *\n",
" * This file is part of 'autowrap' *\n",
" ******************************************************************************/\n",
"#include " + '"' + file[:-1]+ 'h"' + "\n",
"#include <math.h>\n",
"\n",
"double helper(double a, double b, double c) {\n",
"\n",
" double helper_result;\n",
" helper_result = a - b + c;\n",
" return helper_result;\n",
"\n",
"}\n",
"\n",
"double autofunc(double a, double b, double c) {\n",
"\n",
" double autofunc_result;\n",
" autofunc_result = pow(helper(a, b, c), 13);\n",
" return autofunc_result;\n",
"\n",
"}\n",
]
def runtest_issue_15337(language, backend):
has_module('numpy')
# NOTE : autowrap was originally designed to only accept an iterable for
# the kwarg "helpers", but in issue 10274 the user mistakenly thought that
# if there was only a single helper it did not need to be passed via an
# iterable that wrapped the helper tuple. There were no tests for this
# behavior so when the code was changed to accept a single tuple it broke
# the original behavior. These tests below ensure that both now work.
a, b, c, d, e = symbols('a, b, c, d, e')
expr = (a - b + c - d + e)**13
exp_res = (1. - 2. + 3. - 4. + 5.)**13
f = autowrap(expr, language, backend, args=(a, b, c, d, e),
helpers=('f1', a - b + c, (a, b, c)))
numpy.testing.assert_allclose(f(1, 2, 3, 4, 5), exp_res)
f = autowrap(expr, language, backend, args=(a, b, c, d, e),
helpers=(('f1', a - b, (a, b)), ('f2', c - d, (c, d))))
numpy.testing.assert_allclose(f(1, 2, 3, 4, 5), exp_res)
def test_issue_15230():
has_module('f2py')
x, y = symbols('x, y')
expr = Mod(x, 3.0) - Mod(y, -2.0)
f = autowrap(expr, args=[x, y], language='F95')
exp_res = float(expr.xreplace({x: 3.5, y: 2.7}).evalf())
assert abs(f(3.5, 2.7) - exp_res) < 1e-14
x, y = symbols('x, y', integer=True)
expr = Mod(x, 3) - Mod(y, -2)
f = autowrap(expr, args=[x, y], language='F95')
assert f(3, 2) == expr.xreplace({x: 3, y: 2})
#
# tests of language-backend combinations
#
# f2py
def test_wrap_twice_f95_f2py():
has_module('f2py')
runtest_autowrap_twice('f95', 'f2py')
def test_autowrap_trace_f95_f2py():
has_module('f2py')
runtest_autowrap_trace('f95', 'f2py')
def test_autowrap_matrix_vector_f95_f2py():
has_module('f2py')
runtest_autowrap_matrix_vector('f95', 'f2py')
def test_autowrap_matrix_matrix_f95_f2py():
has_module('f2py')
runtest_autowrap_matrix_matrix('f95', 'f2py')
def test_ufuncify_f95_f2py():
has_module('f2py')
runtest_ufuncify('f95', 'f2py')
def test_issue_15337_f95_f2py():
has_module('f2py')
runtest_issue_15337('f95', 'f2py')
# Cython
def test_wrap_twice_c_cython():
has_module('Cython')
runtest_autowrap_twice('C', 'cython')
def test_autowrap_trace_C_Cython():
has_module('Cython')
runtest_autowrap_trace('C99', 'cython')
def test_autowrap_matrix_vector_C_cython():
has_module('Cython')
runtest_autowrap_matrix_vector('C99', 'cython')
def test_autowrap_matrix_matrix_C_cython():
has_module('Cython')
runtest_autowrap_matrix_matrix('C99', 'cython')
def test_ufuncify_C_Cython():
has_module('Cython')
runtest_ufuncify('C99', 'cython')
def test_issue_10274_C_cython():
has_module('Cython')
runtest_issue_10274('C89', 'cython')
def test_issue_15337_C_cython():
has_module('Cython')
runtest_issue_15337('C89', 'cython')
def test_autowrap_custom_printer():
has_module('Cython')
from sympy.core.numbers import pi
from sympy.utilities.codegen import C99CodeGen
from sympy.printing.c import C99CodePrinter
class PiPrinter(C99CodePrinter):
def _print_Pi(self, expr):
return "S_PI"
printer = PiPrinter()
gen = C99CodeGen(printer=printer)
gen.preprocessor_statements.append('#include "shortpi.h"')
expr = pi * a
expected = (
'#include "%s"\n'
'#include <math.h>\n'
'#include "shortpi.h"\n'
'\n'
'double autofunc(double a) {\n'
'\n'
' double autofunc_result;\n'
' autofunc_result = S_PI*a;\n'
' return autofunc_result;\n'
'\n'
'}\n'
)
tmpdir = tempfile.mkdtemp()
# write a trivial header file to use in the generated code
open(os.path.join(tmpdir, 'shortpi.h'), 'w').write('#define S_PI 3.14')
func = autowrap(expr, backend='cython', tempdir=tmpdir, code_gen=gen)
assert func(4.2) == 3.14 * 4.2
# check that the generated code is correct
for filename in os.listdir(tmpdir):
if filename.startswith('wrapped_code') and filename.endswith('.c'):
with open(os.path.join(tmpdir, filename)) as f:
lines = f.readlines()
expected = expected % filename.replace('.c', '.h')
assert ''.join(lines[7:]) == expected
# Numpy
def test_ufuncify_numpy():
# This test doesn't use Cython, but if Cython works, then there is a valid
# C compiler, which is needed.
has_module('Cython')
runtest_ufuncify('C99', 'numpy')
|
0956b0ec3d3ee83391820efc43a6f7e5234a9f4e4f94ac1626ea973ae53ea9d6 | # This testfile tests SymPy <-> SciPy compatibility
# Don't test any SymPy features here. Just pure interaction with SciPy.
# Always write regular SymPy tests for anything, that can be tested in pure
# Python (without scipy). Here we test everything, that a user may need when
# using SymPy with SciPy
from sympy.external import import_module
scipy = import_module('scipy')
if not scipy:
#bin/test will not execute any tests now
disabled = True
from sympy.functions.special.bessel import jn_zeros
def eq(a, b, tol=1e-6):
for x, y in zip(a, b):
if not (abs(x - y) < tol):
return False
return True
def test_jn_zeros():
assert eq(jn_zeros(0, 4, method="scipy"),
[3.141592, 6.283185, 9.424777, 12.566370])
assert eq(jn_zeros(1, 4, method="scipy"),
[4.493409, 7.725251, 10.904121, 14.066193])
assert eq(jn_zeros(2, 4, method="scipy"),
[5.763459, 9.095011, 12.322940, 15.514603])
assert eq(jn_zeros(3, 4, method="scipy"),
[6.987932, 10.417118, 13.698023, 16.923621])
assert eq(jn_zeros(4, 4, method="scipy"),
[8.182561, 11.704907, 15.039664, 18.301255])
|
528c791e6e956637c34f16ea598e79c0f9f308731730ed20653013df2cc495da | # This tests the compilation and execution of the source code generated with
# utilities.codegen. The compilation takes place in a temporary directory that
# is removed after the test. By default the test directory is always removed,
# but this behavior can be changed by setting the environment variable
# SYMPY_TEST_CLEAN_TEMP to:
# export SYMPY_TEST_CLEAN_TEMP=always : the default behavior.
# export SYMPY_TEST_CLEAN_TEMP=success : only remove the directories of working tests.
# export SYMPY_TEST_CLEAN_TEMP=never : never remove the directories with the test code.
# When a directory is not removed, the necessary information is printed on
# screen to find the files that belong to the (failed) tests. If a test does
# not fail, py.test captures all the output and you will not see the directories
# corresponding to the successful tests. Use the --nocapture option to see all
# the output.
# All tests below have a counterpart in utilities/test/test_codegen.py. In the
# latter file, the resulting code is compared with predefined strings, without
# compilation or execution.
# All the generated Fortran code should conform with the Fortran 95 standard,
# and all the generated C code should be ANSI C, which facilitates the
# incorporation in various projects. The tests below assume that the binary cc
# is somewhere in the path and that it can compile ANSI C code.
from sympy.abc import x, y, z
from sympy.testing.pytest import skip
from sympy.utilities.codegen import codegen, make_routine, get_code_generator
import sys
import os
import tempfile
import subprocess
# templates for the main program that will test the generated code.
main_template = {}
main_template['F95'] = """
program main
include "codegen.h"
integer :: result;
result = 0
%(statements)s
call exit(result)
end program
"""
main_template['C89'] = """
#include "codegen.h"
#include <stdio.h>
#include <math.h>
int main() {
int result = 0;
%(statements)s
return result;
}
"""
main_template['C99'] = main_template['C89']
# templates for the numerical tests
numerical_test_template = {}
numerical_test_template['C89'] = """
if (fabs(%(call)s)>%(threshold)s) {
printf("Numerical validation failed: %(call)s=%%e threshold=%(threshold)s\\n", %(call)s);
result = -1;
}
"""
numerical_test_template['C99'] = numerical_test_template['C89']
numerical_test_template['F95'] = """
if (abs(%(call)s)>%(threshold)s) then
write(6,"('Numerical validation failed:')")
write(6,"('%(call)s=',e15.5,'threshold=',e15.5)") %(call)s, %(threshold)s
result = -1;
end if
"""
# command sequences for supported compilers
compile_commands = {}
compile_commands['cc'] = [
"cc -c codegen.c -o codegen.o",
"cc -c main.c -o main.o",
"cc main.o codegen.o -lm -o test.exe"
]
compile_commands['gfortran'] = [
"gfortran -c codegen.f90 -o codegen.o",
"gfortran -ffree-line-length-none -c main.f90 -o main.o",
"gfortran main.o codegen.o -o test.exe"
]
compile_commands['g95'] = [
"g95 -c codegen.f90 -o codegen.o",
"g95 -ffree-line-length-huge -c main.f90 -o main.o",
"g95 main.o codegen.o -o test.exe"
]
compile_commands['ifort'] = [
"ifort -c codegen.f90 -o codegen.o",
"ifort -c main.f90 -o main.o",
"ifort main.o codegen.o -o test.exe"
]
combinations_lang_compiler = [
('C89', 'cc'),
('C99', 'cc'),
('F95', 'ifort'),
('F95', 'gfortran'),
('F95', 'g95')
]
def try_run(commands):
"""Run a series of commands and only return True if all ran fine."""
null = open(os.devnull, 'w')
for command in commands:
retcode = subprocess.call(command, stdout=null, shell=True,
stderr=subprocess.STDOUT)
if retcode != 0:
return False
return True
def run_test(label, routines, numerical_tests, language, commands, friendly=True):
"""A driver for the codegen tests.
This driver assumes that a compiler ifort is present in the PATH and that
ifort is (at least) a Fortran 90 compiler. The generated code is written in
a temporary directory, together with a main program that validates the
generated code. The test passes when the compilation and the validation
run correctly.
"""
# Check input arguments before touching the file system
language = language.upper()
assert language in main_template
assert language in numerical_test_template
# Check that environment variable makes sense
clean = os.getenv('SYMPY_TEST_CLEAN_TEMP', 'always').lower()
if clean not in ('always', 'success', 'never'):
raise ValueError("SYMPY_TEST_CLEAN_TEMP must be one of the following: 'always', 'success' or 'never'.")
# Do all the magic to compile, run and validate the test code
# 1) prepare the temporary working directory, switch to that dir
work = tempfile.mkdtemp("_sympy_%s_test" % language, "%s_" % label)
oldwork = os.getcwd()
os.chdir(work)
# 2) write the generated code
if friendly:
# interpret the routines as a name_expr list and call the friendly
# function codegen
codegen(routines, language, "codegen", to_files=True)
else:
code_gen = get_code_generator(language, "codegen")
code_gen.write(routines, "codegen", to_files=True)
# 3) write a simple main program that links to the generated code, and that
# includes the numerical tests
test_strings = []
for fn_name, args, expected, threshold in numerical_tests:
call_string = "%s(%s)-(%s)" % (
fn_name, ",".join(str(arg) for arg in args), expected)
if language == "F95":
call_string = fortranize_double_constants(call_string)
threshold = fortranize_double_constants(str(threshold))
test_strings.append(numerical_test_template[language] % {
"call": call_string,
"threshold": threshold,
})
if language == "F95":
f_name = "main.f90"
elif language.startswith("C"):
f_name = "main.c"
else:
raise NotImplementedError(
"FIXME: filename extension unknown for language: %s" % language)
with open(f_name, "w") as f:
f.write(
main_template[language] % {'statements': "".join(test_strings)})
# 4) Compile and link
compiled = try_run(commands)
# 5) Run if compiled
if compiled:
executed = try_run(["./test.exe"])
else:
executed = False
# 6) Clean up stuff
if clean == 'always' or (clean == 'success' and compiled and executed):
def safe_remove(filename):
if os.path.isfile(filename):
os.remove(filename)
safe_remove("codegen.f90")
safe_remove("codegen.c")
safe_remove("codegen.h")
safe_remove("codegen.o")
safe_remove("main.f90")
safe_remove("main.c")
safe_remove("main.o")
safe_remove("test.exe")
os.chdir(oldwork)
os.rmdir(work)
else:
print("TEST NOT REMOVED: %s" % work, file=sys.stderr)
os.chdir(oldwork)
# 7) Do the assertions in the end
assert compiled, "failed to compile %s code with:\n%s" % (
language, "\n".join(commands))
assert executed, "failed to execute %s code from:\n%s" % (
language, "\n".join(commands))
def fortranize_double_constants(code_string):
"""
Replaces every literal float with literal doubles
"""
import re
pattern_exp = re.compile(r'\d+(\.)?\d*[eE]-?\d+')
pattern_float = re.compile(r'\d+\.\d*(?!\d*d)')
def subs_exp(matchobj):
return re.sub('[eE]', 'd', matchobj.group(0))
def subs_float(matchobj):
return "%sd0" % matchobj.group(0)
code_string = pattern_exp.sub(subs_exp, code_string)
code_string = pattern_float.sub(subs_float, code_string)
return code_string
def is_feasible(language, commands):
# This test should always work, otherwise the compiler is not present.
routine = make_routine("test", x)
numerical_tests = [
("test", ( 1.0,), 1.0, 1e-15),
("test", (-1.0,), -1.0, 1e-15),
]
try:
run_test("is_feasible", [routine], numerical_tests, language, commands,
friendly=False)
return True
except AssertionError:
return False
valid_lang_commands = []
invalid_lang_compilers = []
for lang, compiler in combinations_lang_compiler:
commands = compile_commands[compiler]
if is_feasible(lang, commands):
valid_lang_commands.append((lang, commands))
else:
invalid_lang_compilers.append((lang, compiler))
# We test all language-compiler combinations, just to report what is skipped
def test_C89_cc():
if ("C89", 'cc') in invalid_lang_compilers:
skip("`cc' command didn't work as expected (C89)")
def test_C99_cc():
if ("C99", 'cc') in invalid_lang_compilers:
skip("`cc' command didn't work as expected (C99)")
def test_F95_ifort():
if ("F95", 'ifort') in invalid_lang_compilers:
skip("`ifort' command didn't work as expected")
def test_F95_gfortran():
if ("F95", 'gfortran') in invalid_lang_compilers:
skip("`gfortran' command didn't work as expected")
def test_F95_g95():
if ("F95", 'g95') in invalid_lang_compilers:
skip("`g95' command didn't work as expected")
# Here comes the actual tests
def test_basic_codegen():
numerical_tests = [
("test", (1.0, 6.0, 3.0), 21.0, 1e-15),
("test", (-1.0, 2.0, -2.5), -2.5, 1e-15),
]
name_expr = [("test", (x + y)*z)]
for lang, commands in valid_lang_commands:
run_test("basic_codegen", name_expr, numerical_tests, lang, commands)
def test_intrinsic_math1_codegen():
# not included: log10
from sympy.core.evalf import N
from sympy.functions import ln
from sympy.functions.elementary.exponential import log
from sympy.functions.elementary.hyperbolic import (cosh, sinh, tanh)
from sympy.functions.elementary.integers import (ceiling, floor)
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.trigonometric import (acos, asin, atan, cos, sin, tan)
name_expr = [
("test_fabs", abs(x)),
("test_acos", acos(x)),
("test_asin", asin(x)),
("test_atan", atan(x)),
("test_cos", cos(x)),
("test_cosh", cosh(x)),
("test_log", log(x)),
("test_ln", ln(x)),
("test_sin", sin(x)),
("test_sinh", sinh(x)),
("test_sqrt", sqrt(x)),
("test_tan", tan(x)),
("test_tanh", tanh(x)),
]
numerical_tests = []
for name, expr in name_expr:
for xval in 0.2, 0.5, 0.8:
expected = N(expr.subs(x, xval))
numerical_tests.append((name, (xval,), expected, 1e-14))
for lang, commands in valid_lang_commands:
if lang.startswith("C"):
name_expr_C = [("test_floor", floor(x)), ("test_ceil", ceiling(x))]
else:
name_expr_C = []
run_test("intrinsic_math1", name_expr + name_expr_C,
numerical_tests, lang, commands)
def test_instrinsic_math2_codegen():
# not included: frexp, ldexp, modf, fmod
from sympy.core.evalf import N
from sympy.functions.elementary.trigonometric import atan2
name_expr = [
("test_atan2", atan2(x, y)),
("test_pow", x**y),
]
numerical_tests = []
for name, expr in name_expr:
for xval, yval in (0.2, 1.3), (0.5, -0.2), (0.8, 0.8):
expected = N(expr.subs(x, xval).subs(y, yval))
numerical_tests.append((name, (xval, yval), expected, 1e-14))
for lang, commands in valid_lang_commands:
run_test("intrinsic_math2", name_expr, numerical_tests, lang, commands)
def test_complicated_codegen():
from sympy.core.evalf import N
from sympy.functions.elementary.trigonometric import (cos, sin, tan)
name_expr = [
("test1", ((sin(x) + cos(y) + tan(z))**7).expand()),
("test2", cos(cos(cos(cos(cos(cos(cos(cos(x + y + z))))))))),
]
numerical_tests = []
for name, expr in name_expr:
for xval, yval, zval in (0.2, 1.3, -0.3), (0.5, -0.2, 0.0), (0.8, 2.1, 0.8):
expected = N(expr.subs(x, xval).subs(y, yval).subs(z, zval))
numerical_tests.append((name, (xval, yval, zval), expected, 1e-12))
for lang, commands in valid_lang_commands:
run_test(
"complicated_codegen", name_expr, numerical_tests, lang, commands)
|
65bb8a51523e5fb9aaa98996498d405a10be8810a49076a3898aa8bd853e896a | """
test_pythonmpq.py
Test the PythonMPQ class for consistency with gmpy2's mpq type. If gmpy2 is
installed run the same tests for both.
"""
from fractions import Fraction
from decimal import Decimal
import pickle
from typing import Callable, List, Tuple, Type
from sympy.testing.pytest import raises
from sympy.external.pythonmpq import PythonMPQ
#
# If gmpy2 is installed then run the tests for both mpq and PythonMPQ.
# That should ensure consistency between the implementation here and mpq.
#
rational_types: List[Tuple[Callable, Type, Callable, Type]]
rational_types = [(PythonMPQ, PythonMPQ, int, int)]
try:
from gmpy2 import mpq, mpz
rational_types.append((mpq, type(mpq(1)), mpz, type(mpz(1))))
except ImportError:
pass
def test_PythonMPQ():
#
# Test PythonMPQ and also mpq if gmpy/gmpy2 is installed.
#
for Q, TQ, Z, TZ in rational_types:
def check_Q(q):
assert isinstance(q, TQ)
assert isinstance(q.numerator, TZ)
assert isinstance(q.denominator, TZ)
return q.numerator, q.denominator
# Check construction from different types
assert check_Q(Q(3)) == (3, 1)
assert check_Q(Q(3, 5)) == (3, 5)
assert check_Q(Q(Q(3, 5))) == (3, 5)
assert check_Q(Q(0.5)) == (1, 2)
assert check_Q(Q('0.5')) == (1, 2)
assert check_Q(Q(Decimal('0.6'))) == (3, 5)
assert check_Q(Q(Fraction(3, 5))) == (3, 5)
# Invalid types
raises(TypeError, lambda: Q([]))
raises(TypeError, lambda: Q([], []))
# Check normalisation of signs
assert check_Q(Q(2, 3)) == (2, 3)
assert check_Q(Q(-2, 3)) == (-2, 3)
assert check_Q(Q(2, -3)) == (-2, 3)
assert check_Q(Q(-2, -3)) == (2, 3)
# Check gcd calculation
assert check_Q(Q(12, 8)) == (3, 2)
# __int__/__float__
assert int(Q(5, 3)) == 1
assert int(Q(-5, 3)) == -1
assert float(Q(5, 2)) == 2.5
assert float(Q(-5, 2)) == -2.5
# __str__/__repr__
assert str(Q(2, 1)) == "2"
assert str(Q(1, 2)) == "1/2"
if Q is PythonMPQ:
assert repr(Q(2, 1)) == "MPQ(2,1)"
assert repr(Q(1, 2)) == "MPQ(1,2)"
else:
assert repr(Q(2, 1)) == "mpq(2,1)"
assert repr(Q(1, 2)) == "mpq(1,2)"
# __bool__
assert bool(Q(1, 2)) is True
assert bool(Q(0)) is False
# __eq__/__ne__
assert (Q(2, 3) == Q(2, 3)) is True
assert (Q(2, 3) == Q(2, 5)) is False
assert (Q(2, 3) != Q(2, 3)) is False
assert (Q(2, 3) != Q(2, 5)) is True
# __hash__
assert hash(Q(3, 5)) == hash(Fraction(3, 5))
# __reduce__
q = Q(2, 3)
assert pickle.loads(pickle.dumps(q)) == q
# __ge__/__gt__/__le__/__lt__
assert (Q(1, 3) < Q(2, 3)) is True
assert (Q(2, 3) < Q(2, 3)) is False
assert (Q(2, 3) < Q(1, 3)) is False
assert (Q(-2, 3) < Q(1, 3)) is True
assert (Q(1, 3) < Q(-2, 3)) is False
assert (Q(1, 3) <= Q(2, 3)) is True
assert (Q(2, 3) <= Q(2, 3)) is True
assert (Q(2, 3) <= Q(1, 3)) is False
assert (Q(-2, 3) <= Q(1, 3)) is True
assert (Q(1, 3) <= Q(-2, 3)) is False
assert (Q(1, 3) > Q(2, 3)) is False
assert (Q(2, 3) > Q(2, 3)) is False
assert (Q(2, 3) > Q(1, 3)) is True
assert (Q(-2, 3) > Q(1, 3)) is False
assert (Q(1, 3) > Q(-2, 3)) is True
assert (Q(1, 3) >= Q(2, 3)) is False
assert (Q(2, 3) >= Q(2, 3)) is True
assert (Q(2, 3) >= Q(1, 3)) is True
assert (Q(-2, 3) >= Q(1, 3)) is False
assert (Q(1, 3) >= Q(-2, 3)) is True
# __abs__/__pos__/__neg__
assert abs(Q(2, 3)) == abs(Q(-2, 3)) == Q(2, 3)
assert +Q(2, 3) == Q(2, 3)
assert -Q(2, 3) == Q(-2, 3)
# __add__/__radd__
assert Q(2, 3) + Q(5, 7) == Q(29, 21)
assert Q(2, 3) + 1 == Q(5, 3)
assert 1 + Q(2, 3) == Q(5, 3)
raises(TypeError, lambda: [] + Q(1))
raises(TypeError, lambda: Q(1) + [])
# __sub__/__rsub__
assert Q(2, 3) - Q(5, 7) == Q(-1, 21)
assert Q(2, 3) - 1 == Q(-1, 3)
assert 1 - Q(2, 3) == Q(1, 3)
raises(TypeError, lambda: [] - Q(1))
raises(TypeError, lambda: Q(1) - [])
# __mul__/__rmul__
assert Q(2, 3) * Q(5, 7) == Q(10, 21)
assert Q(2, 3) * 1 == Q(2, 3)
assert 1 * Q(2, 3) == Q(2, 3)
raises(TypeError, lambda: [] * Q(1))
raises(TypeError, lambda: Q(1) * [])
# __pow__/__rpow__
assert Q(2, 3) ** 2 == Q(4, 9)
assert Q(2, 3) ** 1 == Q(2, 3)
assert Q(-2, 3) ** 2 == Q(4, 9)
assert Q(-2, 3) ** -1 == Q(-3, 2)
if Q is PythonMPQ:
raises(TypeError, lambda: 1 ** Q(2, 3))
raises(TypeError, lambda: Q(1, 4) ** Q(1, 2))
raises(TypeError, lambda: [] ** Q(1))
raises(TypeError, lambda: Q(1) ** [])
# __div__/__rdiv__
assert Q(2, 3) / Q(5, 7) == Q(14, 15)
assert Q(2, 3) / 1 == Q(2, 3)
assert 1 / Q(2, 3) == Q(3, 2)
raises(TypeError, lambda: [] / Q(1))
raises(TypeError, lambda: Q(1) / [])
raises(ZeroDivisionError, lambda: Q(1, 2) / Q(0))
# __divmod__
if Q is PythonMPQ:
raises(TypeError, lambda: Q(2, 3) // Q(1, 3))
raises(TypeError, lambda: Q(2, 3) % Q(1, 3))
raises(TypeError, lambda: 1 // Q(1, 3))
raises(TypeError, lambda: 1 % Q(1, 3))
raises(TypeError, lambda: Q(2, 3) // 1)
raises(TypeError, lambda: Q(2, 3) % 1)
|
fcea0e4705c79089afaebff85e48cddb3fc388563603f92f2339848b3fc0a170 | # This testfile tests SymPy <-> NumPy compatibility
# Don't test any SymPy features here. Just pure interaction with NumPy.
# Always write regular SymPy tests for anything, that can be tested in pure
# Python (without numpy). Here we test everything, that a user may need when
# using SymPy with NumPy
from sympy.external.importtools import version_tuple
from sympy.external import import_module
numpy = import_module('numpy')
if numpy:
array, matrix, ndarray = numpy.array, numpy.matrix, numpy.ndarray
else:
#bin/test will not execute any tests now
disabled = True
from sympy.core.numbers import (Float, Integer, Rational)
from sympy.core.symbol import (Symbol, symbols)
from sympy.functions.elementary.trigonometric import sin
from sympy.matrices.dense import (Matrix, list2numpy, matrix2numpy, symarray)
from sympy.utilities.lambdify import lambdify
import sympy
import mpmath
from sympy.abc import x, y, z
from sympy.utilities.decorator import conserve_mpmath_dps
from sympy.testing.pytest import raises
# first, systematically check, that all operations are implemented and don't
# raise an exception
def test_systematic_basic():
def s(sympy_object, numpy_array):
sympy_object + numpy_array
numpy_array + sympy_object
sympy_object - numpy_array
numpy_array - sympy_object
sympy_object * numpy_array
numpy_array * sympy_object
sympy_object / numpy_array
numpy_array / sympy_object
sympy_object ** numpy_array
numpy_array ** sympy_object
x = Symbol("x")
y = Symbol("y")
sympy_objs = [
Rational(2, 3),
Float("1.3"),
x,
y,
pow(x, y)*y,
Integer(5),
Float(5.5),
]
numpy_objs = [
array([1]),
array([3, 8, -1]),
array([x, x**2, Rational(5)]),
array([x/y*sin(y), 5, Rational(5)]),
]
for x in sympy_objs:
for y in numpy_objs:
s(x, y)
# now some random tests, that test particular problems and that also
# check that the results of the operations are correct
def test_basics():
one = Rational(1)
zero = Rational(0)
assert array(1) == array(one)
assert array([one]) == array([one])
assert array([x]) == array([x])
assert array(x) == array(Symbol("x"))
assert array(one + x) == array(1 + x)
X = array([one, zero, zero])
assert (X == array([one, zero, zero])).all()
assert (X == array([one, 0, 0])).all()
def test_arrays():
one = Rational(1)
zero = Rational(0)
X = array([one, zero, zero])
Y = one*X
X = array([Symbol("a") + Rational(1, 2)])
Y = X + X
assert Y == array([1 + 2*Symbol("a")])
Y = Y + 1
assert Y == array([2 + 2*Symbol("a")])
Y = X - X
assert Y == array([0])
def test_conversion1():
a = list2numpy([x**2, x])
#looks like an array?
assert isinstance(a, ndarray)
assert a[0] == x**2
assert a[1] == x
assert len(a) == 2
#yes, it's the array
def test_conversion2():
a = 2*list2numpy([x**2, x])
b = list2numpy([2*x**2, 2*x])
assert (a == b).all()
one = Rational(1)
zero = Rational(0)
X = list2numpy([one, zero, zero])
Y = one*X
X = list2numpy([Symbol("a") + Rational(1, 2)])
Y = X + X
assert Y == array([1 + 2*Symbol("a")])
Y = Y + 1
assert Y == array([2 + 2*Symbol("a")])
Y = X - X
assert Y == array([0])
def test_list2numpy():
assert (array([x**2, x]) == list2numpy([x**2, x])).all()
def test_Matrix1():
m = Matrix([[x, x**2], [5, 2/x]])
assert (array(m.subs(x, 2)) == array([[2, 4], [5, 1]])).all()
m = Matrix([[sin(x), x**2], [5, 2/x]])
assert (array(m.subs(x, 2)) == array([[sin(2), 4], [5, 1]])).all()
def test_Matrix2():
m = Matrix([[x, x**2], [5, 2/x]])
assert (matrix(m.subs(x, 2)) == matrix([[2, 4], [5, 1]])).all()
m = Matrix([[sin(x), x**2], [5, 2/x]])
assert (matrix(m.subs(x, 2)) == matrix([[sin(2), 4], [5, 1]])).all()
def test_Matrix3():
a = array([[2, 4], [5, 1]])
assert Matrix(a) == Matrix([[2, 4], [5, 1]])
assert Matrix(a) != Matrix([[2, 4], [5, 2]])
a = array([[sin(2), 4], [5, 1]])
assert Matrix(a) == Matrix([[sin(2), 4], [5, 1]])
assert Matrix(a) != Matrix([[sin(0), 4], [5, 1]])
def test_Matrix4():
a = matrix([[2, 4], [5, 1]])
assert Matrix(a) == Matrix([[2, 4], [5, 1]])
assert Matrix(a) != Matrix([[2, 4], [5, 2]])
a = matrix([[sin(2), 4], [5, 1]])
assert Matrix(a) == Matrix([[sin(2), 4], [5, 1]])
assert Matrix(a) != Matrix([[sin(0), 4], [5, 1]])
def test_Matrix_sum():
M = Matrix([[1, 2, 3], [x, y, x], [2*y, -50, z*x]])
m = matrix([[2, 3, 4], [x, 5, 6], [x, y, z**2]])
assert M + m == Matrix([[3, 5, 7], [2*x, y + 5, x + 6], [2*y + x, y - 50, z*x + z**2]])
assert m + M == Matrix([[3, 5, 7], [2*x, y + 5, x + 6], [2*y + x, y - 50, z*x + z**2]])
assert M + m == M.add(m)
def test_Matrix_mul():
M = Matrix([[1, 2, 3], [x, y, x]])
m = matrix([[2, 4], [x, 6], [x, z**2]])
assert M*m == Matrix([
[ 2 + 5*x, 16 + 3*z**2],
[2*x + x*y + x**2, 4*x + 6*y + x*z**2],
])
assert m*M == Matrix([
[ 2 + 4*x, 4 + 4*y, 6 + 4*x],
[ 7*x, 2*x + 6*y, 9*x],
[x + x*z**2, 2*x + y*z**2, 3*x + x*z**2],
])
a = array([2])
assert a[0] * M == 2 * M
assert M * a[0] == 2 * M
def test_Matrix_array():
class matarray:
def __array__(self):
from numpy import array
return array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
matarr = matarray()
assert Matrix(matarr) == Matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
def test_matrix2numpy():
a = matrix2numpy(Matrix([[1, x**2], [3*sin(x), 0]]))
assert isinstance(a, ndarray)
assert a.shape == (2, 2)
assert a[0, 0] == 1
assert a[0, 1] == x**2
assert a[1, 0] == 3*sin(x)
assert a[1, 1] == 0
def test_matrix2numpy_conversion():
a = Matrix([[1, 2, sin(x)], [x**2, x, Rational(1, 2)]])
b = array([[1, 2, sin(x)], [x**2, x, Rational(1, 2)]])
assert (matrix2numpy(a) == b).all()
assert matrix2numpy(a).dtype == numpy.dtype('object')
c = matrix2numpy(Matrix([[1, 2], [10, 20]]), dtype='int8')
d = matrix2numpy(Matrix([[1, 2], [10, 20]]), dtype='float64')
assert c.dtype == numpy.dtype('int8')
assert d.dtype == numpy.dtype('float64')
def test_issue_3728():
assert (Rational(1, 2)*array([2*x, 0]) == array([x, 0])).all()
assert (Rational(1, 2) + array(
[2*x, 0]) == array([2*x + Rational(1, 2), Rational(1, 2)])).all()
assert (Float("0.5")*array([2*x, 0]) == array([Float("1.0")*x, 0])).all()
assert (Float("0.5") + array(
[2*x, 0]) == array([2*x + Float("0.5"), Float("0.5")])).all()
@conserve_mpmath_dps
def test_lambdify():
mpmath.mp.dps = 16
sin02 = mpmath.mpf("0.198669330795061215459412627")
f = lambdify(x, sin(x), "numpy")
prec = 1e-15
assert -prec < f(0.2) - sin02 < prec
# if this succeeds, it can't be a numpy function
if version_tuple(numpy.__version__) >= version_tuple('1.17'):
with raises(TypeError):
f(x)
else:
with raises(AttributeError):
f(x)
def test_lambdify_matrix():
f = lambdify(x, Matrix([[x, 2*x], [1, 2]]), [{'ImmutableMatrix': numpy.array}, "numpy"])
assert (f(1) == array([[1, 2], [1, 2]])).all()
def test_lambdify_matrix_multi_input():
M = sympy.Matrix([[x**2, x*y, x*z],
[y*x, y**2, y*z],
[z*x, z*y, z**2]])
f = lambdify((x, y, z), M, [{'ImmutableMatrix': numpy.array}, "numpy"])
xh, yh, zh = 1.0, 2.0, 3.0
expected = array([[xh**2, xh*yh, xh*zh],
[yh*xh, yh**2, yh*zh],
[zh*xh, zh*yh, zh**2]])
actual = f(xh, yh, zh)
assert numpy.allclose(actual, expected)
def test_lambdify_matrix_vec_input():
X = sympy.DeferredVector('X')
M = Matrix([
[X[0]**2, X[0]*X[1], X[0]*X[2]],
[X[1]*X[0], X[1]**2, X[1]*X[2]],
[X[2]*X[0], X[2]*X[1], X[2]**2]])
f = lambdify(X, M, [{'ImmutableMatrix': numpy.array}, "numpy"])
Xh = array([1.0, 2.0, 3.0])
expected = array([[Xh[0]**2, Xh[0]*Xh[1], Xh[0]*Xh[2]],
[Xh[1]*Xh[0], Xh[1]**2, Xh[1]*Xh[2]],
[Xh[2]*Xh[0], Xh[2]*Xh[1], Xh[2]**2]])
actual = f(Xh)
assert numpy.allclose(actual, expected)
def test_lambdify_transl():
from sympy.utilities.lambdify import NUMPY_TRANSLATIONS
for sym, mat in NUMPY_TRANSLATIONS.items():
assert sym in sympy.__dict__
assert mat in numpy.__dict__
def test_symarray():
"""Test creation of numpy arrays of SymPy symbols."""
import numpy as np
import numpy.testing as npt
syms = symbols('_0,_1,_2')
s1 = symarray("", 3)
s2 = symarray("", 3)
npt.assert_array_equal(s1, np.array(syms, dtype=object))
assert s1[0] == s2[0]
a = symarray('a', 3)
b = symarray('b', 3)
assert not(a[0] == b[0])
asyms = symbols('a_0,a_1,a_2')
npt.assert_array_equal(a, np.array(asyms, dtype=object))
# Multidimensional checks
a2d = symarray('a', (2, 3))
assert a2d.shape == (2, 3)
a00, a12 = symbols('a_0_0,a_1_2')
assert a2d[0, 0] == a00
assert a2d[1, 2] == a12
a3d = symarray('a', (2, 3, 2))
assert a3d.shape == (2, 3, 2)
a000, a120, a121 = symbols('a_0_0_0,a_1_2_0,a_1_2_1')
assert a3d[0, 0, 0] == a000
assert a3d[1, 2, 0] == a120
assert a3d[1, 2, 1] == a121
def test_vectorize():
assert (numpy.vectorize(
sin)([1, 2, 3]) == numpy.array([sin(1), sin(2), sin(3)])).all()
|
54534adcde5e857ca107c9c6af8f5b9dc5877ac6559a1738310cb5398872a57e | from sympy.core.add import Add
from sympy.core.symbol import Symbol
from sympy.series.order import O
x = Symbol('x')
l = list(x**i for i in range(1000))
l.append(O(x**1001))
def timeit_order_1x():
_ = Add(*l)
|
d8fb5d79e26d0faab212fb7d1c536fc939cc33ca61159463b1c8276f87c79dd5 | from sympy.core.numbers import oo
from sympy.core.symbol import Symbol
from sympy.series.limits import limit
x = Symbol('x')
def timeit_limit_1x():
limit(1/x, x, oo)
|
63d3f01935316bc63d9943a56806c6ac11923449f757e65ef58f79e8c79a4e0f | from sympy.core.numbers import E
from sympy.core.singleton import S
from sympy.functions.elementary.exponential import exp
from sympy.functions.elementary.hyperbolic import tanh
from sympy.functions.elementary.trigonometric import (cos, sin)
from sympy.series.order import Order
from sympy.abc import x, y
def test_sin():
e = sin(x).lseries(x)
assert next(e) == x
assert next(e) == -x**3/6
assert next(e) == x**5/120
def test_cos():
e = cos(x).lseries(x)
assert next(e) == 1
assert next(e) == -x**2/2
assert next(e) == x**4/24
def test_exp():
e = exp(x).lseries(x)
assert next(e) == 1
assert next(e) == x
assert next(e) == x**2/2
assert next(e) == x**3/6
def test_exp2():
e = exp(cos(x)).lseries(x)
assert next(e) == E
assert next(e) == -E*x**2/2
assert next(e) == E*x**4/6
assert next(e) == -31*E*x**6/720
def test_simple():
assert [t for t in x.lseries()] == [x]
assert [t for t in S.One.lseries(x)] == [1]
assert not next((x/(x + y)).lseries(y)).has(Order)
def test_issue_5183():
s = (x + 1/x).lseries()
assert [si for si in s] == [1/x, x]
assert next((x + x**2).lseries()) == x
assert next(((1 + x)**7).lseries(x)) == 1
assert next((sin(x + y)).series(x, n=3).lseries(y)) == x
# it would be nice if all terms were grouped, but in the
# following case that would mean that all the terms would have
# to be known since, for example, every term has a constant in it.
s = ((1 + x)**7).series(x, 1, n=None)
assert [next(s) for i in range(2)] == [128, -448 + 448*x]
def test_issue_6999():
s = tanh(x).lseries(x, 1)
assert next(s) == tanh(1)
assert next(s) == x - (x - 1)*tanh(1)**2 - 1
assert next(s) == -(x - 1)**2*tanh(1) + (x - 1)**2*tanh(1)**3
assert next(s) == -(x - 1)**3*tanh(1)**4 - (x - 1)**3/3 + \
4*(x - 1)**3*tanh(1)**2/3
|
2b66a163ab0ac52e8a41ddf67a71adf38c50ee742bb19dd5b8926369a8bec04d | from sympy.concrete.summations import Sum
from sympy.core.add import Add
from sympy.core.numbers import (I, Rational, oo, pi)
from sympy.core.singleton import S
from sympy.core.symbol import (Symbol, symbols)
from sympy.functions.combinatorial.factorials import (binomial, factorial, subfactorial)
from sympy.functions.combinatorial.numbers import (fibonacci, harmonic)
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.trigonometric import (cos, sin)
from sympy.functions.special.gamma_functions import gamma
from sympy.series.limitseq import limit_seq
from sympy.series.limitseq import difference_delta as dd
from sympy.testing.pytest import raises, XFAIL
from sympy.calculus.util import AccumulationBounds
n, m, k = symbols('n m k', integer=True)
def test_difference_delta():
e = n*(n + 1)
e2 = e * k
assert dd(e) == 2*n + 2
assert dd(e2, n, 2) == k*(4*n + 6)
raises(ValueError, lambda: dd(e2))
raises(ValueError, lambda: dd(e2, n, oo))
def test_difference_delta__Sum():
e = Sum(1/k, (k, 1, n))
assert dd(e, n) == 1/(n + 1)
assert dd(e, n, 5) == Add(*[1/(i + n + 1) for i in range(5)])
e = Sum(1/k, (k, 1, 3*n))
assert dd(e, n) == Add(*[1/(i + 3*n + 1) for i in range(3)])
e = n * Sum(1/k, (k, 1, n))
assert dd(e, n) == 1 + Sum(1/k, (k, 1, n))
e = Sum(1/k, (k, 1, n), (m, 1, n))
assert dd(e, n) == harmonic(n)
def test_difference_delta__Add():
e = n + n*(n + 1)
assert dd(e, n) == 2*n + 3
assert dd(e, n, 2) == 4*n + 8
e = n + Sum(1/k, (k, 1, n))
assert dd(e, n) == 1 + 1/(n + 1)
assert dd(e, n, 5) == 5 + Add(*[1/(i + n + 1) for i in range(5)])
def test_difference_delta__Pow():
e = 4**n
assert dd(e, n) == 3*4**n
assert dd(e, n, 2) == 15*4**n
e = 4**(2*n)
assert dd(e, n) == 15*4**(2*n)
assert dd(e, n, 2) == 255*4**(2*n)
e = n**4
assert dd(e, n) == (n + 1)**4 - n**4
e = n**n
assert dd(e, n) == (n + 1)**(n + 1) - n**n
def test_limit_seq():
e = binomial(2*n, n) / Sum(binomial(2*k, k), (k, 1, n))
assert limit_seq(e) == S(3) / 4
assert limit_seq(e, m) == e
e = (5*n**3 + 3*n**2 + 4) / (3*n**3 + 4*n - 5)
assert limit_seq(e, n) == S(5) / 3
e = (harmonic(n) * Sum(harmonic(k), (k, 1, n))) / (n * harmonic(2*n)**2)
assert limit_seq(e, n) == 1
e = Sum(k**2 * Sum(2**m/m, (m, 1, k)), (k, 1, n)) / (2**n*n)
assert limit_seq(e, n) == 4
e = (Sum(binomial(3*k, k) * binomial(5*k, k), (k, 1, n)) /
(binomial(3*n, n) * binomial(5*n, n)))
assert limit_seq(e, n) == S(84375) / 83351
e = Sum(harmonic(k)**2/k, (k, 1, 2*n)) / harmonic(n)**3
assert limit_seq(e, n) == S.One / 3
raises(ValueError, lambda: limit_seq(e * m))
def test_alternating_sign():
assert limit_seq((-1)**n/n**2, n) == 0
assert limit_seq((-2)**(n+1)/(n + 3**n), n) == 0
assert limit_seq((2*n + (-1)**n)/(n + 1), n) == 2
assert limit_seq(sin(pi*n), n) == 0
assert limit_seq(cos(2*pi*n), n) == 1
assert limit_seq((S.NegativeOne/5)**n, n) == 0
assert limit_seq((Rational(-1, 5))**n, n) == 0
assert limit_seq((I/3)**n, n) == 0
assert limit_seq(sqrt(n)*(I/2)**n, n) == 0
assert limit_seq(n**7*(I/3)**n, n) == 0
assert limit_seq(n/(n + 1) + (I/2)**n, n) == 1
def test_accum_bounds():
assert limit_seq((-1)**n, n) == AccumulationBounds(-1, 1)
assert limit_seq(cos(pi*n), n) == AccumulationBounds(-1, 1)
assert limit_seq(sin(pi*n/2)**2, n) == AccumulationBounds(0, 1)
assert limit_seq(2*(-3)**n/(n + 3**n), n) == AccumulationBounds(-2, 2)
assert limit_seq(3*n/(n + 1) + 2*(-1)**n, n) == AccumulationBounds(1, 5)
def test_limitseq_sum():
from sympy.abc import x, y, z
assert limit_seq(Sum(1/x, (x, 1, y)) - log(y), y) == S.EulerGamma
assert limit_seq(Sum(1/x, (x, 1, y)) - 1/y, y) is S.Infinity
assert (limit_seq(binomial(2*x, x) / Sum(binomial(2*y, y), (y, 1, x)), x) ==
S(3) / 4)
assert (limit_seq(Sum(y**2 * Sum(2**z/z, (z, 1, y)), (y, 1, x)) /
(2**x*x), x) == 4)
def test_issue_9308():
assert limit_seq(subfactorial(n)/factorial(n), n) == exp(-1)
def test_issue_10382():
n = Symbol('n', integer=True)
assert limit_seq(fibonacci(n+1)/fibonacci(n), n) == S.GoldenRatio
def test_issue_11672():
assert limit_seq(Rational(-1, 2)**n, n) == 0
def test_issue_16735():
assert limit_seq(5**n/factorial(n), n) == 0
def test_issue_19868():
assert limit_seq(1/gamma(n + S.One/2), n) == 0
@XFAIL
def test_limit_seq_fail():
# improve Summation algorithm or add ad-hoc criteria
e = (harmonic(n)**3 * Sum(1/harmonic(k), (k, 1, n)) /
(n * Sum(harmonic(k)/k, (k, 1, n))))
assert limit_seq(e, n) == 2
# No unique dominant term
e = (Sum(2**k * binomial(2*k, k) / k**2, (k, 1, n)) /
(Sum(2**k/k*2, (k, 1, n)) * Sum(binomial(2*k, k), (k, 1, n))))
assert limit_seq(e, n) == S(3) / 7
# Simplifications of summations needs to be improved.
e = n**3*Sum(2**k/k**2, (k, 1, n))**2 / (2**n * Sum(2**k/k, (k, 1, n)))
assert limit_seq(e, n) == 2
e = (harmonic(n) * Sum(2**k/k, (k, 1, n)) /
(n * Sum(2**k*harmonic(k)/k**2, (k, 1, n))))
assert limit_seq(e, n) == 1
e = (Sum(2**k*factorial(k) / k**2, (k, 1, 2*n)) /
(Sum(4**k/k**2, (k, 1, n)) * Sum(factorial(k), (k, 1, 2*n))))
assert limit_seq(e, n) == S(3) / 16
|
fce976447a299077a0a840206f6006042277e3292420faa67700297364dee3a8 | from sympy.core.containers import Tuple
from sympy.core.function import Function
from sympy.core.numbers import oo, Rational
from sympy.core.singleton import S
from sympy.core.symbol import symbols, Symbol
from sympy.functions.combinatorial.numbers import tribonacci, fibonacci
from sympy.functions.elementary.exponential import exp
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.trigonometric import cos, sin
from sympy.series import EmptySequence
from sympy.series.sequences import (SeqMul, SeqAdd, SeqPer, SeqFormula,
sequence)
from sympy.sets.sets import Interval
from sympy.tensor.indexed import Indexed, Idx
from sympy.series.sequences import SeqExpr, SeqExprOp, RecursiveSeq
from sympy.testing.pytest import raises, slow
x, y, z = symbols('x y z')
n, m = symbols('n m')
def test_EmptySequence():
assert S.EmptySequence is EmptySequence
assert S.EmptySequence.interval is S.EmptySet
assert S.EmptySequence.length is S.Zero
assert list(S.EmptySequence) == []
def test_SeqExpr():
s = SeqExpr((1, n, y), (x, 0, 10))
assert isinstance(s, SeqExpr)
assert s.gen == (1, n, y)
assert s.interval == Interval(0, 10)
assert s.start == 0
assert s.stop == 10
assert s.length == 11
assert s.variables == (x,)
assert SeqExpr((1, 2, 3), (x, 0, oo)).length is oo
def test_SeqPer():
s = SeqPer((1, n, 3), (x, 0, 5))
assert isinstance(s, SeqPer)
assert s.periodical == Tuple(1, n, 3)
assert s.period == 3
assert s.coeff(3) == 1
assert s.free_symbols == {n}
assert list(s) == [1, n, 3, 1, n, 3]
assert s[:] == [1, n, 3, 1, n, 3]
assert SeqPer((1, n, 3), (x, -oo, 0))[0:6] == [1, n, 3, 1, n, 3]
raises(ValueError, lambda: SeqPer((1, 2, 3), (0, 1, 2)))
raises(ValueError, lambda: SeqPer((1, 2, 3), (x, -oo, oo)))
raises(ValueError, lambda: SeqPer(n**2, (0, oo)))
assert SeqPer((n, n**2, n**3), (m, 0, oo))[:6] == \
[n, n**2, n**3, n, n**2, n**3]
assert SeqPer((n, n**2, n**3), (n, 0, oo))[:6] == [0, 1, 8, 3, 16, 125]
assert SeqPer((n, m), (n, 0, oo))[:6] == [0, m, 2, m, 4, m]
def test_SeqFormula():
s = SeqFormula(n**2, (n, 0, 5))
assert isinstance(s, SeqFormula)
assert s.formula == n**2
assert s.coeff(3) == 9
assert list(s) == [i**2 for i in range(6)]
assert s[:] == [i**2 for i in range(6)]
assert SeqFormula(n**2, (n, -oo, 0))[0:6] == [i**2 for i in range(6)]
assert SeqFormula(n**2, (0, oo)) == SeqFormula(n**2, (n, 0, oo))
assert SeqFormula(n**2, (0, m)).subs(m, x) == SeqFormula(n**2, (0, x))
assert SeqFormula(m*n**2, (n, 0, oo)).subs(m, x) == \
SeqFormula(x*n**2, (n, 0, oo))
raises(ValueError, lambda: SeqFormula(n**2, (0, 1, 2)))
raises(ValueError, lambda: SeqFormula(n**2, (n, -oo, oo)))
raises(ValueError, lambda: SeqFormula(m*n**2, (0, oo)))
seq = SeqFormula(x*(y**2 + z), (z, 1, 100))
assert seq.expand() == SeqFormula(x*y**2 + x*z, (z, 1, 100))
seq = SeqFormula(sin(x*(y**2 + z)),(z, 1, 100))
assert seq.expand(trig=True) == SeqFormula(sin(x*y**2)*cos(x*z) + sin(x*z)*cos(x*y**2), (z, 1, 100))
assert seq.expand() == SeqFormula(sin(x*y**2 + x*z), (z, 1, 100))
assert seq.expand(trig=False) == SeqFormula(sin(x*y**2 + x*z), (z, 1, 100))
seq = SeqFormula(exp(x*(y**2 + z)), (z, 1, 100))
assert seq.expand() == SeqFormula(exp(x*y**2)*exp(x*z), (z, 1, 100))
assert seq.expand(power_exp=False) == SeqFormula(exp(x*y**2 + x*z), (z, 1, 100))
assert seq.expand(mul=False, power_exp=False) == SeqFormula(exp(x*(y**2 + z)), (z, 1, 100))
def test_sequence():
form = SeqFormula(n**2, (n, 0, 5))
per = SeqPer((1, 2, 3), (n, 0, 5))
inter = SeqFormula(n**2)
assert sequence(n**2, (n, 0, 5)) == form
assert sequence((1, 2, 3), (n, 0, 5)) == per
assert sequence(n**2) == inter
def test_SeqExprOp():
form = SeqFormula(n**2, (n, 0, 10))
per = SeqPer((1, 2, 3), (m, 5, 10))
s = SeqExprOp(form, per)
assert s.gen == (n**2, (1, 2, 3))
assert s.interval == Interval(5, 10)
assert s.start == 5
assert s.stop == 10
assert s.length == 6
assert s.variables == (n, m)
def test_SeqAdd():
per = SeqPer((1, 2, 3), (n, 0, oo))
form = SeqFormula(n**2)
per_bou = SeqPer((1, 2), (n, 1, 5))
form_bou = SeqFormula(n**2, (6, 10))
form_bou2 = SeqFormula(n**2, (1, 5))
assert SeqAdd() == S.EmptySequence
assert SeqAdd(S.EmptySequence) == S.EmptySequence
assert SeqAdd(per) == per
assert SeqAdd(per, S.EmptySequence) == per
assert SeqAdd(per_bou, form_bou) == S.EmptySequence
s = SeqAdd(per_bou, form_bou2, evaluate=False)
assert s.args == (form_bou2, per_bou)
assert s[:] == [2, 6, 10, 18, 26]
assert list(s) == [2, 6, 10, 18, 26]
assert isinstance(SeqAdd(per, per_bou, evaluate=False), SeqAdd)
s1 = SeqAdd(per, per_bou)
assert isinstance(s1, SeqPer)
assert s1 == SeqPer((2, 4, 4, 3, 3, 5), (n, 1, 5))
s2 = SeqAdd(form, form_bou)
assert isinstance(s2, SeqFormula)
assert s2 == SeqFormula(2*n**2, (6, 10))
assert SeqAdd(form, form_bou, per) == \
SeqAdd(per, SeqFormula(2*n**2, (6, 10)))
assert SeqAdd(form, SeqAdd(form_bou, per)) == \
SeqAdd(per, SeqFormula(2*n**2, (6, 10)))
assert SeqAdd(per, SeqAdd(form, form_bou), evaluate=False) == \
SeqAdd(per, SeqFormula(2*n**2, (6, 10)))
assert SeqAdd(SeqPer((1, 2), (n, 0, oo)), SeqPer((1, 2), (m, 0, oo))) == \
SeqPer((2, 4), (n, 0, oo))
def test_SeqMul():
per = SeqPer((1, 2, 3), (n, 0, oo))
form = SeqFormula(n**2)
per_bou = SeqPer((1, 2), (n, 1, 5))
form_bou = SeqFormula(n**2, (n, 6, 10))
form_bou2 = SeqFormula(n**2, (1, 5))
assert SeqMul() == S.EmptySequence
assert SeqMul(S.EmptySequence) == S.EmptySequence
assert SeqMul(per) == per
assert SeqMul(per, S.EmptySequence) == S.EmptySequence
assert SeqMul(per_bou, form_bou) == S.EmptySequence
s = SeqMul(per_bou, form_bou2, evaluate=False)
assert s.args == (form_bou2, per_bou)
assert s[:] == [1, 8, 9, 32, 25]
assert list(s) == [1, 8, 9, 32, 25]
assert isinstance(SeqMul(per, per_bou, evaluate=False), SeqMul)
s1 = SeqMul(per, per_bou)
assert isinstance(s1, SeqPer)
assert s1 == SeqPer((1, 4, 3, 2, 2, 6), (n, 1, 5))
s2 = SeqMul(form, form_bou)
assert isinstance(s2, SeqFormula)
assert s2 == SeqFormula(n**4, (6, 10))
assert SeqMul(form, form_bou, per) == \
SeqMul(per, SeqFormula(n**4, (6, 10)))
assert SeqMul(form, SeqMul(form_bou, per)) == \
SeqMul(per, SeqFormula(n**4, (6, 10)))
assert SeqMul(per, SeqMul(form, form_bou2,
evaluate=False), evaluate=False) == \
SeqMul(form, per, form_bou2, evaluate=False)
assert SeqMul(SeqPer((1, 2), (n, 0, oo)), SeqPer((1, 2), (n, 0, oo))) == \
SeqPer((1, 4), (n, 0, oo))
def test_add():
per = SeqPer((1, 2), (n, 0, oo))
form = SeqFormula(n**2)
assert per + (SeqPer((2, 3))) == SeqPer((3, 5), (n, 0, oo))
assert form + SeqFormula(n**3) == SeqFormula(n**2 + n**3)
assert per + form == SeqAdd(per, form)
raises(TypeError, lambda: per + n)
raises(TypeError, lambda: n + per)
def test_sub():
per = SeqPer((1, 2), (n, 0, oo))
form = SeqFormula(n**2)
assert per - (SeqPer((2, 3))) == SeqPer((-1, -1), (n, 0, oo))
assert form - (SeqFormula(n**3)) == SeqFormula(n**2 - n**3)
assert per - form == SeqAdd(per, -form)
raises(TypeError, lambda: per - n)
raises(TypeError, lambda: n - per)
def test_mul__coeff_mul():
assert SeqPer((1, 2), (n, 0, oo)).coeff_mul(2) == SeqPer((2, 4), (n, 0, oo))
assert SeqFormula(n**2).coeff_mul(2) == SeqFormula(2*n**2)
assert S.EmptySequence.coeff_mul(100) == S.EmptySequence
assert SeqPer((1, 2), (n, 0, oo)) * (SeqPer((2, 3))) == \
SeqPer((2, 6), (n, 0, oo))
assert SeqFormula(n**2) * SeqFormula(n**3) == SeqFormula(n**5)
assert S.EmptySequence * SeqFormula(n**2) == S.EmptySequence
assert SeqFormula(n**2) * S.EmptySequence == S.EmptySequence
raises(TypeError, lambda: sequence(n**2) * n)
raises(TypeError, lambda: n * sequence(n**2))
def test_neg():
assert -SeqPer((1, -2), (n, 0, oo)) == SeqPer((-1, 2), (n, 0, oo))
assert -SeqFormula(n**2) == SeqFormula(-n**2)
def test_operations():
per = SeqPer((1, 2), (n, 0, oo))
per2 = SeqPer((2, 4), (n, 0, oo))
form = SeqFormula(n**2)
form2 = SeqFormula(n**3)
assert per + form + form2 == SeqAdd(per, form, form2)
assert per + form - form2 == SeqAdd(per, form, -form2)
assert per + form - S.EmptySequence == SeqAdd(per, form)
assert per + per2 + form == SeqAdd(SeqPer((3, 6), (n, 0, oo)), form)
assert S.EmptySequence - per == -per
assert form + form == SeqFormula(2*n**2)
assert per * form * form2 == SeqMul(per, form, form2)
assert form * form == SeqFormula(n**4)
assert form * -form == SeqFormula(-n**4)
assert form * (per + form2) == SeqMul(form, SeqAdd(per, form2))
assert form * (per + per) == SeqMul(form, per2)
assert form.coeff_mul(m) == SeqFormula(m*n**2, (n, 0, oo))
assert per.coeff_mul(m) == SeqPer((m, 2*m), (n, 0, oo))
def test_Idx_limits():
i = symbols('i', cls=Idx)
r = Indexed('r', i)
assert SeqFormula(r, (i, 0, 5))[:] == [r.subs(i, j) for j in range(6)]
assert SeqPer((1, 2), (i, 0, 5))[:] == [1, 2, 1, 2, 1, 2]
@slow
def test_find_linear_recurrence():
assert sequence((0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55), \
(n, 0, 10)).find_linear_recurrence(11) == [1, 1]
assert sequence((1, 2, 4, 7, 28, 128, 582, 2745, 13021, 61699, 292521, \
1387138), (n, 0, 11)).find_linear_recurrence(12) == [5, -2, 6, -11]
assert sequence(x*n**3+y*n, (n, 0, oo)).find_linear_recurrence(10) \
== [4, -6, 4, -1]
assert sequence(x**n, (n,0,20)).find_linear_recurrence(21) == [x]
assert sequence((1,2,3)).find_linear_recurrence(10, 5) == [0, 0, 1]
assert sequence(((1 + sqrt(5))/2)**n + \
(-(1 + sqrt(5))/2)**(-n)).find_linear_recurrence(10) == [1, 1]
assert sequence(x*((1 + sqrt(5))/2)**n + y*(-(1 + sqrt(5))/2)**(-n), \
(n,0,oo)).find_linear_recurrence(10) == [1, 1]
assert sequence((1,2,3,4,6),(n, 0, 4)).find_linear_recurrence(5) == []
assert sequence((2,3,4,5,6,79),(n, 0, 5)).find_linear_recurrence(6,gfvar=x) \
== ([], None)
assert sequence((2,3,4,5,8,30),(n, 0, 5)).find_linear_recurrence(6,gfvar=x) \
== ([Rational(19, 2), -20, Rational(27, 2)], (-31*x**2 + 32*x - 4)/(27*x**3 - 40*x**2 + 19*x -2))
assert sequence(fibonacci(n)).find_linear_recurrence(30,gfvar=x) \
== ([1, 1], -x/(x**2 + x - 1))
assert sequence(tribonacci(n)).find_linear_recurrence(30,gfvar=x) \
== ([1, 1, 1], -x/(x**3 + x**2 + x - 1))
def test_RecursiveSeq():
y = Function('y')
n = Symbol('n')
fib = RecursiveSeq(y(n - 1) + y(n - 2), y(n), n, [0, 1])
assert fib.coeff(3) == 2
|
23d0e2a05a5c26716fa7df9712029123f883bf40b652526ad6733daeb7031bb6 | from sympy.core import EulerGamma
from sympy.core.numbers import (E, I, Integer, Rational, oo, pi)
from sympy.core.singleton import S
from sympy.core.symbol import Symbol
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.trigonometric import (acot, atan, cos, sin)
from sympy.functions.special.error_functions import (Ei, erf)
from sympy.functions.special.gamma_functions import (digamma, gamma, loggamma)
from sympy.functions.special.zeta_functions import zeta
from sympy.polys.polytools import cancel
from sympy.functions.elementary.hyperbolic import cosh, coth, sinh, tanh
from sympy.series.gruntz import compare, mrv, rewrite, mrv_leadterm, gruntz, \
sign
from sympy.testing.pytest import XFAIL, skip, slow
"""
This test suite is testing the limit algorithm using the bottom up approach.
See the documentation in limits2.py. The algorithm itself is highly recursive
by nature, so "compare" is logically the lowest part of the algorithm, yet in
some sense it's the most complex part, because it needs to calculate a limit
to return the result.
Nevertheless, the rest of the algorithm depends on compare working correctly.
"""
x = Symbol('x', real=True)
m = Symbol('m', real=True)
runslow = False
def _sskip():
if not runslow:
skip("slow")
@slow
def test_gruntz_evaluation():
# Gruntz' thesis pp. 122 to 123
# 8.1
assert gruntz(exp(x)*(exp(1/x - exp(-x)) - exp(1/x)), x, oo) == -1
# 8.2
assert gruntz(exp(x)*(exp(1/x + exp(-x) + exp(-x**2))
- exp(1/x - exp(-exp(x)))), x, oo) == 1
# 8.3
assert gruntz(exp(exp(x - exp(-x))/(1 - 1/x)) - exp(exp(x)), x, oo) is oo
# 8.5
assert gruntz(exp(exp(exp(x + exp(-x)))) / exp(exp(exp(x))), x, oo) is oo
# 8.6
assert gruntz(exp(exp(exp(x))) / exp(exp(exp(x - exp(-exp(x))))),
x, oo) is oo
# 8.7
assert gruntz(exp(exp(exp(x))) / exp(exp(exp(x - exp(-exp(exp(x)))))),
x, oo) == 1
# 8.8
assert gruntz(exp(exp(x)) / exp(exp(x - exp(-exp(exp(x))))), x, oo) == 1
# 8.9
assert gruntz(log(x)**2 * exp(sqrt(log(x))*(log(log(x)))**2
* exp(sqrt(log(log(x))) * (log(log(log(x))))**3)) / sqrt(x),
x, oo) == 0
# 8.10
assert gruntz((x*log(x)*(log(x*exp(x) - x**2))**2)
/ (log(log(x**2 + 2*exp(exp(3*x**3*log(x)))))), x, oo) == Rational(1, 3)
# 8.11
assert gruntz((exp(x*exp(-x)/(exp(-x) + exp(-2*x**2/(x + 1)))) - exp(x))/x,
x, oo) == -exp(2)
# 8.12
assert gruntz((3**x + 5**x)**(1/x), x, oo) == 5
# 8.13
assert gruntz(x/log(x**(log(x**(log(2)/log(x))))), x, oo) is oo
# 8.14
assert gruntz(exp(exp(2*log(x**5 + x)*log(log(x))))
/ exp(exp(10*log(x)*log(log(x)))), x, oo) is oo
# 8.15
assert gruntz(exp(exp(Rational(5, 2)*x**Rational(-5, 7) + Rational(21, 8)*x**Rational(6, 11)
+ 2*x**(-8) + Rational(54, 17)*x**Rational(49, 45)))**8
/ log(log(-log(Rational(4, 3)*x**Rational(-5, 14))))**Rational(7, 6), x, oo) is oo
# 8.16
assert gruntz((exp(4*x*exp(-x)/(1/exp(x) + 1/exp(2*x**2/(x + 1)))) - exp(x))
/ exp(x)**4, x, oo) == 1
# 8.17
assert gruntz(exp(x*exp(-x)/(exp(-x) + exp(-2*x**2/(x + 1))))/exp(x), x, oo) \
== 1
# 8.19
assert gruntz(log(x)*(log(log(x) + log(log(x))) - log(log(x)))
/ (log(log(x) + log(log(log(x))))), x, oo) == 1
# 8.20
assert gruntz(exp((log(log(x + exp(log(x)*log(log(x))))))
/ (log(log(log(exp(x) + x + log(x)))))), x, oo) == E
# Another
assert gruntz(exp(exp(exp(x + exp(-x)))) / exp(exp(x)), x, oo) is oo
def test_gruntz_evaluation_slow():
_sskip()
# 8.4
assert gruntz(exp(exp(exp(x)/(1 - 1/x)))
- exp(exp(exp(x)/(1 - 1/x - log(x)**(-log(x))))), x, oo) is -oo
# 8.18
assert gruntz((exp(exp(-x/(1 + exp(-x))))*exp(-x/(1 + exp(-x/(1 + exp(-x)))))
*exp(exp(-x + exp(-x/(1 + exp(-x))))))
/ (exp(-x/(1 + exp(-x))))**2 - exp(x) + x, x, oo) == 2
@slow
def test_gruntz_eval_special():
# Gruntz, p. 126
assert gruntz(exp(x)*(sin(1/x + exp(-x)) - sin(1/x + exp(-x**2))), x, oo) == 1
assert gruntz((erf(x - exp(-exp(x))) - erf(x)) * exp(exp(x)) * exp(x**2),
x, oo) == -2/sqrt(pi)
assert gruntz(exp(exp(x)) * (exp(sin(1/x + exp(-exp(x)))) - exp(sin(1/x))),
x, oo) == 1
assert gruntz(exp(x)*(gamma(x + exp(-x)) - gamma(x)), x, oo) is oo
assert gruntz(exp(exp(digamma(digamma(x))))/x, x, oo) == exp(Rational(-1, 2))
assert gruntz(exp(exp(digamma(log(x))))/x, x, oo) == exp(Rational(-1, 2))
assert gruntz(digamma(digamma(digamma(x))), x, oo) is oo
assert gruntz(loggamma(loggamma(x)), x, oo) is oo
assert gruntz(((gamma(x + 1/gamma(x)) - gamma(x))/log(x) - cos(1/x))
* x*log(x), x, oo) == Rational(-1, 2)
assert gruntz(x * (gamma(x - 1/gamma(x)) - gamma(x) + log(x)), x, oo) \
== S.Half
assert gruntz((gamma(x + 1/gamma(x)) - gamma(x)) / log(x), x, oo) == 1
def test_gruntz_eval_special_slow():
_sskip()
assert gruntz(gamma(x + 1)/sqrt(2*pi)
- exp(-x)*(x**(x + S.Half) + x**(x - S.Half)/12), x, oo) is oo
assert gruntz(exp(exp(exp(digamma(digamma(digamma(x))))))/x, x, oo) == 0
@XFAIL
def test_grunts_eval_special_slow_sometimes_fail():
_sskip()
# XXX This sometimes fails!!!
assert gruntz(exp(gamma(x - exp(-x))*exp(1/x)) - exp(gamma(x)), x, oo) is oo
def test_gruntz_Ei():
assert gruntz((Ei(x - exp(-exp(x))) - Ei(x)) *exp(-x)*exp(exp(x))*x, x, oo) == -1
@XFAIL
def test_gruntz_eval_special_fail():
# TODO zeta function series
assert gruntz(
exp((log(2) + 1)*x) * (zeta(x + exp(-x)) - zeta(x)), x, oo) == -log(2)
# TODO 8.35 - 8.37 (bessel, max-min)
def test_gruntz_hyperbolic():
assert gruntz(cosh(x), x, oo) is oo
assert gruntz(cosh(x), x, -oo) is oo
assert gruntz(sinh(x), x, oo) is oo
assert gruntz(sinh(x), x, -oo) is -oo
assert gruntz(2*cosh(x)*exp(x), x, oo) is oo
assert gruntz(2*cosh(x)*exp(x), x, -oo) == 1
assert gruntz(2*sinh(x)*exp(x), x, oo) is oo
assert gruntz(2*sinh(x)*exp(x), x, -oo) == -1
assert gruntz(tanh(x), x, oo) == 1
assert gruntz(tanh(x), x, -oo) == -1
assert gruntz(coth(x), x, oo) == 1
assert gruntz(coth(x), x, -oo) == -1
def test_compare1():
assert compare(2, x, x) == "<"
assert compare(x, exp(x), x) == "<"
assert compare(exp(x), exp(x**2), x) == "<"
assert compare(exp(x**2), exp(exp(x)), x) == "<"
assert compare(1, exp(exp(x)), x) == "<"
assert compare(x, 2, x) == ">"
assert compare(exp(x), x, x) == ">"
assert compare(exp(x**2), exp(x), x) == ">"
assert compare(exp(exp(x)), exp(x**2), x) == ">"
assert compare(exp(exp(x)), 1, x) == ">"
assert compare(2, 3, x) == "="
assert compare(3, -5, x) == "="
assert compare(2, -5, x) == "="
assert compare(x, x**2, x) == "="
assert compare(x**2, x**3, x) == "="
assert compare(x**3, 1/x, x) == "="
assert compare(1/x, x**m, x) == "="
assert compare(x**m, -x, x) == "="
assert compare(exp(x), exp(-x), x) == "="
assert compare(exp(-x), exp(2*x), x) == "="
assert compare(exp(2*x), exp(x)**2, x) == "="
assert compare(exp(x)**2, exp(x + exp(-x)), x) == "="
assert compare(exp(x), exp(x + exp(-x)), x) == "="
assert compare(exp(x**2), 1/exp(x**2), x) == "="
def test_compare2():
assert compare(exp(x), x**5, x) == ">"
assert compare(exp(x**2), exp(x)**2, x) == ">"
assert compare(exp(x), exp(x + exp(-x)), x) == "="
assert compare(exp(x + exp(-x)), exp(x), x) == "="
assert compare(exp(x + exp(-x)), exp(-x), x) == "="
assert compare(exp(-x), x, x) == ">"
assert compare(x, exp(-x), x) == "<"
assert compare(exp(x + 1/x), x, x) == ">"
assert compare(exp(-exp(x)), exp(x), x) == ">"
assert compare(exp(exp(-exp(x)) + x), exp(-exp(x)), x) == "<"
def test_compare3():
assert compare(exp(exp(x)), exp(x + exp(-exp(x))), x) == ">"
def test_sign1():
assert sign(Rational(0), x) == 0
assert sign(Rational(3), x) == 1
assert sign(Rational(-5), x) == -1
assert sign(log(x), x) == 1
assert sign(exp(-x), x) == 1
assert sign(exp(x), x) == 1
assert sign(-exp(x), x) == -1
assert sign(3 - 1/x, x) == 1
assert sign(-3 - 1/x, x) == -1
assert sign(sin(1/x), x) == 1
assert sign((x**Integer(2)), x) == 1
assert sign(x**2, x) == 1
assert sign(x**5, x) == 1
def test_sign2():
assert sign(x, x) == 1
assert sign(-x, x) == -1
y = Symbol("y", positive=True)
assert sign(y, x) == 1
assert sign(-y, x) == -1
assert sign(y*x, x) == 1
assert sign(-y*x, x) == -1
def mmrv(a, b):
return set(mrv(a, b)[0].keys())
def test_mrv1():
assert mmrv(x, x) == {x}
assert mmrv(x + 1/x, x) == {x}
assert mmrv(x**2, x) == {x}
assert mmrv(log(x), x) == {x}
assert mmrv(exp(x), x) == {exp(x)}
assert mmrv(exp(-x), x) == {exp(-x)}
assert mmrv(exp(x**2), x) == {exp(x**2)}
assert mmrv(-exp(1/x), x) == {x}
assert mmrv(exp(x + 1/x), x) == {exp(x + 1/x)}
def test_mrv2a():
assert mmrv(exp(x + exp(-exp(x))), x) == {exp(-exp(x))}
assert mmrv(exp(x + exp(-x)), x) == {exp(x + exp(-x)), exp(-x)}
assert mmrv(exp(1/x + exp(-x)), x) == {exp(-x)}
#sometimes infinite recursion due to log(exp(x**2)) not simplifying
def test_mrv2b():
assert mmrv(exp(x + exp(-x**2)), x) == {exp(-x**2)}
#sometimes infinite recursion due to log(exp(x**2)) not simplifying
def test_mrv2c():
assert mmrv(
exp(-x + 1/x**2) - exp(x + 1/x), x) == {exp(x + 1/x), exp(1/x**2 - x)}
#sometimes infinite recursion due to log(exp(x**2)) not simplifying
def test_mrv3():
assert mmrv(exp(x**2) + x*exp(x) + log(x)**x/x, x) == {exp(x**2)}
assert mmrv(
exp(x)*(exp(1/x + exp(-x)) - exp(1/x)), x) == {exp(x), exp(-x)}
assert mmrv(log(
x**2 + 2*exp(exp(3*x**3*log(x)))), x) == {exp(exp(3*x**3*log(x)))}
assert mmrv(log(x - log(x))/log(x), x) == {x}
assert mmrv(
(exp(1/x - exp(-x)) - exp(1/x))*exp(x), x) == {exp(x), exp(-x)}
assert mmrv(
1/exp(-x + exp(-x)) - exp(x), x) == {exp(x), exp(-x), exp(x - exp(-x))}
assert mmrv(log(log(x*exp(x*exp(x)) + 1)), x) == {exp(x*exp(x))}
assert mmrv(exp(exp(log(log(x) + 1/x))), x) == {x}
def test_mrv4():
ln = log
assert mmrv((ln(ln(x) + ln(ln(x))) - ln(ln(x)))/ln(ln(x) + ln(ln(ln(x))))*ln(x),
x) == {x}
assert mmrv(log(log(x*exp(x*exp(x)) + 1)) - exp(exp(log(log(x) + 1/x))), x) == \
{exp(x*exp(x))}
def mrewrite(a, b, c):
return rewrite(a[1], a[0], b, c)
def test_rewrite1():
e = exp(x)
assert mrewrite(mrv(e, x), x, m) == (1/m, -x)
e = exp(x**2)
assert mrewrite(mrv(e, x), x, m) == (1/m, -x**2)
e = exp(x + 1/x)
assert mrewrite(mrv(e, x), x, m) == (1/m, -x - 1/x)
e = 1/exp(-x + exp(-x)) - exp(x)
assert mrewrite(mrv(e, x), x, m) == (1/(m*exp(m)) - 1/m, -x)
def test_rewrite2():
e = exp(x)*log(log(exp(x)))
assert mmrv(e, x) == {exp(x)}
assert mrewrite(mrv(e, x), x, m) == (1/m*log(x), -x)
#sometimes infinite recursion due to log(exp(x**2)) not simplifying
def test_rewrite3():
e = exp(-x + 1/x**2) - exp(x + 1/x)
#both of these are correct and should be equivalent:
assert mrewrite(mrv(e, x), x, m) in [(-1/m + m*exp(
1/x + 1/x**2), -x - 1/x), (m - 1/m*exp(1/x + x**(-2)), x**(-2) - x)]
def test_mrv_leadterm1():
assert mrv_leadterm(-exp(1/x), x) == (-1, 0)
assert mrv_leadterm(1/exp(-x + exp(-x)) - exp(x), x) == (-1, 0)
assert mrv_leadterm(
(exp(1/x - exp(-x)) - exp(1/x))*exp(x), x) == (-exp(1/x), 0)
def test_mrv_leadterm2():
#Gruntz: p51, 3.25
assert mrv_leadterm((log(exp(x) + x) - x)/log(exp(x) + log(x))*exp(x), x) == \
(1, 0)
def test_mrv_leadterm3():
#Gruntz: p56, 3.27
assert mmrv(exp(-x + exp(-x)*exp(-x*log(x))), x) == {exp(-x - x*log(x))}
assert mrv_leadterm(exp(-x + exp(-x)*exp(-x*log(x))), x) == (exp(-x), 0)
def test_limit1():
assert gruntz(x, x, oo) is oo
assert gruntz(x, x, -oo) is -oo
assert gruntz(-x, x, oo) is -oo
assert gruntz(x**2, x, -oo) is oo
assert gruntz(-x**2, x, oo) is -oo
assert gruntz(x*log(x), x, 0, dir="+") == 0
assert gruntz(1/x, x, oo) == 0
assert gruntz(exp(x), x, oo) is oo
assert gruntz(-exp(x), x, oo) is -oo
assert gruntz(exp(x)/x, x, oo) is oo
assert gruntz(1/x - exp(-x), x, oo) == 0
assert gruntz(x + 1/x, x, oo) is oo
def test_limit2():
assert gruntz(x**x, x, 0, dir="+") == 1
assert gruntz((exp(x) - 1)/x, x, 0) == 1
assert gruntz(1 + 1/x, x, oo) == 1
assert gruntz(-exp(1/x), x, oo) == -1
assert gruntz(x + exp(-x), x, oo) is oo
assert gruntz(x + exp(-x**2), x, oo) is oo
assert gruntz(x + exp(-exp(x)), x, oo) is oo
assert gruntz(13 + 1/x - exp(-x), x, oo) == 13
def test_limit3():
a = Symbol('a')
assert gruntz(x - log(1 + exp(x)), x, oo) == 0
assert gruntz(x - log(a + exp(x)), x, oo) == 0
assert gruntz(exp(x)/(1 + exp(x)), x, oo) == 1
assert gruntz(exp(x)/(a + exp(x)), x, oo) == 1
def test_limit4():
#issue 3463
assert gruntz((3**x + 5**x)**(1/x), x, oo) == 5
#issue 3463
assert gruntz((3**(1/x) + 5**(1/x))**x, x, 0) == 5
@XFAIL
def test_MrvTestCase_page47_ex3_21():
h = exp(-x/(1 + exp(-x)))
expr = exp(h)*exp(-x/(1 + h))*exp(exp(-x + h))/h**2 - exp(x) + x
assert mmrv(expr, x) == {1/h, exp(-x), exp(x), exp(x - h), exp(x/(1 + h))}
def test_I():
y = Symbol("y")
assert gruntz(I*x, x, oo) == I*oo
assert gruntz(y*I*x, x, oo) == y*I*oo
assert gruntz(y*3*I*x, x, oo) == y*I*oo
assert gruntz(y*3*sin(I)*x, x, oo).simplify().rewrite(sign) == y*I*oo
def test_issue_4814():
assert gruntz((x + 1)**(1/log(x + 1)), x, oo) == E
def test_intractable():
assert gruntz(1/gamma(x), x, oo) == 0
assert gruntz(1/loggamma(x), x, oo) == 0
assert gruntz(gamma(x)/loggamma(x), x, oo) is oo
assert gruntz(exp(gamma(x))/gamma(x), x, oo) is oo
assert gruntz(gamma(x), x, 3) == 2
assert gruntz(gamma(Rational(1, 7) + 1/x), x, oo) == gamma(Rational(1, 7))
assert gruntz(log(x**x)/log(gamma(x)), x, oo) == 1
assert gruntz(log(gamma(gamma(x)))/exp(x), x, oo) is oo
def test_aseries_trig():
assert cancel(gruntz(1/log(atan(x)), x, oo)
- 1/(log(pi) + log(S.Half))) == 0
assert gruntz(1/acot(x), x, -oo) is -oo
def test_exp_log_series():
assert gruntz(x/log(log(x*exp(x))), x, oo) is oo
def test_issue_3644():
assert gruntz(((x**7 + x + 1)/(2**x + x**2))**(-1/x), x, oo) == 2
def test_issue_6843():
n = Symbol('n', integer=True, positive=True)
r = (n + 1)*x**(n + 1)/(x**(n + 1) - 1) - x/(x - 1)
assert gruntz(r, x, 1).simplify() == n/2
def test_issue_4190():
assert gruntz(x - gamma(1/x), x, oo) == S.EulerGamma
@XFAIL
def test_issue_5172():
n = Symbol('n')
r = Symbol('r', positive=True)
c = Symbol('c')
p = Symbol('p', positive=True)
m = Symbol('m', negative=True)
expr = ((2*n*(n - r + 1)/(n + r*(n - r + 1)))**c + \
(r - 1)*(n*(n - r + 2)/(n + r*(n - r + 1)))**c - n)/(n**c - n)
expr = expr.subs(c, c + 1)
assert gruntz(expr.subs(c, m), n, oo) == 1
# fail:
assert gruntz(expr.subs(c, p), n, oo).simplify() == \
(2**(p + 1) + r - 1)/(r + 1)**(p + 1)
def test_issue_4109():
assert gruntz(1/gamma(x), x, 0) == 0
assert gruntz(x*gamma(x), x, 0) == 1
def test_issue_6682():
assert gruntz(exp(2*Ei(-x))/x**2, x, 0) == exp(2*EulerGamma)
def test_issue_7096():
from sympy.functions import sign
assert gruntz(x**-pi, x, 0, dir='-') == oo*sign((-1)**(-pi))
|
9c50a8eeec39f4f7c5ba2b054faedea98fd29193c451d1a25530e3ab60532bd2 | from sympy.concrete.summations import Sum
from sympy.core.add import Add
from sympy.core.function import (Derivative, Function)
from sympy.core.mul import Mul
from sympy.core.numbers import (I, Rational, oo, pi)
from sympy.core.singleton import S
from sympy.core.symbol import symbols
from sympy.functions.combinatorial.factorials import factorial
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.hyperbolic import (acosh, asech)
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.trigonometric import (acos, asin, atan, cos, sin)
from sympy.functions.special.bessel import airyai
from sympy.functions.special.error_functions import erf
from sympy.functions.special.gamma_functions import gamma
from sympy.integrals.integrals import integrate
from sympy.series.formal import fps
from sympy.series.order import O
from sympy.series.formal import (rational_algorithm, FormalPowerSeries,
FormalPowerSeriesProduct, FormalPowerSeriesCompose,
FormalPowerSeriesInverse, simpleDE,
rational_independent, exp_re, hyper_re)
from sympy.testing.pytest import raises, XFAIL, slow
x, y, z = symbols('x y z')
n, m, k = symbols('n m k', integer=True)
f, r = Function('f'), Function('r')
def test_rational_algorithm():
f = 1 / ((x - 1)**2 * (x - 2))
assert rational_algorithm(f, x, k) == \
(-2**(-k - 1) + 1 - (factorial(k + 1) / factorial(k)), 0, 0)
f = (1 + x + x**2 + x**3) / ((x - 1) * (x - 2))
assert rational_algorithm(f, x, k) == \
(-15*2**(-k - 1) + 4, x + 4, 0)
f = z / (y*m - m*x - y*x + x**2)
assert rational_algorithm(f, x, k) == \
(((-y**(-k - 1)*z) / (y - m)) + ((m**(-k - 1)*z) / (y - m)), 0, 0)
f = x / (1 - x - x**2)
assert rational_algorithm(f, x, k) is None
assert rational_algorithm(f, x, k, full=True) == \
(((Rational(-1, 2) + sqrt(5)/2)**(-k - 1) *
(-sqrt(5)/10 + S.Half)) +
((-sqrt(5)/2 - S.Half)**(-k - 1) *
(sqrt(5)/10 + S.Half)), 0, 0)
f = 1 / (x**2 + 2*x + 2)
assert rational_algorithm(f, x, k) is None
assert rational_algorithm(f, x, k, full=True) == \
((I*(-1 + I)**(-k - 1)) / 2 - (I*(-1 - I)**(-k - 1)) / 2, 0, 0)
f = log(1 + x)
assert rational_algorithm(f, x, k) == \
(-(-1)**(-k) / k, 0, 1)
f = atan(x)
assert rational_algorithm(f, x, k) is None
assert rational_algorithm(f, x, k, full=True) == \
(((I*I**(-k)) / 2 - (I*(-I)**(-k)) / 2) / k, 0, 1)
f = x*atan(x) - log(1 + x**2) / 2
assert rational_algorithm(f, x, k) is None
assert rational_algorithm(f, x, k, full=True) == \
(((I*I**(-k + 1)) / 2 - (I*(-I)**(-k + 1)) / 2) /
(k*(k - 1)), 0, 2)
f = log((1 + x) / (1 - x)) / 2 - atan(x)
assert rational_algorithm(f, x, k) is None
assert rational_algorithm(f, x, k, full=True) == \
((-(-1)**(-k) / 2 - (I*I**(-k)) / 2 + (I*(-I)**(-k)) / 2 +
S.Half) / k, 0, 1)
assert rational_algorithm(cos(x), x, k) is None
def test_rational_independent():
ri = rational_independent
assert ri([], x) == []
assert ri([cos(x), sin(x)], x) == [cos(x), sin(x)]
assert ri([x**2, sin(x), x*sin(x), x**3], x) == \
[x**3 + x**2, x*sin(x) + sin(x)]
assert ri([S.One, x*log(x), log(x), sin(x)/x, cos(x), sin(x), x], x) == \
[x + 1, x*log(x) + log(x), sin(x)/x + sin(x), cos(x)]
def test_simpleDE():
# Tests just the first valid DE
for DE in simpleDE(exp(x), x, f):
assert DE == (-f(x) + Derivative(f(x), x), 1)
break
for DE in simpleDE(sin(x), x, f):
assert DE == (f(x) + Derivative(f(x), x, x), 2)
break
for DE in simpleDE(log(1 + x), x, f):
assert DE == ((x + 1)*Derivative(f(x), x, 2) + Derivative(f(x), x), 2)
break
for DE in simpleDE(asin(x), x, f):
assert DE == (x*Derivative(f(x), x) + (x**2 - 1)*Derivative(f(x), x, x),
2)
break
for DE in simpleDE(exp(x)*sin(x), x, f):
assert DE == (2*f(x) - 2*Derivative(f(x)) + Derivative(f(x), x, x), 2)
break
for DE in simpleDE(((1 + x)/(1 - x))**n, x, f):
assert DE == (2*n*f(x) + (x**2 - 1)*Derivative(f(x), x), 1)
break
for DE in simpleDE(airyai(x), x, f):
assert DE == (-x*f(x) + Derivative(f(x), x, x), 2)
break
def test_exp_re():
d = -f(x) + Derivative(f(x), x)
assert exp_re(d, r, k) == -r(k) + r(k + 1)
d = f(x) + Derivative(f(x), x, x)
assert exp_re(d, r, k) == r(k) + r(k + 2)
d = f(x) + Derivative(f(x), x) + Derivative(f(x), x, x)
assert exp_re(d, r, k) == r(k) + r(k + 1) + r(k + 2)
d = Derivative(f(x), x) + Derivative(f(x), x, x)
assert exp_re(d, r, k) == r(k) + r(k + 1)
d = Derivative(f(x), x, 3) + Derivative(f(x), x, 4) + Derivative(f(x))
assert exp_re(d, r, k) == r(k) + r(k + 2) + r(k + 3)
def test_hyper_re():
d = f(x) + Derivative(f(x), x, x)
assert hyper_re(d, r, k) == r(k) + (k+1)*(k+2)*r(k + 2)
d = -x*f(x) + Derivative(f(x), x, x)
assert hyper_re(d, r, k) == (k + 2)*(k + 3)*r(k + 3) - r(k)
d = 2*f(x) - 2*Derivative(f(x), x) + Derivative(f(x), x, x)
assert hyper_re(d, r, k) == \
(-2*k - 2)*r(k + 1) + (k + 1)*(k + 2)*r(k + 2) + 2*r(k)
d = 2*n*f(x) + (x**2 - 1)*Derivative(f(x), x)
assert hyper_re(d, r, k) == \
k*r(k) + 2*n*r(k + 1) + (-k - 2)*r(k + 2)
d = (x**10 + 4)*Derivative(f(x), x) + x*(x**10 - 1)*Derivative(f(x), x, x)
assert hyper_re(d, r, k) == \
(k*(k - 1) + k)*r(k) + (4*k - (k + 9)*(k + 10) + 40)*r(k + 10)
d = ((x**2 - 1)*Derivative(f(x), x, 3) + 3*x*Derivative(f(x), x, x) +
Derivative(f(x), x))
assert hyper_re(d, r, k) == \
((k*(k - 2)*(k - 1) + 3*k*(k - 1) + k)*r(k) +
(-k*(k + 1)*(k + 2))*r(k + 2))
def test_fps():
assert fps(1) == 1
assert fps(2, x) == 2
assert fps(2, x, dir='+') == 2
assert fps(2, x, dir='-') == 2
assert fps(1/x + 1/x**2) == 1/x + 1/x**2
assert fps(log(1 + x), hyper=False, rational=False) == log(1 + x)
f = fps(x**2 + x + 1)
assert isinstance(f, FormalPowerSeries)
assert f.function == x**2 + x + 1
assert f[0] == 1
assert f[2] == x**2
assert f.truncate(4) == x**2 + x + 1 + O(x**4)
assert f.polynomial() == x**2 + x + 1
f = fps(log(1 + x))
assert isinstance(f, FormalPowerSeries)
assert f.function == log(1 + x)
assert f.subs(x, y) == f
assert f[:5] == [0, x, -x**2/2, x**3/3, -x**4/4]
assert f.as_leading_term(x) == x
assert f.polynomial(6) == x - x**2/2 + x**3/3 - x**4/4 + x**5/5
k = f.ak.variables[0]
assert f.infinite == Sum((-(-1)**(-k)*x**k)/k, (k, 1, oo))
ft, s = f.truncate(n=None), f[:5]
for i, t in enumerate(ft):
if i == 5:
break
assert s[i] == t
f = sin(x).fps(x)
assert isinstance(f, FormalPowerSeries)
assert f.truncate() == x - x**3/6 + x**5/120 + O(x**6)
raises(NotImplementedError, lambda: fps(y*x))
raises(ValueError, lambda: fps(x, dir=0))
@slow
def test_fps__rational():
assert fps(1/x) == (1/x)
assert fps((x**2 + x + 1) / x**3, dir=-1) == (x**2 + x + 1) / x**3
f = 1 / ((x - 1)**2 * (x - 2))
assert fps(f, x).truncate() == \
(Rational(-1, 2) - x*Rational(5, 4) - 17*x**2/8 - 49*x**3/16 - 129*x**4/32 -
321*x**5/64 + O(x**6))
f = (1 + x + x**2 + x**3) / ((x - 1) * (x - 2))
assert fps(f, x).truncate() == \
(S.Half + x*Rational(5, 4) + 17*x**2/8 + 49*x**3/16 + 113*x**4/32 +
241*x**5/64 + O(x**6))
f = x / (1 - x - x**2)
assert fps(f, x, full=True).truncate() == \
x + x**2 + 2*x**3 + 3*x**4 + 5*x**5 + O(x**6)
f = 1 / (x**2 + 2*x + 2)
assert fps(f, x, full=True).truncate() == \
S.Half - x/2 + x**2/4 - x**4/8 + x**5/8 + O(x**6)
f = log(1 + x)
assert fps(f, x).truncate() == \
x - x**2/2 + x**3/3 - x**4/4 + x**5/5 + O(x**6)
assert fps(f, x, dir=1).truncate() == fps(f, x, dir=-1).truncate()
assert fps(f, x, 2).truncate() == \
(log(3) - Rational(2, 3) - (x - 2)**2/18 + (x - 2)**3/81 -
(x - 2)**4/324 + (x - 2)**5/1215 + x/3 + O((x - 2)**6, (x, 2)))
assert fps(f, x, 2, dir=-1).truncate() == \
(log(3) - Rational(2, 3) - (-x + 2)**2/18 - (-x + 2)**3/81 -
(-x + 2)**4/324 - (-x + 2)**5/1215 + x/3 + O((x - 2)**6, (x, 2)))
f = atan(x)
assert fps(f, x, full=True).truncate() == x - x**3/3 + x**5/5 + O(x**6)
assert fps(f, x, full=True, dir=1).truncate() == \
fps(f, x, full=True, dir=-1).truncate()
assert fps(f, x, 2, full=True).truncate() == \
(atan(2) - Rational(2, 5) - 2*(x - 2)**2/25 + 11*(x - 2)**3/375 -
6*(x - 2)**4/625 + 41*(x - 2)**5/15625 + x/5 + O((x - 2)**6, (x, 2)))
assert fps(f, x, 2, full=True, dir=-1).truncate() == \
(atan(2) - Rational(2, 5) - 2*(-x + 2)**2/25 - 11*(-x + 2)**3/375 -
6*(-x + 2)**4/625 - 41*(-x + 2)**5/15625 + x/5 + O((x - 2)**6, (x, 2)))
f = x*atan(x) - log(1 + x**2) / 2
assert fps(f, x, full=True).truncate() == x**2/2 - x**4/12 + O(x**6)
f = log((1 + x) / (1 - x)) / 2 - atan(x)
assert fps(f, x, full=True).truncate(n=10) == 2*x**3/3 + 2*x**7/7 + O(x**10)
@slow
def test_fps__hyper():
f = sin(x)
assert fps(f, x).truncate() == x - x**3/6 + x**5/120 + O(x**6)
f = cos(x)
assert fps(f, x).truncate() == 1 - x**2/2 + x**4/24 + O(x**6)
f = exp(x)
assert fps(f, x).truncate() == \
1 + x + x**2/2 + x**3/6 + x**4/24 + x**5/120 + O(x**6)
f = atan(x)
assert fps(f, x).truncate() == x - x**3/3 + x**5/5 + O(x**6)
f = exp(acos(x))
assert fps(f, x).truncate() == \
(exp(pi/2) - x*exp(pi/2) + x**2*exp(pi/2)/2 - x**3*exp(pi/2)/3 +
5*x**4*exp(pi/2)/24 - x**5*exp(pi/2)/6 + O(x**6))
f = exp(acosh(x))
assert fps(f, x).truncate() == I + x - I*x**2/2 - I*x**4/8 + O(x**6)
f = atan(1/x)
assert fps(f, x).truncate() == pi/2 - x + x**3/3 - x**5/5 + O(x**6)
f = x*atan(x) - log(1 + x**2) / 2
assert fps(f, x, rational=False).truncate() == x**2/2 - x**4/12 + O(x**6)
f = log(1 + x)
assert fps(f, x, rational=False).truncate() == \
x - x**2/2 + x**3/3 - x**4/4 + x**5/5 + O(x**6)
f = airyai(x**2)
assert fps(f, x).truncate() == \
(3**Rational(5, 6)*gamma(Rational(1, 3))/(6*pi) -
3**Rational(2, 3)*x**2/(3*gamma(Rational(1, 3))) + O(x**6))
f = exp(x)*sin(x)
assert fps(f, x).truncate() == x + x**2 + x**3/3 - x**5/30 + O(x**6)
f = exp(x)*sin(x)/x
assert fps(f, x).truncate() == 1 + x + x**2/3 - x**4/30 - x**5/90 + O(x**6)
f = sin(x) * cos(x)
assert fps(f, x).truncate() == x - 2*x**3/3 + 2*x**5/15 + O(x**6)
def test_fps_shift():
f = x**-5*sin(x)
assert fps(f, x).truncate() == \
1/x**4 - 1/(6*x**2) + Rational(1, 120) - x**2/5040 + x**4/362880 + O(x**6)
f = x**2*atan(x)
assert fps(f, x, rational=False).truncate() == \
x**3 - x**5/3 + O(x**6)
f = cos(sqrt(x))*x
assert fps(f, x).truncate() == \
x - x**2/2 + x**3/24 - x**4/720 + x**5/40320 + O(x**6)
f = x**2*cos(sqrt(x))
assert fps(f, x).truncate() == \
x**2 - x**3/2 + x**4/24 - x**5/720 + O(x**6)
def test_fps__Add_expr():
f = x*atan(x) - log(1 + x**2) / 2
assert fps(f, x).truncate() == x**2/2 - x**4/12 + O(x**6)
f = sin(x) + cos(x) - exp(x) + log(1 + x)
assert fps(f, x).truncate() == x - 3*x**2/2 - x**4/4 + x**5/5 + O(x**6)
f = 1/x + sin(x)
assert fps(f, x).truncate() == 1/x + x - x**3/6 + x**5/120 + O(x**6)
f = sin(x) - cos(x) + 1/(x - 1)
assert fps(f, x).truncate() == \
-2 - x**2/2 - 7*x**3/6 - 25*x**4/24 - 119*x**5/120 + O(x**6)
def test_fps__asymptotic():
f = exp(x)
assert fps(f, x, oo) == f
assert fps(f, x, -oo).truncate() == O(1/x**6, (x, oo))
f = erf(x)
assert fps(f, x, oo).truncate() == 1 + O(1/x**6, (x, oo))
assert fps(f, x, -oo).truncate() == -1 + O(1/x**6, (x, oo))
f = atan(x)
assert fps(f, x, oo, full=True).truncate() == \
-1/(5*x**5) + 1/(3*x**3) - 1/x + pi/2 + O(1/x**6, (x, oo))
assert fps(f, x, -oo, full=True).truncate() == \
-1/(5*x**5) + 1/(3*x**3) - 1/x - pi/2 + O(1/x**6, (x, oo))
f = log(1 + x)
assert fps(f, x, oo) != \
(-1/(5*x**5) - 1/(4*x**4) + 1/(3*x**3) - 1/(2*x**2) + 1/x - log(1/x) +
O(1/x**6, (x, oo)))
assert fps(f, x, -oo) != \
(-1/(5*x**5) - 1/(4*x**4) + 1/(3*x**3) - 1/(2*x**2) + 1/x + I*pi -
log(-1/x) + O(1/x**6, (x, oo)))
def test_fps__fractional():
f = sin(sqrt(x)) / x
assert fps(f, x).truncate() == \
(1/sqrt(x) - sqrt(x)/6 + x**Rational(3, 2)/120 -
x**Rational(5, 2)/5040 + x**Rational(7, 2)/362880 -
x**Rational(9, 2)/39916800 + x**Rational(11, 2)/6227020800 + O(x**6))
f = sin(sqrt(x)) * x
assert fps(f, x).truncate() == \
(x**Rational(3, 2) - x**Rational(5, 2)/6 + x**Rational(7, 2)/120 -
x**Rational(9, 2)/5040 + x**Rational(11, 2)/362880 + O(x**6))
f = atan(sqrt(x)) / x**2
assert fps(f, x).truncate() == \
(x**Rational(-3, 2) - x**Rational(-1, 2)/3 + x**S.Half/5 -
x**Rational(3, 2)/7 + x**Rational(5, 2)/9 - x**Rational(7, 2)/11 +
x**Rational(9, 2)/13 - x**Rational(11, 2)/15 + O(x**6))
f = exp(sqrt(x))
assert fps(f, x).truncate().expand() == \
(1 + x/2 + x**2/24 + x**3/720 + x**4/40320 + x**5/3628800 + sqrt(x) +
x**Rational(3, 2)/6 + x**Rational(5, 2)/120 + x**Rational(7, 2)/5040 +
x**Rational(9, 2)/362880 + x**Rational(11, 2)/39916800 + O(x**6))
f = exp(sqrt(x))*x
assert fps(f, x).truncate().expand() == \
(x + x**2/2 + x**3/24 + x**4/720 + x**5/40320 + x**Rational(3, 2) +
x**Rational(5, 2)/6 + x**Rational(7, 2)/120 + x**Rational(9, 2)/5040 +
x**Rational(11, 2)/362880 + O(x**6))
def test_fps__logarithmic_singularity():
f = log(1 + 1/x)
assert fps(f, x) != \
-log(x) + x - x**2/2 + x**3/3 - x**4/4 + x**5/5 + O(x**6)
assert fps(f, x, rational=False) != \
-log(x) + x - x**2/2 + x**3/3 - x**4/4 + x**5/5 + O(x**6)
@XFAIL
def test_fps__logarithmic_singularity_fail():
f = asech(x) # Algorithms for computing limits probably needs improvemnts
assert fps(f, x) == log(2) - log(x) - x**2/4 - 3*x**4/64 + O(x**6)
def test_fps_symbolic():
f = x**n*sin(x**2)
assert fps(f, x).truncate(8) == x**(n + 2) - x**(n + 6)/6 + O(x**(n + 8), x)
f = x**n*log(1 + x)
fp = fps(f, x)
k = fp.ak.variables[0]
assert fp.infinite == \
Sum((-(-1)**(-k)*x**(k + n))/k, (k, 1, oo))
f = (x - 2)**n*log(1 + x)
assert fps(f, x, 2).truncate() == \
((x - 2)**n*log(3) + (x - 2)**(n + 1)/3 - (x - 2)**(n + 2)/18 + (x - 2)**(n + 3)/81 -
(x - 2)**(n + 4)/324 + (x - 2)**(n + 5)/1215 + O((x - 2)**(n + 6), (x, 2)))
f = x**(n - 2)*cos(x)
assert fps(f, x).truncate() == \
(x**(n - 2) - x**n/2 + x**(n + 2)/24 - x**(n + 4)/720 + O(x**(n + 6), x))
f = x**(n - 2)*sin(x) + x**n*exp(x)
assert fps(f, x).truncate() == \
(x**(n - 1) + x**n + 5*x**(n + 1)/6 + x**(n + 2)/2 + 7*x**(n + 3)/40 +
x**(n + 4)/24 + 41*x**(n + 5)/5040 + O(x**(n + 6), x))
f = x**n*atan(x)
assert fps(f, x, oo).truncate() == \
(-x**(n - 5)/5 + x**(n - 3)/3 + x**n*(pi/2 - 1/x) +
O((1/x)**(-n)/x**6, (x, oo)))
f = x**(n/2)*cos(x)
assert fps(f, x).truncate() == \
x**(n/2) - x**(n/2 + 2)/2 + x**(n/2 + 4)/24 + O(x**(n/2 + 6), x)
f = x**(n + m)*sin(x)
assert fps(f, x).truncate() == \
x**(m + n + 1) - x**(m + n + 3)/6 + x**(m + n + 5)/120 + O(x**(m + n + 6), x)
def test_fps__slow():
f = x*exp(x)*sin(2*x) # TODO: rsolve needs improvement
assert fps(f, x).truncate() == 2*x**2 + 2*x**3 - x**4/3 - x**5 + O(x**6)
def test_fps__operations():
f1, f2 = fps(sin(x)), fps(cos(x))
fsum = f1 + f2
assert fsum.function == sin(x) + cos(x)
assert fsum.truncate() == \
1 + x - x**2/2 - x**3/6 + x**4/24 + x**5/120 + O(x**6)
fsum = f1 + 1
assert fsum.function == sin(x) + 1
assert fsum.truncate() == 1 + x - x**3/6 + x**5/120 + O(x**6)
fsum = 1 + f2
assert fsum.function == cos(x) + 1
assert fsum.truncate() == 2 - x**2/2 + x**4/24 + O(x**6)
assert (f1 + x) == Add(f1, x)
assert -f2.truncate() == -1 + x**2/2 - x**4/24 + O(x**6)
assert (f1 - f1) is S.Zero
fsub = f1 - f2
assert fsub.function == sin(x) - cos(x)
assert fsub.truncate() == \
-1 + x + x**2/2 - x**3/6 - x**4/24 + x**5/120 + O(x**6)
fsub = f1 - 1
assert fsub.function == sin(x) - 1
assert fsub.truncate() == -1 + x - x**3/6 + x**5/120 + O(x**6)
fsub = 1 - f2
assert fsub.function == -cos(x) + 1
assert fsub.truncate() == x**2/2 - x**4/24 + O(x**6)
raises(ValueError, lambda: f1 + fps(exp(x), dir=-1))
raises(ValueError, lambda: f1 + fps(exp(x), x0=1))
fm = f1 * 3
assert fm.function == 3*sin(x)
assert fm.truncate() == 3*x - x**3/2 + x**5/40 + O(x**6)
fm = 3 * f2
assert fm.function == 3*cos(x)
assert fm.truncate() == 3 - 3*x**2/2 + x**4/8 + O(x**6)
assert (f1 * f2) == Mul(f1, f2)
assert (f1 * x) == Mul(f1, x)
fd = f1.diff()
assert fd.function == cos(x)
assert fd.truncate() == 1 - x**2/2 + x**4/24 + O(x**6)
fd = f2.diff()
assert fd.function == -sin(x)
assert fd.truncate() == -x + x**3/6 - x**5/120 + O(x**6)
fd = f2.diff().diff()
assert fd.function == -cos(x)
assert fd.truncate() == -1 + x**2/2 - x**4/24 + O(x**6)
f3 = fps(exp(sqrt(x)))
fd = f3.diff()
assert fd.truncate().expand() == \
(1/(2*sqrt(x)) + S.Half + x/12 + x**2/240 + x**3/10080 + x**4/725760 +
x**5/79833600 + sqrt(x)/4 + x**Rational(3, 2)/48 + x**Rational(5, 2)/1440 +
x**Rational(7, 2)/80640 + x**Rational(9, 2)/7257600 + x**Rational(11, 2)/958003200 +
O(x**6))
assert f1.integrate((x, 0, 1)) == -cos(1) + 1
assert integrate(f1, (x, 0, 1)) == -cos(1) + 1
fi = integrate(f1, x)
assert fi.function == -cos(x)
assert fi.truncate() == -1 + x**2/2 - x**4/24 + O(x**6)
fi = f2.integrate(x)
assert fi.function == sin(x)
assert fi.truncate() == x - x**3/6 + x**5/120 + O(x**6)
def test_fps__product():
f1, f2, f3 = fps(sin(x)), fps(exp(x)), fps(cos(x))
raises(ValueError, lambda: f1.product(exp(x), x))
raises(ValueError, lambda: f1.product(fps(exp(x), dir=-1), x, 4))
raises(ValueError, lambda: f1.product(fps(exp(x), x0=1), x, 4))
raises(ValueError, lambda: f1.product(fps(exp(y)), x, 4))
fprod = f1.product(f2, x)
assert isinstance(fprod, FormalPowerSeriesProduct)
assert isinstance(fprod.ffps, FormalPowerSeries)
assert isinstance(fprod.gfps, FormalPowerSeries)
assert fprod.f == sin(x)
assert fprod.g == exp(x)
assert fprod.function == sin(x) * exp(x)
assert fprod._eval_terms(4) == x + x**2 + x**3/3
assert fprod.truncate(4) == x + x**2 + x**3/3 + O(x**4)
assert fprod.polynomial(4) == x + x**2 + x**3/3
raises(NotImplementedError, lambda: fprod._eval_term(5))
raises(NotImplementedError, lambda: fprod.infinite)
raises(NotImplementedError, lambda: fprod._eval_derivative(x))
raises(NotImplementedError, lambda: fprod.integrate(x))
assert f1.product(f3, x)._eval_terms(4) == x - 2*x**3/3
assert f1.product(f3, x).truncate(4) == x - 2*x**3/3 + O(x**4)
def test_fps__compose():
f1, f2, f3 = fps(exp(x)), fps(sin(x)), fps(cos(x))
raises(ValueError, lambda: f1.compose(sin(x), x))
raises(ValueError, lambda: f1.compose(fps(sin(x), dir=-1), x, 4))
raises(ValueError, lambda: f1.compose(fps(sin(x), x0=1), x, 4))
raises(ValueError, lambda: f1.compose(fps(sin(y)), x, 4))
raises(ValueError, lambda: f1.compose(f3, x))
raises(ValueError, lambda: f2.compose(f3, x))
fcomp = f1.compose(f2, x)
assert isinstance(fcomp, FormalPowerSeriesCompose)
assert isinstance(fcomp.ffps, FormalPowerSeries)
assert isinstance(fcomp.gfps, FormalPowerSeries)
assert fcomp.f == exp(x)
assert fcomp.g == sin(x)
assert fcomp.function == exp(sin(x))
assert fcomp._eval_terms(6) == 1 + x + x**2/2 - x**4/8 - x**5/15
assert fcomp.truncate() == 1 + x + x**2/2 - x**4/8 - x**5/15 + O(x**6)
assert fcomp.truncate(5) == 1 + x + x**2/2 - x**4/8 + O(x**5)
raises(NotImplementedError, lambda: fcomp._eval_term(5))
raises(NotImplementedError, lambda: fcomp.infinite)
raises(NotImplementedError, lambda: fcomp._eval_derivative(x))
raises(NotImplementedError, lambda: fcomp.integrate(x))
assert f1.compose(f2, x).truncate(4) == 1 + x + x**2/2 + O(x**4)
assert f1.compose(f2, x).truncate(8) == \
1 + x + x**2/2 - x**4/8 - x**5/15 - x**6/240 + x**7/90 + O(x**8)
assert f1.compose(f2, x).truncate(6) == \
1 + x + x**2/2 - x**4/8 - x**5/15 + O(x**6)
assert f2.compose(f2, x).truncate(4) == x - x**3/3 + O(x**4)
assert f2.compose(f2, x).truncate(8) == x - x**3/3 + x**5/10 - 8*x**7/315 + O(x**8)
assert f2.compose(f2, x).truncate(6) == x - x**3/3 + x**5/10 + O(x**6)
def test_fps__inverse():
f1, f2, f3 = fps(sin(x)), fps(exp(x)), fps(cos(x))
raises(ValueError, lambda: f1.inverse(x))
finv = f2.inverse(x)
assert isinstance(finv, FormalPowerSeriesInverse)
assert isinstance(finv.ffps, FormalPowerSeries)
raises(ValueError, lambda: finv.gfps)
assert finv.f == exp(x)
assert finv.function == exp(-x)
assert finv._eval_terms(5) == 1 - x + x**2/2 - x**3/6 + x**4/24
assert finv.truncate() == 1 - x + x**2/2 - x**3/6 + x**4/24 - x**5/120 + O(x**6)
assert finv.truncate(5) == 1 - x + x**2/2 - x**3/6 + x**4/24 + O(x**5)
raises(NotImplementedError, lambda: finv._eval_term(5))
raises(ValueError, lambda: finv.g)
raises(NotImplementedError, lambda: finv.infinite)
raises(NotImplementedError, lambda: finv._eval_derivative(x))
raises(NotImplementedError, lambda: finv.integrate(x))
assert f2.inverse(x).truncate(8) == \
1 - x + x**2/2 - x**3/6 + x**4/24 - x**5/120 + x**6/720 - x**7/5040 + O(x**8)
assert f3.inverse(x).truncate() == 1 + x**2/2 + 5*x**4/24 + O(x**6)
assert f3.inverse(x).truncate(8) == 1 + x**2/2 + 5*x**4/24 + 61*x**6/720 + O(x**8)
|
517ca34f45460c156e2ac993a6a810b3610845c237138e039b48396f0404b91d | from sympy.series import approximants
from sympy.core.symbol import symbols
from sympy.functions.combinatorial.factorials import binomial
from sympy.functions.combinatorial.numbers import (fibonacci, lucas)
def test_approximants():
x, t = symbols("x,t")
g = [lucas(k) for k in range(16)]
assert [e for e in approximants(g)] == (
[2, -4/(x - 2), (5*x - 2)/(3*x - 1), (x - 2)/(x**2 + x - 1)] )
g = [lucas(k)+fibonacci(k+2) for k in range(16)]
assert [e for e in approximants(g)] == (
[3, -3/(x - 1), (3*x - 3)/(2*x - 1), -3/(x**2 + x - 1)] )
g = [lucas(k)**2 for k in range(16)]
assert [e for e in approximants(g)] == (
[4, -16/(x - 4), (35*x - 4)/(9*x - 1), (37*x - 28)/(13*x**2 + 11*x - 7),
(50*x**2 + 63*x - 52)/(37*x**2 + 19*x - 13),
(-x**2 - 7*x + 4)/(x**3 - 2*x**2 - 2*x + 1)] )
p = [sum(binomial(k,i)*x**i for i in range(k+1)) for k in range(16)]
y = approximants(p, t, simplify=True)
assert next(y) == 1
assert next(y) == -1/(t*(x + 1) - 1)
|
63446fcbbbe961e2d802e582facc789eb1e375eeb264a338f2d48ef89d4271cc | from sympy.core.evalf import N
from sympy.core.function import (Derivative, Function, PoleError, Subs)
from sympy.core.numbers import (E, Rational, oo, pi)
from sympy.core.singleton import S
from sympy.core.symbol import (Symbol, symbols)
from sympy.functions.elementary.exponential import (LambertW, exp, log)
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.trigonometric import (atan, cos, sin)
from sympy.integrals.integrals import Integral
from sympy.series.order import O
from sympy.series.series import series
from sympy.abc import x, y, n, k
from sympy.testing.pytest import raises
from sympy.series.gruntz import calculate_series
def test_sin():
e1 = sin(x).series(x, 0)
e2 = series(sin(x), x, 0)
assert e1 == e2
def test_cos():
e1 = cos(x).series(x, 0)
e2 = series(cos(x), x, 0)
assert e1 == e2
def test_exp():
e1 = exp(x).series(x, 0)
e2 = series(exp(x), x, 0)
assert e1 == e2
def test_exp2():
e1 = exp(cos(x)).series(x, 0)
e2 = series(exp(cos(x)), x, 0)
assert e1 == e2
def test_issue_5223():
assert series(1, x) == 1
assert next(S.Zero.lseries(x)) == 0
assert cos(x).series() == cos(x).series(x)
raises(ValueError, lambda: cos(x + y).series())
raises(ValueError, lambda: x.series(dir=""))
assert (cos(x).series(x, 1) -
cos(x + 1).series(x).subs(x, x - 1)).removeO() == 0
e = cos(x).series(x, 1, n=None)
assert [next(e) for i in range(2)] == [cos(1), -((x - 1)*sin(1))]
e = cos(x).series(x, 1, n=None, dir='-')
assert [next(e) for i in range(2)] == [cos(1), (1 - x)*sin(1)]
# the following test is exact so no need for x -> x - 1 replacement
assert abs(x).series(x, 1, dir='-') == x
assert exp(x).series(x, 1, dir='-', n=3).removeO() == \
E - E*(-x + 1) + E*(-x + 1)**2/2
D = Derivative
assert D(x**2 + x**3*y**2, x, 2, y, 1).series(x).doit() == 12*x*y
assert next(D(cos(x), x).lseries()) == D(1, x)
assert D(
exp(x), x).series(n=3) == D(1, x) + D(x, x) + D(x**2/2, x) + D(x**3/6, x) + O(x**3)
assert Integral(x, (x, 1, 3), (y, 1, x)).series(x) == -4 + 4*x
assert (1 + x + O(x**2)).getn() == 2
assert (1 + x).getn() is None
raises(PoleError, lambda: ((1/sin(x))**oo).series())
logx = Symbol('logx')
assert ((sin(x))**y).nseries(x, n=1, logx=logx) == \
exp(y*logx) + O(x*exp(y*logx), x)
assert sin(1/x).series(x, oo, n=5) == 1/x - 1/(6*x**3) + O(x**(-5), (x, oo))
assert abs(x).series(x, oo, n=5, dir='+') == x
assert abs(x).series(x, -oo, n=5, dir='-') == -x
assert abs(-x).series(x, oo, n=5, dir='+') == x
assert abs(-x).series(x, -oo, n=5, dir='-') == -x
assert exp(x*log(x)).series(n=3) == \
1 + x*log(x) + x**2*log(x)**2/2 + O(x**3*log(x)**3)
# XXX is this right? If not, fix "ngot > n" handling in expr.
p = Symbol('p', positive=True)
assert exp(sqrt(p)**3*log(p)).series(n=3) == \
1 + p**S('3/2')*log(p) + O(p**3*log(p)**3)
assert exp(sin(x)*log(x)).series(n=2) == 1 + x*log(x) + O(x**2*log(x)**2)
def test_issue_11313():
assert Integral(cos(x), x).series(x) == sin(x).series(x)
assert Derivative(sin(x), x).series(x, n=3).doit() == cos(x).series(x, n=3)
assert Derivative(x**3, x).as_leading_term(x) == 3*x**2
assert Derivative(x**3, y).as_leading_term(x) == 0
assert Derivative(sin(x), x).as_leading_term(x) == 1
assert Derivative(cos(x), x).as_leading_term(x) == -x
# This result is equivalent to zero, zero is not return because
# `Expr.series` doesn't currently detect an `x` in its `free_symbol`s.
assert Derivative(1, x).as_leading_term(x) == Derivative(1, x)
assert Derivative(exp(x), x).series(x).doit() == exp(x).series(x)
assert 1 + Integral(exp(x), x).series(x) == exp(x).series(x)
assert Derivative(log(x), x).series(x).doit() == (1/x).series(x)
assert Integral(log(x), x).series(x) == Integral(log(x), x).doit().series(x).removeO()
def test_series_of_Subs():
from sympy.abc import z
subs1 = Subs(sin(x), x, y)
subs2 = Subs(sin(x) * cos(z), x, y)
subs3 = Subs(sin(x * z), (x, z), (y, x))
assert subs1.series(x) == subs1
subs1_series = (Subs(x, x, y) + Subs(-x**3/6, x, y) +
Subs(x**5/120, x, y) + O(y**6))
assert subs1.series() == subs1_series
assert subs1.series(y) == subs1_series
assert subs1.series(z) == subs1
assert subs2.series(z) == (Subs(z**4*sin(x)/24, x, y) +
Subs(-z**2*sin(x)/2, x, y) + Subs(sin(x), x, y) + O(z**6))
assert subs3.series(x).doit() == subs3.doit().series(x)
assert subs3.series(z).doit() == sin(x*y)
raises(ValueError, lambda: Subs(x + 2*y, y, z).series())
assert Subs(x + y, y, z).series(x).doit() == x + z
def test_issue_3978():
f = Function('f')
assert f(x).series(x, 0, 3, dir='-') == \
f(0) + x*Subs(Derivative(f(x), x), x, 0) + \
x**2*Subs(Derivative(f(x), x, x), x, 0)/2 + O(x**3)
assert f(x).series(x, 0, 3) == \
f(0) + x*Subs(Derivative(f(x), x), x, 0) + \
x**2*Subs(Derivative(f(x), x, x), x, 0)/2 + O(x**3)
assert f(x**2).series(x, 0, 3) == \
f(0) + x**2*Subs(Derivative(f(x), x), x, 0) + O(x**3)
assert f(x**2+1).series(x, 0, 3) == \
f(1) + x**2*Subs(Derivative(f(x), x), x, 1) + O(x**3)
class TestF(Function):
pass
assert TestF(x).series(x, 0, 3) == TestF(0) + \
x*Subs(Derivative(TestF(x), x), x, 0) + \
x**2*Subs(Derivative(TestF(x), x, x), x, 0)/2 + O(x**3)
from sympy.series.acceleration import richardson, shanks
from sympy.concrete.summations import Sum
from sympy.core.numbers import Integer
def test_acceleration():
e = (1 + 1/n)**n
assert round(richardson(e, n, 10, 20).evalf(), 10) == round(E.evalf(), 10)
A = Sum(Integer(-1)**(k + 1) / k, (k, 1, n))
assert round(shanks(A, n, 25).evalf(), 4) == round(log(2).evalf(), 4)
assert round(shanks(A, n, 25, 5).evalf(), 10) == round(log(2).evalf(), 10)
def test_issue_5852():
assert series(1/cos(x/log(x)), x, 0) == 1 + x**2/(2*log(x)**2) + \
5*x**4/(24*log(x)**4) + O(x**6)
def test_issue_4583():
assert cos(1 + x + x**2).series(x, 0, 5) == cos(1) - x*sin(1) + \
x**2*(-sin(1) - cos(1)/2) + x**3*(-cos(1) + sin(1)/6) + \
x**4*(-11*cos(1)/24 + sin(1)/2) + O(x**5)
def test_issue_6318():
eq = (1/x)**Rational(2, 3)
assert (eq + 1).as_leading_term(x) == eq
def test_x_is_base_detection():
eq = (x**2)**Rational(2, 3)
assert eq.series() == x**Rational(4, 3)
def test_sin_power():
e = sin(x)**1.2
assert calculate_series(e, x) == x**1.2
def test_issue_7203():
assert series(cos(x), x, pi, 3) == \
-1 + (x - pi)**2/2 + O((x - pi)**3, (x, pi))
def test_exp_product_positive_factors():
a, b = symbols('a, b', positive=True)
x = a * b
assert series(exp(x), x, n=8) == 1 + a*b + a**2*b**2/2 + \
a**3*b**3/6 + a**4*b**4/24 + a**5*b**5/120 + a**6*b**6/720 + \
a**7*b**7/5040 + O(a**8*b**8, a, b)
def test_issue_8805():
assert series(1, n=8) == 1
def test_issue_9549():
y = (x**2 + x + 1) / (x**3 + x**2)
assert series(y, x, oo) == x**(-5) - 1/x**4 + x**(-3) + 1/x + O(x**(-6), (x, oo))
def test_issue_10761():
assert series(1/(x**-2 + x**-3), x, 0) == x**3 - x**4 + x**5 + O(x**6)
def test_issue_12578():
y = (1 - 1/(x/2 - 1/(2*x))**4)**(S(1)/8)
assert y.series(x, 0, n=17) == 1 - 2*x**4 - 8*x**6 - 34*x**8 - 152*x**10 - 714*x**12 - \
3472*x**14 - 17318*x**16 + O(x**17)
def test_issue_12791():
beta = symbols('beta', real=True, positive=True)
theta, varphi = symbols('theta varphi', real=True)
expr = (-beta**2*varphi*sin(theta) + beta**2*cos(theta) + \
beta*varphi*sin(theta) - beta*cos(theta) - beta + 1)/(beta*cos(theta) - 1)**2
sol = 0.5/(0.5*cos(theta) - 1.0)**2 - 0.25*cos(theta)/(0.5*cos(theta)\
- 1.0)**2 + (beta - 0.5)*(-0.25*varphi*sin(2*theta) - 1.5*cos(theta)\
+ 0.25*cos(2*theta) + 1.25)/(0.5*cos(theta) - 1.0)**3\
+ 0.25*varphi*sin(theta)/(0.5*cos(theta) - 1.0)**2 + O((beta - S.Half)**2, (beta, S.Half))
assert expr.series(beta, 0.5, 2).trigsimp() == sol
def test_issue_14885():
assert series(x**Rational(-3, 2)*exp(x), x, 0) == (x**Rational(-3, 2) + 1/sqrt(x) +
sqrt(x)/2 + x**Rational(3, 2)/6 + x**Rational(5, 2)/24 + x**Rational(7, 2)/120 +
x**Rational(9, 2)/720 + x**Rational(11, 2)/5040 + O(x**6))
def test_issue_15539():
assert series(atan(x), x, -oo) == (-1/(5*x**5) + 1/(3*x**3) - 1/x - pi/2
+ O(x**(-6), (x, -oo)))
assert series(atan(x), x, oo) == (-1/(5*x**5) + 1/(3*x**3) - 1/x + pi/2
+ O(x**(-6), (x, oo)))
def test_issue_7259():
assert series(LambertW(x), x) == x - x**2 + 3*x**3/2 - 8*x**4/3 + 125*x**5/24 + O(x**6)
assert series(LambertW(x**2), x, n=8) == x**2 - x**4 + 3*x**6/2 + O(x**8)
assert series(LambertW(sin(x)), x, n=4) == x - x**2 + 4*x**3/3 + O(x**4)
def test_issue_11884():
assert cos(x).series(x, 1, n=1) == cos(1) + O(x - 1, (x, 1))
def test_issue_18008():
y = x*(1 + x*(1 - x))/((1 + x*(1 - x)) - (1 - x)*(1 - x))
assert y.series(x, oo, n=4) == -9/(32*x**3) - 3/(16*x**2) - 1/(8*x) + S(1)/4 + x/2 + \
O(x**(-4), (x, oo))
def test_issue_18842():
f = log(x/(1 - x))
assert f.series(x, 0.491, n=1).removeO().nsimplify() == \
-S(180019443780011)/5000000000000000
def test_issue_19534():
dt = symbols('dt', real=True)
expr = 16*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0)/45 + \
49*dt*(-0.049335189898860408029*dt*(2.0*dt + 1.0) + \
0.29601113939316244817*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) - \
0.12564355335492979587*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \
0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.96296296296296296296*dt + 1.0) + 0.051640768506639183825*dt + \
dt*(1/2 - sqrt(21)/14) + 1.0)/180 + 49*dt*(-0.23637909581542530626*dt*(2.0*dt + 1.0) - \
0.74817562366625959291*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.88085458023927036857*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \
0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.96296296296296296296*dt + 1.0) + \
2.1165151389911680013*dt*(-0.049335189898860408029*dt*(2.0*dt + 1.0) + \
0.29601113939316244817*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) - \
0.12564355335492979587*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \
0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.96296296296296296296*dt + 1.0) + 0.22431393315265061193*dt + 1.0) - \
1.1854881643947648988*dt + dt*(sqrt(21)/14 + 1/2) + 1.0)/180 + \
dt*(0.66666666666666666667*dt*(2.0*dt + 1.0) + \
6.0173399699313066769*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) - \
4.1117044797036320069*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \
0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.96296296296296296296*dt + 1.0) - \
7.0189140975801991157*dt*(-0.049335189898860408029*dt*(2.0*dt + 1.0) + \
0.29601113939316244817*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) - \
0.12564355335492979587*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \
0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.96296296296296296296*dt + 1.0) + 0.22431393315265061193*dt + 1.0) + \
0.94010945196161777522*dt*(-0.23637909581542530626*dt*(2.0*dt + 1.0) - \
0.74817562366625959291*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.88085458023927036857*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \
0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.96296296296296296296*dt + 1.0) + \
2.1165151389911680013*dt*(-0.049335189898860408029*dt*(2.0*dt + 1.0) + \
0.29601113939316244817*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) - \
0.12564355335492979587*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \
0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \
0.96296296296296296296*dt + 1.0) + 0.22431393315265061193*dt + 1.0) - \
0.35816132904077632692*dt + 1.0) + 5.5065024887242400038*dt + 1.0)/20 + dt/20 + 1
assert N(expr.series(dt, 0, 8), 20) == -0.00092592592592592596126*dt**7 + 0.0027777777777777783175*dt**6 + \
0.016666666666666656027*dt**5 + 0.083333333333333300952*dt**4 + 0.33333333333333337034*dt**3 + \
1.0*dt**2 + 1.0*dt + 1.0
def test_issue_11407():
a, b, c, x = symbols('a b c x')
assert series(sqrt(a + b + c*x), x, 0, 1) == sqrt(a + b) + O(x)
assert series(sqrt(a + b + c + c*x), x, 0, 1) == sqrt(a + b + c) + O(x)
def test_issue_14037():
assert (sin(x**50)/x**51).series(x, n=0) == 1/x + O(1, x)
def test_issue_20551():
expr = (exp(x)/x).series(x, n=None)
terms = [ next(expr) for i in range(3) ]
assert terms == [1/x, 1, x/2]
def test_issue_20697():
p_0, p_1, p_2, p_3, b_0, b_1, b_2 = symbols('p_0 p_1 p_2 p_3 b_0 b_1 b_2')
Q = (p_0 + (p_1 + (p_2 + p_3/y)/y)/y)/(1 + ((p_3/(b_0*y) + (b_0*p_2\
- b_1*p_3)/b_0**2)/y + (b_0**2*p_1 - b_0*b_1*p_2 - p_3*(b_0*b_2\
- b_1**2))/b_0**3)/y)
assert Q.series(y, n=3).ratsimp() == b_2*y**2 + b_1*y + b_0 + O(y**3)
def test_issue_21245():
fi = (1 + sqrt(5))/2
assert (1/(1 - x - x**2)).series(x, 1/fi, 1).factor() == \
(-6964*sqrt(5) - 15572 + 2440*sqrt(5)*x + 5456*x\
+ O((x - 2/(1 + sqrt(5)))**2, (x, 2/(1 + sqrt(5)))))/((1 + sqrt(5))**2\
*(20 + 9*sqrt(5))**2*(x + sqrt(5)*x - 2))
def test_issue_21938():
expr = sin(1/x + exp(-x)) - sin(1/x)
assert expr.series(x, oo) == (1/(24*x**4) - 1/(2*x**2) + 1 + O(x**(-6), (x, oo)))*exp(-x)
|
24661a72a24c12a1d2ea84f6018b3d77b8aeb4811bdf63e426cf4426a387c5c4 | from sympy.core.numbers import (Rational, oo, pi)
from sympy.core.singleton import S
from sympy.core.symbol import Symbol
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.miscellaneous import (root, sqrt)
from sympy.functions.elementary.trigonometric import (asin, cos, sin, tan)
from sympy.polys.rationaltools import together
from sympy.series.limits import limit
# Numbers listed with the tests refer to problem numbers in the book
# "Anti-demidovich, problemas resueltos, Ed. URSS"
x = Symbol("x")
def test_leadterm():
assert (3 + 2*x**(log(3)/log(2) - 1)).leadterm(x) == (3, 0)
def root3(x):
return root(x, 3)
def root4(x):
return root(x, 4)
def test_Limits_simple_0():
assert limit((2**(x + 1) + 3**(x + 1))/(2**x + 3**x), x, oo) == 3 # 175
def test_Limits_simple_1():
assert limit((x + 1)*(x + 2)*(x + 3)/x**3, x, oo) == 1 # 172
assert limit(sqrt(x + 1) - sqrt(x), x, oo) == 0 # 179
assert limit((2*x - 3)*(3*x + 5)*(4*x - 6)/(3*x**3 + x - 1), x, oo) == 8 # Primjer 1
assert limit(x/root3(x**3 + 10), x, oo) == 1 # Primjer 2
assert limit((x + 1)**2/(x**2 + 1), x, oo) == 1 # 181
def test_Limits_simple_2():
assert limit(1000*x/(x**2 - 1), x, oo) == 0 # 182
assert limit((x**2 - 5*x + 1)/(3*x + 7), x, oo) is oo # 183
assert limit((2*x**2 - x + 3)/(x**3 - 8*x + 5), x, oo) == 0 # 184
assert limit((2*x**2 - 3*x - 4)/sqrt(x**4 + 1), x, oo) == 2 # 186
assert limit((2*x + 3)/(x + root3(x)), x, oo) == 2 # 187
assert limit(x**2/(10 + x*sqrt(x)), x, oo) is oo # 188
assert limit(root3(x**2 + 1)/(x + 1), x, oo) == 0 # 189
assert limit(sqrt(x)/sqrt(x + sqrt(x + sqrt(x))), x, oo) == 1 # 190
def test_Limits_simple_3a():
a = Symbol('a')
#issue 3513
assert together(limit((x**2 - (a + 1)*x + a)/(x**3 - a**3), x, a)) == \
(a - 1)/(3*a**2) # 196
def test_Limits_simple_3b():
h = Symbol("h")
assert limit(((x + h)**3 - x**3)/h, h, 0) == 3*x**2 # 197
assert limit((1/(1 - x) - 3/(1 - x**3)), x, 1) == -1 # 198
assert limit((sqrt(1 + x) - 1)/(root3(1 + x) - 1), x, 0) == Rational(3)/2 # Primer 4
assert limit((sqrt(x) - 1)/(x - 1), x, 1) == Rational(1)/2 # 199
assert limit((sqrt(x) - 8)/(root3(x) - 4), x, 64) == 3 # 200
assert limit((root3(x) - 1)/(root4(x) - 1), x, 1) == Rational(4)/3 # 201
assert limit(
(root3(x**2) - 2*root3(x) + 1)/(x - 1)**2, x, 1) == Rational(1)/9 # 202
def test_Limits_simple_4a():
a = Symbol('a')
assert limit((sqrt(x) - sqrt(a))/(x - a), x, a) == 1/(2*sqrt(a)) # Primer 5
assert limit((sqrt(x) - 1)/(root3(x) - 1), x, 1) == Rational(3, 2) # 205
assert limit((sqrt(1 + x) - sqrt(1 - x))/x, x, 0) == 1 # 207
assert limit(sqrt(x**2 - 5*x + 6) - x, x, oo) == Rational(-5, 2) # 213
def test_limits_simple_4aa():
assert limit(x*(sqrt(x**2 + 1) - x), x, oo) == Rational(1)/2 # 214
def test_Limits_simple_4b():
#issue 3511
assert limit(x - root3(x**3 - 1), x, oo) == 0 # 215
def test_Limits_simple_4c():
assert limit(log(1 + exp(x))/x, x, -oo) == 0 # 267a
assert limit(log(1 + exp(x))/x, x, oo) == 1 # 267b
def test_bounded():
assert limit(sin(x)/x, x, oo) == 0 # 216b
assert limit(x*sin(1/x), x, 0) == 0 # 227a
def test_f1a():
#issue 3508:
assert limit((sin(2*x)/x)**(1 + x), x, 0) == 2 # Primer 7
def test_f1a2():
#issue 3509:
assert limit(((x - 1)/(x + 1))**x, x, oo) == exp(-2) # Primer 9
def test_f1b():
m = Symbol("m")
n = Symbol("n")
h = Symbol("h")
a = Symbol("a")
assert limit(sin(x)/x, x, 2) == sin(2)/2 # 216a
assert limit(sin(3*x)/x, x, 0) == 3 # 217
assert limit(sin(5*x)/sin(2*x), x, 0) == Rational(5, 2) # 218
assert limit(sin(pi*x)/sin(3*pi*x), x, 0) == Rational(1, 3) # 219
assert limit(x*sin(pi/x), x, oo) == pi # 220
assert limit((1 - cos(x))/x**2, x, 0) == S.Half # 221
assert limit(x*sin(1/x), x, oo) == 1 # 227b
assert limit((cos(m*x) - cos(n*x))/x**2, x, 0) == -m**2/2 + n**2/2 # 232
assert limit((tan(x) - sin(x))/x**3, x, 0) == S.Half # 233
assert limit((x - sin(2*x))/(x + sin(3*x)), x, 0) == -Rational(1, 4) # 237
assert limit((1 - sqrt(cos(x)))/x**2, x, 0) == Rational(1, 4) # 239
assert limit((sqrt(1 + sin(x)) - sqrt(1 - sin(x)))/x, x, 0) == 1 # 240
assert limit((1 + h/x)**x, x, oo) == exp(h) # Primer 9
assert limit((sin(x) - sin(a))/(x - a), x, a) == cos(a) # 222, *176
assert limit((cos(x) - cos(a))/(x - a), x, a) == -sin(a) # 223
assert limit((sin(x + h) - sin(x))/h, h, 0) == cos(x) # 225
def test_f2a():
assert limit(((x + 1)/(2*x + 1))**(x**2), x, oo) == 0 # Primer 8
def test_f2():
assert limit((sqrt(
cos(x)) - root3(cos(x)))/(sin(x)**2), x, 0) == -Rational(1, 12) # *184
def test_f3():
a = Symbol('a')
#issue 3504
assert limit(asin(a*x)/x, x, 0) == a
|
0e49e4eb845618d3bc9179a9cb645121b4fc6fed028cbff7e50701ba045e5b7f | from sympy.core.add import Add
from sympy.core.numbers import (Rational, oo, pi)
from sympy.core.singleton import S
from sympy.core.symbol import symbols
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.piecewise import Piecewise
from sympy.functions.elementary.trigonometric import (cos, sin, sinc, tan)
from sympy.series.fourier import fourier_series
from sympy.series.fourier import FourierSeries
from sympy.testing.pytest import raises
from functools import lru_cache
x, y, z = symbols('x y z')
# Don't declare these during import because they are slow
@lru_cache()
def _get_examples():
fo = fourier_series(x, (x, -pi, pi))
fe = fourier_series(x**2, (-pi, pi))
fp = fourier_series(Piecewise((0, x < 0), (pi, True)), (x, -pi, pi))
return fo, fe, fp
def test_FourierSeries():
fo, fe, fp = _get_examples()
assert fourier_series(1, (-pi, pi)) == 1
assert (Piecewise((0, x < 0), (pi, True)).
fourier_series((x, -pi, pi)).truncate()) == fp.truncate()
assert isinstance(fo, FourierSeries)
assert fo.function == x
assert fo.x == x
assert fo.period == (-pi, pi)
assert fo.term(3) == 2*sin(3*x) / 3
assert fe.term(3) == -4*cos(3*x) / 9
assert fp.term(3) == 2*sin(3*x) / 3
assert fo.as_leading_term(x) == 2*sin(x)
assert fe.as_leading_term(x) == pi**2 / 3
assert fp.as_leading_term(x) == pi / 2
assert fo.truncate() == 2*sin(x) - sin(2*x) + (2*sin(3*x) / 3)
assert fe.truncate() == -4*cos(x) + cos(2*x) + pi**2 / 3
assert fp.truncate() == 2*sin(x) + (2*sin(3*x) / 3) + pi / 2
fot = fo.truncate(n=None)
s = [0, 2*sin(x), -sin(2*x)]
for i, t in enumerate(fot):
if i == 3:
break
assert s[i] == t
def _check_iter(f, i):
for ind, t in enumerate(f):
assert t == f[ind]
if ind == i:
break
_check_iter(fo, 3)
_check_iter(fe, 3)
_check_iter(fp, 3)
assert fo.subs(x, x**2) == fo
raises(ValueError, lambda: fourier_series(x, (0, 1, 2)))
raises(ValueError, lambda: fourier_series(x, (x, 0, oo)))
raises(ValueError, lambda: fourier_series(x*y, (0, oo)))
def test_FourierSeries_2():
p = Piecewise((0, x < 0), (x, True))
f = fourier_series(p, (x, -2, 2))
assert f.term(3) == (2*sin(3*pi*x / 2) / (3*pi) -
4*cos(3*pi*x / 2) / (9*pi**2))
assert f.truncate() == (2*sin(pi*x / 2) / pi - sin(pi*x) / pi -
4*cos(pi*x / 2) / pi**2 + S.Half)
def test_square_wave():
"""Test if fourier_series approximates discontinuous function correctly."""
square_wave = Piecewise((1, x < pi), (-1, True))
s = fourier_series(square_wave, (x, 0, 2*pi))
assert s.truncate(3) == 4 / pi * sin(x) + 4 / (3 * pi) * sin(3 * x) + \
4 / (5 * pi) * sin(5 * x)
assert s.sigma_approximation(4) == 4 / pi * sin(x) * sinc(pi / 4) + \
4 / (3 * pi) * sin(3 * x) * sinc(3 * pi / 4)
def test_sawtooth_wave():
s = fourier_series(x, (x, 0, pi))
assert s.truncate(4) == \
pi/2 - sin(2*x) - sin(4*x)/2 - sin(6*x)/3
s = fourier_series(x, (x, 0, 1))
assert s.truncate(4) == \
S.Half - sin(2*pi*x)/pi - sin(4*pi*x)/(2*pi) - sin(6*pi*x)/(3*pi)
def test_FourierSeries__operations():
fo, fe, fp = _get_examples()
fes = fe.scale(-1).shift(pi**2)
assert fes.truncate() == 4*cos(x) - cos(2*x) + 2*pi**2 / 3
assert fp.shift(-pi/2).truncate() == (2*sin(x) + (2*sin(3*x) / 3) +
(2*sin(5*x) / 5))
fos = fo.scale(3)
assert fos.truncate() == 6*sin(x) - 3*sin(2*x) + 2*sin(3*x)
fx = fe.scalex(2).shiftx(1)
assert fx.truncate() == -4*cos(2*x + 2) + cos(4*x + 4) + pi**2 / 3
fl = fe.scalex(3).shift(-pi).scalex(2).shiftx(1).scale(4)
assert fl.truncate() == (-16*cos(6*x + 6) + 4*cos(12*x + 12) -
4*pi + 4*pi**2 / 3)
raises(ValueError, lambda: fo.shift(x))
raises(ValueError, lambda: fo.shiftx(sin(x)))
raises(ValueError, lambda: fo.scale(x*y))
raises(ValueError, lambda: fo.scalex(x**2))
def test_FourierSeries__neg():
fo, fe, fp = _get_examples()
assert (-fo).truncate() == -2*sin(x) + sin(2*x) - (2*sin(3*x) / 3)
assert (-fe).truncate() == +4*cos(x) - cos(2*x) - pi**2 / 3
def test_FourierSeries__add__sub():
fo, fe, fp = _get_examples()
assert fo + fo == fo.scale(2)
assert fo - fo == 0
assert -fe - fe == fe.scale(-2)
assert (fo + fe).truncate() == 2*sin(x) - sin(2*x) - 4*cos(x) + cos(2*x) \
+ pi**2 / 3
assert (fo - fe).truncate() == 2*sin(x) - sin(2*x) + 4*cos(x) - cos(2*x) \
- pi**2 / 3
assert isinstance(fo + 1, Add)
raises(ValueError, lambda: fo + fourier_series(x, (x, 0, 2)))
def test_FourierSeries_finite():
assert fourier_series(sin(x)).truncate(1) == sin(x)
# assert type(fourier_series(sin(x)*log(x))).truncate() == FourierSeries
# assert type(fourier_series(sin(x**2+6))).truncate() == FourierSeries
assert fourier_series(sin(x)*log(y)*exp(z),(x,pi,-pi)).truncate() == sin(x)*log(y)*exp(z)
assert fourier_series(sin(x)**6).truncate(oo) == -15*cos(2*x)/32 + 3*cos(4*x)/16 - cos(6*x)/32 \
+ Rational(5, 16)
assert fourier_series(sin(x) ** 6).truncate() == -15 * cos(2 * x) / 32 + 3 * cos(4 * x) / 16 \
+ Rational(5, 16)
assert fourier_series(sin(4*x+3) + cos(3*x+4)).truncate(oo) == -sin(4)*sin(3*x) + sin(4*x)*cos(3) \
+ cos(4)*cos(3*x) + sin(3)*cos(4*x)
assert fourier_series(sin(x)+cos(x)*tan(x)).truncate(oo) == 2*sin(x)
assert fourier_series(cos(pi*x), (x, -1, 1)).truncate(oo) == cos(pi*x)
assert fourier_series(cos(3*pi*x + 4) - sin(4*pi*x)*log(pi*y), (x, -1, 1)).truncate(oo) == -log(pi*y)*sin(4*pi*x)\
- sin(4)*sin(3*pi*x) + cos(4)*cos(3*pi*x)
|
38fa4966f26b516fa3e9848eb0c82470b5100660dd51230459df20ea7616ef4b | from sympy.core.add import Add
from sympy.core.function import (Function, expand)
from sympy.core.numbers import (I, Rational, nan, oo, pi)
from sympy.core.singleton import S
from sympy.core.symbol import (Symbol, symbols)
from sympy.functions.elementary.complexes import (conjugate, transpose)
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.trigonometric import (cos, sin)
from sympy.integrals.integrals import Integral
from sympy.series.order import O, Order
from sympy.core.expr import unchanged
from sympy.testing.pytest import raises
from sympy.abc import w, x, y, z
def test_caching_bug():
#needs to be a first test, so that all caches are clean
#cache it
O(w)
#and test that this won't raise an exception
O(w**(-1/x/log(3)*log(5)), w)
def test_free_symbols():
assert Order(1).free_symbols == set()
assert Order(x).free_symbols == {x}
assert Order(1, x).free_symbols == {x}
assert Order(x*y).free_symbols == {x, y}
assert Order(x, x, y).free_symbols == {x, y}
def test_simple_1():
o = Rational(0)
assert Order(2*x) == Order(x)
assert Order(x)*3 == Order(x)
assert -28*Order(x) == Order(x)
assert Order(Order(x)) == Order(x)
assert Order(Order(x), y) == Order(Order(x), x, y)
assert Order(-23) == Order(1)
assert Order(exp(x)) == Order(1, x)
assert Order(exp(1/x)).expr == exp(1/x)
assert Order(x*exp(1/x)).expr == x*exp(1/x)
assert Order(x**(o/3)).expr == x**(o/3)
assert Order(x**(o*Rational(5, 3))).expr == x**(o*Rational(5, 3))
assert Order(x**2 + x + y, x) == O(1, x)
assert Order(x**2 + x + y, y) == O(1, y)
raises(ValueError, lambda: Order(exp(x), x, x))
raises(TypeError, lambda: Order(x, 2 - x))
def test_simple_2():
assert Order(2*x)*x == Order(x**2)
assert Order(2*x)/x == Order(1, x)
assert Order(2*x)*x*exp(1/x) == Order(x**2*exp(1/x))
assert (Order(2*x)*x*exp(1/x)/log(x)**3).expr == x**2*exp(1/x)*log(x)**-3
def test_simple_3():
assert Order(x) + x == Order(x)
assert Order(x) + 2 == 2 + Order(x)
assert Order(x) + x**2 == Order(x)
assert Order(x) + 1/x == 1/x + Order(x)
assert Order(1/x) + 1/x**2 == 1/x**2 + Order(1/x)
assert Order(x) + exp(1/x) == Order(x) + exp(1/x)
def test_simple_4():
assert Order(x)**2 == Order(x**2)
def test_simple_5():
assert Order(x) + Order(x**2) == Order(x)
assert Order(x) + Order(x**-2) == Order(x**-2)
assert Order(x) + Order(1/x) == Order(1/x)
def test_simple_6():
assert Order(x) - Order(x) == Order(x)
assert Order(x) + Order(1) == Order(1)
assert Order(x) + Order(x**2) == Order(x)
assert Order(1/x) + Order(1) == Order(1/x)
assert Order(x) + Order(exp(1/x)) == Order(exp(1/x))
assert Order(x**3) + Order(exp(2/x)) == Order(exp(2/x))
assert Order(x**-3) + Order(exp(2/x)) == Order(exp(2/x))
def test_simple_7():
assert 1 + O(1) == O(1)
assert 2 + O(1) == O(1)
assert x + O(1) == O(1)
assert 1/x + O(1) == 1/x + O(1)
def test_simple_8():
assert O(sqrt(-x)) == O(sqrt(x))
assert O(x**2*sqrt(x)) == O(x**Rational(5, 2))
assert O(x**3*sqrt(-(-x)**3)) == O(x**Rational(9, 2))
assert O(x**Rational(3, 2)*sqrt((-x)**3)) == O(x**3)
assert O(x*(-2*x)**(I/2)) == O(x*(-x)**(I/2))
def test_as_expr_variables():
assert Order(x).as_expr_variables(None) == (x, ((x, 0),))
assert Order(x).as_expr_variables(((x, 0),)) == (x, ((x, 0),))
assert Order(y).as_expr_variables(((x, 0),)) == (y, ((x, 0), (y, 0)))
assert Order(y).as_expr_variables(((x, 0), (y, 0))) == (y, ((x, 0), (y, 0)))
def test_contains_0():
assert Order(1, x).contains(Order(1, x))
assert Order(1, x).contains(Order(1))
assert Order(1).contains(Order(1, x)) is False
def test_contains_1():
assert Order(x).contains(Order(x))
assert Order(x).contains(Order(x**2))
assert not Order(x**2).contains(Order(x))
assert not Order(x).contains(Order(1/x))
assert not Order(1/x).contains(Order(exp(1/x)))
assert not Order(x).contains(Order(exp(1/x)))
assert Order(1/x).contains(Order(x))
assert Order(exp(1/x)).contains(Order(x))
assert Order(exp(1/x)).contains(Order(1/x))
assert Order(exp(1/x)).contains(Order(exp(1/x)))
assert Order(exp(2/x)).contains(Order(exp(1/x)))
assert not Order(exp(1/x)).contains(Order(exp(2/x)))
def test_contains_2():
assert Order(x).contains(Order(y)) is None
assert Order(x).contains(Order(y*x))
assert Order(y*x).contains(Order(x))
assert Order(y).contains(Order(x*y))
assert Order(x).contains(Order(y**2*x))
def test_contains_3():
assert Order(x*y**2).contains(Order(x**2*y)) is None
assert Order(x**2*y).contains(Order(x*y**2)) is None
def test_contains_4():
assert Order(sin(1/x**2)).contains(Order(cos(1/x**2))) is True
assert Order(cos(1/x**2)).contains(Order(sin(1/x**2))) is True
def test_contains():
assert Order(1, x) not in Order(1)
assert Order(1) in Order(1, x)
raises(TypeError, lambda: Order(x*y**2) in Order(x**2*y))
def test_add_1():
assert Order(x + x) == Order(x)
assert Order(3*x - 2*x**2) == Order(x)
assert Order(1 + x) == Order(1, x)
assert Order(1 + 1/x) == Order(1/x)
assert Order(log(x) + 1/log(x)) == Order(log(x))
assert Order(exp(1/x) + x) == Order(exp(1/x))
assert Order(exp(1/x) + 1/x**20) == Order(exp(1/x))
def test_ln_args():
assert O(log(x)) + O(log(2*x)) == O(log(x))
assert O(log(x)) + O(log(x**3)) == O(log(x))
assert O(log(x*y)) + O(log(x) + log(y)) == O(log(x*y))
def test_multivar_0():
assert Order(x*y).expr == x*y
assert Order(x*y**2).expr == x*y**2
assert Order(x*y, x).expr == x
assert Order(x*y**2, y).expr == y**2
assert Order(x*y*z).expr == x*y*z
assert Order(x/y).expr == x/y
assert Order(x*exp(1/y)).expr == x*exp(1/y)
assert Order(exp(x)*exp(1/y)).expr == exp(x)*exp(1/y)
def test_multivar_0a():
assert Order(exp(1/x)*exp(1/y)).expr == exp(1/x)*exp(1/y)
def test_multivar_1():
assert Order(x + y).expr == x + y
assert Order(x + 2*y).expr == x + y
assert (Order(x + y) + x).expr == (x + y)
assert (Order(x + y) + x**2) == Order(x + y)
assert (Order(x + y) + 1/x) == 1/x + Order(x + y)
assert Order(x**2 + y*x).expr == x**2 + y*x
def test_multivar_2():
assert Order(x**2*y + y**2*x, x, y).expr == x**2*y + y**2*x
def test_multivar_mul_1():
assert Order(x + y)*x == Order(x**2 + y*x, x, y)
def test_multivar_3():
assert (Order(x) + Order(y)).args in [
(Order(x), Order(y)),
(Order(y), Order(x))]
assert Order(x) + Order(y) + Order(x + y) == Order(x + y)
assert (Order(x**2*y) + Order(y**2*x)).args in [
(Order(x*y**2), Order(y*x**2)),
(Order(y*x**2), Order(x*y**2))]
assert (Order(x**2*y) + Order(y*x)) == Order(x*y)
def test_issue_3468():
y = Symbol('y', negative=True)
z = Symbol('z', complex=True)
# check that Order does not modify assumptions about symbols
Order(x)
Order(y)
Order(z)
assert x.is_positive is None
assert y.is_positive is False
assert z.is_positive is None
def test_leading_order():
assert (x + 1 + 1/x**5).extract_leading_order(x) == ((1/x**5, O(1/x**5)),)
assert (1 + 1/x).extract_leading_order(x) == ((1/x, O(1/x)),)
assert (1 + x).extract_leading_order(x) == ((1, O(1, x)),)
assert (1 + x**2).extract_leading_order(x) == ((1, O(1, x)),)
assert (2 + x**2).extract_leading_order(x) == ((2, O(1, x)),)
assert (x + x**2).extract_leading_order(x) == ((x, O(x)),)
def test_leading_order2():
assert set((2 + pi + x**2).extract_leading_order(x)) == {(pi, O(1, x)),
(S(2), O(1, x))}
assert set((2*x + pi*x + x**2).extract_leading_order(x)) == {(2*x, O(x)),
(x*pi, O(x))}
def test_order_leadterm():
assert O(x**2)._eval_as_leading_term(x) == O(x**2)
def test_order_symbols():
e = x*y*sin(x)*Integral(x, (x, 1, 2))
assert O(e) == O(x**2*y, x, y)
assert O(e, x) == O(x**2)
def test_nan():
assert O(nan) is nan
assert not O(x).contains(nan)
def test_O1():
assert O(1, x) * x == O(x)
assert O(1, y) * x == O(1, y)
def test_getn():
# other lines are tested incidentally by the suite
assert O(x).getn() == 1
assert O(x/log(x)).getn() == 1
assert O(x**2/log(x)**2).getn() == 2
assert O(x*log(x)).getn() == 1
raises(NotImplementedError, lambda: (O(x) + O(y)).getn())
def test_diff():
assert O(x**2).diff(x) == O(x)
def test_getO():
assert (x).getO() is None
assert (x).removeO() == x
assert (O(x)).getO() == O(x)
assert (O(x)).removeO() == 0
assert (z + O(x) + O(y)).getO() == O(x) + O(y)
assert (z + O(x) + O(y)).removeO() == z
raises(NotImplementedError, lambda: (O(x) + O(y)).getn())
def test_leading_term():
from sympy.functions.special.gamma_functions import digamma
assert O(1/digamma(1/x)) == O(1/log(x))
def test_eval():
assert Order(x).subs(Order(x), 1) == 1
assert Order(x).subs(x, y) == Order(y)
assert Order(x).subs(y, x) == Order(x)
assert Order(x).subs(x, x + y) == Order(x + y, (x, -y))
assert (O(1)**x).is_Pow
def test_issue_4279():
a, b = symbols('a b')
assert O(a, a, b) + O(1, a, b) == O(1, a, b)
assert O(b, a, b) + O(1, a, b) == O(1, a, b)
assert O(a + b, a, b) + O(1, a, b) == O(1, a, b)
assert O(1, a, b) + O(a, a, b) == O(1, a, b)
assert O(1, a, b) + O(b, a, b) == O(1, a, b)
assert O(1, a, b) + O(a + b, a, b) == O(1, a, b)
def test_issue_4855():
assert 1/O(1) != O(1)
assert 1/O(x) != O(1/x)
assert 1/O(x, (x, oo)) != O(1/x, (x, oo))
f = Function('f')
assert 1/O(f(x)) != O(1/x)
def test_order_conjugate_transpose():
x = Symbol('x', real=True)
y = Symbol('y', imaginary=True)
assert conjugate(Order(x)) == Order(conjugate(x))
assert conjugate(Order(y)) == Order(conjugate(y))
assert conjugate(Order(x**2)) == Order(conjugate(x)**2)
assert conjugate(Order(y**2)) == Order(conjugate(y)**2)
assert transpose(Order(x)) == Order(transpose(x))
assert transpose(Order(y)) == Order(transpose(y))
assert transpose(Order(x**2)) == Order(transpose(x)**2)
assert transpose(Order(y**2)) == Order(transpose(y)**2)
def test_order_noncommutative():
A = Symbol('A', commutative=False)
assert Order(A + A*x, x) == Order(1, x)
assert (A + A*x)*Order(x) == Order(x)
assert (A*x)*Order(x) == Order(x**2, x)
assert expand((1 + Order(x))*A*A*x) == A*A*x + Order(x**2, x)
assert expand((A*A + Order(x))*x) == A*A*x + Order(x**2, x)
assert expand((A + Order(x))*A*x) == A*A*x + Order(x**2, x)
def test_issue_6753():
assert (1 + x**2)**10000*O(x) == O(x)
def test_order_at_infinity():
assert Order(1 + x, (x, oo)) == Order(x, (x, oo))
assert Order(3*x, (x, oo)) == Order(x, (x, oo))
assert Order(x, (x, oo))*3 == Order(x, (x, oo))
assert -28*Order(x, (x, oo)) == Order(x, (x, oo))
assert Order(Order(x, (x, oo)), (x, oo)) == Order(x, (x, oo))
assert Order(Order(x, (x, oo)), (y, oo)) == Order(x, (x, oo), (y, oo))
assert Order(3, (x, oo)) == Order(1, (x, oo))
assert Order(x**2 + x + y, (x, oo)) == O(x**2, (x, oo))
assert Order(x**2 + x + y, (y, oo)) == O(y, (y, oo))
assert Order(2*x, (x, oo))*x == Order(x**2, (x, oo))
assert Order(2*x, (x, oo))/x == Order(1, (x, oo))
assert Order(2*x, (x, oo))*x*exp(1/x) == Order(x**2*exp(1/x), (x, oo))
assert Order(2*x, (x, oo))*x*exp(1/x)/log(x)**3 == Order(x**2*exp(1/x)*log(x)**-3, (x, oo))
assert Order(x, (x, oo)) + 1/x == 1/x + Order(x, (x, oo)) == Order(x, (x, oo))
assert Order(x, (x, oo)) + 1 == 1 + Order(x, (x, oo)) == Order(x, (x, oo))
assert Order(x, (x, oo)) + x == x + Order(x, (x, oo)) == Order(x, (x, oo))
assert Order(x, (x, oo)) + x**2 == x**2 + Order(x, (x, oo))
assert Order(1/x, (x, oo)) + 1/x**2 == 1/x**2 + Order(1/x, (x, oo)) == Order(1/x, (x, oo))
assert Order(x, (x, oo)) + exp(1/x) == exp(1/x) + Order(x, (x, oo))
assert Order(x, (x, oo))**2 == Order(x**2, (x, oo))
assert Order(x, (x, oo)) + Order(x**2, (x, oo)) == Order(x**2, (x, oo))
assert Order(x, (x, oo)) + Order(x**-2, (x, oo)) == Order(x, (x, oo))
assert Order(x, (x, oo)) + Order(1/x, (x, oo)) == Order(x, (x, oo))
assert Order(x, (x, oo)) - Order(x, (x, oo)) == Order(x, (x, oo))
assert Order(x, (x, oo)) + Order(1, (x, oo)) == Order(x, (x, oo))
assert Order(x, (x, oo)) + Order(x**2, (x, oo)) == Order(x**2, (x, oo))
assert Order(1/x, (x, oo)) + Order(1, (x, oo)) == Order(1, (x, oo))
assert Order(x, (x, oo)) + Order(exp(1/x), (x, oo)) == Order(x, (x, oo))
assert Order(x**3, (x, oo)) + Order(exp(2/x), (x, oo)) == Order(x**3, (x, oo))
assert Order(x**-3, (x, oo)) + Order(exp(2/x), (x, oo)) == Order(exp(2/x), (x, oo))
# issue 7207
assert Order(exp(x), (x, oo)).expr == Order(2*exp(x), (x, oo)).expr == exp(x)
assert Order(y**x, (x, oo)).expr == Order(2*y**x, (x, oo)).expr == exp(log(y)*x)
# issue 19545
assert Order(1/x - 3/(3*x + 2), (x, oo)).expr == x**(-2)
def test_mixing_order_at_zero_and_infinity():
assert (Order(x, (x, 0)) + Order(x, (x, oo))).is_Add
assert Order(x, (x, 0)) + Order(x, (x, oo)) == Order(x, (x, oo)) + Order(x, (x, 0))
assert Order(Order(x, (x, oo))) == Order(x, (x, oo))
# not supported (yet)
raises(NotImplementedError, lambda: Order(x, (x, 0))*Order(x, (x, oo)))
raises(NotImplementedError, lambda: Order(x, (x, oo))*Order(x, (x, 0)))
raises(NotImplementedError, lambda: Order(Order(x, (x, oo)), y))
raises(NotImplementedError, lambda: Order(Order(x), (x, oo)))
def test_order_at_some_point():
assert Order(x, (x, 1)) == Order(1, (x, 1))
assert Order(2*x - 2, (x, 1)) == Order(x - 1, (x, 1))
assert Order(-x + 1, (x, 1)) == Order(x - 1, (x, 1))
assert Order(x - 1, (x, 1))**2 == Order((x - 1)**2, (x, 1))
assert Order(x - 2, (x, 2)) - O(x - 2, (x, 2)) == Order(x - 2, (x, 2))
def test_order_subs_limits():
# issue 3333
assert (1 + Order(x)).subs(x, 1/x) == 1 + Order(1/x, (x, oo))
assert (1 + Order(x)).limit(x, 0) == 1
# issue 5769
assert ((x + Order(x**2))/x).limit(x, 0) == 1
assert Order(x**2).subs(x, y - 1) == Order((y - 1)**2, (y, 1))
assert Order(10*x**2, (x, 2)).subs(x, y - 1) == Order(1, (y, 3))
def test_issue_9351():
assert exp(x).series(x, 10, 1) == exp(10) + Order(x - 10, (x, 10))
def test_issue_9192():
assert O(1)*O(1) == O(1)
assert O(1)**O(1) == O(1)
def test_issue_9910():
assert O(x*log(x) + sin(x), (x, oo)) == O(x*log(x), (x, oo))
def test_performance_of_adding_order():
l = list(x**i for i in range(1000))
l.append(O(x**1001))
assert Add(*l).subs(x,1) == O(1)
def test_issue_14622():
assert (x**(-4) + x**(-3) + x**(-1) + O(x**(-6), (x, oo))).as_numer_denom() == (
x**4 + x**5 + x**7 + O(x**2, (x, oo)), x**8)
assert (x**3 + O(x**2, (x, oo))).is_Add
assert O(x**2, (x, oo)).contains(x**3) is False
assert O(x, (x, oo)).contains(O(x, (x, 0))) is None
assert O(x, (x, 0)).contains(O(x, (x, oo))) is None
raises(NotImplementedError, lambda: O(x**3).contains(x**w))
def test_issue_15539():
assert O(1/x**2 + 1/x**4, (x, -oo)) == O(1/x**2, (x, -oo))
assert O(1/x**4 + exp(x), (x, -oo)) == O(1/x**4, (x, -oo))
assert O(1/x**4 + exp(-x), (x, -oo)) == O(exp(-x), (x, -oo))
assert O(1/x, (x, oo)).subs(x, -x) == O(-1/x, (x, -oo))
def test_issue_18606():
assert unchanged(Order, 0)
def test_issue_22165():
assert O(log(x)).contains(2)
def test_issue_9917():
assert O(x*sin(x) + 1, (x, oo)) == O(x, (x, oo))
|
67ce4585f5ce395922d0734678ae4110164ea64b81e929ca2b716a7cad7e68b4 | from sympy.series.kauers import finite_diff
from sympy.series.kauers import finite_diff_kauers
from sympy.abc import x, y, z, m, n, w
from sympy.core.numbers import pi
from sympy.functions.elementary.trigonometric import (cos, sin)
from sympy.concrete.summations import Sum
def test_finite_diff():
assert finite_diff(x**2 + 2*x + 1, x) == 2*x + 3
assert finite_diff(y**3 + 2*y**2 + 3*y + 5, y) == 3*y**2 + 7*y + 6
assert finite_diff(z**2 - 2*z + 3, z) == 2*z - 1
assert finite_diff(w**2 + 3*w - 2, w) == 2*w + 4
assert finite_diff(sin(x), x, pi/6) == -sin(x) + sin(x + pi/6)
assert finite_diff(cos(y), y, pi/3) == -cos(y) + cos(y + pi/3)
assert finite_diff(x**2 - 2*x + 3, x, 2) == 4*x
assert finite_diff(n**2 - 2*n + 3, n, 3) == 6*n + 3
def test_finite_diff_kauers():
assert finite_diff_kauers(Sum(x**2, (x, 1, n))) == (n + 1)**2
assert finite_diff_kauers(Sum(y, (y, 1, m))) == (m + 1)
assert finite_diff_kauers(Sum((x*y), (x, 1, m), (y, 1, n))) == (m + 1)*(n + 1)
assert finite_diff_kauers(Sum((x*y**2), (x, 1, m), (y, 1, n))) == (n + 1)**2*(m + 1)
|
f2e6fa8ca37242f21c90a5b2e0f227da934be45bb210b962706f92cc46aaddab | from itertools import product
from sympy.concrete.summations import Sum
from sympy.core.function import (Function, diff)
from sympy.core import EulerGamma
from sympy.core.numbers import (E, I, Rational, oo, pi, zoo)
from sympy.core.singleton import S
from sympy.core.symbol import (Symbol, symbols)
from sympy.functions.combinatorial.factorials import (binomial, factorial, subfactorial)
from sympy.functions.elementary.complexes import (Abs, re, sign)
from sympy.functions.elementary.exponential import (LambertW, exp, log)
from sympy.functions.elementary.hyperbolic import (acoth, atanh, sinh)
from sympy.functions.elementary.integers import (ceiling, floor, frac)
from sympy.functions.elementary.miscellaneous import (cbrt, real_root, sqrt)
from sympy.functions.elementary.trigonometric import (acos, acot, acsc, asec, asin, atan, cos, cot, sec, sin, tan)
from sympy.functions.special.bessel import (besselj, besselk)
from sympy.functions.special.error_functions import (Ei, erf, erfc, erfi, fresnelc, fresnels)
from sympy.functions.special.gamma_functions import (digamma, gamma, uppergamma)
from sympy.integrals.integrals import (Integral, integrate)
from sympy.series.limits import (Limit, limit)
from sympy.simplify.simplify import simplify
from sympy.calculus.util import AccumBounds
from sympy.core.mul import Mul
from sympy.series.limits import heuristics
from sympy.series.order import Order
from sympy.testing.pytest import XFAIL, raises
from sympy.abc import x, y, z, k
n = Symbol('n', integer=True, positive=True)
def test_basic1():
assert limit(x, x, oo) is oo
assert limit(x, x, -oo) is -oo
assert limit(-x, x, oo) is -oo
assert limit(x**2, x, -oo) is oo
assert limit(-x**2, x, oo) is -oo
assert limit(x*log(x), x, 0, dir="+") == 0
assert limit(1/x, x, oo) == 0
assert limit(exp(x), x, oo) is oo
assert limit(-exp(x), x, oo) is -oo
assert limit(exp(x)/x, x, oo) is oo
assert limit(1/x - exp(-x), x, oo) == 0
assert limit(x + 1/x, x, oo) is oo
assert limit(x - x**2, x, oo) is -oo
assert limit((1 + x)**(1 + sqrt(2)), x, 0) == 1
assert limit((1 + x)**oo, x, 0) == Limit((x + 1)**oo, x, 0)
assert limit((1 + x)**oo, x, 0, dir='-') == Limit((x + 1)**oo, x, 0, dir='-')
assert limit((1 + x + y)**oo, x, 0, dir='-') == Limit((1 + x + y)**oo, x, 0, dir='-')
assert limit(y/x/log(x), x, 0) == -oo*sign(y)
assert limit(cos(x + y)/x, x, 0) == sign(cos(y))*oo
assert limit(gamma(1/x + 3), x, oo) == 2
assert limit(S.NaN, x, -oo) is S.NaN
assert limit(Order(2)*x, x, S.NaN) is S.NaN
assert limit(1/(x - 1), x, 1, dir="+") is oo
assert limit(1/(x - 1), x, 1, dir="-") is -oo
assert limit(1/(5 - x)**3, x, 5, dir="+") is -oo
assert limit(1/(5 - x)**3, x, 5, dir="-") is oo
assert limit(1/sin(x), x, pi, dir="+") is -oo
assert limit(1/sin(x), x, pi, dir="-") is oo
assert limit(1/cos(x), x, pi/2, dir="+") is -oo
assert limit(1/cos(x), x, pi/2, dir="-") is oo
assert limit(1/tan(x**3), x, (2*pi)**Rational(1, 3), dir="+") is oo
assert limit(1/tan(x**3), x, (2*pi)**Rational(1, 3), dir="-") is -oo
assert limit(1/cot(x)**3, x, (pi*Rational(3, 2)), dir="+") is -oo
assert limit(1/cot(x)**3, x, (pi*Rational(3, 2)), dir="-") is oo
# test bi-directional limits
assert limit(sin(x)/x, x, 0, dir="+-") == 1
assert limit(x**2, x, 0, dir="+-") == 0
assert limit(1/x**2, x, 0, dir="+-") is oo
# test failing bi-directional limits
assert limit(1/x, x, 0, dir="+-") is zoo
# approaching 0
# from dir="+"
assert limit(1 + 1/x, x, 0) is oo
# from dir='-'
# Add
assert limit(1 + 1/x, x, 0, dir='-') is -oo
# Pow
assert limit(x**(-2), x, 0, dir='-') is oo
assert limit(x**(-3), x, 0, dir='-') is -oo
assert limit(1/sqrt(x), x, 0, dir='-') == (-oo)*I
assert limit(x**2, x, 0, dir='-') == 0
assert limit(sqrt(x), x, 0, dir='-') == 0
assert limit(x**-pi, x, 0, dir='-') == -oo*(-1)**(1 - pi)
assert limit((1 + cos(x))**oo, x, 0) == Limit((cos(x) + 1)**oo, x, 0)
def test_basic2():
assert limit(x**x, x, 0, dir="+") == 1
assert limit((exp(x) - 1)/x, x, 0) == 1
assert limit(1 + 1/x, x, oo) == 1
assert limit(-exp(1/x), x, oo) == -1
assert limit(x + exp(-x), x, oo) is oo
assert limit(x + exp(-x**2), x, oo) is oo
assert limit(x + exp(-exp(x)), x, oo) is oo
assert limit(13 + 1/x - exp(-x), x, oo) == 13
def test_basic3():
assert limit(1/x, x, 0, dir="+") is oo
assert limit(1/x, x, 0, dir="-") is -oo
def test_basic4():
assert limit(2*x + y*x, x, 0) == 0
assert limit(2*x + y*x, x, 1) == 2 + y
assert limit(2*x**8 + y*x**(-3), x, -2) == 512 - y/8
assert limit(sqrt(x + 1) - sqrt(x), x, oo) == 0
assert integrate(1/(x**3 + 1), (x, 0, oo)) == 2*pi*sqrt(3)/9
def test_log():
# https://github.com/sympy/sympy/issues/21598
a, b, c = symbols('a b c', positive=True)
A = log(a/b) - (log(a) - log(b))
assert A.limit(a, oo) == 0
assert (A * c).limit(a, oo) == 0
tau, x = symbols('tau x', positive=True)
# The value of manualintegrate in the issue
expr = tau**2*((tau - 1)*(tau + 1)*log(x + 1)/(tau**2 + 1)**2 + 1/((tau**2\
+ 1)*(x + 1)) - (-2*tau*atan(x/tau) + (tau**2/2 - 1/2)*log(tau**2\
+ x**2))/(tau**2 + 1)**2)
assert limit(expr, x, oo) == pi*tau**3/(tau**2 + 1)**2
def test_piecewise():
# https://github.com/sympy/sympy/issues/18363
assert limit((real_root(x - 6, 3) + 2)/(x + 2), x, -2, '+') == Rational(1, 12)
def test_basic5():
class my(Function):
@classmethod
def eval(cls, arg):
if arg is S.Infinity:
return S.NaN
assert limit(my(x), x, oo) == Limit(my(x), x, oo)
def test_issue_3885():
assert limit(x*y + x*z, z, 2) == x*y + 2*x
def test_Limit():
assert Limit(sin(x)/x, x, 0) != 1
assert Limit(sin(x)/x, x, 0).doit() == 1
assert Limit(x, x, 0, dir='+-').args == (x, x, 0, Symbol('+-'))
def test_floor():
assert limit(floor(x), x, -2, "+") == -2
assert limit(floor(x), x, -2, "-") == -3
assert limit(floor(x), x, -1, "+") == -1
assert limit(floor(x), x, -1, "-") == -2
assert limit(floor(x), x, 0, "+") == 0
assert limit(floor(x), x, 0, "-") == -1
assert limit(floor(x), x, 1, "+") == 1
assert limit(floor(x), x, 1, "-") == 0
assert limit(floor(x), x, 2, "+") == 2
assert limit(floor(x), x, 2, "-") == 1
assert limit(floor(x), x, 248, "+") == 248
assert limit(floor(x), x, 248, "-") == 247
# https://github.com/sympy/sympy/issues/14478
assert limit(x*floor(3/x)/2, x, 0, '+') == Rational(3, 2)
assert limit(floor(x + 1/2) - floor(x), x, oo) == AccumBounds(-S.Half, S(3)/2)
def test_floor_requires_robust_assumptions():
assert limit(floor(sin(x)), x, 0, "+") == 0
assert limit(floor(sin(x)), x, 0, "-") == -1
assert limit(floor(cos(x)), x, 0, "+") == 0
assert limit(floor(cos(x)), x, 0, "-") == 0
assert limit(floor(5 + sin(x)), x, 0, "+") == 5
assert limit(floor(5 + sin(x)), x, 0, "-") == 4
assert limit(floor(5 + cos(x)), x, 0, "+") == 5
assert limit(floor(5 + cos(x)), x, 0, "-") == 5
def test_ceiling():
assert limit(ceiling(x), x, -2, "+") == -1
assert limit(ceiling(x), x, -2, "-") == -2
assert limit(ceiling(x), x, -1, "+") == 0
assert limit(ceiling(x), x, -1, "-") == -1
assert limit(ceiling(x), x, 0, "+") == 1
assert limit(ceiling(x), x, 0, "-") == 0
assert limit(ceiling(x), x, 1, "+") == 2
assert limit(ceiling(x), x, 1, "-") == 1
assert limit(ceiling(x), x, 2, "+") == 3
assert limit(ceiling(x), x, 2, "-") == 2
assert limit(ceiling(x), x, 248, "+") == 249
assert limit(ceiling(x), x, 248, "-") == 248
# https://github.com/sympy/sympy/issues/14478
assert limit(x*ceiling(3/x)/2, x, 0, '+') == Rational(3, 2)
assert limit(ceiling(x + 1/2) - ceiling(x), x, oo) == AccumBounds(-S.Half, S(3)/2)
def test_ceiling_requires_robust_assumptions():
assert limit(ceiling(sin(x)), x, 0, "+") == 1
assert limit(ceiling(sin(x)), x, 0, "-") == 0
assert limit(ceiling(cos(x)), x, 0, "+") == 1
assert limit(ceiling(cos(x)), x, 0, "-") == 1
assert limit(ceiling(5 + sin(x)), x, 0, "+") == 6
assert limit(ceiling(5 + sin(x)), x, 0, "-") == 5
assert limit(ceiling(5 + cos(x)), x, 0, "+") == 6
assert limit(ceiling(5 + cos(x)), x, 0, "-") == 6
def test_atan():
x = Symbol("x", real=True)
assert limit(atan(x)*sin(1/x), x, 0) == 0
assert limit(atan(x) + sqrt(x + 1) - sqrt(x), x, oo) == pi/2
def test_set_signs():
assert limit(abs(x), x, 0) == 0
assert limit(abs(sin(x)), x, 0) == 0
assert limit(abs(cos(x)), x, 0) == 1
assert limit(abs(sin(x + 1)), x, 0) == sin(1)
# https://github.com/sympy/sympy/issues/9449
assert limit((Abs(x + y) - Abs(x - y))/(2*x), x, 0) == sign(y)
# https://github.com/sympy/sympy/issues/12398
assert limit(Abs(log(x)/x**3), x, oo) == 0
assert limit(x*(Abs(log(x)/x**3)/Abs(log(x + 1)/(x + 1)**3) - 1), x, oo) == 3
# https://github.com/sympy/sympy/issues/18501
assert limit(Abs(log(x - 1)**3 - 1), x, 1, '+') == oo
# https://github.com/sympy/sympy/issues/18997
assert limit(Abs(log(x)), x, 0) == oo
assert limit(Abs(log(Abs(x))), x, 0) == oo
# https://github.com/sympy/sympy/issues/19026
z = Symbol('z', positive=True)
assert limit(Abs(log(z) + 1)/log(z), z, oo) == 1
# https://github.com/sympy/sympy/issues/20704
assert limit(z*(Abs(1/z + y) - Abs(y - 1/z))/2, z, 0) == 0
# https://github.com/sympy/sympy/issues/21606
assert limit(cos(z)/sign(z), z, pi, '-') == -1
def test_heuristic():
x = Symbol("x", real=True)
assert heuristics(sin(1/x) + atan(x), x, 0, '+') == AccumBounds(-1, 1)
assert limit(log(2 + sqrt(atan(x))*sqrt(sin(1/x))), x, 0) == log(2)
def test_issue_3871():
z = Symbol("z", positive=True)
f = -1/z*exp(-z*x)
assert limit(f, x, oo) == 0
assert f.limit(x, oo) == 0
def test_exponential():
n = Symbol('n')
x = Symbol('x', real=True)
assert limit((1 + x/n)**n, n, oo) == exp(x)
assert limit((1 + x/(2*n))**n, n, oo) == exp(x/2)
assert limit((1 + x/(2*n + 1))**n, n, oo) == exp(x/2)
assert limit(((x - 1)/(x + 1))**x, x, oo) == exp(-2)
assert limit(1 + (1 + 1/x)**x, x, oo) == 1 + S.Exp1
assert limit((2 + 6*x)**x/(6*x)**x, x, oo) == exp(S('1/3'))
def test_exponential2():
n = Symbol('n')
assert limit((1 + x/(n + sin(n)))**n, n, oo) == exp(x)
def test_doit():
f = Integral(2 * x, x)
l = Limit(f, x, oo)
assert l.doit() is oo
def test_series_AccumBounds():
assert limit(sin(k) - sin(k + 1), k, oo) == AccumBounds(-2, 2)
assert limit(cos(k) - cos(k + 1) + 1, k, oo) == AccumBounds(-1, 3)
# not the exact bound
assert limit(sin(k) - sin(k)*cos(k), k, oo) == AccumBounds(-2, 2)
# test for issue #9934
lo = (-3 + cos(1))/2
hi = (1 + cos(1))/2
t1 = Mul(AccumBounds(lo, hi), 1/(-1 + cos(1)), evaluate=False)
assert limit(simplify(Sum(cos(n).rewrite(exp), (n, 0, k)).doit().rewrite(sin)), k, oo) == t1
t2 = Mul(AccumBounds(-1 + sin(1)/2, sin(1)/2 + 1), 1/(1 - cos(1)))
assert limit(simplify(Sum(sin(n).rewrite(exp), (n, 0, k)).doit().rewrite(sin)), k, oo) == t2
assert limit(frac(x)**x, x, oo) == AccumBounds(0, oo) # wolfram gives (0, 1)
assert limit(((sin(x) + 1)/2)**x, x, oo) == AccumBounds(0, oo) # wolfram says 0
# https://github.com/sympy/sympy/issues/12312
e = 2**(-x)*(sin(x) + 1)**x
assert limit(e, x, oo) == AccumBounds(0, oo)
@XFAIL
def test_doit2():
f = Integral(2 * x, x)
l = Limit(f, x, oo)
# limit() breaks on the contained Integral.
assert l.doit(deep=False) == l
def test_issue_2929():
assert limit((x * exp(x))/(exp(x) - 1), x, -oo) == 0
def test_issue_3792():
assert limit((1 - cos(x))/x**2, x, S.Half) == 4 - 4*cos(S.Half)
assert limit(sin(sin(x + 1) + 1), x, 0) == sin(1 + sin(1))
assert limit(abs(sin(x + 1) + 1), x, 0) == 1 + sin(1)
def test_issue_4090():
assert limit(1/(x + 3), x, 2) == Rational(1, 5)
assert limit(1/(x + pi), x, 2) == S.One/(2 + pi)
assert limit(log(x)/(x**2 + 3), x, 2) == log(2)/7
assert limit(log(x)/(x**2 + pi), x, 2) == log(2)/(4 + pi)
def test_issue_4547():
assert limit(cot(x), x, 0, dir='+') is oo
assert limit(cot(x), x, pi/2, dir='+') == 0
def test_issue_5164():
assert limit(x**0.5, x, oo) == oo**0.5 is oo
assert limit(x**0.5, x, 16) == S(16)**0.5
assert limit(x**0.5, x, 0) == 0
assert limit(x**(-0.5), x, oo) == 0
assert limit(x**(-0.5), x, 4) == S(4)**(-0.5)
def test_issue_5383():
func = (1.0 * 1 + 1.0 * x)**(1.0 * 1 / x)
assert limit(func, x, 0) == E
def test_issue_14793():
expr = ((x + S(1)/2) * log(x) - x + log(2*pi)/2 - \
log(factorial(x)) + S(1)/(12*x))*x**3
assert limit(expr, x, oo) == S(1)/360
def test_issue_5183():
# using list(...) so py.test can recalculate values
tests = list(product([x, -x],
[-1, 1],
[2, 3, S.Half, Rational(2, 3)],
['-', '+']))
results = (oo, oo, -oo, oo, -oo*I, oo, -oo*(-1)**Rational(1, 3), oo,
0, 0, 0, 0, 0, 0, 0, 0,
oo, oo, oo, -oo, oo, -oo*I, oo, -oo*(-1)**Rational(1, 3),
0, 0, 0, 0, 0, 0, 0, 0)
assert len(tests) == len(results)
for i, (args, res) in enumerate(zip(tests, results)):
y, s, e, d = args
eq = y**(s*e)
try:
assert limit(eq, x, 0, dir=d) == res
except AssertionError:
if 0: # change to 1 if you want to see the failing tests
print()
print(i, res, eq, d, limit(eq, x, 0, dir=d))
else:
assert None
def test_issue_5184():
assert limit(sin(x)/x, x, oo) == 0
assert limit(atan(x), x, oo) == pi/2
assert limit(gamma(x), x, oo) is oo
assert limit(cos(x)/x, x, oo) == 0
assert limit(gamma(x), x, S.Half) == sqrt(pi)
r = Symbol('r', real=True)
assert limit(r*sin(1/r), r, 0) == 0
def test_issue_5229():
assert limit((1 + y)**(1/y) - S.Exp1, y, 0) == 0
def test_issue_4546():
# using list(...) so py.test can recalculate values
tests = list(product([cot, tan],
[-pi/2, 0, pi/2, pi, pi*Rational(3, 2)],
['-', '+']))
results = (0, 0, -oo, oo, 0, 0, -oo, oo, 0, 0,
oo, -oo, 0, 0, oo, -oo, 0, 0, oo, -oo)
assert len(tests) == len(results)
for i, (args, res) in enumerate(zip(tests, results)):
f, l, d = args
eq = f(x)
try:
assert limit(eq, x, l, dir=d) == res
except AssertionError:
if 0: # change to 1 if you want to see the failing tests
print()
print(i, res, eq, l, d, limit(eq, x, l, dir=d))
else:
assert None
def test_issue_3934():
assert limit((1 + x**log(3))**(1/x), x, 0) == 1
assert limit((5**(1/x) + 3**(1/x))**x, x, 0) == 5
def test_calculate_series():
# needs gruntz calculate_series to go to n = 32
assert limit(x**Rational(77, 3)/(1 + x**Rational(77, 3)), x, oo) == 1
# needs gruntz calculate_series to go to n = 128
assert limit(x**101.1/(1 + x**101.1), x, oo) == 1
def test_issue_5955():
assert limit((x**16)/(1 + x**16), x, oo) == 1
assert limit((x**100)/(1 + x**100), x, oo) == 1
assert limit((x**1885)/(1 + x**1885), x, oo) == 1
assert limit((x**1000/((x + 1)**1000 + exp(-x))), x, oo) == 1
def test_newissue():
assert limit(exp(1/sin(x))/exp(cot(x)), x, 0) == 1
def test_extended_real_line():
assert limit(x - oo, x, oo) == Limit(x - oo, x, oo)
assert limit(1/(x + sin(x)) - oo, x, 0) == Limit(1/(x + sin(x)) - oo, x, 0)
assert limit(oo/x, x, oo) == Limit(oo/x, x, oo)
assert limit(x - oo + 1/x, x, oo) == Limit(x - oo + 1/x, x, oo)
@XFAIL
def test_order_oo():
x = Symbol('x', positive=True)
assert Order(x)*oo != Order(1, x)
assert limit(oo/(x**2 - 4), x, oo) is oo
def test_issue_5436():
raises(NotImplementedError, lambda: limit(exp(x*y), x, oo))
raises(NotImplementedError, lambda: limit(exp(-x*y), x, oo))
def test_Limit_dir():
raises(TypeError, lambda: Limit(x, x, 0, dir=0))
raises(ValueError, lambda: Limit(x, x, 0, dir='0'))
def test_polynomial():
assert limit((x + 1)**1000/((x + 1)**1000 + 1), x, oo) == 1
assert limit((x + 1)**1000/((x + 1)**1000 + 1), x, -oo) == 1
def test_rational():
assert limit(1/y - (1/(y + x) + x/(y + x)/y)/z, x, oo) == (z - 1)/(y*z)
assert limit(1/y - (1/(y + x) + x/(y + x)/y)/z, x, -oo) == (z - 1)/(y*z)
def test_issue_5740():
assert limit(log(x)*z - log(2*x)*y, x, 0) == oo*sign(y - z)
def test_issue_6366():
n = Symbol('n', integer=True, positive=True)
r = (n + 1)*x**(n + 1)/(x**(n + 1) - 1) - x/(x - 1)
assert limit(r, x, 1).cancel() == n/2
def test_factorial():
f = factorial(x)
assert limit(f, x, oo) is oo
assert limit(x/f, x, oo) == 0
# see Stirling's approximation:
# https://en.wikipedia.org/wiki/Stirling's_approximation
assert limit(f/(sqrt(2*pi*x)*(x/E)**x), x, oo) == 1
assert limit(f, x, -oo) == factorial(-oo)
def test_issue_6560():
e = (5*x**3/4 - x*Rational(3, 4) + (y*(3*x**2/2 - S.Half) +
35*x**4/8 - 15*x**2/4 + Rational(3, 8))/(2*(y + 1)))
assert limit(e, y, oo) == 5*x**3/4 + 3*x**2/4 - 3*x/4 - Rational(1, 4)
@XFAIL
def test_issue_5172():
n = Symbol('n')
r = Symbol('r', positive=True)
c = Symbol('c')
p = Symbol('p', positive=True)
m = Symbol('m', negative=True)
expr = ((2*n*(n - r + 1)/(n + r*(n - r + 1)))**c +
(r - 1)*(n*(n - r + 2)/(n + r*(n - r + 1)))**c - n)/(n**c - n)
expr = expr.subs(c, c + 1)
raises(NotImplementedError, lambda: limit(expr, n, oo))
assert limit(expr.subs(c, m), n, oo) == 1
assert limit(expr.subs(c, p), n, oo).simplify() == \
(2**(p + 1) + r - 1)/(r + 1)**(p + 1)
def test_issue_7088():
a = Symbol('a')
assert limit(sqrt(x/(x + a)), x, oo) == 1
def test_branch_cuts():
assert limit(asin(I*x + 2), x, 0) == pi - asin(2)
assert limit(asin(I*x + 2), x, 0, '-') == asin(2)
assert limit(asin(I*x - 2), x, 0) == -asin(2)
assert limit(asin(I*x - 2), x, 0, '-') == -pi + asin(2)
assert limit(acos(I*x + 2), x, 0) == -acos(2)
assert limit(acos(I*x + 2), x, 0, '-') == acos(2)
assert limit(acos(I*x - 2), x, 0) == acos(-2)
assert limit(acos(I*x - 2), x, 0, '-') == 2*pi - acos(-2)
assert limit(atan(x + 2*I), x, 0) == I*atanh(2)
assert limit(atan(x + 2*I), x, 0, '-') == -pi + I*atanh(2)
assert limit(atan(x - 2*I), x, 0) == pi - I*atanh(2)
assert limit(atan(x - 2*I), x, 0, '-') == -I*atanh(2)
assert limit(atan(1/x), x, 0) == pi/2
assert limit(atan(1/x), x, 0, '-') == -pi/2
assert limit(atan(x), x, oo) == pi/2
assert limit(atan(x), x, -oo) == -pi/2
assert limit(acot(x + S(1)/2*I), x, 0) == pi - I*acoth(S(1)/2)
assert limit(acot(x + S(1)/2*I), x, 0, '-') == -I*acoth(S(1)/2)
assert limit(acot(x - S(1)/2*I), x, 0) == I*acoth(S(1)/2)
assert limit(acot(x - S(1)/2*I), x, 0, '-') == -pi + I*acoth(S(1)/2)
assert limit(acot(x), x, 0) == pi/2
assert limit(acot(x), x, 0, '-') == -pi/2
assert limit(asec(I*x + S(1)/2), x, 0) == asec(S(1)/2)
assert limit(asec(I*x + S(1)/2), x, 0, '-') == -asec(S(1)/2)
assert limit(asec(I*x - S(1)/2), x, 0) == 2*pi - asec(-S(1)/2)
assert limit(asec(I*x - S(1)/2), x, 0, '-') == asec(-S(1)/2)
assert limit(acsc(I*x + S(1)/2), x, 0) == acsc(S(1)/2)
assert limit(acsc(I*x + S(1)/2), x, 0, '-') == pi - acsc(S(1)/2)
assert limit(acsc(I*x - S(1)/2), x, 0) == -pi + acsc(S(1)/2)
assert limit(acsc(I*x - S(1)/2), x, 0, '-') == -acsc(S(1)/2)
assert limit(log(I*x - 1), x, 0) == I*pi
assert limit(log(I*x - 1), x, 0, '-') == -I*pi
assert limit(log(-I*x - 1), x, 0) == -I*pi
assert limit(log(-I*x - 1), x, 0, '-') == I*pi
assert limit(sqrt(I*x - 1), x, 0) == I
assert limit(sqrt(I*x - 1), x, 0, '-') == -I
assert limit(sqrt(-I*x - 1), x, 0) == -I
assert limit(sqrt(-I*x - 1), x, 0, '-') == I
assert limit(cbrt(I*x - 1), x, 0) == (-1)**(S(1)/3)
assert limit(cbrt(I*x - 1), x, 0, '-') == -(-1)**(S(2)/3)
assert limit(cbrt(-I*x - 1), x, 0) == -(-1)**(S(2)/3)
assert limit(cbrt(-I*x - 1), x, 0, '-') == (-1)**(S(1)/3)
def test_issue_6364():
a = Symbol('a')
e = z/(1 - sqrt(1 + z)*sin(a)**2 - sqrt(1 - z)*cos(a)**2)
assert limit(e, z, 0) == 1/(cos(a)**2 - S.Half)
def test_issue_4099():
a = Symbol('a')
assert limit(a/x, x, 0) == oo*sign(a)
assert limit(-a/x, x, 0) == -oo*sign(a)
assert limit(-a*x, x, oo) == -oo*sign(a)
assert limit(a*x, x, oo) == oo*sign(a)
def test_issue_4503():
dx = Symbol('dx')
assert limit((sqrt(1 + exp(x + dx)) - sqrt(1 + exp(x)))/dx, dx, 0) == \
exp(x)/(2*sqrt(exp(x) + 1))
def test_issue_8208():
assert limit(n**(Rational(1, 1e9) - 1), n, oo) == 0
def test_issue_8229():
assert limit((x**Rational(1, 4) - 2)/(sqrt(x) - 4)**Rational(2, 3), x, 16) == 0
def test_issue_8433():
d, t = symbols('d t', positive=True)
assert limit(erf(1 - t/d), t, oo) == -1
def test_issue_8481():
k = Symbol('k', integer=True, nonnegative=True)
lamda = Symbol('lamda', real=True, positive=True)
limit(lamda**k * exp(-lamda) / factorial(k), k, oo) == 0
def test_issue_8635_18176():
x = Symbol('x', real=True)
k = Symbol('k', positive=True)
assert limit(x**n - x**(n - 0), x, oo) == 0
assert limit(x**n - x**(n - 5), x, oo) == oo
assert limit(x**n - x**(n - 2.5), x, oo) == oo
assert limit(x**n - x**(n - k - 1), x, oo) == oo
x = Symbol('x', positive=True)
assert limit(x**n - x**(n - 1), x, oo) == oo
assert limit(x**n - x**(n + 2), x, oo) == -oo
def test_issue_8730():
assert limit(subfactorial(x), x, oo) is oo
def test_issue_9252():
n = Symbol('n', integer=True)
c = Symbol('c', positive=True)
assert limit((log(n))**(n/log(n)) / (1 + c)**n, n, oo) == 0
# limit should depend on the value of c
raises(NotImplementedError, lambda: limit((log(n))**(n/log(n)) / c**n, n, oo))
def test_issue_9558():
assert limit(sin(x)**15, x, 0, '-') == 0
def test_issue_10801():
# make sure limits work with binomial
assert limit(16**k / (k * binomial(2*k, k)**2), k, oo) == pi
def test_issue_10976():
s, x = symbols('s x', real=True)
assert limit(erf(s*x)/erf(s), s, 0) == x
def test_issue_9041():
assert limit(factorial(n) / ((n/exp(1))**n * sqrt(2*pi*n)), n, oo) == 1
def test_issue_9205():
x, y, a = symbols('x, y, a')
assert Limit(x, x, a).free_symbols == {a}
assert Limit(x, x, a, '-').free_symbols == {a}
assert Limit(x + y, x + y, a).free_symbols == {a}
assert Limit(-x**2 + y, x**2, a).free_symbols == {y, a}
def test_issue_9471():
assert limit(((27**(log(n,3)))/n**3),n,oo) == 1
assert limit(((27**(log(n,3)+1))/n**3),n,oo) == 27
def test_issue_11496():
assert limit(erfc(log(1/x)), x, oo) == 2
def test_issue_11879():
assert simplify(limit(((x+y)**n-x**n)/y, y, 0)) == n*x**(n-1)
def test_limit_with_Float():
k = symbols("k")
assert limit(1.0 ** k, k, oo) == 1
assert limit(0.3*1.0**k, k, oo) == Rational(3, 10)
def test_issue_10610():
assert limit(3**x*3**(-x - 1)*(x + 1)**2/x**2, x, oo) == Rational(1, 3)
def test_issue_6599():
assert limit((n + cos(n))/n, n, oo) == 1
def test_issue_12555():
assert limit((3**x + 2* x**10) / (x**10 + exp(x)), x, -oo) == 2
assert limit((3**x + 2* x**10) / (x**10 + exp(x)), x, oo) is oo
def test_issue_12769():
r, z, x = symbols('r z x', real=True)
a, b, s0, K, F0, s, T = symbols('a b s0 K F0 s T', positive=True, real=True)
fx = (F0**b*K**b*r*s0 - sqrt((F0**2*K**(2*b)*a**2*(b - 1) + \
F0**(2*b)*K**2*a**2*(b - 1) + F0**(2*b)*K**(2*b)*s0**2*(b - 1)*(b**2 - 2*b + 1) - \
2*F0**(2*b)*K**(b + 1)*a*r*s0*(b**2 - 2*b + 1) + \
2*F0**(b + 1)*K**(2*b)*a*r*s0*(b**2 - 2*b + 1) - \
2*F0**(b + 1)*K**(b + 1)*a**2*(b - 1))/((b - 1)*(b**2 - 2*b + 1))))*(b*r - b - r + 1)
assert fx.subs(K, F0).factor(deep=True) == limit(fx, K, F0).factor(deep=True)
def test_issue_13332():
assert limit(sqrt(30)*5**(-5*x - 1)*(46656*x)**x*(5*x + 2)**(5*x + 5*S.Half) *
(6*x + 2)**(-6*x - 5*S.Half), x, oo) == Rational(25, 36)
def test_issue_12564():
assert limit(x**2 + x*sin(x) + cos(x), x, -oo) is oo
assert limit(x**2 + x*sin(x) + cos(x), x, oo) is oo
assert limit(((x + cos(x))**2).expand(), x, oo) is oo
assert limit(((x + sin(x))**2).expand(), x, oo) is oo
assert limit(((x + cos(x))**2).expand(), x, -oo) is oo
assert limit(((x + sin(x))**2).expand(), x, -oo) is oo
def test_issue_14456():
raises(NotImplementedError, lambda: Limit(exp(x), x, zoo).doit())
raises(NotImplementedError, lambda: Limit(x**2/(x+1), x, zoo).doit())
def test_issue_14411():
assert limit(3*sec(4*pi*x - x/3), x, 3*pi/(24*pi - 2)) is -oo
def test_issue_13382():
assert limit(x*(((x + 1)**2 + 1)/(x**2 + 1) - 1), x, oo) == 2
def test_issue_13403():
assert limit(x*(-1 + (x + log(x + 1) + 1)/(x + log(x))), x, oo) == 1
def test_issue_13416():
assert limit((-x**3*log(x)**3 + (x - 1)*(x + 1)**2*log(x + 1)**3)/(x**2*log(x)**3), x, oo) == 1
def test_issue_13462():
assert limit(n**2*(2*n*(-(1 - 1/(2*n))**x + 1) - x - (-x**2/4 + x/4)/n), n, oo) == x**3/24 - x**2/8 + x/12
def test_issue_13750():
a = Symbol('a')
assert limit(erf(a - x), x, oo) == -1
assert limit(erf(sqrt(x) - x), x, oo) == -1
def test_issue_14514():
assert limit((1/(log(x)**log(x)))**(1/x), x, oo) == 1
def test_issue_14574():
assert limit(sqrt(x)*cos(x - x**2) / (x + 1), x, oo) == 0
def test_issue_10102():
assert limit(fresnels(x), x, oo) == S.Half
assert limit(3 + fresnels(x), x, oo) == 3 + S.Half
assert limit(5*fresnels(x), x, oo) == Rational(5, 2)
assert limit(fresnelc(x), x, oo) == S.Half
assert limit(fresnels(x), x, -oo) == Rational(-1, 2)
assert limit(4*fresnelc(x), x, -oo) == -2
def test_issue_14377():
raises(NotImplementedError, lambda: limit(exp(I*x)*sin(pi*x), x, oo))
def test_issue_15146():
e = (x/2) * (-2*x**3 - 2*(x**3 - 1) * x**2 * digamma(x**3 + 1) + \
2*(x**3 - 1) * x**2 * digamma(x**3 + x + 1) + x + 3)
assert limit(e, x, oo) == S(1)/3
def test_issue_15202():
e = (2**x*(2 + 2**(-x)*(-2*2**x + x + 2))/(x + 1))**(x + 1)
assert limit(e, x, oo) == exp(1)
e = (log(x, 2)**7 + 10*x*factorial(x) + 5**x) / (factorial(x + 1) + 3*factorial(x) + 10**x)
assert limit(e, x, oo) == 10
def test_issue_15282():
assert limit((x**2000 - (x + 1)**2000) / x**1999, x, oo) == -2000
def test_issue_15984():
assert limit((-x + log(exp(x) + 1))/x, x, oo, dir='-') == 0
def test_issue_13571():
assert limit(uppergamma(x, 1) / gamma(x), x, oo) == 1
def test_issue_13575():
assert limit(acos(erfi(x)), x, 1) == acos(erfi(S.One))
def test_issue_17325():
assert Limit(sin(x)/x, x, 0, dir="+-").doit() == 1
assert Limit(x**2, x, 0, dir="+-").doit() == 0
assert Limit(1/x**2, x, 0, dir="+-").doit() is oo
assert Limit(1/x, x, 0, dir="+-").doit() is zoo
def test_issue_10978():
assert LambertW(x).limit(x, 0) == 0
def test_issue_14313_comment():
assert limit(floor(n/2), n, oo) is oo
@XFAIL
def test_issue_15323():
d = ((1 - 1/x)**x).diff(x)
assert limit(d, x, 1, dir='+') == 1
def test_issue_12571():
assert limit(-LambertW(-log(x))/log(x), x, 1) == 1
def test_issue_14590():
assert limit((x**3*((x + 1)/x)**x)/((x + 1)*(x + 2)*(x + 3)), x, oo) == exp(1)
def test_issue_14393():
a, b = symbols('a b')
assert limit((x**b - y**b)/(x**a - y**a), x, y) == b*y**(-a + b)/a
def test_issue_14556():
assert limit(factorial(n + 1)**(1/(n + 1)) - factorial(n)**(1/n), n, oo) == exp(-1)
def test_issue_14811():
assert limit(((1 + ((S(2)/3)**(x + 1)))**(2**x))/(2**((S(4)/3)**(x - 1))), x, oo) == oo
def test_issue_14874():
assert limit(besselk(0, x), x, oo) == 0
def test_issue_16222():
assert limit(exp(x), x, 1000000000) == exp(1000000000)
def test_issue_16714():
assert limit(((x**(x + 1) + (x + 1)**x) / x**(x + 1))**x, x, oo) == exp(exp(1))
def test_issue_16722():
z = symbols('z', positive=True)
assert limit(binomial(n + z, n)*n**-z, n, oo) == 1/gamma(z + 1)
z = symbols('z', positive=True, integer=True)
assert limit(binomial(n + z, n)*n**-z, n, oo) == 1/gamma(z + 1)
def test_issue_17431():
assert limit(((n + 1) + 1) / (((n + 1) + 2) * factorial(n + 1)) *
(n + 2) * factorial(n) / (n + 1), n, oo) == 0
assert limit((n + 2)**2*factorial(n)/((n + 1)*(n + 3)*factorial(n + 1))
, n, oo) == 0
assert limit((n + 1) * factorial(n) / (n * factorial(n + 1)), n, oo) == 0
def test_issue_17671():
assert limit(Ei(-log(x)) - log(log(x))/x, x, 1) == EulerGamma
def test_issue_17751():
a, b, c, x = symbols('a b c x', positive=True)
assert limit((a + 1)*x - sqrt((a + 1)**2*x**2 + b*x + c), x, oo) == -b/(2*a + 2)
def test_issue_17792():
assert limit(factorial(n)/sqrt(n)*(exp(1)/n)**n, n, oo) == sqrt(2)*sqrt(pi)
def test_issue_18118():
assert limit(sign(sin(x)), x, 0, "-") == -1
assert limit(sign(sin(x)), x, 0, "+") == 1
def test_issue_18306():
assert limit(sin(sqrt(x))/sqrt(sin(x)), x, 0, '+') == 1
def test_issue_18378():
assert limit(log(exp(3*x) + x)/log(exp(x) + x**100), x, oo) == 3
def test_issue_18399():
assert limit((1 - S(1)/2*x)**(3*x), x, oo) is zoo
assert limit((-x)**x, x, oo) is zoo
def test_issue_18442():
assert limit(tan(x)**(2**(sqrt(pi))), x, oo, dir='-') == Limit(tan(x)**(2**(sqrt(pi))), x, oo, dir='-')
def test_issue_18452():
assert limit(abs(log(x))**x, x, 0) == 1
assert limit(abs(log(x))**x, x, 0, "-") == 1
def test_issue_18482():
assert limit((2*exp(3*x)/(exp(2*x) + 1))**(1/x), x, oo) == exp(1)
def test_issue_18508():
assert limit(sin(x)/sqrt(1-cos(x)), x, 0) == sqrt(2)
assert limit(sin(x)/sqrt(1-cos(x)), x, 0, dir='+') == sqrt(2)
assert limit(sin(x)/sqrt(1-cos(x)), x, 0, dir='-') == -sqrt(2)
def test_issue_18521():
raises(NotImplementedError, lambda: limit(exp((2 - n) * x), x, oo))
def test_issue_18969():
a, b = symbols('a b', positive=True)
assert limit(LambertW(a), a, b) == LambertW(b)
assert limit(exp(LambertW(a)), a, b) == exp(LambertW(b))
def test_issue_18992():
assert limit(n/(factorial(n)**(1/n)), n, oo) == exp(1)
def test_issue_19067():
x = Symbol('x')
assert limit(gamma(x)/(gamma(x - 1)*gamma(x + 2)), x, 0) == -1
def test_issue_19586():
assert limit(x**(2**x*3**(-x)), x, oo) == 1
def test_issue_13715():
n = Symbol('n')
p = Symbol('p', zero=True)
assert limit(n + p, n, 0) == 0
def test_issue_15055():
assert limit(n**3*((-n - 1)*sin(1/n) + (n + 2)*sin(1/(n + 1)))/(-n + 1), n, oo) == 1
def test_issue_16708():
m, vi = symbols('m vi', positive=True)
B, ti, d = symbols('B ti d')
assert limit((B*ti*vi - sqrt(m)*sqrt(-2*B*d*vi + m*(vi)**2) + m*vi)/(B*vi), B, 0) == (d + ti*vi)/vi
def test_issue_19453():
beta = Symbol("beta", real=True, positive=True)
h = Symbol("h", real=True, positive=True)
m = Symbol("m", real=True, positive=True)
w = Symbol("omega", real=True, positive=True)
g = Symbol("g", real=True, positive=True)
e = exp(1)
q = 3*h**2*beta*g*e**(0.5*h*beta*w)
p = m**2*w**2
s = e**(h*beta*w) - 1
Z = -q/(4*p*s) - q/(2*p*s**2) - q*(e**(h*beta*w) + 1)/(2*p*s**3)\
+ e**(0.5*h*beta*w)/s
E = -diff(log(Z), beta)
assert limit(E - 0.5*h*w, beta, oo) == 0
assert limit(E.simplify() - 0.5*h*w, beta, oo) == 0
def test_issue_19739():
assert limit((-S(1)/4)**x, x, oo) == 0
def test_issue_19766():
assert limit(2**(-x)*sqrt(4**(x + 1) + 1), x, oo) == 2
def test_issue_19770():
m = Symbol('m')
# the result is not 0 for non-real m
assert limit(cos(m*x)/x, x, oo) == Limit(cos(m*x)/x, x, oo, dir='-')
m = Symbol('m', real=True)
# can be improved to give the correct result 0
assert limit(cos(m*x)/x, x, oo) == Limit(cos(m*x)/x, x, oo, dir='-')
m = Symbol('m', nonzero=True)
assert limit(cos(m*x), x, oo) == AccumBounds(-1, 1)
assert limit(cos(m*x)/x, x, oo) == 0
def test_issue_7535():
assert limit(tan(x)/sin(tan(x)), x, pi/2) == Limit(tan(x)/sin(tan(x)), x, pi/2, dir='+')
assert limit(tan(x)/sin(tan(x)), x, pi/2, dir='-') == Limit(tan(x)/sin(tan(x)), x, pi/2, dir='-')
assert limit(tan(x)/sin(tan(x)), x, pi/2, dir='+-') == Limit(tan(x)/sin(tan(x)), x, pi/2, dir='+-')
assert limit(sin(tan(x)),x,pi/2) == AccumBounds(-1, 1)
assert -oo*(1/sin(-oo)) == AccumBounds(-oo, oo)
assert oo*(1/sin(oo)) == AccumBounds(-oo, oo)
assert oo*(1/sin(-oo)) == AccumBounds(-oo, oo)
assert -oo*(1/sin(oo)) == AccumBounds(-oo, oo)
def test_issue_20365():
assert limit(((x + 1)**(1/x) - E)/x, x, 0) == -E/2
def test_issue_21031():
assert limit(((1 + x)**(1/x) - (1 + 2*x)**(1/(2*x)))/asin(x), x, 0) == E/2
def test_issue_21038():
assert limit(sin(pi*x)/(3*x - 12), x, 4) == pi/3
def test_issue_20578():
expr = abs(x) * sin(1/x)
assert limit(expr,x,0,'+') == 0
assert limit(expr,x,0,'-') == 0
assert limit(expr,x,0,'+-') == 0
def test_issue_21415():
exp = (x-1)*cos(1/(x-1))
assert exp.limit(x,1) == 0
assert exp.expand().limit(x,1) == 0
def test_issue_21530():
assert limit(sinh(n + 1)/sinh(n), n, oo) == E
def test_issue_21550():
r = (sqrt(5) - 1)/2
assert limit((x - r)/(x**2 + x - 1), x, r) == sqrt(5)/5
def test_issue_21661():
out = limit((x**(x + 1) * (log(x) + 1) + 1) / x, x, 11)
assert out == S(3138428376722)/11 + 285311670611*log(11)
def test_issue_21701():
assert limit((besselj(z, x)/x**z).subs(z, 7), x, 0) == S(1)/645120
def test_issue_21721():
a = Symbol('a', real=True)
I = integrate(1/(pi*(1 + (x - a)**2)), x)
assert I.limit(x, oo) == S.Half
def test_issue_21756():
term = (1 - exp(-2*I*pi*z))/(1 - exp(-2*I*pi*z/5))
assert term.limit(z, 0) == 5
assert re(term).limit(z, 0) == 5
def test_issue_21785():
a = Symbol('a')
assert sqrt((-a**2 + x**2)/(1 - x**2)).limit(a, 1, '-') == I
def test_issue_22181():
assert limit((-1)**x * 2**(-x), x, oo) == 0
|
2db956e210435618a05fd62f35cfc716f326f2724c493013f4f7142b7a7ef475 | from sympy.core.function import PoleError
from sympy.core.numbers import oo
from sympy.core.singleton import S
from sympy.core.symbol import Symbol
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.trigonometric import (cos, sin)
from sympy.series.order import O
from sympy.abc import x
from sympy.testing.pytest import raises
def test_simple():
# Gruntz' theses pp. 91 to 96
# 6.6
e = sin(1/x + exp(-x)) - sin(1/x)
assert e.aseries(x) == (1/(24*x**4) - 1/(2*x**2) + 1 + O(x**(-6), (x, oo)))*exp(-x)
e = exp(x) * (exp(1/x + exp(-x)) - exp(1/x))
assert e.aseries(x, n=4) == 1/(6*x**3) + 1/(2*x**2) + 1/x + 1 + O(x**(-4), (x, oo))
e = exp(exp(x) / (1 - 1/x))
assert e.aseries(x) == exp(exp(x) / (1 - 1/x))
# The implementation of bound in aseries is incorrect currently. This test
# should be commented out when that is fixed.
# assert e.aseries(x, bound=3) == exp(exp(x) / x**2)*exp(exp(x) / x)*exp(-exp(x) + exp(x)/(1 - 1/x) - \
# exp(x) / x - exp(x) / x**2) * exp(exp(x))
e = exp(sin(1/x + exp(-exp(x)))) - exp(sin(1/x))
assert e.aseries(x, n=4) == (-1/(2*x**3) + 1/x + 1 + O(x**(-4), (x, oo)))*exp(-exp(x))
e3 = lambda x:exp(exp(exp(x)))
e = e3(x)/e3(x - 1/e3(x))
assert e.aseries(x, n=3) == 1 + exp(x + exp(x))*exp(-exp(exp(x)))\
+ ((-exp(x)/2 - S.Half)*exp(x + exp(x))\
+ exp(2*x + 2*exp(x))/2)*exp(-2*exp(exp(x))) + O(exp(-3*exp(exp(x))), (x, oo))
e = exp(exp(x)) * (exp(sin(1/x + 1/exp(exp(x)))) - exp(sin(1/x)))
assert e.aseries(x, n=4) == -1/(2*x**3) + 1/x + 1 + O(x**(-4), (x, oo))
n = Symbol('n', integer=True)
e = (sqrt(n)*log(n)**2*exp(sqrt(log(n))*log(log(n))**2*exp(sqrt(log(log(n)))*log(log(log(n)))**3)))/n
assert e.aseries(n) == \
exp(exp(sqrt(log(log(n)))*log(log(log(n)))**3)*sqrt(log(n))*log(log(n))**2)*log(n)**2/sqrt(n)
def test_hierarchical():
e = sin(1/x + exp(-x))
assert e.aseries(x, n=3, hir=True) == -exp(-2*x)*sin(1/x)/2 + \
exp(-x)*cos(1/x) + sin(1/x) + O(exp(-3*x), (x, oo))
e = sin(x) * cos(exp(-x))
assert e.aseries(x, hir=True) == exp(-4*x)*sin(x)/24 - \
exp(-2*x)*sin(x)/2 + sin(x) + O(exp(-6*x), (x, oo))
raises(PoleError, lambda: e.aseries(x))
|
f72090e5bcfc17b1b15120af72811f2da1ca9e3cf10b5bb205f85d95e2b0f147 | from sympy.core.function import Function
from sympy.core.numbers import (I, Rational, pi)
from sympy.core.singleton import S
from sympy.core.symbol import Symbol
from sympy.functions.combinatorial.factorials import factorial
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.hyperbolic import tanh
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.trigonometric import (cot, sin, tan)
from sympy.series.residues import residue
from sympy.testing.pytest import XFAIL, raises
from sympy.abc import x, z, a, s
def test_basic1():
assert residue(1/x, x, 0) == 1
assert residue(-2/x, x, 0) == -2
assert residue(81/x, x, 0) == 81
assert residue(1/x**2, x, 0) == 0
assert residue(0, x, 0) == 0
assert residue(5, x, 0) == 0
assert residue(x, x, 0) == 0
assert residue(x**2, x, 0) == 0
def test_basic2():
assert residue(1/x, x, 1) == 0
assert residue(-2/x, x, 1) == 0
assert residue(81/x, x, -1) == 0
assert residue(1/x**2, x, 1) == 0
assert residue(0, x, 1) == 0
assert residue(5, x, 1) == 0
assert residue(x, x, 1) == 0
assert residue(x**2, x, 5) == 0
def test_f():
f = Function("f")
assert residue(f(x)/x**5, x, 0) == f(x).diff(x, 4).subs(x, 0)/24
def test_functions():
assert residue(1/sin(x), x, 0) == 1
assert residue(2/sin(x), x, 0) == 2
assert residue(1/sin(x)**2, x, 0) == 0
assert residue(1/sin(x)**5, x, 0) == Rational(3, 8)
def test_expressions():
assert residue(1/(x + 1), x, 0) == 0
assert residue(1/(x + 1), x, -1) == 1
assert residue(1/(x**2 + 1), x, -1) == 0
assert residue(1/(x**2 + 1), x, I) == -I/2
assert residue(1/(x**2 + 1), x, -I) == I/2
assert residue(1/(x**4 + 1), x, 0) == 0
assert residue(1/(x**4 + 1), x, exp(I*pi/4)).equals(-(Rational(1, 4) + I/4)/sqrt(2))
assert residue(1/(x**2 + a**2)**2, x, a*I) == -I/4/a**3
@XFAIL
def test_expressions_failing():
n = Symbol('n', integer=True, positive=True)
assert residue(exp(z)/(z - pi*I/4*a)**n, z, I*pi*a) == \
exp(I*pi*a/4)/factorial(n - 1)
def test_NotImplemented():
raises(NotImplementedError, lambda: residue(exp(1/z), z, 0))
def test_bug():
assert residue(2**(z)*(s + z)*(1 - s - z)/z**2, z, 0) == \
1 + s*log(2) - s**2*log(2) - 2*s
def test_issue_5654():
assert residue(1/(x**2 + a**2)**2, x, a*I) == -I/(4*a**3)
def test_issue_6499():
assert residue(1/(exp(z) - 1), z, 0) == 1
def test_issue_14037():
assert residue(sin(x**50)/x**51, x, 0) == 1
def test_issue_21176():
f = x**2*cot(pi*x)/(x**4 + 1)
assert residue(f, x, -sqrt(2)/2 - sqrt(2)*I/2).cancel().together(deep=True)\
== sqrt(2)*(1 - I)/(8*tan(sqrt(2)*pi*(1 + I)/2))
def test_issue_21177():
r = -sqrt(3)*tanh(sqrt(3)*pi/2)/3
a = residue(cot(pi*x)/((x - 1)*(x - 2) + 1), x, S(3)/2 - sqrt(3)*I/2)
b = residue(cot(pi*x)/(x**2 - 3*x + 3), x, S(3)/2 - sqrt(3)*I/2)
assert a == r
assert (b - a).cancel() == 0
|
67f69c188398f59b6a0a7e938e29b8bfb059318a457df4afc312935b48e0d599 | from sympy.core.function import (Derivative, PoleError)
from sympy.core.numbers import (E, I, Integer, Rational, pi)
from sympy.core.singleton import S
from sympy.core.symbol import (Symbol, symbols)
from sympy.functions.elementary.complexes import sign
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.hyperbolic import (acosh, acoth, asinh, atanh, cosh, coth, sinh, tanh)
from sympy.functions.elementary.integers import (ceiling, floor)
from sympy.functions.elementary.miscellaneous import (cbrt, sqrt)
from sympy.functions.elementary.trigonometric import (asin, cos, cot, sin, tan)
from sympy.series.limits import limit
from sympy.series.order import O
from sympy.abc import x, y, z
from sympy.testing.pytest import raises, XFAIL
def test_simple_1():
assert x.nseries(x, n=5) == x
assert y.nseries(x, n=5) == y
assert (1/(x*y)).nseries(y, n=5) == 1/(x*y)
assert Rational(3, 4).nseries(x, n=5) == Rational(3, 4)
assert x.nseries() == x
def test_mul_0():
assert (x*log(x)).nseries(x, n=5) == x*log(x)
def test_mul_1():
assert (x*log(2 + x)).nseries(x, n=5) == x*log(2) + x**2/2 - x**3/8 + \
x**4/24 + O(x**5)
assert (x*log(1 + x)).nseries(
x, n=5) == x**2 - x**3/2 + x**4/3 + O(x**5)
def test_pow_0():
assert (x**2).nseries(x, n=5) == x**2
assert (1/x).nseries(x, n=5) == 1/x
assert (1/x**2).nseries(x, n=5) == 1/x**2
assert (x**Rational(2, 3)).nseries(x, n=5) == (x**Rational(2, 3))
assert (sqrt(x)**3).nseries(x, n=5) == (sqrt(x)**3)
def test_pow_1():
assert ((1 + x)**2).nseries(x, n=5) == x**2 + 2*x + 1
# https://github.com/sympy/sympy/issues/21075
assert ((sqrt(x) + 1)**2).nseries(x) == 2*sqrt(x) + x + 1
assert ((sqrt(x) + cbrt(x))**2).nseries(x) == 2*x**Rational(5, 6)\
+ x**Rational(2, 3) + x
def test_geometric_1():
assert (1/(1 - x)).nseries(x, n=5) == 1 + x + x**2 + x**3 + x**4 + O(x**5)
assert (x/(1 - x)).nseries(x, n=6) == x + x**2 + x**3 + x**4 + x**5 + O(x**6)
assert (x**3/(1 - x)).nseries(x, n=8) == x**3 + x**4 + x**5 + x**6 + \
x**7 + O(x**8)
def test_sqrt_1():
assert sqrt(1 + x).nseries(x, n=5) == 1 + x/2 - x**2/8 + x**3/16 - 5*x**4/128 + O(x**5)
def test_exp_1():
assert exp(x).nseries(x, n=5) == 1 + x + x**2/2 + x**3/6 + x**4/24 + O(x**5)
assert exp(x).nseries(x, n=12) == 1 + x + x**2/2 + x**3/6 + x**4/24 + x**5/120 + \
x**6/720 + x**7/5040 + x**8/40320 + x**9/362880 + x**10/3628800 + \
x**11/39916800 + O(x**12)
assert exp(1/x).nseries(x, n=5) == exp(1/x)
assert exp(1/(1 + x)).nseries(x, n=4) == \
(E*(1 - x - 13*x**3/6 + 3*x**2/2)).expand() + O(x**4)
assert exp(2 + x).nseries(x, n=5) == \
(exp(2)*(1 + x + x**2/2 + x**3/6 + x**4/24)).expand() + O(x**5)
def test_exp_sqrt_1():
assert exp(1 + sqrt(x)).nseries(x, n=3) == \
(exp(1)*(1 + sqrt(x) + x/2 + sqrt(x)*x/6)).expand() + O(sqrt(x)**3)
def test_power_x_x1():
assert (exp(x*log(x))).nseries(x, n=4) == \
1 + x*log(x) + x**2*log(x)**2/2 + x**3*log(x)**3/6 + O(x**4*log(x)**4)
def test_power_x_x2():
assert (x**x).nseries(x, n=4) == \
1 + x*log(x) + x**2*log(x)**2/2 + x**3*log(x)**3/6 + O(x**4*log(x)**4)
def test_log_singular1():
assert log(1 + 1/x).nseries(x, n=5) == x - log(x) - x**2/2 + x**3/3 - \
x**4/4 + O(x**5)
def test_log_power1():
e = 1 / (1/x + x ** (log(3)/log(2)))
assert e.nseries(x, n=5) == -x**(log(3)/log(2) + 2) + x + O(x**5)
def test_log_series():
l = Symbol('l')
e = 1/(1 - log(x))
assert e.nseries(x, n=5, logx=l) == 1/(1 - l)
def test_log2():
e = log(-1/x)
assert e.nseries(x, n=5) == -log(x) + log(-1)
def test_log3():
l = Symbol('l')
e = 1/log(-1/x)
assert e.nseries(x, n=4, logx=l) == 1/(-l + log(-1))
def test_series1():
e = sin(x)
assert e.nseries(x, 0, 0) != 0
assert e.nseries(x, 0, 0) == O(1, x)
assert e.nseries(x, 0, 1) == O(x, x)
assert e.nseries(x, 0, 2) == x + O(x**2, x)
assert e.nseries(x, 0, 3) == x + O(x**3, x)
assert e.nseries(x, 0, 4) == x - x**3/6 + O(x**4, x)
e = (exp(x) - 1)/x
assert e.nseries(x, 0, 3) == 1 + x/2 + x**2/6 + O(x**3)
assert x.nseries(x, 0, 2) == x
@XFAIL
def test_series1_failing():
assert x.nseries(x, 0, 0) == O(1, x)
assert x.nseries(x, 0, 1) == O(x, x)
def test_seriesbug1():
assert (1/x).nseries(x, 0, 3) == 1/x
assert (x + 1/x).nseries(x, 0, 3) == x + 1/x
def test_series2x():
assert ((x + 1)**(-2)).nseries(x, 0, 4) == 1 - 2*x + 3*x**2 - 4*x**3 + O(x**4, x)
assert ((x + 1)**(-1)).nseries(x, 0, 4) == 1 - x + x**2 - x**3 + O(x**4, x)
assert ((x + 1)**0).nseries(x, 0, 3) == 1
assert ((x + 1)**1).nseries(x, 0, 3) == 1 + x
assert ((x + 1)**2).nseries(x, 0, 3) == x**2 + 2*x + 1
assert ((x + 1)**3).nseries(x, 0, 3) == 1 + 3*x + 3*x**2 + O(x**3)
assert (1/(1 + x)).nseries(x, 0, 4) == 1 - x + x**2 - x**3 + O(x**4, x)
assert (x + 3/(1 + 2*x)).nseries(x, 0, 4) == 3 - 5*x + 12*x**2 - 24*x**3 + O(x**4, x)
assert ((1/x + 1)**3).nseries(x, 0, 3) == 1 + 3/x + 3/x**2 + x**(-3)
assert (1/(1 + 1/x)).nseries(x, 0, 4) == x - x**2 + x**3 - O(x**4, x)
assert (1/(1 + 1/x**2)).nseries(x, 0, 6) == x**2 - x**4 + O(x**6, x)
def test_bug2(): # 1/log(0)*log(0) problem
w = Symbol("w")
e = (w**(-1) + w**(
-log(3)*log(2)**(-1)))**(-1)*(3*w**(-log(3)*log(2)**(-1)) + 2*w**(-1))
e = e.expand()
assert e.nseries(w, 0, 4).subs(w, 0) == 3
def test_exp():
e = (1 + x)**(1/x)
assert e.nseries(x, n=3) == exp(1) - x*exp(1)/2 + 11*exp(1)*x**2/24 + O(x**3)
def test_exp2():
w = Symbol("w")
e = w**(1 - log(x)/(log(2) + log(x)))
logw = Symbol("logw")
assert e.nseries(
w, 0, 1, logx=logw) == exp(logw*log(2)/(log(x) + log(2)))
def test_bug3():
e = (2/x + 3/x**2)/(1/x + 1/x**2)
assert e.nseries(x, n=3) == 3 - x + x**2 + O(x**3)
def test_generalexponent():
p = 2
e = (2/x + 3/x**p)/(1/x + 1/x**p)
assert e.nseries(x, 0, 3) == 3 - x + x**2 + O(x**3)
p = S.Half
e = (2/x + 3/x**p)/(1/x + 1/x**p)
assert e.nseries(x, 0, 2) == 2 - x + sqrt(x) + x**(S(3)/2) + O(x**2)
e = 1 + sqrt(x)
assert e.nseries(x, 0, 4) == 1 + sqrt(x)
# more complicated example
def test_genexp_x():
e = 1/(1 + sqrt(x))
assert e.nseries(x, 0, 2) == \
1 + x - sqrt(x) - sqrt(x)**3 + O(x**2, x)
# more complicated example
def test_genexp_x2():
p = Rational(3, 2)
e = (2/x + 3/x**p)/(1/x + 1/x**p)
assert e.nseries(x, 0, 3) == 3 + x + x**2 - sqrt(x) - x**(S(3)/2) - x**(S(5)/2) + O(x**3)
def test_seriesbug2():
w = Symbol("w")
#simple case (1):
e = ((2*w)/w)**(1 + w)
assert e.nseries(w, 0, 1) == 2 + O(w, w)
assert e.nseries(w, 0, 1).subs(w, 0) == 2
def test_seriesbug2b():
w = Symbol("w")
#test sin
e = sin(2*w)/w
assert e.nseries(w, 0, 3) == 2 - 4*w**2/3 + O(w**3)
def test_seriesbug2d():
w = Symbol("w", real=True)
e = log(sin(2*w)/w)
assert e.series(w, n=5) == log(2) - 2*w**2/3 - 4*w**4/45 + O(w**5)
def test_seriesbug2c():
w = Symbol("w", real=True)
#more complicated case, but sin(x)~x, so the result is the same as in (1)
e = (sin(2*w)/w)**(1 + w)
assert e.series(w, 0, 1) == 2 + O(w)
assert e.series(w, 0, 3) == 2 + 2*w*log(2) + \
w**2*(Rational(-4, 3) + log(2)**2) + O(w**3)
assert e.series(w, 0, 2).subs(w, 0) == 2
def test_expbug4():
x = Symbol("x", real=True)
assert (log(
sin(2*x)/x)*(1 + x)).series(x, 0, 2) == log(2) + x*log(2) + O(x**2, x)
assert exp(
log(sin(2*x)/x)*(1 + x)).series(x, 0, 2) == 2 + 2*x*log(2) + O(x**2)
assert exp(log(2) + O(x)).nseries(x, 0, 2) == 2 + O(x)
assert ((2 + O(x))**(1 + x)).nseries(x, 0, 2) == 2 + O(x)
def test_logbug4():
assert log(2 + O(x)).nseries(x, 0, 2) == log(2) + O(x, x)
def test_expbug5():
assert exp(log(1 + x)/x).nseries(x, n=3) == exp(1) + -exp(1)*x/2 + 11*exp(1)*x**2/24 + O(x**3)
assert exp(O(x)).nseries(x, 0, 2) == 1 + O(x)
def test_sinsinbug():
assert sin(sin(x)).nseries(x, 0, 8) == x - x**3/3 + x**5/10 - 8*x**7/315 + O(x**8)
def test_issue_3258():
a = x/(exp(x) - 1)
assert a.nseries(x, 0, 5) == 1 - x/2 - x**4/720 + x**2/12 + O(x**5)
def test_issue_3204():
x = Symbol("x", nonnegative=True)
f = sin(x**3)**Rational(1, 3)
assert f.nseries(x, 0, 17) == x - x**7/18 - x**13/3240 + O(x**17)
def test_issue_3224():
f = sqrt(1 - sqrt(y))
assert f.nseries(y, 0, 2) == 1 - sqrt(y)/2 - y/8 - sqrt(y)**3/16 + O(y**2)
def test_issue_3463():
w, i = symbols('w,i')
r = log(5)/log(3)
p = w**(-1 + r)
e = 1/x*(-log(w**(1 + r)) + log(w + w**r))
e_ser = -r*log(w)/x + p/x - p**2/(2*x) + O(w)
assert e.nseries(w, n=1) == e_ser
def test_sin():
assert sin(8*x).nseries(x, n=4) == 8*x - 256*x**3/3 + O(x**4)
assert sin(x + y).nseries(x, n=1) == sin(y) + O(x)
assert sin(x + y).nseries(x, n=2) == sin(y) + cos(y)*x + O(x**2)
assert sin(x + y).nseries(x, n=5) == sin(y) + cos(y)*x - sin(y)*x**2/2 - \
cos(y)*x**3/6 + sin(y)*x**4/24 + O(x**5)
def test_issue_3515():
e = sin(8*x)/x
assert e.nseries(x, n=6) == 8 - 256*x**2/3 + 4096*x**4/15 + O(x**6)
def test_issue_3505():
e = sin(x)**(-4)*(sqrt(cos(x))*sin(x)**2 -
cos(x)**Rational(1, 3)*sin(x)**2)
assert e.nseries(x, n=9) == Rational(-1, 12) - 7*x**2/288 - \
43*x**4/10368 - 1123*x**6/2488320 + 377*x**8/29859840 + O(x**9)
def test_issue_3501():
a = Symbol("a")
e = x**(-2)*(x*sin(a + x) - x*sin(a))
assert e.nseries(x, n=6) == cos(a) - sin(a)*x/2 - cos(a)*x**2/6 + \
x**3*sin(a)/24 + x**4*cos(a)/120 - x**5*sin(a)/720 + O(x**6)
e = x**(-2)*(x*cos(a + x) - x*cos(a))
assert e.nseries(x, n=6) == -sin(a) - cos(a)*x/2 + sin(a)*x**2/6 + \
cos(a)*x**3/24 - x**4*sin(a)/120 - x**5*cos(a)/720 + O(x**6)
def test_issue_3502():
e = sin(5*x)/sin(2*x)
assert e.nseries(x, n=2) == Rational(5, 2) + O(x**2)
assert e.nseries(x, n=6) == \
Rational(5, 2) - 35*x**2/4 + 329*x**4/48 + O(x**6)
def test_issue_3503():
e = sin(2 + x)/(2 + x)
assert e.nseries(x, n=2) == sin(2)/2 + x*cos(2)/2 - x*sin(2)/4 + O(x**2)
def test_issue_3506():
e = (x + sin(3*x))**(-2)*(x*(x + sin(3*x)) - (x + sin(3*x))*sin(2*x))
assert e.nseries(x, n=7) == \
Rational(-1, 4) + 5*x**2/96 + 91*x**4/768 + 11117*x**6/129024 + O(x**7)
def test_issue_3508():
x = Symbol("x", real=True)
assert log(sin(x)).series(x, n=5) == log(x) - x**2/6 - x**4/180 + O(x**5)
e = -log(x) + x*(-log(x) + log(sin(2*x))) + log(sin(2*x))
assert e.series(x, n=5) == \
log(2) + log(2)*x - 2*x**2/3 - 2*x**3/3 - 4*x**4/45 + O(x**5)
def test_issue_3507():
e = x**(-4)*(x**2 - x**2*sqrt(cos(x)))
assert e.nseries(x, n=9) == \
Rational(1, 4) + x**2/96 + 19*x**4/5760 + 559*x**6/645120 + 29161*x**8/116121600 + O(x**9)
def test_issue_3639():
assert sin(cos(x)).nseries(x, n=5) == \
sin(1) - x**2*cos(1)/2 - x**4*sin(1)/8 + x**4*cos(1)/24 + O(x**5)
def test_hyperbolic():
assert sinh(x).nseries(x, n=6) == x + x**3/6 + x**5/120 + O(x**6)
assert cosh(x).nseries(x, n=5) == 1 + x**2/2 + x**4/24 + O(x**5)
assert tanh(x).nseries(x, n=6) == x - x**3/3 + 2*x**5/15 + O(x**6)
assert coth(x).nseries(x, n=6) == \
1/x - x**3/45 + x/3 + 2*x**5/945 + O(x**6)
assert asinh(x).nseries(x, n=6) == x - x**3/6 + 3*x**5/40 + O(x**6)
assert acosh(x).nseries(x, n=6) == \
pi*I/2 - I*x - 3*I*x**5/40 - I*x**3/6 + O(x**6)
assert atanh(x).nseries(x, n=6) == x + x**3/3 + x**5/5 + O(x**6)
assert acoth(x).nseries(x, n=6) == x + x**3/3 + x**5/5 + pi*I/2 + O(x**6)
def test_series2():
w = Symbol("w", real=True)
x = Symbol("x", real=True)
e = w**(-2)*(w*exp(1/x - w) - w*exp(1/x))
assert e.nseries(w, n=4) == -exp(1/x) + w*exp(1/x)/2 - w**2*exp(1/x)/6 + w**3*exp(1/x)/24 + O(w**4)
def test_series3():
w = Symbol("w", real=True)
e = w**(-6)*(w**3*tan(w) - w**3*sin(w))
assert e.nseries(w, n=8) == Integer(1)/2 + w**2/8 + 13*w**4/240 + 529*w**6/24192 + O(w**8)
def test_bug4():
w = Symbol("w")
e = x/(w**4 + x**2*w**4 + 2*x*w**4)*w**4
assert e.nseries(w, n=2).removeO().expand() in [x/(1 + 2*x + x**2),
1/(1 + x/2 + 1/x/2)/2, 1/x/(1 + 2/x + x**(-2))]
def test_bug5():
w = Symbol("w")
l = Symbol('l')
e = (-log(w) + log(1 + w*log(x)))**(-2)*w**(-2)*((-log(w) +
log(1 + x*w))*(-log(w) + log(1 + w*log(x)))*w - x*(-log(w) +
log(1 + w*log(x)))*w)
assert e.nseries(w, n=0, logx=l) == x/w/l + 1/w + O(1, w)
assert e.nseries(w, n=1, logx=l) == x/w/l + 1/w - x/l + 1/l*log(x) \
+ x*log(x)/l**2 + O(w)
def test_issue_4115():
assert (sin(x)/(1 - cos(x))).nseries(x, n=1) == 2/x + O(x)
assert (sin(x)**2/(1 - cos(x))).nseries(x, n=1) == 2 + O(x)
def test_pole():
raises(PoleError, lambda: sin(1/x).series(x, 0, 5))
raises(PoleError, lambda: sin(1 + 1/x).series(x, 0, 5))
raises(PoleError, lambda: (x*sin(1/x)).series(x, 0, 5))
def test_expsinbug():
assert exp(sin(x)).series(x, 0, 0) == O(1, x)
assert exp(sin(x)).series(x, 0, 1) == 1 + O(x)
assert exp(sin(x)).series(x, 0, 2) == 1 + x + O(x**2)
assert exp(sin(x)).series(x, 0, 3) == 1 + x + x**2/2 + O(x**3)
assert exp(sin(x)).series(x, 0, 4) == 1 + x + x**2/2 + O(x**4)
assert exp(sin(x)).series(x, 0, 5) == 1 + x + x**2/2 - x**4/8 + O(x**5)
def test_floor():
x = Symbol('x')
assert floor(x).series(x) == 0
assert floor(-x).series(x) == -1
assert floor(sin(x)).series(x) == 0
assert floor(sin(-x)).series(x) == -1
assert floor(x**3).series(x) == 0
assert floor(-x**3).series(x) == -1
assert floor(cos(x)).series(x) == 0
assert floor(cos(-x)).series(x) == 0
assert floor(5 + sin(x)).series(x) == 5
assert floor(5 + sin(-x)).series(x) == 4
assert floor(x).series(x, 2) == 2
assert floor(-x).series(x, 2) == -3
x = Symbol('x', negative=True)
assert floor(x + 1.5).series(x) == 1
def test_ceiling():
assert ceiling(x).series(x) == 1
assert ceiling(-x).series(x) == 0
assert ceiling(sin(x)).series(x) == 1
assert ceiling(sin(-x)).series(x) == 0
assert ceiling(1 - cos(x)).series(x) == 1
assert ceiling(1 - cos(-x)).series(x) == 1
assert ceiling(x).series(x, 2) == 3
assert ceiling(-x).series(x, 2) == -2
def test_abs():
a = Symbol('a')
assert abs(x).nseries(x, n=4) == x
assert abs(-x).nseries(x, n=4) == x
assert abs(x + 1).nseries(x, n=4) == x + 1
assert abs(sin(x)).nseries(x, n=4) == x - Rational(1, 6)*x**3 + O(x**4)
assert abs(sin(-x)).nseries(x, n=4) == x - Rational(1, 6)*x**3 + O(x**4)
assert abs(x - a).nseries(x, 1) == -a*sign(1 - a) + (x - 1)*sign(1 - a) + sign(1 - a)
def test_dir():
assert abs(x).series(x, 0, dir="+") == x
assert abs(x).series(x, 0, dir="-") == -x
assert floor(x + 2).series(x, 0, dir='+') == 2
assert floor(x + 2).series(x, 0, dir='-') == 1
assert floor(x + 2.2).series(x, 0, dir='-') == 2
assert ceiling(x + 2.2).series(x, 0, dir='-') == 3
assert sin(x + y).series(x, 0, dir='-') == sin(x + y).series(x, 0, dir='+')
def test_issue_3504():
a = Symbol("a")
e = asin(a*x)/x
assert e.series(x, 4, n=2).removeO() == \
(x - 4)*(a/(4*sqrt(-16*a**2 + 1)) - asin(4*a)/16) + asin(4*a)/4
def test_issue_4441():
a, b = symbols('a,b')
f = 1/(1 + a*x)
assert f.series(x, 0, 5) == 1 - a*x + a**2*x**2 - a**3*x**3 + \
a**4*x**4 + O(x**5)
f = 1/(1 + (a + b)*x)
assert f.series(x, 0, 3) == 1 + x*(-a - b)\
+ x**2*(a + b)**2 + O(x**3)
def test_issue_4329():
assert tan(x).series(x, pi/2, n=3).removeO() == \
-pi/6 + x/3 - 1/(x - pi/2)
assert cot(x).series(x, pi, n=3).removeO() == \
-x/3 + pi/3 + 1/(x - pi)
assert limit(tan(x)**tan(2*x), x, pi/4) == exp(-1)
def test_issue_5183():
assert abs(x + x**2).series(n=1) == O(x)
assert abs(x + x**2).series(n=2) == x + O(x**2)
assert ((1 + x)**2).series(x, n=6) == x**2 + 2*x + 1
assert (1 + 1/x).series() == 1 + 1/x
assert Derivative(exp(x).series(), x).doit() == \
1 + x + x**2/2 + x**3/6 + x**4/24 + O(x**5)
def test_issue_5654():
a = Symbol('a')
assert (1/(x**2+a**2)**2).nseries(x, x0=I*a, n=0) == \
-I/(4*a**3*(-I*a + x)) - 1/(4*a**2*(-I*a + x)**2) + O(1, (x, I*a))
assert (1/(x**2+a**2)**2).nseries(x, x0=I*a, n=1) == 3/(16*a**4) \
-I/(4*a**3*(-I*a + x)) - 1/(4*a**2*(-I*a + x)**2) + O(-I*a + x, (x, I*a))
def test_issue_5925():
sx = sqrt(x + z).series(z, 0, 1)
sxy = sqrt(x + y + z).series(z, 0, 1)
s1, s2 = sx.subs(x, x + y), sxy
assert (s1 - s2).expand().removeO().simplify() == 0
sx = sqrt(x + z).series(z, 0, 1)
sxy = sqrt(x + y + z).series(z, 0, 1)
assert sxy.subs({x:1, y:2}) == sx.subs(x, 3)
def test_exp_2():
assert exp(x**3).nseries(x, 0, 14) == 1 + x**3 + x**6/2 + x**9/6 + x**12/24 + O(x**14)
|
e3346d0d0546a4a4510584809c4179a52334011fdf00cba638dbb639c6f7b6a8 | from sympy.core.mul import Mul
from sympy.core.numbers import (I, Integer, Rational)
from sympy.core.symbol import Symbol
from sympy.functions.elementary.miscellaneous import (root, sqrt)
from sympy.functions.elementary.trigonometric import cos
from sympy.integrals.integrals import Integral
from sympy.simplify.sqrtdenest import sqrtdenest
from sympy.simplify.sqrtdenest import (
_subsets as subsets, _sqrt_numeric_denest)
r2, r3, r5, r6, r7, r10, r15, r29 = [sqrt(x) for x in (2, 3, 5, 6, 7, 10,
15, 29)]
def test_sqrtdenest():
d = {sqrt(5 + 2 * r6): r2 + r3,
sqrt(5. + 2 * r6): sqrt(5. + 2 * r6),
sqrt(5. + 4*sqrt(5 + 2 * r6)): sqrt(5.0 + 4*r2 + 4*r3),
sqrt(r2): sqrt(r2),
sqrt(5 + r7): sqrt(5 + r7),
sqrt(3 + sqrt(5 + 2*r7)):
3*r2*(5 + 2*r7)**Rational(1, 4)/(2*sqrt(6 + 3*r7)) +
r2*sqrt(6 + 3*r7)/(2*(5 + 2*r7)**Rational(1, 4)),
sqrt(3 + 2*r3): 3**Rational(3, 4)*(r6/2 + 3*r2/2)/3}
for i in d:
assert sqrtdenest(i) == d[i], i
def test_sqrtdenest2():
assert sqrtdenest(sqrt(16 - 2*r29 + 2*sqrt(55 - 10*r29))) == \
r5 + sqrt(11 - 2*r29)
e = sqrt(-r5 + sqrt(-2*r29 + 2*sqrt(-10*r29 + 55) + 16))
assert sqrtdenest(e) == root(-2*r29 + 11, 4)
r = sqrt(1 + r7)
assert sqrtdenest(sqrt(1 + r)) == sqrt(1 + r)
e = sqrt(((1 + sqrt(1 + 2*sqrt(3 + r2 + r5)))**2).expand())
assert sqrtdenest(e) == 1 + sqrt(1 + 2*sqrt(r2 + r5 + 3))
assert sqrtdenest(sqrt(5*r3 + 6*r2)) == \
sqrt(2)*root(3, 4) + root(3, 4)**3
assert sqrtdenest(sqrt(((1 + r5 + sqrt(1 + r3))**2).expand())) == \
1 + r5 + sqrt(1 + r3)
assert sqrtdenest(sqrt(((1 + r5 + r7 + sqrt(1 + r3))**2).expand())) == \
1 + sqrt(1 + r3) + r5 + r7
e = sqrt(((1 + cos(2) + cos(3) + sqrt(1 + r3))**2).expand())
assert sqrtdenest(e) == cos(3) + cos(2) + 1 + sqrt(1 + r3)
e = sqrt(-2*r10 + 2*r2*sqrt(-2*r10 + 11) + 14)
assert sqrtdenest(e) == sqrt(-2*r10 - 2*r2 + 4*r5 + 14)
# check that the result is not more complicated than the input
z = sqrt(-2*r29 + cos(2) + 2*sqrt(-10*r29 + 55) + 16)
assert sqrtdenest(z) == z
assert sqrtdenest(sqrt(r6 + sqrt(15))) == sqrt(r6 + sqrt(15))
z = sqrt(15 - 2*sqrt(31) + 2*sqrt(55 - 10*r29))
assert sqrtdenest(z) == z
def test_sqrtdenest_rec():
assert sqrtdenest(sqrt(-4*sqrt(14) - 2*r6 + 4*sqrt(21) + 33)) == \
-r2 + r3 + 2*r7
assert sqrtdenest(sqrt(-28*r7 - 14*r5 + 4*sqrt(35) + 82)) == \
-7 + r5 + 2*r7
assert sqrtdenest(sqrt(6*r2/11 + 2*sqrt(22)/11 + 6*sqrt(11)/11 + 2)) == \
sqrt(11)*(r2 + 3 + sqrt(11))/11
assert sqrtdenest(sqrt(468*r3 + 3024*r2 + 2912*r6 + 19735)) == \
9*r3 + 26 + 56*r6
z = sqrt(-490*r3 - 98*sqrt(115) - 98*sqrt(345) - 2107)
assert sqrtdenest(z) == sqrt(-1)*(7*r5 + 7*r15 + 7*sqrt(23))
z = sqrt(-4*sqrt(14) - 2*r6 + 4*sqrt(21) + 34)
assert sqrtdenest(z) == z
assert sqrtdenest(sqrt(-8*r2 - 2*r5 + 18)) == -r10 + 1 + r2 + r5
assert sqrtdenest(sqrt(8*r2 + 2*r5 - 18)) == \
sqrt(-1)*(-r10 + 1 + r2 + r5)
assert sqrtdenest(sqrt(8*r2/3 + 14*r5/3 + Rational(154, 9))) == \
-r10/3 + r2 + r5 + 3
assert sqrtdenest(sqrt(sqrt(2*r6 + 5) + sqrt(2*r7 + 8))) == \
sqrt(1 + r2 + r3 + r7)
assert sqrtdenest(sqrt(4*r15 + 8*r5 + 12*r3 + 24)) == 1 + r3 + r5 + r15
w = 1 + r2 + r3 + r5 + r7
assert sqrtdenest(sqrt((w**2).expand())) == w
z = sqrt((w**2).expand() + 1)
assert sqrtdenest(z) == z
z = sqrt(2*r10 + 6*r2 + 4*r5 + 12 + 10*r15 + 30*r3)
assert sqrtdenest(z) == z
def test_issue_6241():
z = sqrt( -320 + 32*sqrt(5) + 64*r15)
assert sqrtdenest(z) == z
def test_sqrtdenest3():
z = sqrt(13 - 2*r10 + 2*r2*sqrt(-2*r10 + 11))
assert sqrtdenest(z) == -1 + r2 + r10
assert sqrtdenest(z, max_iter=1) == -1 + sqrt(2) + sqrt(10)
z = sqrt(sqrt(r2 + 2) + 2)
assert sqrtdenest(z) == z
assert sqrtdenest(sqrt(-2*r10 + 4*r2*sqrt(-2*r10 + 11) + 20)) == \
sqrt(-2*r10 - 4*r2 + 8*r5 + 20)
assert sqrtdenest(sqrt((112 + 70*r2) + (46 + 34*r2)*r5)) == \
r10 + 5 + 4*r2 + 3*r5
z = sqrt(5 + sqrt(2*r6 + 5)*sqrt(-2*r29 + 2*sqrt(-10*r29 + 55) + 16))
r = sqrt(-2*r29 + 11)
assert sqrtdenest(z) == sqrt(r2*r + r3*r + r10 + r15 + 5)
n = sqrt(2*r6/7 + 2*r7/7 + 2*sqrt(42)/7 + 2)
d = sqrt(16 - 2*r29 + 2*sqrt(55 - 10*r29))
assert sqrtdenest(n/d) == r7*(1 + r6 + r7)/(Mul(7, (sqrt(-2*r29 + 11) + r5),
evaluate=False))
def test_sqrtdenest4():
# see Denest_en.pdf in https://github.com/sympy/sympy/issues/3192
z = sqrt(8 - r2*sqrt(5 - r5) - sqrt(3)*(1 + r5))
z1 = sqrtdenest(z)
c = sqrt(-r5 + 5)
z1 = ((-r15*c - r3*c + c + r5*c - r6 - r2 + r10 + sqrt(30))/4).expand()
assert sqrtdenest(z) == z1
z = sqrt(2*r2*sqrt(r2 + 2) + 5*r2 + 4*sqrt(r2 + 2) + 8)
assert sqrtdenest(z) == r2 + sqrt(r2 + 2) + 2
w = 2 + r2 + r3 + (1 + r3)*sqrt(2 + r2 + 5*r3)
z = sqrt((w**2).expand())
assert sqrtdenest(z) == w.expand()
def test_sqrt_symbolic_denest():
x = Symbol('x')
z = sqrt(((1 + sqrt(sqrt(2 + x) + 3))**2).expand())
assert sqrtdenest(z) == sqrt((1 + sqrt(sqrt(2 + x) + 3))**2)
z = sqrt(((1 + sqrt(sqrt(2 + cos(1)) + 3))**2).expand())
assert sqrtdenest(z) == 1 + sqrt(sqrt(2 + cos(1)) + 3)
z = ((1 + cos(2))**4 + 1).expand()
assert sqrtdenest(z) == z
z = sqrt(((1 + sqrt(sqrt(2 + cos(3*x)) + 3))**2 + 1).expand())
assert sqrtdenest(z) == z
c = cos(3)
c2 = c**2
assert sqrtdenest(sqrt(2*sqrt(1 + r3)*c + c2 + 1 + r3*c2)) == \
-1 - sqrt(1 + r3)*c
ra = sqrt(1 + r3)
z = sqrt(20*ra*sqrt(3 + 3*r3) + 12*r3*ra*sqrt(3 + 3*r3) + 64*r3 + 112)
assert sqrtdenest(z) == z
def test_issue_5857():
from sympy.abc import x, y
z = sqrt(1/(4*r3 + 7) + 1)
ans = (r2 + r6)/(r3 + 2)
assert sqrtdenest(z) == ans
assert sqrtdenest(1 + z) == 1 + ans
assert sqrtdenest(Integral(z + 1, (x, 1, 2))) == \
Integral(1 + ans, (x, 1, 2))
assert sqrtdenest(x + sqrt(y)) == x + sqrt(y)
ans = (r2 + r6)/(r3 + 2)
assert sqrtdenest(z) == ans
assert sqrtdenest(1 + z) == 1 + ans
assert sqrtdenest(Integral(z + 1, (x, 1, 2))) == \
Integral(1 + ans, (x, 1, 2))
assert sqrtdenest(x + sqrt(y)) == x + sqrt(y)
def test_subsets():
assert subsets(1) == [[1]]
assert subsets(4) == [
[1, 0, 0, 0], [0, 1, 0, 0], [1, 1, 0, 0], [0, 0, 1, 0], [1, 0, 1, 0],
[0, 1, 1, 0], [1, 1, 1, 0], [0, 0, 0, 1], [1, 0, 0, 1], [0, 1, 0, 1],
[1, 1, 0, 1], [0, 0, 1, 1], [1, 0, 1, 1], [0, 1, 1, 1], [1, 1, 1, 1]]
def test_issue_5653():
assert sqrtdenest(
sqrt(2 + sqrt(2 + sqrt(2)))) == sqrt(2 + sqrt(2 + sqrt(2)))
def test_issue_12420():
assert sqrtdenest((3 - sqrt(2)*sqrt(4 + 3*I) + 3*I)/2) == I
e = 3 - sqrt(2)*sqrt(4 + I) + 3*I
assert sqrtdenest(e) == e
def test_sqrt_ratcomb():
assert sqrtdenest(sqrt(1 + r3) + sqrt(3 + 3*r3) - sqrt(10 + 6*r3)) == 0
def test_issue_18041():
e = -sqrt(-2 + 2*sqrt(3)*I)
assert sqrtdenest(e) == -1 - sqrt(3)*I
def test_issue_19914():
a = Integer(-8)
b = Integer(-1)
r = Integer(63)
d2 = a*a - b*b*r
assert _sqrt_numeric_denest(a, b, r, d2) == \
sqrt(14)*I/2 + 3*sqrt(2)*I/2
assert sqrtdenest(sqrt(-8-sqrt(63))) == sqrt(14)*I/2 + 3*sqrt(2)*I/2
|
b42b2cd6cffed5748f1c7a16dd32461ef556662e29889f553fd29d92d895af62 | from sympy.core.add import Add
from sympy.core.mul import Mul
from sympy.core.numbers import (I, Rational, pi)
from sympy.core.singleton import S
from sympy.core.symbol import (Dummy, Symbol, symbols)
from sympy.functions.elementary.hyperbolic import (cosh, coth, csch, sech, sinh, tanh)
from sympy.functions.elementary.miscellaneous import (root, sqrt)
from sympy.functions.elementary.trigonometric import (cos, cot, csc, sec, sin, tan)
from sympy.simplify.powsimp import powsimp
from sympy.simplify.fu import (
L, TR1, TR10, TR10i, TR11, _TR11, TR12, TR12i, TR13, TR14, TR15, TR16,
TR111, TR2, TR2i, TR3, TR5, TR6, TR7, TR8, TR9, TRmorrie, _TR56 as T,
TRpower, hyper_as_trig, fu, process_common_addends, trig_split,
as_f_sign_1)
from sympy.testing.randtest import verify_numerically
from sympy.abc import a, b, c, x, y, z
def test_TR1():
assert TR1(2*csc(x) + sec(x)) == 1/cos(x) + 2/sin(x)
def test_TR2():
assert TR2(tan(x)) == sin(x)/cos(x)
assert TR2(cot(x)) == cos(x)/sin(x)
assert TR2(tan(tan(x) - sin(x)/cos(x))) == 0
def test_TR2i():
# just a reminder that ratios of powers only simplify if both
# numerator and denominator satisfy the condition that each
# has a positive base or an integer exponent; e.g. the following,
# at y=-1, x=1/2 gives sqrt(2)*I != -sqrt(2)*I
assert powsimp(2**x/y**x) != (2/y)**x
assert TR2i(sin(x)/cos(x)) == tan(x)
assert TR2i(sin(x)*sin(y)/cos(x)) == tan(x)*sin(y)
assert TR2i(1/(sin(x)/cos(x))) == 1/tan(x)
assert TR2i(1/(sin(x)*sin(y)/cos(x))) == 1/tan(x)/sin(y)
assert TR2i(sin(x)/2/(cos(x) + 1)) == sin(x)/(cos(x) + 1)/2
assert TR2i(sin(x)/2/(cos(x) + 1), half=True) == tan(x/2)/2
assert TR2i(sin(1)/(cos(1) + 1), half=True) == tan(S.Half)
assert TR2i(sin(2)/(cos(2) + 1), half=True) == tan(1)
assert TR2i(sin(4)/(cos(4) + 1), half=True) == tan(2)
assert TR2i(sin(5)/(cos(5) + 1), half=True) == tan(5*S.Half)
assert TR2i((cos(1) + 1)/sin(1), half=True) == 1/tan(S.Half)
assert TR2i((cos(2) + 1)/sin(2), half=True) == 1/tan(1)
assert TR2i((cos(4) + 1)/sin(4), half=True) == 1/tan(2)
assert TR2i((cos(5) + 1)/sin(5), half=True) == 1/tan(5*S.Half)
assert TR2i((cos(1) + 1)**(-a)*sin(1)**a, half=True) == tan(S.Half)**a
assert TR2i((cos(2) + 1)**(-a)*sin(2)**a, half=True) == tan(1)**a
assert TR2i((cos(4) + 1)**(-a)*sin(4)**a, half=True) == (cos(4) + 1)**(-a)*sin(4)**a
assert TR2i((cos(5) + 1)**(-a)*sin(5)**a, half=True) == (cos(5) + 1)**(-a)*sin(5)**a
assert TR2i((cos(1) + 1)**a*sin(1)**(-a), half=True) == tan(S.Half)**(-a)
assert TR2i((cos(2) + 1)**a*sin(2)**(-a), half=True) == tan(1)**(-a)
assert TR2i((cos(4) + 1)**a*sin(4)**(-a), half=True) == (cos(4) + 1)**a*sin(4)**(-a)
assert TR2i((cos(5) + 1)**a*sin(5)**(-a), half=True) == (cos(5) + 1)**a*sin(5)**(-a)
i = symbols('i', integer=True)
assert TR2i(((cos(5) + 1)**i*sin(5)**(-i)), half=True) == tan(5*S.Half)**(-i)
assert TR2i(1/((cos(5) + 1)**i*sin(5)**(-i)), half=True) == tan(5*S.Half)**i
def test_TR3():
assert TR3(cos(y - x*(y - x))) == cos(x*(x - y) + y)
assert cos(pi/2 + x) == -sin(x)
assert cos(30*pi/2 + x) == -cos(x)
for f in (cos, sin, tan, cot, csc, sec):
i = f(pi*Rational(3, 7))
j = TR3(i)
assert verify_numerically(i, j) and i.func != j.func
def test__TR56():
h = lambda x: 1 - x
assert T(sin(x)**3, sin, cos, h, 4, False) == sin(x)*(-cos(x)**2 + 1)
assert T(sin(x)**10, sin, cos, h, 4, False) == sin(x)**10
assert T(sin(x)**6, sin, cos, h, 6, False) == (-cos(x)**2 + 1)**3
assert T(sin(x)**6, sin, cos, h, 6, True) == sin(x)**6
assert T(sin(x)**8, sin, cos, h, 10, True) == (-cos(x)**2 + 1)**4
# issue 17137
assert T(sin(x)**I, sin, cos, h, 4, True) == sin(x)**I
assert T(sin(x)**(2*I + 1), sin, cos, h, 4, True) == sin(x)**(2*I + 1)
def test_TR5():
assert TR5(sin(x)**2) == -cos(x)**2 + 1
assert TR5(sin(x)**-2) == sin(x)**(-2)
assert TR5(sin(x)**4) == (-cos(x)**2 + 1)**2
def test_TR6():
assert TR6(cos(x)**2) == -sin(x)**2 + 1
assert TR6(cos(x)**-2) == cos(x)**(-2)
assert TR6(cos(x)**4) == (-sin(x)**2 + 1)**2
def test_TR7():
assert TR7(cos(x)**2) == cos(2*x)/2 + S.Half
assert TR7(cos(x)**2 + 1) == cos(2*x)/2 + Rational(3, 2)
def test_TR8():
assert TR8(cos(2)*cos(3)) == cos(5)/2 + cos(1)/2
assert TR8(cos(2)*sin(3)) == sin(5)/2 + sin(1)/2
assert TR8(sin(2)*sin(3)) == -cos(5)/2 + cos(1)/2
assert TR8(sin(1)*sin(2)*sin(3)) == sin(4)/4 - sin(6)/4 + sin(2)/4
assert TR8(cos(2)*cos(3)*cos(4)*cos(5)) == \
cos(4)/4 + cos(10)/8 + cos(2)/8 + cos(8)/8 + cos(14)/8 + \
cos(6)/8 + Rational(1, 8)
assert TR8(cos(2)*cos(3)*cos(4)*cos(5)*cos(6)) == \
cos(10)/8 + cos(4)/8 + 3*cos(2)/16 + cos(16)/16 + cos(8)/8 + \
cos(14)/16 + cos(20)/16 + cos(12)/16 + Rational(1, 16) + cos(6)/8
assert TR8(sin(pi*Rational(3, 7))**2*cos(pi*Rational(3, 7))**2/(16*sin(pi/7)**2)) == Rational(1, 64)
def test_TR9():
a = S.Half
b = 3*a
assert TR9(a) == a
assert TR9(cos(1) + cos(2)) == 2*cos(a)*cos(b)
assert TR9(cos(1) - cos(2)) == 2*sin(a)*sin(b)
assert TR9(sin(1) - sin(2)) == -2*sin(a)*cos(b)
assert TR9(sin(1) + sin(2)) == 2*sin(b)*cos(a)
assert TR9(cos(1) + 2*sin(1) + 2*sin(2)) == cos(1) + 4*sin(b)*cos(a)
assert TR9(cos(4) + cos(2) + 2*cos(1)*cos(3)) == 4*cos(1)*cos(3)
assert TR9((cos(4) + cos(2))/cos(3)/2 + cos(3)) == 2*cos(1)*cos(2)
assert TR9(cos(3) + cos(4) + cos(5) + cos(6)) == \
4*cos(S.Half)*cos(1)*cos(Rational(9, 2))
assert TR9(cos(3) + cos(3)*cos(2)) == cos(3) + cos(2)*cos(3)
assert TR9(-cos(y) + cos(x*y)) == -2*sin(x*y/2 - y/2)*sin(x*y/2 + y/2)
assert TR9(-sin(y) + sin(x*y)) == 2*sin(x*y/2 - y/2)*cos(x*y/2 + y/2)
c = cos(x)
s = sin(x)
for si in ((1, 1), (1, -1), (-1, 1), (-1, -1)):
for a in ((c, s), (s, c), (cos(x), cos(x*y)), (sin(x), sin(x*y))):
args = zip(si, a)
ex = Add(*[Mul(*ai) for ai in args])
t = TR9(ex)
assert not (a[0].func == a[1].func and (
not verify_numerically(ex, t.expand(trig=True)) or t.is_Add)
or a[1].func != a[0].func and ex != t)
def test_TR10():
assert TR10(cos(a + b)) == -sin(a)*sin(b) + cos(a)*cos(b)
assert TR10(sin(a + b)) == sin(a)*cos(b) + sin(b)*cos(a)
assert TR10(sin(a + b + c)) == \
(-sin(a)*sin(b) + cos(a)*cos(b))*sin(c) + \
(sin(a)*cos(b) + sin(b)*cos(a))*cos(c)
assert TR10(cos(a + b + c)) == \
(-sin(a)*sin(b) + cos(a)*cos(b))*cos(c) - \
(sin(a)*cos(b) + sin(b)*cos(a))*sin(c)
def test_TR10i():
assert TR10i(cos(1)*cos(3) + sin(1)*sin(3)) == cos(2)
assert TR10i(cos(1)*cos(3) - sin(1)*sin(3)) == cos(4)
assert TR10i(cos(1)*sin(3) - sin(1)*cos(3)) == sin(2)
assert TR10i(cos(1)*sin(3) + sin(1)*cos(3)) == sin(4)
assert TR10i(cos(1)*sin(3) + sin(1)*cos(3) + 7) == sin(4) + 7
assert TR10i(cos(1)*sin(3) + sin(1)*cos(3) + cos(3)) == cos(3) + sin(4)
assert TR10i(2*cos(1)*sin(3) + 2*sin(1)*cos(3) + cos(3)) == \
2*sin(4) + cos(3)
assert TR10i(cos(2)*cos(3) + sin(2)*(cos(1)*sin(2) + cos(2)*sin(1))) == \
cos(1)
eq = (cos(2)*cos(3) + sin(2)*(
cos(1)*sin(2) + cos(2)*sin(1)))*cos(5) + sin(1)*sin(5)
assert TR10i(eq) == TR10i(eq.expand()) == cos(4)
assert TR10i(sqrt(2)*cos(x)*x + sqrt(6)*sin(x)*x) == \
2*sqrt(2)*x*sin(x + pi/6)
assert TR10i(cos(x)/sqrt(6) + sin(x)/sqrt(2) +
cos(x)/sqrt(6)/3 + sin(x)/sqrt(2)/3) == 4*sqrt(6)*sin(x + pi/6)/9
assert TR10i(cos(x)/sqrt(6) + sin(x)/sqrt(2) +
cos(y)/sqrt(6)/3 + sin(y)/sqrt(2)/3) == \
sqrt(6)*sin(x + pi/6)/3 + sqrt(6)*sin(y + pi/6)/9
assert TR10i(cos(x) + sqrt(3)*sin(x) + 2*sqrt(3)*cos(x + pi/6)) == 4*cos(x)
assert TR10i(cos(x) + sqrt(3)*sin(x) +
2*sqrt(3)*cos(x + pi/6) + 4*sin(x)) == 4*sqrt(2)*sin(x + pi/4)
assert TR10i(cos(2)*sin(3) + sin(2)*cos(4)) == \
sin(2)*cos(4) + sin(3)*cos(2)
A = Symbol('A', commutative=False)
assert TR10i(sqrt(2)*cos(x)*A + sqrt(6)*sin(x)*A) == \
2*sqrt(2)*sin(x + pi/6)*A
c = cos(x)
s = sin(x)
h = sin(y)
r = cos(y)
for si in ((1, 1), (1, -1), (-1, 1), (-1, -1)):
for argsi in ((c*r, s*h), (c*h, s*r)): # explicit 2-args
args = zip(si, argsi)
ex = Add(*[Mul(*ai) for ai in args])
t = TR10i(ex)
assert not (ex - t.expand(trig=True) or t.is_Add)
c = cos(x)
s = sin(x)
h = sin(pi/6)
r = cos(pi/6)
for si in ((1, 1), (1, -1), (-1, 1), (-1, -1)):
for argsi in ((c*r, s*h), (c*h, s*r)): # induced
args = zip(si, argsi)
ex = Add(*[Mul(*ai) for ai in args])
t = TR10i(ex)
assert not (ex - t.expand(trig=True) or t.is_Add)
def test_TR11():
assert TR11(sin(2*x)) == 2*sin(x)*cos(x)
assert TR11(sin(4*x)) == 4*((-sin(x)**2 + cos(x)**2)*sin(x)*cos(x))
assert TR11(sin(x*Rational(4, 3))) == \
4*((-sin(x/3)**2 + cos(x/3)**2)*sin(x/3)*cos(x/3))
assert TR11(cos(2*x)) == -sin(x)**2 + cos(x)**2
assert TR11(cos(4*x)) == \
(-sin(x)**2 + cos(x)**2)**2 - 4*sin(x)**2*cos(x)**2
assert TR11(cos(2)) == cos(2)
assert TR11(cos(pi*Rational(3, 7)), pi*Rational(2, 7)) == -cos(pi*Rational(2, 7))**2 + sin(pi*Rational(2, 7))**2
assert TR11(cos(4), 2) == -sin(2)**2 + cos(2)**2
assert TR11(cos(6), 2) == cos(6)
assert TR11(sin(x)/cos(x/2), x/2) == 2*sin(x/2)
def test__TR11():
assert _TR11(sin(x/3)*sin(2*x)*sin(x/4)/(cos(x/6)*cos(x/8))) == \
4*sin(x/8)*sin(x/6)*sin(2*x),_TR11(sin(x/3)*sin(2*x)*sin(x/4)/(cos(x/6)*cos(x/8)))
assert _TR11(sin(x/3)/cos(x/6)) == 2*sin(x/6)
assert _TR11(cos(x/6)/sin(x/3)) == 1/(2*sin(x/6))
assert _TR11(sin(2*x)*cos(x/8)/sin(x/4)) == sin(2*x)/(2*sin(x/8)), _TR11(sin(2*x)*cos(x/8)/sin(x/4))
assert _TR11(sin(x)/sin(x/2)) == 2*cos(x/2)
def test_TR12():
assert TR12(tan(x + y)) == (tan(x) + tan(y))/(-tan(x)*tan(y) + 1)
assert TR12(tan(x + y + z)) ==\
(tan(z) + (tan(x) + tan(y))/(-tan(x)*tan(y) + 1))/(
1 - (tan(x) + tan(y))*tan(z)/(-tan(x)*tan(y) + 1))
assert TR12(tan(x*y)) == tan(x*y)
def test_TR13():
assert TR13(tan(3)*tan(2)) == -tan(2)/tan(5) - tan(3)/tan(5) + 1
assert TR13(cot(3)*cot(2)) == 1 + cot(3)*cot(5) + cot(2)*cot(5)
assert TR13(tan(1)*tan(2)*tan(3)) == \
(-tan(2)/tan(5) - tan(3)/tan(5) + 1)*tan(1)
assert TR13(tan(1)*tan(2)*cot(3)) == \
(-tan(2)/tan(3) + 1 - tan(1)/tan(3))*cot(3)
def test_L():
assert L(cos(x) + sin(x)) == 2
def test_fu():
assert fu(sin(50)**2 + cos(50)**2 + sin(pi/6)) == Rational(3, 2)
assert fu(sqrt(6)*cos(x) + sqrt(2)*sin(x)) == 2*sqrt(2)*sin(x + pi/3)
eq = sin(x)**4 - cos(y)**2 + sin(y)**2 + 2*cos(x)**2
assert fu(eq) == cos(x)**4 - 2*cos(y)**2 + 2
assert fu(S.Half - cos(2*x)/2) == sin(x)**2
assert fu(sin(a)*(cos(b) - sin(b)) + cos(a)*(sin(b) + cos(b))) == \
sqrt(2)*sin(a + b + pi/4)
assert fu(sqrt(3)*cos(x)/2 + sin(x)/2) == sin(x + pi/3)
assert fu(1 - sin(2*x)**2/4 - sin(y)**2 - cos(x)**4) == \
-cos(x)**2 + cos(y)**2
assert fu(cos(pi*Rational(4, 9))) == sin(pi/18)
assert fu(cos(pi/9)*cos(pi*Rational(2, 9))*cos(pi*Rational(3, 9))*cos(pi*Rational(4, 9))) == Rational(1, 16)
assert fu(
tan(pi*Rational(7, 18)) + tan(pi*Rational(5, 18)) - sqrt(3)*tan(pi*Rational(5, 18))*tan(pi*Rational(7, 18))) == \
-sqrt(3)
assert fu(tan(1)*tan(2)) == tan(1)*tan(2)
expr = Mul(*[cos(2**i) for i in range(10)])
assert fu(expr) == sin(1024)/(1024*sin(1))
# issue #18059:
assert fu(cos(x) + sqrt(sin(x)**2)) == cos(x) + sqrt(sin(x)**2)
assert fu((-14*sin(x)**3 + 35*sin(x) + 6*sqrt(3)*cos(x)**3 + 9*sqrt(3)*cos(x))/((cos(2*x) + 4))) == \
7*sin(x) + 3*sqrt(3)*cos(x)
def test_objective():
assert fu(sin(x)/cos(x), measure=lambda x: x.count_ops()) == \
tan(x)
assert fu(sin(x)/cos(x), measure=lambda x: -x.count_ops()) == \
sin(x)/cos(x)
def test_process_common_addends():
# this tests that the args are not evaluated as they are given to do
# and that key2 works when key1 is False
do = lambda x: Add(*[i**(i%2) for i in x.args])
process_common_addends(Add(*[1, 2, 3, 4], evaluate=False), do,
key2=lambda x: x%2, key1=False) == 1**1 + 3**1 + 2**0 + 4**0
def test_trig_split():
assert trig_split(cos(x), cos(y)) == (1, 1, 1, x, y, True)
assert trig_split(2*cos(x), -2*cos(y)) == (2, 1, -1, x, y, True)
assert trig_split(cos(x)*sin(y), cos(y)*sin(y)) == \
(sin(y), 1, 1, x, y, True)
assert trig_split(cos(x), -sqrt(3)*sin(x), two=True) == \
(2, 1, -1, x, pi/6, False)
assert trig_split(cos(x), sin(x), two=True) == \
(sqrt(2), 1, 1, x, pi/4, False)
assert trig_split(cos(x), -sin(x), two=True) == \
(sqrt(2), 1, -1, x, pi/4, False)
assert trig_split(sqrt(2)*cos(x), -sqrt(6)*sin(x), two=True) == \
(2*sqrt(2), 1, -1, x, pi/6, False)
assert trig_split(-sqrt(6)*cos(x), -sqrt(2)*sin(x), two=True) == \
(-2*sqrt(2), 1, 1, x, pi/3, False)
assert trig_split(cos(x)/sqrt(6), sin(x)/sqrt(2), two=True) == \
(sqrt(6)/3, 1, 1, x, pi/6, False)
assert trig_split(-sqrt(6)*cos(x)*sin(y),
-sqrt(2)*sin(x)*sin(y), two=True) == \
(-2*sqrt(2)*sin(y), 1, 1, x, pi/3, False)
assert trig_split(cos(x), sin(x)) is None
assert trig_split(cos(x), sin(z)) is None
assert trig_split(2*cos(x), -sin(x)) is None
assert trig_split(cos(x), -sqrt(3)*sin(x)) is None
assert trig_split(cos(x)*cos(y), sin(x)*sin(z)) is None
assert trig_split(cos(x)*cos(y), sin(x)*sin(y)) is None
assert trig_split(-sqrt(6)*cos(x), sqrt(2)*sin(x)*sin(y), two=True) is \
None
assert trig_split(sqrt(3)*sqrt(x), cos(3), two=True) is None
assert trig_split(sqrt(3)*root(x, 3), sin(3)*cos(2), two=True) is None
assert trig_split(cos(5)*cos(6), cos(7)*sin(5), two=True) is None
def test_TRmorrie():
assert TRmorrie(7*Mul(*[cos(i) for i in range(10)])) == \
7*sin(12)*sin(16)*cos(5)*cos(7)*cos(9)/(64*sin(1)*sin(3))
assert TRmorrie(x) == x
assert TRmorrie(2*x) == 2*x
e = cos(pi/7)*cos(pi*Rational(2, 7))*cos(pi*Rational(4, 7))
assert TR8(TRmorrie(e)) == Rational(-1, 8)
e = Mul(*[cos(2**i*pi/17) for i in range(1, 17)])
assert TR8(TR3(TRmorrie(e))) == Rational(1, 65536)
# issue 17063
eq = cos(x)/cos(x/2)
assert TRmorrie(eq) == eq
# issue #20430
eq = cos(x/2)*sin(x/2)*cos(x)**3
assert TRmorrie(eq) == sin(2*x)*cos(x)**2/4
def test_TRpower():
assert TRpower(1/sin(x)**2) == 1/sin(x)**2
assert TRpower(cos(x)**3*sin(x/2)**4) == \
(3*cos(x)/4 + cos(3*x)/4)*(-cos(x)/2 + cos(2*x)/8 + Rational(3, 8))
for k in range(2, 8):
assert verify_numerically(sin(x)**k, TRpower(sin(x)**k))
assert verify_numerically(cos(x)**k, TRpower(cos(x)**k))
def test_hyper_as_trig():
from sympy.simplify.fu import _osborne, _osbornei
eq = sinh(x)**2 + cosh(x)**2
t, f = hyper_as_trig(eq)
assert f(fu(t)) == cosh(2*x)
e, f = hyper_as_trig(tanh(x + y))
assert f(TR12(e)) == (tanh(x) + tanh(y))/(tanh(x)*tanh(y) + 1)
d = Dummy()
assert _osborne(sinh(x), d) == I*sin(x*d)
assert _osborne(tanh(x), d) == I*tan(x*d)
assert _osborne(coth(x), d) == cot(x*d)/I
assert _osborne(cosh(x), d) == cos(x*d)
assert _osborne(sech(x), d) == sec(x*d)
assert _osborne(csch(x), d) == csc(x*d)/I
for func in (sinh, cosh, tanh, coth, sech, csch):
h = func(pi)
assert _osbornei(_osborne(h, d), d) == h
# /!\ the _osborne functions are not meant to work
# in the o(i(trig, d), d) direction so we just check
# that they work as they are supposed to work
assert _osbornei(cos(x*y + z), y) == cosh(x + z*I)
assert _osbornei(sin(x*y + z), y) == sinh(x + z*I)/I
assert _osbornei(tan(x*y + z), y) == tanh(x + z*I)/I
assert _osbornei(cot(x*y + z), y) == coth(x + z*I)*I
assert _osbornei(sec(x*y + z), y) == sech(x + z*I)
assert _osbornei(csc(x*y + z), y) == csch(x + z*I)*I
def test_TR12i():
ta, tb, tc = [tan(i) for i in (a, b, c)]
assert TR12i((ta + tb)/(-ta*tb + 1)) == tan(a + b)
assert TR12i((ta + tb)/(ta*tb - 1)) == -tan(a + b)
assert TR12i((-ta - tb)/(ta*tb - 1)) == tan(a + b)
eq = (ta + tb)/(-ta*tb + 1)**2*(-3*ta - 3*tc)/(2*(ta*tc - 1))
assert TR12i(eq.expand()) == \
-3*tan(a + b)*tan(a + c)/(tan(a) + tan(b) - 1)/2
assert TR12i(tan(x)/sin(x)) == tan(x)/sin(x)
eq = (ta + cos(2))/(-ta*tb + 1)
assert TR12i(eq) == eq
eq = (ta + tb + 2)**2/(-ta*tb + 1)
assert TR12i(eq) == eq
eq = ta/(-ta*tb + 1)
assert TR12i(eq) == eq
eq = (((ta + tb)*(a + 1)).expand())**2/(ta*tb - 1)
assert TR12i(eq) == -(a + 1)**2*tan(a + b)
def test_TR14():
eq = (cos(x) - 1)*(cos(x) + 1)
ans = -sin(x)**2
assert TR14(eq) == ans
assert TR14(1/eq) == 1/ans
assert TR14((cos(x) - 1)**2*(cos(x) + 1)**2) == ans**2
assert TR14((cos(x) - 1)**2*(cos(x) + 1)**3) == ans**2*(cos(x) + 1)
assert TR14((cos(x) - 1)**3*(cos(x) + 1)**2) == ans**2*(cos(x) - 1)
eq = (cos(x) - 1)**y*(cos(x) + 1)**y
assert TR14(eq) == eq
eq = (cos(x) - 2)**y*(cos(x) + 1)
assert TR14(eq) == eq
eq = (tan(x) - 2)**2*(cos(x) + 1)
assert TR14(eq) == eq
i = symbols('i', integer=True)
assert TR14((cos(x) - 1)**i*(cos(x) + 1)**i) == ans**i
assert TR14((sin(x) - 1)**i*(sin(x) + 1)**i) == (-cos(x)**2)**i
# could use extraction in this case
eq = (cos(x) - 1)**(i + 1)*(cos(x) + 1)**i
assert TR14(eq) in [(cos(x) - 1)*ans**i, eq]
assert TR14((sin(x) - 1)*(sin(x) + 1)) == -cos(x)**2
p1 = (cos(x) + 1)*(cos(x) - 1)
p2 = (cos(y) - 1)*2*(cos(y) + 1)
p3 = (3*(cos(y) - 1))*(3*(cos(y) + 1))
assert TR14(p1*p2*p3*(x - 1)) == -18*((x - 1)*sin(x)**2*sin(y)**4)
def test_TR15_16_17():
assert TR15(1 - 1/sin(x)**2) == -cot(x)**2
assert TR16(1 - 1/cos(x)**2) == -tan(x)**2
assert TR111(1 - 1/tan(x)**2) == 1 - cot(x)**2
def test_as_f_sign_1():
assert as_f_sign_1(x + 1) == (1, x, 1)
assert as_f_sign_1(x - 1) == (1, x, -1)
assert as_f_sign_1(-x + 1) == (-1, x, -1)
assert as_f_sign_1(-x - 1) == (-1, x, 1)
assert as_f_sign_1(2*x + 2) == (2, x, 1)
assert as_f_sign_1(x*y - y) == (y, x, -1)
assert as_f_sign_1(-x*y + y) == (-y, x, -1)
|
ece6331148ad3639fbeb59ee6fc4fbb9fe5b39361335a6d5966887b424d77584 | from sympy.core.function import (Subs, count_ops, diff, expand)
from sympy.core.numbers import (E, I, Rational, pi)
from sympy.core.singleton import S
from sympy.core.symbol import (Symbol, symbols)
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.hyperbolic import (cosh, coth, sinh, tanh)
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.piecewise import Piecewise
from sympy.functions.elementary.trigonometric import (cos, cot, sin, tan)
from sympy.integrals.integrals import integrate
from sympy.matrices.dense import Matrix
from sympy.simplify.simplify import simplify
from sympy.simplify.trigsimp import (exptrigsimp, trigsimp)
from sympy.testing.pytest import XFAIL
from sympy.abc import x, y
def test_trigsimp1():
x, y = symbols('x,y')
assert trigsimp(1 - sin(x)**2) == cos(x)**2
assert trigsimp(1 - cos(x)**2) == sin(x)**2
assert trigsimp(sin(x)**2 + cos(x)**2) == 1
assert trigsimp(1 + tan(x)**2) == 1/cos(x)**2
assert trigsimp(1/cos(x)**2 - 1) == tan(x)**2
assert trigsimp(1/cos(x)**2 - tan(x)**2) == 1
assert trigsimp(1 + cot(x)**2) == 1/sin(x)**2
assert trigsimp(1/sin(x)**2 - 1) == 1/tan(x)**2
assert trigsimp(1/sin(x)**2 - cot(x)**2) == 1
assert trigsimp(5*cos(x)**2 + 5*sin(x)**2) == 5
assert trigsimp(5*cos(x/2)**2 + 2*sin(x/2)**2) == 3*cos(x)/2 + Rational(7, 2)
assert trigsimp(sin(x)/cos(x)) == tan(x)
assert trigsimp(2*tan(x)*cos(x)) == 2*sin(x)
assert trigsimp(cot(x)**3*sin(x)**3) == cos(x)**3
assert trigsimp(y*tan(x)**2/sin(x)**2) == y/cos(x)**2
assert trigsimp(cot(x)/cos(x)) == 1/sin(x)
assert trigsimp(sin(x + y) + sin(x - y)) == 2*sin(x)*cos(y)
assert trigsimp(sin(x + y) - sin(x - y)) == 2*sin(y)*cos(x)
assert trigsimp(cos(x + y) + cos(x - y)) == 2*cos(x)*cos(y)
assert trigsimp(cos(x + y) - cos(x - y)) == -2*sin(x)*sin(y)
assert trigsimp(tan(x + y) - tan(x)/(1 - tan(x)*tan(y))) == \
sin(y)/(-sin(y)*tan(x) + cos(y)) # -tan(y)/(tan(x)*tan(y) - 1)
assert trigsimp(sinh(x + y) + sinh(x - y)) == 2*sinh(x)*cosh(y)
assert trigsimp(sinh(x + y) - sinh(x - y)) == 2*sinh(y)*cosh(x)
assert trigsimp(cosh(x + y) + cosh(x - y)) == 2*cosh(x)*cosh(y)
assert trigsimp(cosh(x + y) - cosh(x - y)) == 2*sinh(x)*sinh(y)
assert trigsimp(tanh(x + y) - tanh(x)/(1 + tanh(x)*tanh(y))) == \
sinh(y)/(sinh(y)*tanh(x) + cosh(y))
assert trigsimp(cos(0.12345)**2 + sin(0.12345)**2) == 1
e = 2*sin(x)**2 + 2*cos(x)**2
assert trigsimp(log(e)) == log(2)
def test_trigsimp1a():
assert trigsimp(sin(2)**2*cos(3)*exp(2)/cos(2)**2) == tan(2)**2*cos(3)*exp(2)
assert trigsimp(tan(2)**2*cos(3)*exp(2)*cos(2)**2) == sin(2)**2*cos(3)*exp(2)
assert trigsimp(cot(2)*cos(3)*exp(2)*sin(2)) == cos(3)*exp(2)*cos(2)
assert trigsimp(tan(2)*cos(3)*exp(2)/sin(2)) == cos(3)*exp(2)/cos(2)
assert trigsimp(cot(2)*cos(3)*exp(2)/cos(2)) == cos(3)*exp(2)/sin(2)
assert trigsimp(cot(2)*cos(3)*exp(2)*tan(2)) == cos(3)*exp(2)
assert trigsimp(sinh(2)*cos(3)*exp(2)/cosh(2)) == tanh(2)*cos(3)*exp(2)
assert trigsimp(tanh(2)*cos(3)*exp(2)*cosh(2)) == sinh(2)*cos(3)*exp(2)
assert trigsimp(coth(2)*cos(3)*exp(2)*sinh(2)) == cosh(2)*cos(3)*exp(2)
assert trigsimp(tanh(2)*cos(3)*exp(2)/sinh(2)) == cos(3)*exp(2)/cosh(2)
assert trigsimp(coth(2)*cos(3)*exp(2)/cosh(2)) == cos(3)*exp(2)/sinh(2)
assert trigsimp(coth(2)*cos(3)*exp(2)*tanh(2)) == cos(3)*exp(2)
def test_trigsimp2():
x, y = symbols('x,y')
assert trigsimp(cos(x)**2*sin(y)**2 + cos(x)**2*cos(y)**2 + sin(x)**2,
recursive=True) == 1
assert trigsimp(sin(x)**2*sin(y)**2 + sin(x)**2*cos(y)**2 + cos(x)**2,
recursive=True) == 1
assert trigsimp(
Subs(x, x, sin(y)**2 + cos(y)**2)) == Subs(x, x, 1)
def test_issue_4373():
x = Symbol("x")
assert abs(trigsimp(2.0*sin(x)**2 + 2.0*cos(x)**2) - 2.0) < 1e-10
def test_trigsimp3():
x, y = symbols('x,y')
assert trigsimp(sin(x)/cos(x)) == tan(x)
assert trigsimp(sin(x)**2/cos(x)**2) == tan(x)**2
assert trigsimp(sin(x)**3/cos(x)**3) == tan(x)**3
assert trigsimp(sin(x)**10/cos(x)**10) == tan(x)**10
assert trigsimp(cos(x)/sin(x)) == 1/tan(x)
assert trigsimp(cos(x)**2/sin(x)**2) == 1/tan(x)**2
assert trigsimp(cos(x)**10/sin(x)**10) == 1/tan(x)**10
assert trigsimp(tan(x)) == trigsimp(sin(x)/cos(x))
def test_issue_4661():
a, x, y = symbols('a x y')
eq = -4*sin(x)**4 + 4*cos(x)**4 - 8*cos(x)**2
assert trigsimp(eq) == -4
n = sin(x)**6 + 4*sin(x)**4*cos(x)**2 + 5*sin(x)**2*cos(x)**4 + 2*cos(x)**6
d = -sin(x)**2 - 2*cos(x)**2
assert simplify(n/d) == -1
assert trigsimp(-2*cos(x)**2 + cos(x)**4 - sin(x)**4) == -1
eq = (- sin(x)**3/4)*cos(x) + (cos(x)**3/4)*sin(x) - sin(2*x)*cos(2*x)/8
assert trigsimp(eq) == 0
def test_issue_4494():
a, b = symbols('a b')
eq = sin(a)**2*sin(b)**2 + cos(a)**2*cos(b)**2*tan(a)**2 + cos(a)**2
assert trigsimp(eq) == 1
def test_issue_5948():
a, x, y = symbols('a x y')
assert trigsimp(diff(integrate(cos(x)/sin(x)**7, x), x)) == \
cos(x)/sin(x)**7
def test_issue_4775():
a, x, y = symbols('a x y')
assert trigsimp(sin(x)*cos(y)+cos(x)*sin(y)) == sin(x + y)
assert trigsimp(sin(x)*cos(y)+cos(x)*sin(y)+3) == sin(x + y) + 3
def test_issue_4280():
a, x, y = symbols('a x y')
assert trigsimp(cos(x)**2 + cos(y)**2*sin(x)**2 + sin(y)**2*sin(x)**2) == 1
assert trigsimp(a**2*sin(x)**2 + a**2*cos(y)**2*cos(x)**2 + a**2*cos(x)**2*sin(y)**2) == a**2
assert trigsimp(a**2*cos(y)**2*sin(x)**2 + a**2*sin(y)**2*sin(x)**2) == a**2*sin(x)**2
def test_issue_3210():
eqs = (sin(2)*cos(3) + sin(3)*cos(2),
-sin(2)*sin(3) + cos(2)*cos(3),
sin(2)*cos(3) - sin(3)*cos(2),
sin(2)*sin(3) + cos(2)*cos(3),
sin(2)*sin(3) + cos(2)*cos(3) + cos(2),
sinh(2)*cosh(3) + sinh(3)*cosh(2),
sinh(2)*sinh(3) + cosh(2)*cosh(3),
)
assert [trigsimp(e) for e in eqs] == [
sin(5),
cos(5),
-sin(1),
cos(1),
cos(1) + cos(2),
sinh(5),
cosh(5),
]
def test_trigsimp_issues():
a, x, y = symbols('a x y')
# issue 4625 - factor_terms works, too
assert trigsimp(sin(x)**3 + cos(x)**2*sin(x)) == sin(x)
# issue 5948
assert trigsimp(diff(integrate(cos(x)/sin(x)**3, x), x)) == \
cos(x)/sin(x)**3
assert trigsimp(diff(integrate(sin(x)/cos(x)**3, x), x)) == \
sin(x)/cos(x)**3
# check integer exponents
e = sin(x)**y/cos(x)**y
assert trigsimp(e) == e
assert trigsimp(e.subs(y, 2)) == tan(x)**2
assert trigsimp(e.subs(x, 1)) == tan(1)**y
# check for multiple patterns
assert (cos(x)**2/sin(x)**2*cos(y)**2/sin(y)**2).trigsimp() == \
1/tan(x)**2/tan(y)**2
assert trigsimp(cos(x)/sin(x)*cos(x+y)/sin(x+y)) == \
1/(tan(x)*tan(x + y))
eq = cos(2)*(cos(3) + 1)**2/(cos(3) - 1)**2
assert trigsimp(eq) == eq.factor() # factor makes denom (-1 + cos(3))**2
assert trigsimp(cos(2)*(cos(3) + 1)**2*(cos(3) - 1)**2) == \
cos(2)*sin(3)**4
# issue 6789; this generates an expression that formerly caused
# trigsimp to hang
assert cot(x).equals(tan(x)) is False
# nan or the unchanged expression is ok, but not sin(1)
z = cos(x)**2 + sin(x)**2 - 1
z1 = tan(x)**2 - 1/cot(x)**2
n = (1 + z1/z)
assert trigsimp(sin(n)) != sin(1)
eq = x*(n - 1) - x*n
assert trigsimp(eq) is S.NaN
assert trigsimp(eq, recursive=True) is S.NaN
assert trigsimp(1).is_Integer
assert trigsimp(-sin(x)**4 - 2*sin(x)**2*cos(x)**2 - cos(x)**4) == -1
def test_trigsimp_issue_2515():
x = Symbol('x')
assert trigsimp(x*cos(x)*tan(x)) == x*sin(x)
assert trigsimp(-sin(x) + cos(x)*tan(x)) == 0
def test_trigsimp_issue_3826():
assert trigsimp(tan(2*x).expand(trig=True)) == tan(2*x)
def test_trigsimp_issue_4032():
n = Symbol('n', integer=True, positive=True)
assert trigsimp(2**(n/2)*cos(pi*n/4)/2 + 2**(n - 1)/2) == \
2**(n/2)*cos(pi*n/4)/2 + 2**n/4
def test_trigsimp_issue_7761():
assert trigsimp(cosh(pi/4)) == cosh(pi/4)
def test_trigsimp_noncommutative():
x, y = symbols('x,y')
A, B = symbols('A,B', commutative=False)
assert trigsimp(A - A*sin(x)**2) == A*cos(x)**2
assert trigsimp(A - A*cos(x)**2) == A*sin(x)**2
assert trigsimp(A*sin(x)**2 + A*cos(x)**2) == A
assert trigsimp(A + A*tan(x)**2) == A/cos(x)**2
assert trigsimp(A/cos(x)**2 - A) == A*tan(x)**2
assert trigsimp(A/cos(x)**2 - A*tan(x)**2) == A
assert trigsimp(A + A*cot(x)**2) == A/sin(x)**2
assert trigsimp(A/sin(x)**2 - A) == A/tan(x)**2
assert trigsimp(A/sin(x)**2 - A*cot(x)**2) == A
assert trigsimp(y*A*cos(x)**2 + y*A*sin(x)**2) == y*A
assert trigsimp(A*sin(x)/cos(x)) == A*tan(x)
assert trigsimp(A*tan(x)*cos(x)) == A*sin(x)
assert trigsimp(A*cot(x)**3*sin(x)**3) == A*cos(x)**3
assert trigsimp(y*A*tan(x)**2/sin(x)**2) == y*A/cos(x)**2
assert trigsimp(A*cot(x)/cos(x)) == A/sin(x)
assert trigsimp(A*sin(x + y) + A*sin(x - y)) == 2*A*sin(x)*cos(y)
assert trigsimp(A*sin(x + y) - A*sin(x - y)) == 2*A*sin(y)*cos(x)
assert trigsimp(A*cos(x + y) + A*cos(x - y)) == 2*A*cos(x)*cos(y)
assert trigsimp(A*cos(x + y) - A*cos(x - y)) == -2*A*sin(x)*sin(y)
assert trigsimp(A*sinh(x + y) + A*sinh(x - y)) == 2*A*sinh(x)*cosh(y)
assert trigsimp(A*sinh(x + y) - A*sinh(x - y)) == 2*A*sinh(y)*cosh(x)
assert trigsimp(A*cosh(x + y) + A*cosh(x - y)) == 2*A*cosh(x)*cosh(y)
assert trigsimp(A*cosh(x + y) - A*cosh(x - y)) == 2*A*sinh(x)*sinh(y)
assert trigsimp(A*cos(0.12345)**2 + A*sin(0.12345)**2) == 1.0*A
def test_hyperbolic_simp():
x, y = symbols('x,y')
assert trigsimp(sinh(x)**2 + 1) == cosh(x)**2
assert trigsimp(cosh(x)**2 - 1) == sinh(x)**2
assert trigsimp(cosh(x)**2 - sinh(x)**2) == 1
assert trigsimp(1 - tanh(x)**2) == 1/cosh(x)**2
assert trigsimp(1 - 1/cosh(x)**2) == tanh(x)**2
assert trigsimp(tanh(x)**2 + 1/cosh(x)**2) == 1
assert trigsimp(coth(x)**2 - 1) == 1/sinh(x)**2
assert trigsimp(1/sinh(x)**2 + 1) == 1/tanh(x)**2
assert trigsimp(coth(x)**2 - 1/sinh(x)**2) == 1
assert trigsimp(5*cosh(x)**2 - 5*sinh(x)**2) == 5
assert trigsimp(5*cosh(x/2)**2 - 2*sinh(x/2)**2) == 3*cosh(x)/2 + Rational(7, 2)
assert trigsimp(sinh(x)/cosh(x)) == tanh(x)
assert trigsimp(tanh(x)) == trigsimp(sinh(x)/cosh(x))
assert trigsimp(cosh(x)/sinh(x)) == 1/tanh(x)
assert trigsimp(2*tanh(x)*cosh(x)) == 2*sinh(x)
assert trigsimp(coth(x)**3*sinh(x)**3) == cosh(x)**3
assert trigsimp(y*tanh(x)**2/sinh(x)**2) == y/cosh(x)**2
assert trigsimp(coth(x)/cosh(x)) == 1/sinh(x)
for a in (pi/6*I, pi/4*I, pi/3*I):
assert trigsimp(sinh(a)*cosh(x) + cosh(a)*sinh(x)) == sinh(x + a)
assert trigsimp(-sinh(a)*cosh(x) + cosh(a)*sinh(x)) == sinh(x - a)
e = 2*cosh(x)**2 - 2*sinh(x)**2
assert trigsimp(log(e)) == log(2)
# issue 19535:
assert trigsimp(sqrt(cosh(x)**2 - 1)) == sqrt(sinh(x)**2)
assert trigsimp(cosh(x)**2*cosh(y)**2 - cosh(x)**2*sinh(y)**2 - sinh(x)**2,
recursive=True) == 1
assert trigsimp(sinh(x)**2*sinh(y)**2 - sinh(x)**2*cosh(y)**2 + cosh(x)**2,
recursive=True) == 1
assert abs(trigsimp(2.0*cosh(x)**2 - 2.0*sinh(x)**2) - 2.0) < 1e-10
assert trigsimp(sinh(x)**2/cosh(x)**2) == tanh(x)**2
assert trigsimp(sinh(x)**3/cosh(x)**3) == tanh(x)**3
assert trigsimp(sinh(x)**10/cosh(x)**10) == tanh(x)**10
assert trigsimp(cosh(x)**3/sinh(x)**3) == 1/tanh(x)**3
assert trigsimp(cosh(x)/sinh(x)) == 1/tanh(x)
assert trigsimp(cosh(x)**2/sinh(x)**2) == 1/tanh(x)**2
assert trigsimp(cosh(x)**10/sinh(x)**10) == 1/tanh(x)**10
assert trigsimp(x*cosh(x)*tanh(x)) == x*sinh(x)
assert trigsimp(-sinh(x) + cosh(x)*tanh(x)) == 0
assert tan(x) != 1/cot(x) # cot doesn't auto-simplify
assert trigsimp(tan(x) - 1/cot(x)) == 0
assert trigsimp(3*tanh(x)**7 - 2/coth(x)**7) == tanh(x)**7
def test_trigsimp_groebner():
from sympy.simplify.trigsimp import trigsimp_groebner
c = cos(x)
s = sin(x)
ex = (4*s*c + 12*s + 5*c**3 + 21*c**2 + 23*c + 15)/(
-s*c**2 + 2*s*c + 15*s + 7*c**3 + 31*c**2 + 37*c + 21)
resnum = (5*s - 5*c + 1)
resdenom = (8*s - 6*c)
results = [resnum/resdenom, (-resnum)/(-resdenom)]
assert trigsimp_groebner(ex) in results
assert trigsimp_groebner(s/c, hints=[tan]) == tan(x)
assert trigsimp_groebner(c*s) == c*s
assert trigsimp((-s + 1)/c + c/(-s + 1),
method='groebner') == 2/c
assert trigsimp((-s + 1)/c + c/(-s + 1),
method='groebner', polynomial=True) == 2/c
# Test quick=False works
assert trigsimp_groebner(ex, hints=[2]) in results
assert trigsimp_groebner(ex, hints=[int(2)]) in results
# test "I"
assert trigsimp_groebner(sin(I*x)/cos(I*x), hints=[tanh]) == I*tanh(x)
# test hyperbolic / sums
assert trigsimp_groebner((tanh(x)+tanh(y))/(1+tanh(x)*tanh(y)),
hints=[(tanh, x, y)]) == tanh(x + y)
def test_issue_2827_trigsimp_methods():
measure1 = lambda expr: len(str(expr))
measure2 = lambda expr: -count_ops(expr)
# Return the most complicated result
expr = (x + 1)/(x + sin(x)**2 + cos(x)**2)
ans = Matrix([1])
M = Matrix([expr])
assert trigsimp(M, method='fu', measure=measure1) == ans
assert trigsimp(M, method='fu', measure=measure2) != ans
# all methods should work with Basic expressions even if they
# aren't Expr
M = Matrix.eye(1)
assert all(trigsimp(M, method=m) == M for m in
'fu matching groebner old'.split())
# watch for E in exptrigsimp, not only exp()
eq = 1/sqrt(E) + E
assert exptrigsimp(eq) == eq
def test_issue_15129_trigsimp_methods():
t1 = Matrix([sin(Rational(1, 50)), cos(Rational(1, 50)), 0])
t2 = Matrix([sin(Rational(1, 25)), cos(Rational(1, 25)), 0])
t3 = Matrix([cos(Rational(1, 25)), sin(Rational(1, 25)), 0])
r1 = t1.dot(t2)
r2 = t1.dot(t3)
assert trigsimp(r1) == cos(Rational(1, 50))
assert trigsimp(r2) == sin(Rational(3, 50))
def test_exptrigsimp():
def valid(a, b):
from sympy.testing.randtest import verify_numerically as tn
if not (tn(a, b) and a == b):
return False
return True
assert exptrigsimp(exp(x) + exp(-x)) == 2*cosh(x)
assert exptrigsimp(exp(x) - exp(-x)) == 2*sinh(x)
assert exptrigsimp((2*exp(x)-2*exp(-x))/(exp(x)+exp(-x))) == 2*tanh(x)
assert exptrigsimp((2*exp(2*x)-2)/(exp(2*x)+1)) == 2*tanh(x)
e = [cos(x) + I*sin(x), cos(x) - I*sin(x),
cosh(x) - sinh(x), cosh(x) + sinh(x)]
ok = [exp(I*x), exp(-I*x), exp(-x), exp(x)]
assert all(valid(i, j) for i, j in zip(
[exptrigsimp(ei) for ei in e], ok))
ue = [cos(x) + sin(x), cos(x) - sin(x),
cosh(x) + I*sinh(x), cosh(x) - I*sinh(x)]
assert [exptrigsimp(ei) == ei for ei in ue]
res = []
ok = [y*tanh(1), 1/(y*tanh(1)), I*y*tan(1), -I/(y*tan(1)),
y*tanh(x), 1/(y*tanh(x)), I*y*tan(x), -I/(y*tan(x)),
y*tanh(1 + I), 1/(y*tanh(1 + I))]
for a in (1, I, x, I*x, 1 + I):
w = exp(a)
eq = y*(w - 1/w)/(w + 1/w)
res.append(simplify(eq))
res.append(simplify(1/eq))
assert all(valid(i, j) for i, j in zip(res, ok))
for a in range(1, 3):
w = exp(a)
e = w + 1/w
s = simplify(e)
assert s == exptrigsimp(e)
assert valid(s, 2*cosh(a))
e = w - 1/w
s = simplify(e)
assert s == exptrigsimp(e)
assert valid(s, 2*sinh(a))
def test_exptrigsimp_noncommutative():
a,b = symbols('a b', commutative=False)
x = Symbol('x', commutative=True)
assert exp(a + x) == exptrigsimp(exp(a)*exp(x))
p = exp(a)*exp(b) - exp(b)*exp(a)
assert p == exptrigsimp(p) != 0
def test_powsimp_on_numbers():
assert 2**(Rational(1, 3) - 2) == 2**Rational(1, 3)/4
@XFAIL
def test_issue_6811_fail():
# from doc/src/modules/physics/mechanics/examples.rst, the current `eq`
# at Line 576 (in different variables) was formerly the equivalent and
# shorter expression given below...it would be nice to get the short one
# back again
xp, y, x, z = symbols('xp, y, x, z')
eq = 4*(-19*sin(x)*y + 5*sin(3*x)*y + 15*cos(2*x)*z - 21*z)*xp/(9*cos(x) - 5*cos(3*x))
assert trigsimp(eq) == -2*(2*cos(x)*tan(x)*y + 3*z)*xp/cos(x)
def test_Piecewise():
e1 = x*(x + y) - y*(x + y)
e2 = sin(x)**2 + cos(x)**2
e3 = expand((x + y)*y/x)
# s1 = simplify(e1)
s2 = simplify(e2)
# s3 = simplify(e3)
# trigsimp tries not to touch non-trig containing args
assert trigsimp(Piecewise((e1, e3 < e2), (e3, True))) == \
Piecewise((e1, e3 < s2), (e3, True))
def test_issue_21594():
assert simplify(exp(Rational(1,2)) + exp(Rational(-1,2))) == cosh(S.Half)*2
def test_trigsimp_old():
x, y = symbols('x,y')
assert trigsimp(1 - sin(x)**2, old=True) == cos(x)**2
assert trigsimp(1 - cos(x)**2, old=True) == sin(x)**2
assert trigsimp(sin(x)**2 + cos(x)**2, old=True) == 1
assert trigsimp(1 + tan(x)**2, old=True) == 1/cos(x)**2
assert trigsimp(1/cos(x)**2 - 1, old=True) == tan(x)**2
assert trigsimp(1/cos(x)**2 - tan(x)**2, old=True) == 1
assert trigsimp(1 + cot(x)**2, old=True) == 1/sin(x)**2
assert trigsimp(1/sin(x)**2 - cot(x)**2, old=True) == 1
assert trigsimp(5*cos(x)**2 + 5*sin(x)**2, old=True) == 5
assert trigsimp(sin(x)/cos(x), old=True) == tan(x)
assert trigsimp(2*tan(x)*cos(x), old=True) == 2*sin(x)
assert trigsimp(cot(x)**3*sin(x)**3, old=True) == cos(x)**3
assert trigsimp(y*tan(x)**2/sin(x)**2, old=True) == y/cos(x)**2
assert trigsimp(cot(x)/cos(x), old=True) == 1/sin(x)
assert trigsimp(sin(x + y) + sin(x - y), old=True) == 2*sin(x)*cos(y)
assert trigsimp(sin(x + y) - sin(x - y), old=True) == 2*sin(y)*cos(x)
assert trigsimp(cos(x + y) + cos(x - y), old=True) == 2*cos(x)*cos(y)
assert trigsimp(cos(x + y) - cos(x - y), old=True) == -2*sin(x)*sin(y)
assert trigsimp(sinh(x + y) + sinh(x - y), old=True) == 2*sinh(x)*cosh(y)
assert trigsimp(sinh(x + y) - sinh(x - y), old=True) == 2*sinh(y)*cosh(x)
assert trigsimp(cosh(x + y) + cosh(x - y), old=True) == 2*cosh(x)*cosh(y)
assert trigsimp(cosh(x + y) - cosh(x - y), old=True) == 2*sinh(x)*sinh(y)
assert trigsimp(cos(0.12345)**2 + sin(0.12345)**2, old=True) == 1
assert trigsimp(sin(x)/cos(x), old=True, method='combined') == tan(x)
assert trigsimp(sin(x)/cos(x), old=True, method='groebner') == sin(x)/cos(x)
assert trigsimp(sin(x)/cos(x), old=True, method='groebner', hints=[tan]) == tan(x)
assert trigsimp(1-sin(sin(x)**2+cos(x)**2)**2, old=True, deep=True) == cos(1)**2
|
2093f398517ec111480dd1dad89c3a135308e78658af311dd82e200c698f98f2 | from sympy.core.add import Add
from sympy.core.function import (Derivative, Function, diff)
from sympy.core.mul import Mul
from sympy.core.numbers import (I, Rational)
from sympy.core.power import Pow
from sympy.core.singleton import S
from sympy.core.symbol import (Symbol, Wild, symbols)
from sympy.functions.elementary.complexes import Abs
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.miscellaneous import (root, sqrt)
from sympy.functions.elementary.trigonometric import (cos, sin)
from sympy.polys.polytools import factor
from sympy.series.order import O
from sympy.simplify.radsimp import (collect, collect_const, fraction, radsimp, rcollect)
from sympy.core.expr import unchanged
from sympy.core.mul import _unevaluated_Mul as umul
from sympy.simplify.radsimp import (_unevaluated_Add,
collect_sqrt, fraction_expand, collect_abs)
from sympy.testing.pytest import raises
from sympy.abc import x, y, z, a, b, c, d
def test_radsimp():
r2 = sqrt(2)
r3 = sqrt(3)
r5 = sqrt(5)
r7 = sqrt(7)
assert fraction(radsimp(1/r2)) == (sqrt(2), 2)
assert radsimp(1/(1 + r2)) == \
-1 + sqrt(2)
assert radsimp(1/(r2 + r3)) == \
-sqrt(2) + sqrt(3)
assert fraction(radsimp(1/(1 + r2 + r3))) == \
(-sqrt(6) + sqrt(2) + 2, 4)
assert fraction(radsimp(1/(r2 + r3 + r5))) == \
(-sqrt(30) + 2*sqrt(3) + 3*sqrt(2), 12)
assert fraction(radsimp(1/(1 + r2 + r3 + r5))) == (
(-34*sqrt(10) - 26*sqrt(15) - 55*sqrt(3) - 61*sqrt(2) + 14*sqrt(30) +
93 + 46*sqrt(6) + 53*sqrt(5), 71))
assert fraction(radsimp(1/(r2 + r3 + r5 + r7))) == (
(-50*sqrt(42) - 133*sqrt(5) - 34*sqrt(70) - 145*sqrt(3) + 22*sqrt(105)
+ 185*sqrt(2) + 62*sqrt(30) + 135*sqrt(7), 215))
z = radsimp(1/(1 + r2/3 + r3/5 + r5 + r7))
assert len((3616791619821680643598*z).args) == 16
assert radsimp(1/z) == 1/z
assert radsimp(1/z, max_terms=20).expand() == 1 + r2/3 + r3/5 + r5 + r7
assert radsimp(1/(r2*3)) == \
sqrt(2)/6
assert radsimp(1/(r2*a + r3 + r5 + r7)) == (
(8*sqrt(2)*a**7 - 8*sqrt(7)*a**6 - 8*sqrt(5)*a**6 - 8*sqrt(3)*a**6 -
180*sqrt(2)*a**5 + 8*sqrt(30)*a**5 + 8*sqrt(42)*a**5 + 8*sqrt(70)*a**5
- 24*sqrt(105)*a**4 + 84*sqrt(3)*a**4 + 100*sqrt(5)*a**4 +
116*sqrt(7)*a**4 - 72*sqrt(70)*a**3 - 40*sqrt(42)*a**3 -
8*sqrt(30)*a**3 + 782*sqrt(2)*a**3 - 462*sqrt(3)*a**2 -
302*sqrt(7)*a**2 - 254*sqrt(5)*a**2 + 120*sqrt(105)*a**2 -
795*sqrt(2)*a - 62*sqrt(30)*a + 82*sqrt(42)*a + 98*sqrt(70)*a -
118*sqrt(105) + 59*sqrt(7) + 295*sqrt(5) + 531*sqrt(3))/(16*a**8 -
480*a**6 + 3128*a**4 - 6360*a**2 + 3481))
assert radsimp(1/(r2*a + r2*b + r3 + r7)) == (
(sqrt(2)*a*(a + b)**2 - 5*sqrt(2)*a + sqrt(42)*a + sqrt(2)*b*(a +
b)**2 - 5*sqrt(2)*b + sqrt(42)*b - sqrt(7)*(a + b)**2 - sqrt(3)*(a +
b)**2 - 2*sqrt(3) + 2*sqrt(7))/(2*a**4 + 8*a**3*b + 12*a**2*b**2 -
20*a**2 + 8*a*b**3 - 40*a*b + 2*b**4 - 20*b**2 + 8))
assert radsimp(1/(r2*a + r2*b + r2*c + r2*d)) == \
sqrt(2)/(2*a + 2*b + 2*c + 2*d)
assert radsimp(1/(1 + r2*a + r2*b + r2*c + r2*d)) == (
(sqrt(2)*a + sqrt(2)*b + sqrt(2)*c + sqrt(2)*d - 1)/(2*a**2 + 4*a*b +
4*a*c + 4*a*d + 2*b**2 + 4*b*c + 4*b*d + 2*c**2 + 4*c*d + 2*d**2 - 1))
assert radsimp((y**2 - x)/(y - sqrt(x))) == \
sqrt(x) + y
assert radsimp(-(y**2 - x)/(y - sqrt(x))) == \
-(sqrt(x) + y)
assert radsimp(1/(1 - I + a*I)) == \
(-I*a + 1 + I)/(a**2 - 2*a + 2)
assert radsimp(1/((-x + y)*(x - sqrt(y)))) == \
(-x - sqrt(y))/((x - y)*(x**2 - y))
e = (3 + 3*sqrt(2))*x*(3*x - 3*sqrt(y))
assert radsimp(e) == x*(3 + 3*sqrt(2))*(3*x - 3*sqrt(y))
assert radsimp(1/e) == (
(-9*x + 9*sqrt(2)*x - 9*sqrt(y) + 9*sqrt(2)*sqrt(y))/(9*x*(9*x**2 -
9*y)))
assert radsimp(1 + 1/(1 + sqrt(3))) == \
Mul(S.Half, -1 + sqrt(3), evaluate=False) + 1
A = symbols("A", commutative=False)
assert radsimp(x**2 + sqrt(2)*x**2 - sqrt(2)*x*A) == \
x**2 + sqrt(2)*x**2 - sqrt(2)*x*A
assert radsimp(1/sqrt(5 + 2 * sqrt(6))) == -sqrt(2) + sqrt(3)
assert radsimp(1/sqrt(5 + 2 * sqrt(6))**3) == -(-sqrt(3) + sqrt(2))**3
# issue 6532
assert fraction(radsimp(1/sqrt(x))) == (sqrt(x), x)
assert fraction(radsimp(1/sqrt(2*x + 3))) == (sqrt(2*x + 3), 2*x + 3)
assert fraction(radsimp(1/sqrt(2*(x + 3)))) == (sqrt(2*x + 6), 2*x + 6)
# issue 5994
e = S('-(2 + 2*sqrt(2) + 4*2**(1/4))/'
'(1 + 2**(3/4) + 3*2**(1/4) + 3*sqrt(2))')
assert radsimp(e).expand() == -2*2**Rational(3, 4) - 2*2**Rational(1, 4) + 2 + 2*sqrt(2)
# issue 5986 (modifications to radimp didn't initially recognize this so
# the test is included here)
assert radsimp(1/(-sqrt(5)/2 - S.Half + (-sqrt(5)/2 - S.Half)**2)) == 1
# from issue 5934
eq = (
(-240*sqrt(2)*sqrt(sqrt(5) + 5)*sqrt(8*sqrt(5) + 40) -
360*sqrt(2)*sqrt(-8*sqrt(5) + 40)*sqrt(-sqrt(5) + 5) -
120*sqrt(10)*sqrt(-8*sqrt(5) + 40)*sqrt(-sqrt(5) + 5) +
120*sqrt(2)*sqrt(-sqrt(5) + 5)*sqrt(8*sqrt(5) + 40) +
120*sqrt(2)*sqrt(-8*sqrt(5) + 40)*sqrt(sqrt(5) + 5) +
120*sqrt(10)*sqrt(-sqrt(5) + 5)*sqrt(8*sqrt(5) + 40) +
120*sqrt(10)*sqrt(-8*sqrt(5) + 40)*sqrt(sqrt(5) + 5))/(-36000 -
7200*sqrt(5) + (12*sqrt(10)*sqrt(sqrt(5) + 5) +
24*sqrt(10)*sqrt(-sqrt(5) + 5))**2))
assert radsimp(eq) is S.NaN # it's 0/0
# work with normal form
e = 1/sqrt(sqrt(7)/7 + 2*sqrt(2) + 3*sqrt(3) + 5*sqrt(5)) + 3
assert radsimp(e) == (
-sqrt(sqrt(7) + 14*sqrt(2) + 21*sqrt(3) +
35*sqrt(5))*(-11654899*sqrt(35) - 1577436*sqrt(210) - 1278438*sqrt(15)
- 1346996*sqrt(10) + 1635060*sqrt(6) + 5709765 + 7539830*sqrt(14) +
8291415*sqrt(21))/1300423175 + 3)
# obey power rules
base = sqrt(3) - sqrt(2)
assert radsimp(1/base**3) == (sqrt(3) + sqrt(2))**3
assert radsimp(1/(-base)**3) == -(sqrt(2) + sqrt(3))**3
assert radsimp(1/(-base)**x) == (-base)**(-x)
assert radsimp(1/base**x) == (sqrt(2) + sqrt(3))**x
assert radsimp(root(1/(-1 - sqrt(2)), -x)) == (-1)**(-1/x)*(1 + sqrt(2))**(1/x)
# recurse
e = cos(1/(1 + sqrt(2)))
assert radsimp(e) == cos(-sqrt(2) + 1)
assert radsimp(e/2) == cos(-sqrt(2) + 1)/2
assert radsimp(1/e) == 1/cos(-sqrt(2) + 1)
assert radsimp(2/e) == 2/cos(-sqrt(2) + 1)
assert fraction(radsimp(e/sqrt(x))) == (sqrt(x)*cos(-sqrt(2)+1), x)
# test that symbolic denominators are not processed
r = 1 + sqrt(2)
assert radsimp(x/r, symbolic=False) == -x*(-sqrt(2) + 1)
assert radsimp(x/(y + r), symbolic=False) == x/(y + 1 + sqrt(2))
assert radsimp(x/(y + r)/r, symbolic=False) == \
-x*(-sqrt(2) + 1)/(y + 1 + sqrt(2))
# issue 7408
eq = sqrt(x)/sqrt(y)
assert radsimp(eq) == umul(sqrt(x), sqrt(y), 1/y)
assert radsimp(eq, symbolic=False) == eq
# issue 7498
assert radsimp(sqrt(x)/sqrt(y)**3) == umul(sqrt(x), sqrt(y**3), 1/y**3)
# for coverage
eq = sqrt(x)/y**2
assert radsimp(eq) == eq
def test_radsimp_issue_3214():
c, p = symbols('c p', positive=True)
s = sqrt(c**2 - p**2)
b = (c + I*p - s)/(c + I*p + s)
assert radsimp(b) == -I*(c + I*p - sqrt(c**2 - p**2))**2/(2*c*p)
def test_collect_1():
"""Collect with respect to a Symbol"""
x, y, z, n = symbols('x,y,z,n')
assert collect(1, x) == 1
assert collect( x + y*x, x ) == x * (1 + y)
assert collect( x + x**2, x ) == x + x**2
assert collect( x**2 + y*x**2, x ) == (x**2)*(1 + y)
assert collect( x**2 + y*x, x ) == x*y + x**2
assert collect( 2*x**2 + y*x**2 + 3*x*y, [x] ) == x**2*(2 + y) + 3*x*y
assert collect( 2*x**2 + y*x**2 + 3*x*y, [y] ) == 2*x**2 + y*(x**2 + 3*x)
assert collect( ((1 + y + x)**4).expand(), x) == ((1 + y)**4).expand() + \
x*(4*(1 + y)**3).expand() + x**2*(6*(1 + y)**2).expand() + \
x**3*(4*(1 + y)).expand() + x**4
# symbols can be given as any iterable
expr = x + y
assert collect(expr, expr.free_symbols) == expr
def test_collect_2():
"""Collect with respect to a sum"""
a, b, x = symbols('a,b,x')
assert collect(a*(cos(x) + sin(x)) + b*(cos(x) + sin(x)),
sin(x) + cos(x)) == (a + b)*(cos(x) + sin(x))
def test_collect_3():
"""Collect with respect to a product"""
a, b, c = symbols('a,b,c')
f = Function('f')
x, y, z, n = symbols('x,y,z,n')
assert collect(-x/8 + x*y, -x) == x*(y - Rational(1, 8))
assert collect( 1 + x*(y**2), x*y ) == 1 + x*(y**2)
assert collect( x*y + a*x*y, x*y) == x*y*(1 + a)
assert collect( 1 + x*y + a*x*y, x*y) == 1 + x*y*(1 + a)
assert collect(a*x*f(x) + b*(x*f(x)), x*f(x)) == x*(a + b)*f(x)
assert collect(a*x*log(x) + b*(x*log(x)), x*log(x)) == x*(a + b)*log(x)
assert collect(a*x**2*log(x)**2 + b*(x*log(x))**2, x*log(x)) == \
x**2*log(x)**2*(a + b)
# with respect to a product of three symbols
assert collect(y*x*z + a*x*y*z, x*y*z) == (1 + a)*x*y*z
def test_collect_4():
"""Collect with respect to a power"""
a, b, c, x = symbols('a,b,c,x')
assert collect(a*x**c + b*x**c, x**c) == x**c*(a + b)
# issue 6096: 2 stays with c (unless c is integer or x is positive0
assert collect(a*x**(2*c) + b*x**(2*c), x**c) == x**(2*c)*(a + b)
def test_collect_5():
"""Collect with respect to a tuple"""
a, x, y, z, n = symbols('a,x,y,z,n')
assert collect(x**2*y**4 + z*(x*y**2)**2 + z + a*z, [x*y**2, z]) in [
z*(1 + a + x**2*y**4) + x**2*y**4,
z*(1 + a) + x**2*y**4*(1 + z) ]
assert collect((1 + (x + y) + (x + y)**2).expand(),
[x, y]) == 1 + y + x*(1 + 2*y) + x**2 + y**2
def test_collect_pr19431():
"""Unevaluated collect with respect to a product"""
a = symbols('a')
assert collect(a**2*(a**2 + 1), a**2, evaluate=False)[a**2] == (a**2 + 1)
def test_collect_D():
D = Derivative
f = Function('f')
x, a, b = symbols('x,a,b')
fx = D(f(x), x)
fxx = D(f(x), x, x)
assert collect(a*fx + b*fx, fx) == (a + b)*fx
assert collect(a*D(fx, x) + b*D(fx, x), fx) == (a + b)*D(fx, x)
assert collect(a*fxx + b*fxx, fx) == (a + b)*D(fx, x)
# issue 4784
assert collect(5*f(x) + 3*fx, fx) == 5*f(x) + 3*fx
assert collect(f(x) + f(x)*diff(f(x), x) + x*diff(f(x), x)*f(x), f(x).diff(x)) == \
(x*f(x) + f(x))*D(f(x), x) + f(x)
assert collect(f(x) + f(x)*diff(f(x), x) + x*diff(f(x), x)*f(x), f(x).diff(x), exact=True) == \
(x*f(x) + f(x))*D(f(x), x) + f(x)
assert collect(1/f(x) + 1/f(x)*diff(f(x), x) + x*diff(f(x), x)/f(x), f(x).diff(x), exact=True) == \
(1/f(x) + x/f(x))*D(f(x), x) + 1/f(x)
e = (1 + x*fx + fx)/f(x)
assert collect(e.expand(), fx) == fx*(x/f(x) + 1/f(x)) + 1/f(x)
def test_collect_func():
f = ((x + a + 1)**3).expand()
assert collect(f, x) == a**3 + 3*a**2 + 3*a + x**3 + x**2*(3*a + 3) + \
x*(3*a**2 + 6*a + 3) + 1
assert collect(f, x, factor) == x**3 + 3*x**2*(a + 1) + 3*x*(a + 1)**2 + \
(a + 1)**3
assert collect(f, x, evaluate=False) == {
S.One: a**3 + 3*a**2 + 3*a + 1,
x: 3*a**2 + 6*a + 3, x**2: 3*a + 3,
x**3: 1
}
assert collect(f, x, factor, evaluate=False) == {
S.One: (a + 1)**3, x: 3*(a + 1)**2,
x**2: umul(S(3), a + 1), x**3: 1}
def test_collect_order():
a, b, x, t = symbols('a,b,x,t')
assert collect(t + t*x + t*x**2 + O(x**3), t) == t*(1 + x + x**2 + O(x**3))
assert collect(t + t*x + x**2 + O(x**3), t) == \
t*(1 + x + O(x**3)) + x**2 + O(x**3)
f = a*x + b*x + c*x**2 + d*x**2 + O(x**3)
g = x*(a + b) + x**2*(c + d) + O(x**3)
assert collect(f, x) == g
assert collect(f, x, distribute_order_term=False) == g
f = sin(a + b).series(b, 0, 10)
assert collect(f, [sin(a), cos(a)]) == \
sin(a)*cos(b).series(b, 0, 10) + cos(a)*sin(b).series(b, 0, 10)
assert collect(f, [sin(a), cos(a)], distribute_order_term=False) == \
sin(a)*cos(b).series(b, 0, 10).removeO() + \
cos(a)*sin(b).series(b, 0, 10).removeO() + O(b**10)
def test_rcollect():
assert rcollect((x**2*y + x*y + x + y)/(x + y), y) == \
(x + y*(1 + x + x**2))/(x + y)
assert rcollect(sqrt(-((x + 1)*(y + 1))), z) == sqrt(-((x + 1)*(y + 1)))
def test_collect_D_0():
D = Derivative
f = Function('f')
x, a, b = symbols('x,a,b')
fxx = D(f(x), x, x)
assert collect(a*fxx + b*fxx, fxx) == (a + b)*fxx
def test_collect_Wild():
"""Collect with respect to functions with Wild argument"""
a, b, x, y = symbols('a b x y')
f = Function('f')
w1 = Wild('.1')
w2 = Wild('.2')
assert collect(f(x) + a*f(x), f(w1)) == (1 + a)*f(x)
assert collect(f(x, y) + a*f(x, y), f(w1)) == f(x, y) + a*f(x, y)
assert collect(f(x, y) + a*f(x, y), f(w1, w2)) == (1 + a)*f(x, y)
assert collect(f(x, y) + a*f(x, y), f(w1, w1)) == f(x, y) + a*f(x, y)
assert collect(f(x, x) + a*f(x, x), f(w1, w1)) == (1 + a)*f(x, x)
assert collect(a*(x + 1)**y + (x + 1)**y, w1**y) == (1 + a)*(x + 1)**y
assert collect(a*(x + 1)**y + (x + 1)**y, w1**b) == \
a*(x + 1)**y + (x + 1)**y
assert collect(a*(x + 1)**y + (x + 1)**y, (x + 1)**w2) == \
(1 + a)*(x + 1)**y
assert collect(a*(x + 1)**y + (x + 1)**y, w1**w2) == (1 + a)*(x + 1)**y
def test_collect_const():
# coverage not provided by above tests
assert collect_const(2*sqrt(3) + 4*a*sqrt(5)) == \
2*(2*sqrt(5)*a + sqrt(3)) # let the primitive reabsorb
assert collect_const(2*sqrt(3) + 4*a*sqrt(5), sqrt(3)) == \
2*sqrt(3) + 4*a*sqrt(5)
assert collect_const(sqrt(2)*(1 + sqrt(2)) + sqrt(3) + x*sqrt(2)) == \
sqrt(2)*(x + 1 + sqrt(2)) + sqrt(3)
# issue 5290
assert collect_const(2*x + 2*y + 1, 2) == \
collect_const(2*x + 2*y + 1) == \
Add(S.One, Mul(2, x + y, evaluate=False), evaluate=False)
assert collect_const(-y - z) == Mul(-1, y + z, evaluate=False)
assert collect_const(2*x - 2*y - 2*z, 2) == \
Mul(2, x - y - z, evaluate=False)
assert collect_const(2*x - 2*y - 2*z, -2) == \
_unevaluated_Add(2*x, Mul(-2, y + z, evaluate=False))
# this is why the content_primitive is used
eq = (sqrt(15 + 5*sqrt(2))*x + sqrt(3 + sqrt(2))*y)*2
assert collect_sqrt(eq + 2) == \
2*sqrt(sqrt(2) + 3)*(sqrt(5)*x + y) + 2
# issue 16296
assert collect_const(a + b + x/2 + y/2) == a + b + Mul(S.Half, x + y, evaluate=False)
def test_issue_13143():
f = Function('f')
fx = f(x).diff(x)
e = f(x) + fx + f(x)*fx
# collect function before derivative
assert collect(e, Wild('w')) == f(x)*(fx + 1) + fx
e = f(x) + f(x)*fx + x*fx*f(x)
assert collect(e, fx) == (x*f(x) + f(x))*fx + f(x)
assert collect(e, f(x)) == (x*fx + fx + 1)*f(x)
e = f(x) + fx + f(x)*fx
assert collect(e, [f(x), fx]) == f(x)*(1 + fx) + fx
assert collect(e, [fx, f(x)]) == fx*(1 + f(x)) + f(x)
def test_issue_6097():
assert collect(a*y**(2.0*x) + b*y**(2.0*x), y**x) == (a + b)*(y**x)**2.0
assert collect(a*2**(2.0*x) + b*2**(2.0*x), 2**x) == (a + b)*(2**x)**2.0
def test_fraction_expand():
eq = (x + y)*y/x
assert eq.expand(frac=True) == fraction_expand(eq) == (x*y + y**2)/x
assert eq.expand() == y + y**2/x
def test_fraction():
x, y, z = map(Symbol, 'xyz')
A = Symbol('A', commutative=False)
assert fraction(S.Half) == (1, 2)
assert fraction(x) == (x, 1)
assert fraction(1/x) == (1, x)
assert fraction(x/y) == (x, y)
assert fraction(x/2) == (x, 2)
assert fraction(x*y/z) == (x*y, z)
assert fraction(x/(y*z)) == (x, y*z)
assert fraction(1/y**2) == (1, y**2)
assert fraction(x/y**2) == (x, y**2)
assert fraction((x**2 + 1)/y) == (x**2 + 1, y)
assert fraction(x*(y + 1)/y**7) == (x*(y + 1), y**7)
assert fraction(exp(-x), exact=True) == (exp(-x), 1)
assert fraction((1/(x + y))/2, exact=True) == (1, Mul(2,(x + y), evaluate=False))
assert fraction(x*A/y) == (x*A, y)
assert fraction(x*A**-1/y) == (x*A**-1, y)
n = symbols('n', negative=True)
assert fraction(exp(n)) == (1, exp(-n))
assert fraction(exp(-n)) == (exp(-n), 1)
p = symbols('p', positive=True)
assert fraction(exp(-p)*log(p), exact=True) == (exp(-p)*log(p), 1)
m = Mul(1, 1, S.Half, evaluate=False)
assert fraction(m) == (1, 2)
assert fraction(m, exact=True) == (Mul(1, 1, evaluate=False), 2)
m = Mul(1, 1, S.Half, S.Half, Pow(1, -1, evaluate=False), evaluate=False)
assert fraction(m) == (1, 4)
assert fraction(m, exact=True) == \
(Mul(1, 1, evaluate=False), Mul(2, 2, 1, evaluate=False))
def test_issue_5615():
aA, Re, a, b, D = symbols('aA Re a b D')
e = ((D**3*a + b*aA**3)/Re).expand()
assert collect(e, [aA**3/Re, a]) == e
def test_issue_5933():
from sympy.geometry.polygon import (Polygon, RegularPolygon)
from sympy.simplify.radsimp import denom
x = Polygon(*RegularPolygon((0, 0), 1, 5).vertices).centroid.x
assert abs(denom(x).n()) > 1e-12
assert abs(denom(radsimp(x))) > 1e-12 # in case simplify didn't handle it
def test_issue_14608():
a, b = symbols('a b', commutative=False)
x, y = symbols('x y')
raises(AttributeError, lambda: collect(a*b + b*a, a))
assert collect(x*y + y*(x+1), a) == x*y + y*(x+1)
assert collect(x*y + y*(x+1) + a*b + b*a, y) == y*(2*x + 1) + a*b + b*a
def test_collect_abs():
s = abs(x) + abs(y)
assert collect_abs(s) == s
assert unchanged(Mul, abs(x), abs(y))
ans = Abs(x*y)
assert isinstance(ans, Abs)
assert collect_abs(abs(x)*abs(y)) == ans
assert collect_abs(1 + exp(abs(x)*abs(y))) == 1 + exp(ans)
# See https://github.com/sympy/sympy/issues/12910
p = Symbol('p', positive=True)
assert collect_abs(p/abs(1-p)).is_commutative is True
def test_issue_19149():
eq = exp(3*x/4)
assert collect(eq, exp(x)) == eq
def test_issue_19719():
a, b = symbols('a, b')
expr = a**2 * (b + 1) + (7 + 1/b)/a
collected = collect(expr, (a**2, 1/a), evaluate=False)
# Would return {_Dummy_20**(-2): b + 1, 1/a: 7 + 1/b} without xreplace
assert collected == {a**2: b + 1, 1/a: 7 + 1/b}
def test_issue_21355():
assert radsimp(1/(x + sqrt(x**2))) == 1/(x + sqrt(x**2))
assert radsimp(1/(x - sqrt(x**2))) == 1/(x - sqrt(x**2))
|
2d98f857a6bde46263d68dcd94a4681cc93bb1618f012165c36e27b26e33e379 | from sympy.core.numbers import I
from sympy.core.symbol import symbols
from sympy.functions.elementary.exponential import exp
from sympy.functions.elementary.trigonometric import (cos, cot, sin)
from sympy.testing.pytest import _both_exp_pow
x, y, z, n = symbols('x,y,z,n')
@_both_exp_pow
def test_has():
assert cot(x).has(x)
assert cot(x).has(cot)
assert not cot(x).has(sin)
assert sin(x).has(x)
assert sin(x).has(sin)
assert not sin(x).has(cot)
assert exp(x).has(exp)
@_both_exp_pow
def test_sin_exp_rewrite():
assert sin(x).rewrite(sin, exp) == -I/2*(exp(I*x) - exp(-I*x))
assert sin(x).rewrite(sin, exp).rewrite(exp, sin) == sin(x)
assert cos(x).rewrite(cos, exp).rewrite(exp, cos) == cos(x)
assert (sin(5*y) - sin(
2*x)).rewrite(sin, exp).rewrite(exp, sin) == sin(5*y) - sin(2*x)
assert sin(x + y).rewrite(sin, exp).rewrite(exp, sin) == sin(x + y)
assert cos(x + y).rewrite(cos, exp).rewrite(exp, cos) == cos(x + y)
# This next test currently passes... not clear whether it should or not?
assert cos(x).rewrite(cos, exp).rewrite(exp, sin) == cos(x)
|
f9c08573320822c844e1dd33a21899ea8210a5ec07356af05d8e021721ee4f61 | from sympy.core.function import Function
from sympy.core.mul import Mul
from sympy.core.numbers import (E, I, Rational, oo, pi)
from sympy.core.singleton import S
from sympy.core.symbol import (Dummy, Symbol, symbols)
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.miscellaneous import (root, sqrt)
from sympy.functions.elementary.trigonometric import sin
from sympy.functions.special.gamma_functions import gamma
from sympy.functions.special.hyper import hyper
from sympy.matrices.expressions.matexpr import MatrixSymbol
from sympy.simplify.powsimp import (powdenest, powsimp)
from sympy.simplify.simplify import (signsimp, simplify)
from sympy.core.symbol import Str
from sympy.abc import x, y, z, a, b
def test_powsimp():
x, y, z, n = symbols('x,y,z,n')
f = Function('f')
assert powsimp( 4**x * 2**(-x) * 2**(-x) ) == 1
assert powsimp( (-4)**x * (-2)**(-x) * 2**(-x) ) == 1
assert powsimp(
f(4**x * 2**(-x) * 2**(-x)) ) == f(4**x * 2**(-x) * 2**(-x))
assert powsimp( f(4**x * 2**(-x) * 2**(-x)), deep=True ) == f(1)
assert exp(x)*exp(y) == exp(x)*exp(y)
assert powsimp(exp(x)*exp(y)) == exp(x + y)
assert powsimp(exp(x)*exp(y)*2**x*2**y) == (2*E)**(x + y)
assert powsimp(exp(x)*exp(y)*2**x*2**y, combine='exp') == \
exp(x + y)*2**(x + y)
assert powsimp(exp(x)*exp(y)*exp(2)*sin(x) + sin(y) + 2**x*2**y) == \
exp(2 + x + y)*sin(x) + sin(y) + 2**(x + y)
assert powsimp(sin(exp(x)*exp(y))) == sin(exp(x)*exp(y))
assert powsimp(sin(exp(x)*exp(y)), deep=True) == sin(exp(x + y))
assert powsimp(x**2*x**y) == x**(2 + y)
# This should remain factored, because 'exp' with deep=True is supposed
# to act like old automatic exponent combining.
assert powsimp((1 + E*exp(E))*exp(-E), combine='exp', deep=True) == \
(1 + exp(1 + E))*exp(-E)
assert powsimp((1 + E*exp(E))*exp(-E), deep=True) == \
(1 + exp(1 + E))*exp(-E)
assert powsimp((1 + E*exp(E))*exp(-E)) == (1 + exp(1 + E))*exp(-E)
assert powsimp((1 + E*exp(E))*exp(-E), combine='exp') == \
(1 + exp(1 + E))*exp(-E)
assert powsimp((1 + E*exp(E))*exp(-E), combine='base') == \
(1 + E*exp(E))*exp(-E)
x, y = symbols('x,y', nonnegative=True)
n = Symbol('n', real=True)
assert powsimp(y**n * (y/x)**(-n)) == x**n
assert powsimp(x**(x**(x*y)*y**(x*y))*y**(x**(x*y)*y**(x*y)), deep=True) \
== (x*y)**(x*y)**(x*y)
assert powsimp(2**(2**(2*x)*x), deep=False) == 2**(2**(2*x)*x)
assert powsimp(2**(2**(2*x)*x), deep=True) == 2**(x*4**x)
assert powsimp(
exp(-x + exp(-x)*exp(-x*log(x))), deep=False, combine='exp') == \
exp(-x + exp(-x)*exp(-x*log(x)))
assert powsimp(
exp(-x + exp(-x)*exp(-x*log(x))), deep=False, combine='exp') == \
exp(-x + exp(-x)*exp(-x*log(x)))
assert powsimp((x + y)/(3*z), deep=False, combine='exp') == (x + y)/(3*z)
assert powsimp((x/3 + y/3)/z, deep=True, combine='exp') == (x/3 + y/3)/z
assert powsimp(exp(x)/(1 + exp(x)*exp(y)), deep=True) == \
exp(x)/(1 + exp(x + y))
assert powsimp(x*y**(z**x*z**y), deep=True) == x*y**(z**(x + y))
assert powsimp((z**x*z**y)**x, deep=True) == (z**(x + y))**x
assert powsimp(x*(z**x*z**y)**x, deep=True) == x*(z**(x + y))**x
p = symbols('p', positive=True)
assert powsimp((1/x)**log(2)/x) == (1/x)**(1 + log(2))
assert powsimp((1/p)**log(2)/p) == p**(-1 - log(2))
# coefficient of exponent can only be simplified for positive bases
assert powsimp(2**(2*x)) == 4**x
assert powsimp((-1)**(2*x)) == (-1)**(2*x)
i = symbols('i', integer=True)
assert powsimp((-1)**(2*i)) == 1
assert powsimp((-1)**(-x)) != (-1)**x # could be 1/((-1)**x), but is not
# force=True overrides assumptions
assert powsimp((-1)**(2*x), force=True) == 1
# rational exponents allow combining of negative terms
w, n, m = symbols('w n m', negative=True)
e = i/a # not a rational exponent if `a` is unknown
ex = w**e*n**e*m**e
assert powsimp(ex) == m**(i/a)*n**(i/a)*w**(i/a)
e = i/3
ex = w**e*n**e*m**e
assert powsimp(ex) == (-1)**i*(-m*n*w)**(i/3)
e = (3 + i)/i
ex = w**e*n**e*m**e
assert powsimp(ex) == (-1)**(3*e)*(-m*n*w)**e
eq = x**(a*Rational(2, 3))
# eq != (x**a)**(2/3) (try x = -1 and a = 3 to see)
assert powsimp(eq).exp == eq.exp == a*Rational(2, 3)
# powdenest goes the other direction
assert powsimp(2**(2*x)) == 4**x
assert powsimp(exp(p/2)) == exp(p/2)
# issue 6368
eq = Mul(*[sqrt(Dummy(imaginary=True)) for i in range(3)])
assert powsimp(eq) == eq and eq.is_Mul
assert all(powsimp(e) == e for e in (sqrt(x**a), sqrt(x**2)))
# issue 8836
assert str( powsimp(exp(I*pi/3)*root(-1,3)) ) == '(-1)**(2/3)'
# issue 9183
assert powsimp(-0.1**x) == -0.1**x
# issue 10095
assert powsimp((1/(2*E))**oo) == (exp(-1)/2)**oo
# PR 13131
eq = sin(2*x)**2*sin(2.0*x)**2
assert powsimp(eq) == eq
# issue 14615
assert powsimp(x**2*y**3*(x*y**2)**Rational(3, 2)
) == x*y*(x*y**2)**Rational(5, 2)
def test_powsimp_negated_base():
assert powsimp((-x + y)/sqrt(x - y)) == -sqrt(x - y)
assert powsimp((-x + y)*(-z + y)/sqrt(x - y)/sqrt(z - y)) == sqrt(x - y)*sqrt(z - y)
p = symbols('p', positive=True)
reps = {p: 2, a: S.Half}
assert powsimp((-p)**a/p**a).subs(reps) == ((-1)**a).subs(reps)
assert powsimp((-p)**a*p**a).subs(reps) == ((-p**2)**a).subs(reps)
n = symbols('n', negative=True)
reps = {p: -2, a: S.Half}
assert powsimp((-n)**a/n**a).subs(reps) == (-1)**(-a).subs(a, S.Half)
assert powsimp((-n)**a*n**a).subs(reps) == ((-n**2)**a).subs(reps)
# if x is 0 then the lhs is 0**a*oo**a which is not (-1)**a
eq = (-x)**a/x**a
assert powsimp(eq) == eq
def test_powsimp_nc():
x, y, z = symbols('x,y,z')
A, B, C = symbols('A B C', commutative=False)
assert powsimp(A**x*A**y, combine='all') == A**(x + y)
assert powsimp(A**x*A**y, combine='base') == A**x*A**y
assert powsimp(A**x*A**y, combine='exp') == A**(x + y)
assert powsimp(A**x*B**x, combine='all') == A**x*B**x
assert powsimp(A**x*B**x, combine='base') == A**x*B**x
assert powsimp(A**x*B**x, combine='exp') == A**x*B**x
assert powsimp(B**x*A**x, combine='all') == B**x*A**x
assert powsimp(B**x*A**x, combine='base') == B**x*A**x
assert powsimp(B**x*A**x, combine='exp') == B**x*A**x
assert powsimp(A**x*A**y*A**z, combine='all') == A**(x + y + z)
assert powsimp(A**x*A**y*A**z, combine='base') == A**x*A**y*A**z
assert powsimp(A**x*A**y*A**z, combine='exp') == A**(x + y + z)
assert powsimp(A**x*B**x*C**x, combine='all') == A**x*B**x*C**x
assert powsimp(A**x*B**x*C**x, combine='base') == A**x*B**x*C**x
assert powsimp(A**x*B**x*C**x, combine='exp') == A**x*B**x*C**x
assert powsimp(B**x*A**x*C**x, combine='all') == B**x*A**x*C**x
assert powsimp(B**x*A**x*C**x, combine='base') == B**x*A**x*C**x
assert powsimp(B**x*A**x*C**x, combine='exp') == B**x*A**x*C**x
def test_issue_6440():
assert powsimp(16*2**a*8**b) == 2**(a + 3*b + 4)
def test_powdenest():
x, y = symbols('x,y')
p, q = symbols('p q', positive=True)
i, j = symbols('i,j', integer=True)
assert powdenest(x) == x
assert powdenest(x + 2*(x**(a*Rational(2, 3)))**(3*x)) == (x + 2*(x**(a*Rational(2, 3)))**(3*x))
assert powdenest((exp(a*Rational(2, 3)))**(3*x)) # -X-> (exp(a/3))**(6*x)
assert powdenest((x**(a*Rational(2, 3)))**(3*x)) == ((x**(a*Rational(2, 3)))**(3*x))
assert powdenest(exp(3*x*log(2))) == 2**(3*x)
assert powdenest(sqrt(p**2)) == p
eq = p**(2*i)*q**(4*i)
assert powdenest(eq) == (p*q**2)**(2*i)
# -X-> (x**x)**i*(x**x)**j == x**(x*(i + j))
assert powdenest((x**x)**(i + j))
assert powdenest(exp(3*y*log(x))) == x**(3*y)
assert powdenest(exp(y*(log(a) + log(b)))) == (a*b)**y
assert powdenest(exp(3*(log(a) + log(b)))) == a**3*b**3
assert powdenest(((x**(2*i))**(3*y))**x) == ((x**(2*i))**(3*y))**x
assert powdenest(((x**(2*i))**(3*y))**x, force=True) == x**(6*i*x*y)
assert powdenest(((x**(a*Rational(2, 3)))**(3*y/i))**x) == \
(((x**(a*Rational(2, 3)))**(3*y/i))**x)
assert powdenest((x**(2*i)*y**(4*i))**z, force=True) == (x*y**2)**(2*i*z)
assert powdenest((p**(2*i)*q**(4*i))**j) == (p*q**2)**(2*i*j)
e = ((p**(2*a))**(3*y))**x
assert powdenest(e) == e
e = ((x**2*y**4)**a)**(x*y)
assert powdenest(e) == e
e = (((x**2*y**4)**a)**(x*y))**3
assert powdenest(e) == ((x**2*y**4)**a)**(3*x*y)
assert powdenest((((x**2*y**4)**a)**(x*y)), force=True) == \
(x*y**2)**(2*a*x*y)
assert powdenest((((x**2*y**4)**a)**(x*y))**3, force=True) == \
(x*y**2)**(6*a*x*y)
assert powdenest((x**2*y**6)**i) != (x*y**3)**(2*i)
x, y = symbols('x,y', positive=True)
assert powdenest((x**2*y**6)**i) == (x*y**3)**(2*i)
assert powdenest((x**(i*Rational(2, 3))*y**(i/2))**(2*i)) == (x**Rational(4, 3)*y)**(i**2)
assert powdenest(sqrt(x**(2*i)*y**(6*i))) == (x*y**3)**i
assert powdenest(4**x) == 2**(2*x)
assert powdenest((4**x)**y) == 2**(2*x*y)
assert powdenest(4**x*y) == 2**(2*x)*y
def test_powdenest_polar():
x, y, z = symbols('x y z', polar=True)
a, b, c = symbols('a b c')
assert powdenest((x*y*z)**a) == x**a*y**a*z**a
assert powdenest((x**a*y**b)**c) == x**(a*c)*y**(b*c)
assert powdenest(((x**a)**b*y**c)**c) == x**(a*b*c)*y**(c**2)
def test_issue_5805():
arg = ((gamma(x)*hyper((), (), x))*pi)**2
assert powdenest(arg) == (pi*gamma(x)*hyper((), (), x))**2
assert arg.is_positive is None
def test_issue_9324_powsimp_on_matrix_symbol():
M = MatrixSymbol('M', 10, 10)
expr = powsimp(M, deep=True)
assert expr == M
assert expr.args[0] == Str('M')
def test_issue_6367():
z = -5*sqrt(2)/(2*sqrt(2*sqrt(29) + 29)) + sqrt(-sqrt(29)/29 + S.Half)
assert Mul(*[powsimp(a) for a in Mul.make_args(z.normal())]) == 0
assert powsimp(z.normal()) == 0
assert simplify(z) == 0
assert powsimp(sqrt(2 + sqrt(3))*sqrt(2 - sqrt(3)) + 1) == 2
assert powsimp(z) != 0
def test_powsimp_polar():
from sympy.functions.elementary.complexes import polar_lift
from sympy.functions.elementary.exponential import exp_polar
x, y, z = symbols('x y z')
p, q, r = symbols('p q r', polar=True)
assert (polar_lift(-1))**(2*x) == exp_polar(2*pi*I*x)
assert powsimp(p**x * q**x) == (p*q)**x
assert p**x * (1/p)**x == 1
assert (1/p)**x == p**(-x)
assert exp_polar(x)*exp_polar(y) == exp_polar(x)*exp_polar(y)
assert powsimp(exp_polar(x)*exp_polar(y)) == exp_polar(x + y)
assert powsimp(exp_polar(x)*exp_polar(y)*p**x*p**y) == \
(p*exp_polar(1))**(x + y)
assert powsimp(exp_polar(x)*exp_polar(y)*p**x*p**y, combine='exp') == \
exp_polar(x + y)*p**(x + y)
assert powsimp(
exp_polar(x)*exp_polar(y)*exp_polar(2)*sin(x) + sin(y) + p**x*p**y) \
== p**(x + y) + sin(x)*exp_polar(2 + x + y) + sin(y)
assert powsimp(sin(exp_polar(x)*exp_polar(y))) == \
sin(exp_polar(x)*exp_polar(y))
assert powsimp(sin(exp_polar(x)*exp_polar(y)), deep=True) == \
sin(exp_polar(x + y))
def test_issue_5728():
b = x*sqrt(y)
a = sqrt(b)
c = sqrt(sqrt(x)*y)
assert powsimp(a*b) == sqrt(b)**3
assert powsimp(a*b**2*sqrt(y)) == sqrt(y)*a**5
assert powsimp(a*x**2*c**3*y) == c**3*a**5
assert powsimp(a*x*c**3*y**2) == c**7*a
assert powsimp(x*c**3*y**2) == c**7
assert powsimp(x*c**3*y) == x*y*c**3
assert powsimp(sqrt(x)*c**3*y) == c**5
assert powsimp(sqrt(x)*a**3*sqrt(y)) == sqrt(x)*sqrt(y)*a**3
assert powsimp(Mul(sqrt(x)*c**3*sqrt(y), y, evaluate=False)) == \
sqrt(x)*sqrt(y)**3*c**3
assert powsimp(a**2*a*x**2*y) == a**7
# symbolic powers work, too
b = x**y*y
a = b*sqrt(b)
assert a.is_Mul is True
assert powsimp(a) == sqrt(b)**3
# as does exp
a = x*exp(y*Rational(2, 3))
assert powsimp(a*sqrt(a)) == sqrt(a)**3
assert powsimp(a**2*sqrt(a)) == sqrt(a)**5
assert powsimp(a**2*sqrt(sqrt(a))) == sqrt(sqrt(a))**9
def test_issue_from_PR1599():
n1, n2, n3, n4 = symbols('n1 n2 n3 n4', negative=True)
assert (powsimp(sqrt(n1)*sqrt(n2)*sqrt(n3)) ==
-I*sqrt(-n1)*sqrt(-n2)*sqrt(-n3))
assert (powsimp(root(n1, 3)*root(n2, 3)*root(n3, 3)*root(n4, 3)) ==
-(-1)**Rational(1, 3)*
(-n1)**Rational(1, 3)*(-n2)**Rational(1, 3)*(-n3)**Rational(1, 3)*(-n4)**Rational(1, 3))
def test_issue_10195():
a = Symbol('a', integer=True)
l = Symbol('l', even=True, nonzero=True)
n = Symbol('n', odd=True)
e_x = (-1)**(n/2 - S.Half) - (-1)**(n*Rational(3, 2) - S.Half)
assert powsimp((-1)**(l/2)) == I**l
assert powsimp((-1)**(n/2)) == I**n
assert powsimp((-1)**(n*Rational(3, 2))) == -I**n
assert powsimp(e_x) == (-1)**(n/2 - S.Half) + (-1)**(n*Rational(3, 2) +
S.Half)
assert powsimp((-1)**(a*Rational(3, 2))) == (-I)**a
def test_issue_15709():
assert powsimp(3**x*Rational(2, 3)) == 2*3**(x-1)
assert powsimp(2*3**x/3) == 2*3**(x-1)
def test_issue_11981():
x, y = symbols('x y', commutative=False)
assert powsimp((x*y)**2 * (y*x)**2) == (x*y)**2 * (y*x)**2
def test_issue_17524():
a = symbols("a", real=True)
e = (-1 - a**2)*sqrt(1 + a**2)
assert signsimp(powsimp(e)) == signsimp(e) == -(a**2 + 1)**(S(3)/2)
def test_issue_19627():
# if you use force the user must verify
assert powdenest(sqrt(sin(x)**2), force=True) == sin(x)
assert powdenest((x**(S.Half/y))**(2*y), force=True) == x
from sympy.core.function import expand_power_base
e = 1 - a
expr = (exp(z/e)*x**(b/e)*y**((1 - b)/e))**e
assert powdenest(expand_power_base(expr, force=True), force=True
) == x**b*y**(1 - b)*exp(z)
|
3bde564b10afa367c342cf9495aac07127f4ffc3373ee4d1efa9614440e8340f | from sympy.core.numbers import Rational
from sympy.core.symbol import symbols
from sympy.functions.combinatorial.factorials import (FallingFactorial, RisingFactorial, binomial, factorial)
from sympy.functions.special.gamma_functions import gamma
from sympy.simplify.combsimp import combsimp
from sympy.abc import x
def test_combsimp():
k, m, n = symbols('k m n', integer = True)
assert combsimp(factorial(n)) == factorial(n)
assert combsimp(binomial(n, k)) == binomial(n, k)
assert combsimp(factorial(n)/factorial(n - 3)) == n*(-1 + n)*(-2 + n)
assert combsimp(binomial(n + 1, k + 1)/binomial(n, k)) == (1 + n)/(1 + k)
assert combsimp(binomial(3*n + 4, n + 1)/binomial(3*n + 1, n)) == \
Rational(3, 2)*((3*n + 2)*(3*n + 4)/((n + 1)*(2*n + 3)))
assert combsimp(factorial(n)**2/factorial(n - 3)) == \
factorial(n)*n*(-1 + n)*(-2 + n)
assert combsimp(factorial(n)*binomial(n + 1, k + 1)/binomial(n, k)) == \
factorial(n + 1)/(1 + k)
assert combsimp(gamma(n + 3)) == factorial(n + 2)
assert combsimp(factorial(x)) == gamma(x + 1)
# issue 9699
assert combsimp((n + 1)*factorial(n)) == factorial(n + 1)
assert combsimp(factorial(n)/n) == factorial(n-1)
# issue 6658
assert combsimp(binomial(n, n - k)) == binomial(n, k)
# issue 6341, 7135
assert combsimp(factorial(n)/(factorial(k)*factorial(n - k))) == \
binomial(n, k)
assert combsimp(factorial(k)*factorial(n - k)/factorial(n)) == \
1/binomial(n, k)
assert combsimp(factorial(2*n)/factorial(n)**2) == binomial(2*n, n)
assert combsimp(factorial(2*n)*factorial(k)*factorial(n - k)/
factorial(n)**3) == binomial(2*n, n)/binomial(n, k)
assert combsimp(factorial(n*(1 + n) - n**2 - n)) == 1
assert combsimp(6*FallingFactorial(-4, n)/factorial(n)) == \
(-1)**n*(n + 1)*(n + 2)*(n + 3)
assert combsimp(6*FallingFactorial(-4, n - 1)/factorial(n - 1)) == \
(-1)**(n - 1)*n*(n + 1)*(n + 2)
assert combsimp(6*FallingFactorial(-4, n - 3)/factorial(n - 3)) == \
(-1)**(n - 3)*n*(n - 1)*(n - 2)
assert combsimp(6*FallingFactorial(-4, -n - 1)/factorial(-n - 1)) == \
-(-1)**(-n - 1)*n*(n - 1)*(n - 2)
assert combsimp(6*RisingFactorial(4, n)/factorial(n)) == \
(n + 1)*(n + 2)*(n + 3)
assert combsimp(6*RisingFactorial(4, n - 1)/factorial(n - 1)) == \
n*(n + 1)*(n + 2)
assert combsimp(6*RisingFactorial(4, n - 3)/factorial(n - 3)) == \
n*(n - 1)*(n - 2)
assert combsimp(6*RisingFactorial(4, -n - 1)/factorial(-n - 1)) == \
-n*(n - 1)*(n - 2)
def test_issue_6878():
n = symbols('n', integer=True)
assert combsimp(RisingFactorial(-10, n)) == 3628800*(-1)**n/factorial(10 - n)
def test_issue_14528():
p = symbols("p", integer=True, positive=True)
assert combsimp(binomial(1,p)) == 1/(factorial(p)*factorial(1-p))
assert combsimp(factorial(2-p)) == factorial(2-p)
|
a249c2efebeb418b40174dd37c09f7a0463b435a5c24f3af6d6c231d2a66e77c | from random import randrange
from sympy.simplify.hyperexpand import (ShiftA, ShiftB, UnShiftA, UnShiftB,
MeijerShiftA, MeijerShiftB, MeijerShiftC, MeijerShiftD,
MeijerUnShiftA, MeijerUnShiftB, MeijerUnShiftC,
MeijerUnShiftD,
ReduceOrder, reduce_order, apply_operators,
devise_plan, make_derivative_operator, Formula,
hyperexpand, Hyper_Function, G_Function,
reduce_order_meijer,
build_hypergeometric_formula)
from sympy.concrete.summations import Sum
from sympy.core.containers import Tuple
from sympy.core.expr import Expr
from sympy.core.numbers import I
from sympy.core.singleton import S
from sympy.core.symbol import symbols
from sympy.functions.combinatorial.factorials import binomial
from sympy.functions.elementary.piecewise import Piecewise
from sympy.functions.special.hyper import (hyper, meijerg)
from sympy.abc import z, a, b, c
from sympy.testing.pytest import XFAIL, raises, slow, ON_TRAVIS, skip
from sympy.testing.randtest import verify_numerically as tn
from sympy.core.numbers import (Rational, pi)
from sympy.functions.elementary.exponential import (exp, exp_polar, log)
from sympy.functions.elementary.hyperbolic import atanh
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.trigonometric import (asin, cos, sin)
from sympy.functions.special.bessel import besseli
from sympy.functions.special.error_functions import erf
from sympy.functions.special.gamma_functions import (gamma, lowergamma)
def test_branch_bug():
assert hyperexpand(hyper((Rational(-1, 3), S.Half), (Rational(2, 3), Rational(3, 2)), -z)) == \
-z**S('1/3')*lowergamma(exp_polar(I*pi)/3, z)/5 \
+ sqrt(pi)*erf(sqrt(z))/(5*sqrt(z))
assert hyperexpand(meijerg([Rational(7, 6), 1], [], [Rational(2, 3)], [Rational(1, 6), 0], z)) == \
2*z**S('2/3')*(2*sqrt(pi)*erf(sqrt(z))/sqrt(z) - 2*lowergamma(
Rational(2, 3), z)/z**S('2/3'))*gamma(Rational(2, 3))/gamma(Rational(5, 3))
def test_hyperexpand():
# Luke, Y. L. (1969), The Special Functions and Their Approximations,
# Volume 1, section 6.2
assert hyperexpand(hyper([], [], z)) == exp(z)
assert hyperexpand(hyper([1, 1], [2], -z)*z) == log(1 + z)
assert hyperexpand(hyper([], [S.Half], -z**2/4)) == cos(z)
assert hyperexpand(z*hyper([], [S('3/2')], -z**2/4)) == sin(z)
assert hyperexpand(hyper([S('1/2'), S('1/2')], [S('3/2')], z**2)*z) \
== asin(z)
assert isinstance(Sum(binomial(2, z)*z**2, (z, 0, a)).doit(), Expr)
def can_do(ap, bq, numerical=True, div=1, lowerplane=False):
r = hyperexpand(hyper(ap, bq, z))
if r.has(hyper):
return False
if not numerical:
return True
repl = {}
randsyms = r.free_symbols - {z}
while randsyms:
# Only randomly generated parameters are checked.
for n, ai in enumerate(randsyms):
repl[ai] = randcplx(n)/div
if not any(b.is_Integer and b <= 0 for b in Tuple(*bq).subs(repl)):
break
[a, b, c, d] = [2, -1, 3, 1]
if lowerplane:
[a, b, c, d] = [2, -2, 3, -1]
return tn(
hyper(ap, bq, z).subs(repl),
r.replace(exp_polar, exp).subs(repl),
z, a=a, b=b, c=c, d=d)
def test_roach():
# Kelly B. Roach. Meijer G Function Representations.
# Section "Gallery"
assert can_do([S.Half], [Rational(9, 2)])
assert can_do([], [1, Rational(5, 2), 4])
assert can_do([Rational(-1, 2), 1, 2], [3, 4])
assert can_do([Rational(1, 3)], [Rational(-2, 3), Rational(-1, 2), S.Half, 1])
assert can_do([Rational(-3, 2), Rational(-1, 2)], [Rational(-5, 2), 1])
assert can_do([Rational(-3, 2), ], [Rational(-1, 2), S.Half]) # shine-integral
assert can_do([Rational(-3, 2), Rational(-1, 2)], [2]) # elliptic integrals
@XFAIL
def test_roach_fail():
assert can_do([Rational(-1, 2), 1], [Rational(1, 4), S.Half, Rational(3, 4)]) # PFDD
assert can_do([Rational(3, 2)], [Rational(5, 2), 5]) # struve function
assert can_do([Rational(-1, 2), S.Half, 1], [Rational(3, 2), Rational(5, 2)]) # polylog, pfdd
assert can_do([1, 2, 3], [S.Half, 4]) # XXX ?
assert can_do([S.Half], [Rational(-1, 3), Rational(-1, 2), Rational(-2, 3)]) # PFDD ?
# For the long table tests, see end of file
def test_polynomial():
from sympy.core.numbers import oo
assert hyperexpand(hyper([], [-1], z)) is oo
assert hyperexpand(hyper([-2], [-1], z)) is oo
assert hyperexpand(hyper([0, 0], [-1], z)) == 1
assert can_do([-5, -2, randcplx(), randcplx()], [-10, randcplx()])
assert hyperexpand(hyper((-1, 1), (-2,), z)) == 1 + z/2
def test_hyperexpand_bases():
assert hyperexpand(hyper([2], [a], z)) == \
a + z**(-a + 1)*(-a**2 + 3*a + z*(a - 1) - 2)*exp(z)* \
lowergamma(a - 1, z) - 1
# TODO [a+1, aRational(-1, 2)], [2*a]
assert hyperexpand(hyper([1, 2], [3], z)) == -2/z - 2*log(-z + 1)/z**2
assert hyperexpand(hyper([S.Half, 2], [Rational(3, 2)], z)) == \
-1/(2*z - 2) + atanh(sqrt(z))/sqrt(z)/2
assert hyperexpand(hyper([S.Half, S.Half], [Rational(5, 2)], z)) == \
(-3*z + 3)/4/(z*sqrt(-z + 1)) \
+ (6*z - 3)*asin(sqrt(z))/(4*z**Rational(3, 2))
assert hyperexpand(hyper([1, 2], [Rational(3, 2)], z)) == -1/(2*z - 2) \
- asin(sqrt(z))/(sqrt(z)*(2*z - 2)*sqrt(-z + 1))
assert hyperexpand(hyper([Rational(-1, 2) - 1, 1, 2], [S.Half, 3], z)) == \
sqrt(z)*(z*Rational(6, 7) - Rational(6, 5))*atanh(sqrt(z)) \
+ (-30*z**2 + 32*z - 6)/35/z - 6*log(-z + 1)/(35*z**2)
assert hyperexpand(hyper([1 + S.Half, 1, 1], [2, 2], z)) == \
-4*log(sqrt(-z + 1)/2 + S.Half)/z
# TODO hyperexpand(hyper([a], [2*a + 1], z))
# TODO [S.Half, a], [Rational(3, 2), a+1]
assert hyperexpand(hyper([2], [b, 1], z)) == \
z**(-b/2 + S.Half)*besseli(b - 1, 2*sqrt(z))*gamma(b) \
+ z**(-b/2 + 1)*besseli(b, 2*sqrt(z))*gamma(b)
# TODO [a], [a - S.Half, 2*a]
def test_hyperexpand_parametric():
assert hyperexpand(hyper([a, S.Half + a], [S.Half], z)) \
== (1 + sqrt(z))**(-2*a)/2 + (1 - sqrt(z))**(-2*a)/2
assert hyperexpand(hyper([a, Rational(-1, 2) + a], [2*a], z)) \
== 2**(2*a - 1)*((-z + 1)**S.Half + 1)**(-2*a + 1)
def test_shifted_sum():
from sympy.simplify.simplify import simplify
assert simplify(hyperexpand(z**4*hyper([2], [3, S('3/2')], -z**2))) \
== z*sin(2*z) + (-z**2 + S.Half)*cos(2*z) - S.Half
def _randrat():
""" Steer clear of integers. """
return S(randrange(25) + 10)/50
def randcplx(offset=-1):
""" Polys is not good with real coefficients. """
return _randrat() + I*_randrat() + I*(1 + offset)
@slow
def test_formulae():
from sympy.simplify.hyperexpand import FormulaCollection
formulae = FormulaCollection().formulae
for formula in formulae:
h = formula.func(formula.z)
rep = {}
for n, sym in enumerate(formula.symbols):
rep[sym] = randcplx(n)
# NOTE hyperexpand returns truly branched functions. We know we are
# on the main sheet, but numerical evaluation can still go wrong
# (e.g. if exp_polar cannot be evalf'd).
# Just replace all exp_polar by exp, this usually works.
# first test if the closed-form is actually correct
h = h.subs(rep)
closed_form = formula.closed_form.subs(rep).rewrite('nonrepsmall')
z = formula.z
assert tn(h, closed_form.replace(exp_polar, exp), z)
# now test the computed matrix
cl = (formula.C * formula.B)[0].subs(rep).rewrite('nonrepsmall')
assert tn(closed_form.replace(
exp_polar, exp), cl.replace(exp_polar, exp), z)
deriv1 = z*formula.B.applyfunc(lambda t: t.rewrite(
'nonrepsmall')).diff(z)
deriv2 = formula.M * formula.B
for d1, d2 in zip(deriv1, deriv2):
assert tn(d1.subs(rep).replace(exp_polar, exp),
d2.subs(rep).rewrite('nonrepsmall').replace(exp_polar, exp), z)
def test_meijerg_formulae():
from sympy.simplify.hyperexpand import MeijerFormulaCollection
formulae = MeijerFormulaCollection().formulae
for sig in formulae:
for formula in formulae[sig]:
g = meijerg(formula.func.an, formula.func.ap,
formula.func.bm, formula.func.bq,
formula.z)
rep = {}
for sym in formula.symbols:
rep[sym] = randcplx()
# first test if the closed-form is actually correct
g = g.subs(rep)
closed_form = formula.closed_form.subs(rep)
z = formula.z
assert tn(g, closed_form, z)
# now test the computed matrix
cl = (formula.C * formula.B)[0].subs(rep)
assert tn(closed_form, cl, z)
deriv1 = z*formula.B.diff(z)
deriv2 = formula.M * formula.B
for d1, d2 in zip(deriv1, deriv2):
assert tn(d1.subs(rep), d2.subs(rep), z)
def op(f):
return z*f.diff(z)
def test_plan():
assert devise_plan(Hyper_Function([0], ()),
Hyper_Function([0], ()), z) == []
with raises(ValueError):
devise_plan(Hyper_Function([1], ()), Hyper_Function((), ()), z)
with raises(ValueError):
devise_plan(Hyper_Function([2], [1]), Hyper_Function([2], [2]), z)
with raises(ValueError):
devise_plan(Hyper_Function([2], []), Hyper_Function([S("1/2")], []), z)
# We cannot use pi/(10000 + n) because polys is insanely slow.
a1, a2, b1 = (randcplx(n) for n in range(3))
b1 += 2*I
h = hyper([a1, a2], [b1], z)
h2 = hyper((a1 + 1, a2), [b1], z)
assert tn(apply_operators(h,
devise_plan(Hyper_Function((a1 + 1, a2), [b1]),
Hyper_Function((a1, a2), [b1]), z), op),
h2, z)
h2 = hyper((a1 + 1, a2 - 1), [b1], z)
assert tn(apply_operators(h,
devise_plan(Hyper_Function((a1 + 1, a2 - 1), [b1]),
Hyper_Function((a1, a2), [b1]), z), op),
h2, z)
def test_plan_derivatives():
a1, a2, a3 = 1, 2, S('1/2')
b1, b2 = 3, S('5/2')
h = Hyper_Function((a1, a2, a3), (b1, b2))
h2 = Hyper_Function((a1 + 1, a2 + 1, a3 + 2), (b1 + 1, b2 + 1))
ops = devise_plan(h2, h, z)
f = Formula(h, z, h(z), [])
deriv = make_derivative_operator(f.M, z)
assert tn((apply_operators(f.C, ops, deriv)*f.B)[0], h2(z), z)
h2 = Hyper_Function((a1, a2 - 1, a3 - 2), (b1 - 1, b2 - 1))
ops = devise_plan(h2, h, z)
assert tn((apply_operators(f.C, ops, deriv)*f.B)[0], h2(z), z)
def test_reduction_operators():
a1, a2, b1 = (randcplx(n) for n in range(3))
h = hyper([a1], [b1], z)
assert ReduceOrder(2, 0) is None
assert ReduceOrder(2, -1) is None
assert ReduceOrder(1, S('1/2')) is None
h2 = hyper((a1, a2), (b1, a2), z)
assert tn(ReduceOrder(a2, a2).apply(h, op), h2, z)
h2 = hyper((a1, a2 + 1), (b1, a2), z)
assert tn(ReduceOrder(a2 + 1, a2).apply(h, op), h2, z)
h2 = hyper((a2 + 4, a1), (b1, a2), z)
assert tn(ReduceOrder(a2 + 4, a2).apply(h, op), h2, z)
# test several step order reduction
ap = (a2 + 4, a1, b1 + 1)
bq = (a2, b1, b1)
func, ops = reduce_order(Hyper_Function(ap, bq))
assert func.ap == (a1,)
assert func.bq == (b1,)
assert tn(apply_operators(h, ops, op), hyper(ap, bq, z), z)
def test_shift_operators():
a1, a2, b1, b2, b3 = (randcplx(n) for n in range(5))
h = hyper((a1, a2), (b1, b2, b3), z)
raises(ValueError, lambda: ShiftA(0))
raises(ValueError, lambda: ShiftB(1))
assert tn(ShiftA(a1).apply(h, op), hyper((a1 + 1, a2), (b1, b2, b3), z), z)
assert tn(ShiftA(a2).apply(h, op), hyper((a1, a2 + 1), (b1, b2, b3), z), z)
assert tn(ShiftB(b1).apply(h, op), hyper((a1, a2), (b1 - 1, b2, b3), z), z)
assert tn(ShiftB(b2).apply(h, op), hyper((a1, a2), (b1, b2 - 1, b3), z), z)
assert tn(ShiftB(b3).apply(h, op), hyper((a1, a2), (b1, b2, b3 - 1), z), z)
def test_ushift_operators():
a1, a2, b1, b2, b3 = (randcplx(n) for n in range(5))
h = hyper((a1, a2), (b1, b2, b3), z)
raises(ValueError, lambda: UnShiftA((1,), (), 0, z))
raises(ValueError, lambda: UnShiftB((), (-1,), 0, z))
raises(ValueError, lambda: UnShiftA((1,), (0, -1, 1), 0, z))
raises(ValueError, lambda: UnShiftB((0, 1), (1,), 0, z))
s = UnShiftA((a1, a2), (b1, b2, b3), 0, z)
assert tn(s.apply(h, op), hyper((a1 - 1, a2), (b1, b2, b3), z), z)
s = UnShiftA((a1, a2), (b1, b2, b3), 1, z)
assert tn(s.apply(h, op), hyper((a1, a2 - 1), (b1, b2, b3), z), z)
s = UnShiftB((a1, a2), (b1, b2, b3), 0, z)
assert tn(s.apply(h, op), hyper((a1, a2), (b1 + 1, b2, b3), z), z)
s = UnShiftB((a1, a2), (b1, b2, b3), 1, z)
assert tn(s.apply(h, op), hyper((a1, a2), (b1, b2 + 1, b3), z), z)
s = UnShiftB((a1, a2), (b1, b2, b3), 2, z)
assert tn(s.apply(h, op), hyper((a1, a2), (b1, b2, b3 + 1), z), z)
def can_do_meijer(a1, a2, b1, b2, numeric=True):
"""
This helper function tries to hyperexpand() the meijer g-function
corresponding to the parameters a1, a2, b1, b2.
It returns False if this expansion still contains g-functions.
If numeric is True, it also tests the so-obtained formula numerically
(at random values) and returns False if the test fails.
Else it returns True.
"""
from sympy.core.function import expand
from sympy.functions.elementary.complexes import unpolarify
r = hyperexpand(meijerg(a1, a2, b1, b2, z))
if r.has(meijerg):
return False
# NOTE hyperexpand() returns a truly branched function, whereas numerical
# evaluation only works on the main branch. Since we are evaluating on
# the main branch, this should not be a problem, but expressions like
# exp_polar(I*pi/2*x)**a are evaluated incorrectly. We thus have to get
# rid of them. The expand heuristically does this...
r = unpolarify(expand(r, force=True, power_base=True, power_exp=False,
mul=False, log=False, multinomial=False, basic=False))
if not numeric:
return True
repl = {}
for n, ai in enumerate(meijerg(a1, a2, b1, b2, z).free_symbols - {z}):
repl[ai] = randcplx(n)
return tn(meijerg(a1, a2, b1, b2, z).subs(repl), r.subs(repl), z)
@slow
def test_meijerg_expand():
from sympy.simplify.gammasimp import gammasimp
from sympy.simplify.simplify import simplify
# from mpmath docs
assert hyperexpand(meijerg([[], []], [[0], []], -z)) == exp(z)
assert hyperexpand(meijerg([[1, 1], []], [[1], [0]], z)) == \
log(z + 1)
assert hyperexpand(meijerg([[1, 1], []], [[1], [1]], z)) == \
z/(z + 1)
assert hyperexpand(meijerg([[], []], [[S.Half], [0]], (z/2)**2)) \
== sin(z)/sqrt(pi)
assert hyperexpand(meijerg([[], []], [[0], [S.Half]], (z/2)**2)) \
== cos(z)/sqrt(pi)
assert can_do_meijer([], [a], [a - 1, a - S.Half], [])
assert can_do_meijer([], [], [a/2], [-a/2], False) # branches...
assert can_do_meijer([a], [b], [a], [b, a - 1])
# wikipedia
assert hyperexpand(meijerg([1], [], [], [0], z)) == \
Piecewise((0, abs(z) < 1), (1, abs(1/z) < 1),
(meijerg([1], [], [], [0], z), True))
assert hyperexpand(meijerg([], [1], [0], [], z)) == \
Piecewise((1, abs(z) < 1), (0, abs(1/z) < 1),
(meijerg([], [1], [0], [], z), True))
# The Special Functions and their Approximations
assert can_do_meijer([], [], [a + b/2], [a, a - b/2, a + S.Half])
assert can_do_meijer(
[], [], [a], [b], False) # branches only agree for small z
assert can_do_meijer([], [S.Half], [a], [-a])
assert can_do_meijer([], [], [a, b], [])
assert can_do_meijer([], [], [a, b], [])
assert can_do_meijer([], [], [a, a + S.Half], [b, b + S.Half])
assert can_do_meijer([], [], [a, -a], [0, S.Half], False) # dito
assert can_do_meijer([], [], [a, a + S.Half, b, b + S.Half], [])
assert can_do_meijer([S.Half], [], [0], [a, -a])
assert can_do_meijer([S.Half], [], [a], [0, -a], False) # dito
assert can_do_meijer([], [a - S.Half], [a, b], [a - S.Half], False)
assert can_do_meijer([], [a + S.Half], [a + b, a - b, a], [], False)
assert can_do_meijer([a + S.Half], [], [b, 2*a - b, a], [], False)
# This for example is actually zero.
assert can_do_meijer([], [], [], [a, b])
# Testing a bug:
assert hyperexpand(meijerg([0, 2], [], [], [-1, 1], z)) == \
Piecewise((0, abs(z) < 1),
(z*(1 - 1/z**2)/2, abs(1/z) < 1),
(meijerg([0, 2], [], [], [-1, 1], z), True))
# Test that the simplest possible answer is returned:
assert gammasimp(simplify(hyperexpand(
meijerg([1], [1 - a], [-a/2, -a/2 + S.Half], [], 1/z)))) == \
-2*sqrt(pi)*(sqrt(z + 1) + 1)**a/a
# Test that hyper is returned
assert hyperexpand(meijerg([1], [], [a], [0, 0], z)) == hyper(
(a,), (a + 1, a + 1), z*exp_polar(I*pi))*z**a*gamma(a)/gamma(a + 1)**2
# Test place option
f = meijerg(((0, 1), ()), ((S.Half,), (0,)), z**2)
assert hyperexpand(f) == sqrt(pi)/sqrt(1 + z**(-2))
assert hyperexpand(f, place=0) == sqrt(pi)*z/sqrt(z**2 + 1)
def test_meijerg_lookup():
from sympy.functions.special.error_functions import (Ci, Si)
from sympy.functions.special.gamma_functions import uppergamma
assert hyperexpand(meijerg([a], [], [b, a], [], z)) == \
z**b*exp(z)*gamma(-a + b + 1)*uppergamma(a - b, z)
assert hyperexpand(meijerg([0], [], [0, 0], [], z)) == \
exp(z)*uppergamma(0, z)
assert can_do_meijer([a], [], [b, a + 1], [])
assert can_do_meijer([a], [], [b + 2, a], [])
assert can_do_meijer([a], [], [b - 2, a], [])
assert hyperexpand(meijerg([a], [], [a, a, a - S.Half], [], z)) == \
-sqrt(pi)*z**(a - S.Half)*(2*cos(2*sqrt(z))*(Si(2*sqrt(z)) - pi/2)
- 2*sin(2*sqrt(z))*Ci(2*sqrt(z))) == \
hyperexpand(meijerg([a], [], [a, a - S.Half, a], [], z)) == \
hyperexpand(meijerg([a], [], [a - S.Half, a, a], [], z))
assert can_do_meijer([a - 1], [], [a + 2, a - Rational(3, 2), a + 1], [])
@XFAIL
def test_meijerg_expand_fail():
# These basically test hyper([], [1/2 - a, 1/2 + 1, 1/2], z),
# which is *very* messy. But since the meijer g actually yields a
# sum of bessel functions, things can sometimes be simplified a lot and
# are then put into tables...
assert can_do_meijer([], [], [a + S.Half], [a, a - b/2, a + b/2])
assert can_do_meijer([], [], [0, S.Half], [a, -a])
assert can_do_meijer([], [], [3*a - S.Half, a, -a - S.Half], [a - S.Half])
assert can_do_meijer([], [], [0, a - S.Half, -a - S.Half], [S.Half])
assert can_do_meijer([], [], [a, b + S.Half, b], [2*b - a])
assert can_do_meijer([], [], [a, b + S.Half, b, 2*b - a])
assert can_do_meijer([S.Half], [], [-a, a], [0])
@slow
def test_meijerg():
# carefully set up the parameters.
# NOTE: this used to fail sometimes. I believe it is fixed, but if you
# hit an inexplicable test failure here, please let me know the seed.
a1, a2 = (randcplx(n) - 5*I - n*I for n in range(2))
b1, b2 = (randcplx(n) + 5*I + n*I for n in range(2))
b3, b4, b5, a3, a4, a5 = (randcplx() for n in range(6))
g = meijerg([a1], [a3, a4], [b1], [b3, b4], z)
assert ReduceOrder.meijer_minus(3, 4) is None
assert ReduceOrder.meijer_plus(4, 3) is None
g2 = meijerg([a1, a2], [a3, a4], [b1], [b3, b4, a2], z)
assert tn(ReduceOrder.meijer_plus(a2, a2).apply(g, op), g2, z)
g2 = meijerg([a1, a2], [a3, a4], [b1], [b3, b4, a2 + 1], z)
assert tn(ReduceOrder.meijer_plus(a2, a2 + 1).apply(g, op), g2, z)
g2 = meijerg([a1, a2 - 1], [a3, a4], [b1], [b3, b4, a2 + 2], z)
assert tn(ReduceOrder.meijer_plus(a2 - 1, a2 + 2).apply(g, op), g2, z)
g2 = meijerg([a1], [a3, a4, b2 - 1], [b1, b2 + 2], [b3, b4], z)
assert tn(ReduceOrder.meijer_minus(
b2 + 2, b2 - 1).apply(g, op), g2, z, tol=1e-6)
# test several-step reduction
an = [a1, a2]
bq = [b3, b4, a2 + 1]
ap = [a3, a4, b2 - 1]
bm = [b1, b2 + 1]
niq, ops = reduce_order_meijer(G_Function(an, ap, bm, bq))
assert niq.an == (a1,)
assert set(niq.ap) == {a3, a4}
assert niq.bm == (b1,)
assert set(niq.bq) == {b3, b4}
assert tn(apply_operators(g, ops, op), meijerg(an, ap, bm, bq, z), z)
def test_meijerg_shift_operators():
# carefully set up the parameters. XXX this still fails sometimes
a1, a2, a3, a4, a5, b1, b2, b3, b4, b5 = (randcplx(n) for n in range(10))
g = meijerg([a1], [a3, a4], [b1], [b3, b4], z)
assert tn(MeijerShiftA(b1).apply(g, op),
meijerg([a1], [a3, a4], [b1 + 1], [b3, b4], z), z)
assert tn(MeijerShiftB(a1).apply(g, op),
meijerg([a1 - 1], [a3, a4], [b1], [b3, b4], z), z)
assert tn(MeijerShiftC(b3).apply(g, op),
meijerg([a1], [a3, a4], [b1], [b3 + 1, b4], z), z)
assert tn(MeijerShiftD(a3).apply(g, op),
meijerg([a1], [a3 - 1, a4], [b1], [b3, b4], z), z)
s = MeijerUnShiftA([a1], [a3, a4], [b1], [b3, b4], 0, z)
assert tn(
s.apply(g, op), meijerg([a1], [a3, a4], [b1 - 1], [b3, b4], z), z)
s = MeijerUnShiftC([a1], [a3, a4], [b1], [b3, b4], 0, z)
assert tn(
s.apply(g, op), meijerg([a1], [a3, a4], [b1], [b3 - 1, b4], z), z)
s = MeijerUnShiftB([a1], [a3, a4], [b1], [b3, b4], 0, z)
assert tn(
s.apply(g, op), meijerg([a1 + 1], [a3, a4], [b1], [b3, b4], z), z)
s = MeijerUnShiftD([a1], [a3, a4], [b1], [b3, b4], 0, z)
assert tn(
s.apply(g, op), meijerg([a1], [a3 + 1, a4], [b1], [b3, b4], z), z)
@slow
def test_meijerg_confluence():
def t(m, a, b):
from sympy.core.sympify import sympify
a, b = sympify([a, b])
m_ = m
m = hyperexpand(m)
if not m == Piecewise((a, abs(z) < 1), (b, abs(1/z) < 1), (m_, True)):
return False
if not (m.args[0].args[0] == a and m.args[1].args[0] == b):
return False
z0 = randcplx()/10
if abs(m.subs(z, z0).n() - a.subs(z, z0).n()).n() > 1e-10:
return False
if abs(m.subs(z, 1/z0).n() - b.subs(z, 1/z0).n()).n() > 1e-10:
return False
return True
assert t(meijerg([], [1, 1], [0, 0], [], z), -log(z), 0)
assert t(meijerg(
[], [3, 1], [0, 0], [], z), -z**2/4 + z - log(z)/2 - Rational(3, 4), 0)
assert t(meijerg([], [3, 1], [-1, 0], [], z),
z**2/12 - z/2 + log(z)/2 + Rational(1, 4) + 1/(6*z), 0)
assert t(meijerg([], [1, 1, 1, 1], [0, 0, 0, 0], [], z), -log(z)**3/6, 0)
assert t(meijerg([1, 1], [], [], [0, 0], z), 0, -log(1/z))
assert t(meijerg([1, 1], [2, 2], [1, 1], [0, 0], z),
-z*log(z) + 2*z, -log(1/z) + 2)
assert t(meijerg([S.Half], [1, 1], [0, 0], [Rational(3, 2)], z), log(z)/2 - 1, 0)
def u(an, ap, bm, bq):
m = meijerg(an, ap, bm, bq, z)
m2 = hyperexpand(m, allow_hyper=True)
if m2.has(meijerg) and not (m2.is_Piecewise and len(m2.args) == 3):
return False
return tn(m, m2, z)
assert u([], [1], [0, 0], [])
assert u([1, 1], [], [], [0])
assert u([1, 1], [2, 2, 5], [1, 1, 6], [0, 0])
assert u([1, 1], [2, 2, 5], [1, 1, 6], [0])
def test_meijerg_with_Floats():
# see issue #10681
from sympy.polys.domains.realfield import RR
f = meijerg(((3.0, 1), ()), ((Rational(3, 2),), (0,)), z)
a = -2.3632718012073
g = a*z**Rational(3, 2)*hyper((-0.5, Rational(3, 2)), (Rational(5, 2),), z*exp_polar(I*pi))
assert RR.almosteq((hyperexpand(f)/g).n(), 1.0, 1e-12)
def test_lerchphi():
from sympy.functions.special.zeta_functions import (lerchphi, polylog)
from sympy.simplify.gammasimp import gammasimp
assert hyperexpand(hyper([1, a], [a + 1], z)/a) == lerchphi(z, 1, a)
assert hyperexpand(
hyper([1, a, a], [a + 1, a + 1], z)/a**2) == lerchphi(z, 2, a)
assert hyperexpand(hyper([1, a, a, a], [a + 1, a + 1, a + 1], z)/a**3) == \
lerchphi(z, 3, a)
assert hyperexpand(hyper([1] + [a]*10, [a + 1]*10, z)/a**10) == \
lerchphi(z, 10, a)
assert gammasimp(hyperexpand(meijerg([0, 1 - a], [], [0],
[-a], exp_polar(-I*pi)*z))) == lerchphi(z, 1, a)
assert gammasimp(hyperexpand(meijerg([0, 1 - a, 1 - a], [], [0],
[-a, -a], exp_polar(-I*pi)*z))) == lerchphi(z, 2, a)
assert gammasimp(hyperexpand(meijerg([0, 1 - a, 1 - a, 1 - a], [], [0],
[-a, -a, -a], exp_polar(-I*pi)*z))) == lerchphi(z, 3, a)
assert hyperexpand(z*hyper([1, 1], [2], z)) == -log(1 + -z)
assert hyperexpand(z*hyper([1, 1, 1], [2, 2], z)) == polylog(2, z)
assert hyperexpand(z*hyper([1, 1, 1, 1], [2, 2, 2], z)) == polylog(3, z)
assert hyperexpand(hyper([1, a, 1 + S.Half], [a + 1, S.Half], z)) == \
-2*a/(z - 1) + (-2*a**2 + a)*lerchphi(z, 1, a)
# Now numerical tests. These make sure reductions etc are carried out
# correctly
# a rational function (polylog at negative integer order)
assert can_do([2, 2, 2], [1, 1])
# NOTE these contain log(1-x) etc ... better make sure we have |z| < 1
# reduction of order for polylog
assert can_do([1, 1, 1, b + 5], [2, 2, b], div=10)
# reduction of order for lerchphi
# XXX lerchphi in mpmath is flaky
assert can_do(
[1, a, a, a, b + 5], [a + 1, a + 1, a + 1, b], numerical=False)
# test a bug
from sympy.functions.elementary.complexes import Abs
assert hyperexpand(hyper([S.Half, S.Half, S.Half, 1],
[Rational(3, 2), Rational(3, 2), Rational(3, 2)], Rational(1, 4))) == \
Abs(-polylog(3, exp_polar(I*pi)/2) + polylog(3, S.Half))
def test_partial_simp():
# First test that hypergeometric function formulae work.
a, b, c, d, e = (randcplx() for _ in range(5))
for func in [Hyper_Function([a, b, c], [d, e]),
Hyper_Function([], [a, b, c, d, e])]:
f = build_hypergeometric_formula(func)
z = f.z
assert f.closed_form == func(z)
deriv1 = f.B.diff(z)*z
deriv2 = f.M*f.B
for func1, func2 in zip(deriv1, deriv2):
assert tn(func1, func2, z)
# Now test that formulae are partially simplified.
a, b, z = symbols('a b z')
assert hyperexpand(hyper([3, a], [1, b], z)) == \
(-a*b/2 + a*z/2 + 2*a)*hyper([a + 1], [b], z) \
+ (a*b/2 - 2*a + 1)*hyper([a], [b], z)
assert tn(
hyperexpand(hyper([3, d], [1, e], z)), hyper([3, d], [1, e], z), z)
assert hyperexpand(hyper([3], [1, a, b], z)) == \
hyper((), (a, b), z) \
+ z*hyper((), (a + 1, b), z)/(2*a) \
- z*(b - 4)*hyper((), (a + 1, b + 1), z)/(2*a*b)
assert tn(
hyperexpand(hyper([3], [1, d, e], z)), hyper([3], [1, d, e], z), z)
def test_hyperexpand_special():
assert hyperexpand(hyper([a, b], [c], 1)) == \
gamma(c)*gamma(c - a - b)/gamma(c - a)/gamma(c - b)
assert hyperexpand(hyper([a, b], [1 + a - b], -1)) == \
gamma(1 + a/2)*gamma(1 + a - b)/gamma(1 + a)/gamma(1 + a/2 - b)
assert hyperexpand(hyper([a, b], [1 + b - a], -1)) == \
gamma(1 + b/2)*gamma(1 + b - a)/gamma(1 + b)/gamma(1 + b/2 - a)
assert hyperexpand(meijerg([1 - z - a/2], [1 - z + a/2], [b/2], [-b/2], 1)) == \
gamma(1 - 2*z)*gamma(z + a/2 + b/2)/gamma(1 - z + a/2 - b/2) \
/gamma(1 - z - a/2 + b/2)/gamma(1 - z + a/2 + b/2)
assert hyperexpand(hyper([a], [b], 0)) == 1
assert hyper([a], [b], 0) != 0
def test_Mod1_behavior():
from sympy.core.symbol import Symbol
from sympy.simplify.simplify import simplify
n = Symbol('n', integer=True)
# Note: this should not hang.
assert simplify(hyperexpand(meijerg([1], [], [n + 1], [0], z))) == \
lowergamma(n + 1, z)
@slow
def test_prudnikov_misc():
assert can_do([1, (3 + I)/2, (3 - I)/2], [Rational(3, 2), 2])
assert can_do([S.Half, a - 1], [Rational(3, 2), a + 1], lowerplane=True)
assert can_do([], [b + 1])
assert can_do([a], [a - 1, b + 1])
assert can_do([a], [a - S.Half, 2*a])
assert can_do([a], [a - S.Half, 2*a + 1])
assert can_do([a], [a - S.Half, 2*a - 1])
assert can_do([a], [a + S.Half, 2*a])
assert can_do([a], [a + S.Half, 2*a + 1])
assert can_do([a], [a + S.Half, 2*a - 1])
assert can_do([S.Half], [b, 2 - b])
assert can_do([S.Half], [b, 3 - b])
assert can_do([1], [2, b])
assert can_do([a, a + S.Half], [2*a, b, 2*a - b + 1])
assert can_do([a, a + S.Half], [S.Half, 2*a, 2*a + S.Half])
assert can_do([a], [a + 1], lowerplane=True) # lowergamma
def test_prudnikov_1():
# A. P. Prudnikov, Yu. A. Brychkov and O. I. Marichev (1990).
# Integrals and Series: More Special Functions, Vol. 3,.
# Gordon and Breach Science Publisher
# 7.3.1
assert can_do([a, -a], [S.Half])
assert can_do([a, 1 - a], [S.Half])
assert can_do([a, 1 - a], [Rational(3, 2)])
assert can_do([a, 2 - a], [S.Half])
assert can_do([a, 2 - a], [Rational(3, 2)])
assert can_do([a, 2 - a], [Rational(3, 2)])
assert can_do([a, a + S.Half], [2*a - 1])
assert can_do([a, a + S.Half], [2*a])
assert can_do([a, a + S.Half], [2*a + 1])
assert can_do([a, a + S.Half], [S.Half])
assert can_do([a, a + S.Half], [Rational(3, 2)])
assert can_do([a, a/2 + 1], [a/2])
assert can_do([1, b], [2])
assert can_do([1, b], [b + 1], numerical=False) # Lerch Phi
# NOTE: branches are complicated for |z| > 1
assert can_do([a], [2*a])
assert can_do([a], [2*a + 1])
assert can_do([a], [2*a - 1])
@slow
def test_prudnikov_2():
h = S.Half
assert can_do([-h, -h], [h])
assert can_do([-h, h], [3*h])
assert can_do([-h, h], [5*h])
assert can_do([-h, h], [7*h])
assert can_do([-h, 1], [h])
for p in [-h, h]:
for n in [-h, h, 1, 3*h, 2, 5*h, 3, 7*h, 4]:
for m in [-h, h, 3*h, 5*h, 7*h]:
assert can_do([p, n], [m])
for n in [1, 2, 3, 4]:
for m in [1, 2, 3, 4]:
assert can_do([p, n], [m])
@slow
def test_prudnikov_3():
if ON_TRAVIS:
# See https://github.com/sympy/sympy/pull/12795
skip("Too slow for travis.")
h = S.Half
assert can_do([Rational(1, 4), Rational(3, 4)], [h])
assert can_do([Rational(1, 4), Rational(3, 4)], [3*h])
assert can_do([Rational(1, 3), Rational(2, 3)], [3*h])
assert can_do([Rational(3, 4), Rational(5, 4)], [h])
assert can_do([Rational(3, 4), Rational(5, 4)], [3*h])
for p in [1, 2, 3, 4]:
for n in [-h, h, 1, 3*h, 2, 5*h, 3, 7*h, 4, 9*h]:
for m in [1, 3*h, 2, 5*h, 3, 7*h, 4]:
assert can_do([p, m], [n])
@slow
def test_prudnikov_4():
h = S.Half
for p in [3*h, 5*h, 7*h]:
for n in [-h, h, 3*h, 5*h, 7*h]:
for m in [3*h, 2, 5*h, 3, 7*h, 4]:
assert can_do([p, m], [n])
for n in [1, 2, 3, 4]:
for m in [2, 3, 4]:
assert can_do([p, m], [n])
@slow
def test_prudnikov_5():
h = S.Half
for p in [1, 2, 3]:
for q in range(p, 4):
for r in [1, 2, 3]:
for s in range(r, 4):
assert can_do([-h, p, q], [r, s])
for p in [h, 1, 3*h, 2, 5*h, 3]:
for q in [h, 3*h, 5*h]:
for r in [h, 3*h, 5*h]:
for s in [h, 3*h, 5*h]:
if s <= q and s <= r:
assert can_do([-h, p, q], [r, s])
for p in [h, 1, 3*h, 2, 5*h, 3]:
for q in [1, 2, 3]:
for r in [h, 3*h, 5*h]:
for s in [1, 2, 3]:
assert can_do([-h, p, q], [r, s])
@slow
def test_prudnikov_6():
h = S.Half
for m in [3*h, 5*h]:
for n in [1, 2, 3]:
for q in [h, 1, 2]:
for p in [1, 2, 3]:
assert can_do([h, q, p], [m, n])
for q in [1, 2, 3]:
for p in [3*h, 5*h]:
assert can_do([h, q, p], [m, n])
for q in [1, 2]:
for p in [1, 2, 3]:
for m in [1, 2, 3]:
for n in [1, 2, 3]:
assert can_do([h, q, p], [m, n])
assert can_do([h, h, 5*h], [3*h, 3*h])
assert can_do([h, 1, 5*h], [3*h, 3*h])
assert can_do([h, 2, 2], [1, 3])
# pages 435 to 457 contain more PFDD and stuff like this
@slow
def test_prudnikov_7():
assert can_do([3], [6])
h = S.Half
for n in [h, 3*h, 5*h, 7*h]:
assert can_do([-h], [n])
for m in [-h, h, 1, 3*h, 2, 5*h, 3, 7*h, 4]: # HERE
for n in [-h, h, 3*h, 5*h, 7*h, 1, 2, 3, 4]:
assert can_do([m], [n])
@slow
def test_prudnikov_8():
h = S.Half
# 7.12.2
for ai in [1, 2, 3]:
for bi in [1, 2, 3]:
for ci in range(1, ai + 1):
for di in [h, 1, 3*h, 2, 5*h, 3]:
assert can_do([ai, bi], [ci, di])
for bi in [3*h, 5*h]:
for ci in [h, 1, 3*h, 2, 5*h, 3]:
for di in [1, 2, 3]:
assert can_do([ai, bi], [ci, di])
for ai in [-h, h, 3*h, 5*h]:
for bi in [1, 2, 3]:
for ci in [h, 1, 3*h, 2, 5*h, 3]:
for di in [1, 2, 3]:
assert can_do([ai, bi], [ci, di])
for bi in [h, 3*h, 5*h]:
for ci in [h, 3*h, 5*h, 3]:
for di in [h, 1, 3*h, 2, 5*h, 3]:
if ci <= bi:
assert can_do([ai, bi], [ci, di])
def test_prudnikov_9():
# 7.13.1 [we have a general formula ... so this is a bit pointless]
for i in range(9):
assert can_do([], [(S(i) + 1)/2])
for i in range(5):
assert can_do([], [-(2*S(i) + 1)/2])
@slow
def test_prudnikov_10():
# 7.14.2
h = S.Half
for p in [-h, h, 1, 3*h, 2, 5*h, 3, 7*h, 4]:
for m in [1, 2, 3, 4]:
for n in range(m, 5):
assert can_do([p], [m, n])
for p in [1, 2, 3, 4]:
for n in [h, 3*h, 5*h, 7*h]:
for m in [1, 2, 3, 4]:
assert can_do([p], [n, m])
for p in [3*h, 5*h, 7*h]:
for m in [h, 1, 2, 5*h, 3, 7*h, 4]:
assert can_do([p], [h, m])
assert can_do([p], [3*h, m])
for m in [h, 1, 2, 5*h, 3, 7*h, 4]:
assert can_do([7*h], [5*h, m])
assert can_do([Rational(-1, 2)], [S.Half, S.Half]) # shine-integral shi
def test_prudnikov_11():
# 7.15
assert can_do([a, a + S.Half], [2*a, b, 2*a - b])
assert can_do([a, a + S.Half], [Rational(3, 2), 2*a, 2*a - S.Half])
assert can_do([Rational(1, 4), Rational(3, 4)], [S.Half, S.Half, 1])
assert can_do([Rational(5, 4), Rational(3, 4)], [Rational(3, 2), S.Half, 2])
assert can_do([Rational(5, 4), Rational(3, 4)], [Rational(3, 2), Rational(3, 2), 1])
assert can_do([Rational(5, 4), Rational(7, 4)], [Rational(3, 2), Rational(5, 2), 2])
assert can_do([1, 1], [Rational(3, 2), 2, 2]) # cosh-integral chi
def test_prudnikov_12():
# 7.16
assert can_do(
[], [a, a + S.Half, 2*a], False) # branches only agree for some z!
assert can_do([], [a, a + S.Half, 2*a + 1], False) # dito
assert can_do([], [S.Half, a, a + S.Half])
assert can_do([], [Rational(3, 2), a, a + S.Half])
assert can_do([], [Rational(1, 4), S.Half, Rational(3, 4)])
assert can_do([], [S.Half, S.Half, 1])
assert can_do([], [S.Half, Rational(3, 2), 1])
assert can_do([], [Rational(3, 4), Rational(3, 2), Rational(5, 4)])
assert can_do([], [1, 1, Rational(3, 2)])
assert can_do([], [1, 2, Rational(3, 2)])
assert can_do([], [1, Rational(3, 2), Rational(3, 2)])
assert can_do([], [Rational(5, 4), Rational(3, 2), Rational(7, 4)])
assert can_do([], [2, Rational(3, 2), Rational(3, 2)])
@slow
def test_prudnikov_2F1():
h = S.Half
# Elliptic integrals
for p in [-h, h]:
for m in [h, 3*h, 5*h, 7*h]:
for n in [1, 2, 3, 4]:
assert can_do([p, m], [n])
@XFAIL
def test_prudnikov_fail_2F1():
assert can_do([a, b], [b + 1]) # incomplete beta function
assert can_do([-1, b], [c]) # Poly. also -2, -3 etc
# TODO polys
# Legendre functions:
assert can_do([a, b], [a + b + S.Half])
assert can_do([a, b], [a + b - S.Half])
assert can_do([a, b], [a + b + Rational(3, 2)])
assert can_do([a, b], [(a + b + 1)/2])
assert can_do([a, b], [(a + b)/2 + 1])
assert can_do([a, b], [a - b + 1])
assert can_do([a, b], [a - b + 2])
assert can_do([a, b], [2*b])
assert can_do([a, b], [S.Half])
assert can_do([a, b], [Rational(3, 2)])
assert can_do([a, 1 - a], [c])
assert can_do([a, 2 - a], [c])
assert can_do([a, 3 - a], [c])
assert can_do([a, a + S.Half], [c])
assert can_do([1, b], [c])
assert can_do([1, b], [Rational(3, 2)])
assert can_do([Rational(1, 4), Rational(3, 4)], [1])
# PFDD
o = S.One
assert can_do([o/8, 1], [o/8*9])
assert can_do([o/6, 1], [o/6*7])
assert can_do([o/6, 1], [o/6*13])
assert can_do([o/5, 1], [o/5*6])
assert can_do([o/5, 1], [o/5*11])
assert can_do([o/4, 1], [o/4*5])
assert can_do([o/4, 1], [o/4*9])
assert can_do([o/3, 1], [o/3*4])
assert can_do([o/3, 1], [o/3*7])
assert can_do([o/8*3, 1], [o/8*11])
assert can_do([o/5*2, 1], [o/5*7])
assert can_do([o/5*2, 1], [o/5*12])
assert can_do([o/5*3, 1], [o/5*8])
assert can_do([o/5*3, 1], [o/5*13])
assert can_do([o/8*5, 1], [o/8*13])
assert can_do([o/4*3, 1], [o/4*7])
assert can_do([o/4*3, 1], [o/4*11])
assert can_do([o/3*2, 1], [o/3*5])
assert can_do([o/3*2, 1], [o/3*8])
assert can_do([o/5*4, 1], [o/5*9])
assert can_do([o/5*4, 1], [o/5*14])
assert can_do([o/6*5, 1], [o/6*11])
assert can_do([o/6*5, 1], [o/6*17])
assert can_do([o/8*7, 1], [o/8*15])
@XFAIL
def test_prudnikov_fail_3F2():
assert can_do([a, a + Rational(1, 3), a + Rational(2, 3)], [Rational(1, 3), Rational(2, 3)])
assert can_do([a, a + Rational(1, 3), a + Rational(2, 3)], [Rational(2, 3), Rational(4, 3)])
assert can_do([a, a + Rational(1, 3), a + Rational(2, 3)], [Rational(4, 3), Rational(5, 3)])
# page 421
assert can_do([a, a + Rational(1, 3), a + Rational(2, 3)], [a*Rational(3, 2), (3*a + 1)/2])
# pages 422 ...
assert can_do([Rational(-1, 2), S.Half, S.Half], [1, 1]) # elliptic integrals
assert can_do([Rational(-1, 2), S.Half, 1], [Rational(3, 2), Rational(3, 2)])
# TODO LOTS more
# PFDD
assert can_do([Rational(1, 8), Rational(3, 8), 1], [Rational(9, 8), Rational(11, 8)])
assert can_do([Rational(1, 8), Rational(5, 8), 1], [Rational(9, 8), Rational(13, 8)])
assert can_do([Rational(1, 8), Rational(7, 8), 1], [Rational(9, 8), Rational(15, 8)])
assert can_do([Rational(1, 6), Rational(1, 3), 1], [Rational(7, 6), Rational(4, 3)])
assert can_do([Rational(1, 6), Rational(2, 3), 1], [Rational(7, 6), Rational(5, 3)])
assert can_do([Rational(1, 6), Rational(2, 3), 1], [Rational(5, 3), Rational(13, 6)])
assert can_do([S.Half, 1, 1], [Rational(1, 4), Rational(3, 4)])
# LOTS more
@XFAIL
def test_prudnikov_fail_other():
# 7.11.2
# 7.12.1
assert can_do([1, a], [b, 1 - 2*a + b]) # ???
# 7.14.2
assert can_do([Rational(-1, 2)], [S.Half, 1]) # struve
assert can_do([1], [S.Half, S.Half]) # struve
assert can_do([Rational(1, 4)], [S.Half, Rational(5, 4)]) # PFDD
assert can_do([Rational(3, 4)], [Rational(3, 2), Rational(7, 4)]) # PFDD
assert can_do([1], [Rational(1, 4), Rational(3, 4)]) # PFDD
assert can_do([1], [Rational(3, 4), Rational(5, 4)]) # PFDD
assert can_do([1], [Rational(5, 4), Rational(7, 4)]) # PFDD
# TODO LOTS more
# 7.15.2
assert can_do([S.Half, 1], [Rational(3, 4), Rational(5, 4), Rational(3, 2)]) # PFDD
assert can_do([S.Half, 1], [Rational(7, 4), Rational(5, 4), Rational(3, 2)]) # PFDD
# 7.16.1
assert can_do([], [Rational(1, 3), S(2/3)]) # PFDD
assert can_do([], [Rational(2, 3), S(4/3)]) # PFDD
assert can_do([], [Rational(5, 3), S(4/3)]) # PFDD
# XXX this does not *evaluate* right??
assert can_do([], [a, a + S.Half, 2*a - 1])
def test_bug():
h = hyper([-1, 1], [z], -1)
assert hyperexpand(h) == (z + 1)/z
def test_omgissue_203():
h = hyper((-5, -3, -4), (-6, -6), 1)
assert hyperexpand(h) == Rational(1, 30)
h = hyper((-6, -7, -5), (-6, -6), 1)
assert hyperexpand(h) == Rational(-1, 6)
|
cceb8ed74c262f907cf9b7f04b551b83981e66d52fcd1ac12f42e9c1d3dd2bf7 | from sympy.concrete.summations import Sum
from sympy.core.add import Add
from sympy.core.basic import Basic
from sympy.core.expr import unchanged
from sympy.core.function import (count_ops, diff, expand, expand_multinomial, Function, Derivative)
from sympy.core.mul import Mul, _keep_coeff
from sympy.core import GoldenRatio
from sympy.core.numbers import (E, Float, I, oo, pi, Rational, zoo)
from sympy.core.relational import (Eq, Lt, Gt, Ge, Le)
from sympy.core.singleton import S
from sympy.core.symbol import (Symbol, symbols)
from sympy.core.sympify import sympify
from sympy.functions.combinatorial.factorials import (binomial, factorial)
from sympy.functions.elementary.complexes import (Abs, sign)
from sympy.functions.elementary.exponential import (exp, exp_polar, log)
from sympy.functions.elementary.hyperbolic import (cosh, csch, sinh)
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.piecewise import Piecewise
from sympy.functions.elementary.trigonometric import (acos, asin, atan, cos, sin, sinc, tan)
from sympy.functions.special.error_functions import erf
from sympy.functions.special.gamma_functions import gamma
from sympy.functions.special.hyper import hyper
from sympy.functions.special.tensor_functions import KroneckerDelta
from sympy.geometry.polygon import rad
from sympy.integrals.integrals import (Integral, integrate)
from sympy.logic.boolalg import (And, Or)
from sympy.matrices.dense import (Matrix, eye)
from sympy.matrices.expressions.matexpr import MatrixSymbol
from sympy.polys.polytools import (factor, Poly)
from sympy.simplify.simplify import (besselsimp, hypersimp, inversecombine, logcombine, nsimplify, nthroot, posify, separatevars, signsimp, simplify)
from sympy.solvers.solvers import solve
from sympy.testing.pytest import XFAIL, slow, _both_exp_pow
from sympy.abc import x, y, z, t, a, b, c, d, e, f, g, h, i, n
def test_issue_7263():
assert abs((simplify(30.8**2 - 82.5**2 * sin(rad(11.6))**2)).evalf() - \
673.447451402970) < 1e-12
def test_factorial_simplify():
# There are more tests in test_factorials.py.
x = Symbol('x')
assert simplify(factorial(x)/x) == gamma(x)
assert simplify(factorial(factorial(x))) == factorial(factorial(x))
def test_simplify_expr():
x, y, z, k, n, m, w, s, A = symbols('x,y,z,k,n,m,w,s,A')
f = Function('f')
assert all(simplify(tmp) == tmp for tmp in [I, E, oo, x, -x, -oo, -E, -I])
e = 1/x + 1/y
assert e != (x + y)/(x*y)
assert simplify(e) == (x + y)/(x*y)
e = A**2*s**4/(4*pi*k*m**3)
assert simplify(e) == e
e = (4 + 4*x - 2*(2 + 2*x))/(2 + 2*x)
assert simplify(e) == 0
e = (-4*x*y**2 - 2*y**3 - 2*x**2*y)/(x + y)**2
assert simplify(e) == -2*y
e = -x - y - (x + y)**(-1)*y**2 + (x + y)**(-1)*x**2
assert simplify(e) == -2*y
e = (x + x*y)/x
assert simplify(e) == 1 + y
e = (f(x) + y*f(x))/f(x)
assert simplify(e) == 1 + y
e = (2 * (1/n - cos(n * pi)/n))/pi
assert simplify(e) == (-cos(pi*n) + 1)/(pi*n)*2
e = integrate(1/(x**3 + 1), x).diff(x)
assert simplify(e) == 1/(x**3 + 1)
e = integrate(x/(x**2 + 3*x + 1), x).diff(x)
assert simplify(e) == x/(x**2 + 3*x + 1)
f = Symbol('f')
A = Matrix([[2*k - m*w**2, -k], [-k, k - m*w**2]]).inv()
assert simplify((A*Matrix([0, f]))[1] -
(-f*(2*k - m*w**2)/(k**2 - (k - m*w**2)*(2*k - m*w**2)))) == 0
f = -x + y/(z + t) + z*x/(z + t) + z*a/(z + t) + t*x/(z + t)
assert simplify(f) == (y + a*z)/(z + t)
# issue 10347
expr = -x*(y**2 - 1)*(2*y**2*(x**2 - 1)/(a*(x**2 - y**2)**2) + (x**2 - 1)
/(a*(x**2 - y**2)))/(a*(x**2 - y**2)) + x*(-2*x**2*sqrt(-x**2*y**2 + x**2
+ y**2 - 1)*sin(z)/(a*(x**2 - y**2)**2) - x**2*sqrt(-x**2*y**2 + x**2 +
y**2 - 1)*sin(z)/(a*(x**2 - 1)*(x**2 - y**2)) + (x**2*sqrt((-x**2 + 1)*
(y**2 - 1))*sqrt(-x**2*y**2 + x**2 + y**2 - 1)*sin(z)/(x**2 - 1) + sqrt(
(-x**2 + 1)*(y**2 - 1))*(x*(-x*y**2 + x)/sqrt(-x**2*y**2 + x**2 + y**2 -
1) + sqrt(-x**2*y**2 + x**2 + y**2 - 1))*sin(z))/(a*sqrt((-x**2 + 1)*(
y**2 - 1))*(x**2 - y**2)))*sqrt(-x**2*y**2 + x**2 + y**2 - 1)*sin(z)/(a*
(x**2 - y**2)) + x*(-2*x**2*sqrt(-x**2*y**2 + x**2 + y**2 - 1)*cos(z)/(a*
(x**2 - y**2)**2) - x**2*sqrt(-x**2*y**2 + x**2 + y**2 - 1)*cos(z)/(a*
(x**2 - 1)*(x**2 - y**2)) + (x**2*sqrt((-x**2 + 1)*(y**2 - 1))*sqrt(-x**2
*y**2 + x**2 + y**2 - 1)*cos(z)/(x**2 - 1) + x*sqrt((-x**2 + 1)*(y**2 -
1))*(-x*y**2 + x)*cos(z)/sqrt(-x**2*y**2 + x**2 + y**2 - 1) + sqrt((-x**2
+ 1)*(y**2 - 1))*sqrt(-x**2*y**2 + x**2 + y**2 - 1)*cos(z))/(a*sqrt((-x**2
+ 1)*(y**2 - 1))*(x**2 - y**2)))*sqrt(-x**2*y**2 + x**2 + y**2 - 1)*cos(
z)/(a*(x**2 - y**2)) - y*sqrt((-x**2 + 1)*(y**2 - 1))*(-x*y*sqrt(-x**2*
y**2 + x**2 + y**2 - 1)*sin(z)/(a*(x**2 - y**2)*(y**2 - 1)) + 2*x*y*sqrt(
-x**2*y**2 + x**2 + y**2 - 1)*sin(z)/(a*(x**2 - y**2)**2) + (x*y*sqrt((
-x**2 + 1)*(y**2 - 1))*sqrt(-x**2*y**2 + x**2 + y**2 - 1)*sin(z)/(y**2 -
1) + x*sqrt((-x**2 + 1)*(y**2 - 1))*(-x**2*y + y)*sin(z)/sqrt(-x**2*y**2
+ x**2 + y**2 - 1))/(a*sqrt((-x**2 + 1)*(y**2 - 1))*(x**2 - y**2)))*sin(
z)/(a*(x**2 - y**2)) + y*(x**2 - 1)*(-2*x*y*(x**2 - 1)/(a*(x**2 - y**2)
**2) + 2*x*y/(a*(x**2 - y**2)))/(a*(x**2 - y**2)) + y*(x**2 - 1)*(y**2 -
1)*(-x*y*sqrt(-x**2*y**2 + x**2 + y**2 - 1)*cos(z)/(a*(x**2 - y**2)*(y**2
- 1)) + 2*x*y*sqrt(-x**2*y**2 + x**2 + y**2 - 1)*cos(z)/(a*(x**2 - y**2)
**2) + (x*y*sqrt((-x**2 + 1)*(y**2 - 1))*sqrt(-x**2*y**2 + x**2 + y**2 -
1)*cos(z)/(y**2 - 1) + x*sqrt((-x**2 + 1)*(y**2 - 1))*(-x**2*y + y)*cos(
z)/sqrt(-x**2*y**2 + x**2 + y**2 - 1))/(a*sqrt((-x**2 + 1)*(y**2 - 1)
)*(x**2 - y**2)))*cos(z)/(a*sqrt((-x**2 + 1)*(y**2 - 1))*(x**2 - y**2)
) - x*sqrt((-x**2 + 1)*(y**2 - 1))*sqrt(-x**2*y**2 + x**2 + y**2 - 1)*sin(
z)**2/(a**2*(x**2 - 1)*(x**2 - y**2)*(y**2 - 1)) - x*sqrt((-x**2 + 1)*(
y**2 - 1))*sqrt(-x**2*y**2 + x**2 + y**2 - 1)*cos(z)**2/(a**2*(x**2 - 1)*(
x**2 - y**2)*(y**2 - 1))
assert simplify(expr) == 2*x/(a**2*(x**2 - y**2))
#issue 17631
assert simplify('((-1/2)*Boole(True)*Boole(False)-1)*Boole(True)') == \
Mul(sympify('(2 + Boole(True)*Boole(False))'), sympify('-Boole(True)/2'))
A, B = symbols('A,B', commutative=False)
assert simplify(A*B - B*A) == A*B - B*A
assert simplify(A/(1 + y/x)) == x*A/(x + y)
assert simplify(A*(1/x + 1/y)) == A/x + A/y #(x + y)*A/(x*y)
assert simplify(log(2) + log(3)) == log(6)
assert simplify(log(2*x) - log(2)) == log(x)
assert simplify(hyper([], [], x)) == exp(x)
def test_issue_3557():
f_1 = x*a + y*b + z*c - 1
f_2 = x*d + y*e + z*f - 1
f_3 = x*g + y*h + z*i - 1
solutions = solve([f_1, f_2, f_3], x, y, z, simplify=False)
assert simplify(solutions[y]) == \
(a*i + c*d + f*g - a*f - c*g - d*i)/ \
(a*e*i + b*f*g + c*d*h - a*f*h - b*d*i - c*e*g)
def test_simplify_other():
assert simplify(sin(x)**2 + cos(x)**2) == 1
assert simplify(gamma(x + 1)/gamma(x)) == x
assert simplify(sin(x)**2 + cos(x)**2 + factorial(x)/gamma(x)) == 1 + x
assert simplify(
Eq(sin(x)**2 + cos(x)**2, factorial(x)/gamma(x))) == Eq(x, 1)
nc = symbols('nc', commutative=False)
assert simplify(x + x*nc) == x*(1 + nc)
# issue 6123
# f = exp(-I*(k*sqrt(t) + x/(2*sqrt(t)))**2)
# ans = integrate(f, (k, -oo, oo), conds='none')
ans = I*(-pi*x*exp(I*pi*Rational(-3, 4) + I*x**2/(4*t))*erf(x*exp(I*pi*Rational(-3, 4))/
(2*sqrt(t)))/(2*sqrt(t)) + pi*x*exp(I*pi*Rational(-3, 4) + I*x**2/(4*t))/
(2*sqrt(t)))*exp(-I*x**2/(4*t))/(sqrt(pi)*x) - I*sqrt(pi) * \
(-erf(x*exp(I*pi/4)/(2*sqrt(t))) + 1)*exp(I*pi/4)/(2*sqrt(t))
assert simplify(ans) == -(-1)**Rational(3, 4)*sqrt(pi)/sqrt(t)
# issue 6370
assert simplify(2**(2 + x)/4) == 2**x
@_both_exp_pow
def test_simplify_complex():
cosAsExp = cos(x)._eval_rewrite_as_exp(x)
tanAsExp = tan(x)._eval_rewrite_as_exp(x)
assert simplify(cosAsExp*tanAsExp) == sin(x) # issue 4341
# issue 10124
assert simplify(exp(Matrix([[0, -1], [1, 0]]))) == Matrix([[cos(1),
-sin(1)], [sin(1), cos(1)]])
def test_simplify_ratio():
# roots of x**3-3*x+5
roots = ['(1/2 - sqrt(3)*I/2)*(sqrt(21)/2 + 5/2)**(1/3) + 1/((1/2 - '
'sqrt(3)*I/2)*(sqrt(21)/2 + 5/2)**(1/3))',
'1/((1/2 + sqrt(3)*I/2)*(sqrt(21)/2 + 5/2)**(1/3)) + '
'(1/2 + sqrt(3)*I/2)*(sqrt(21)/2 + 5/2)**(1/3)',
'-(sqrt(21)/2 + 5/2)**(1/3) - 1/(sqrt(21)/2 + 5/2)**(1/3)']
for r in roots:
r = S(r)
assert count_ops(simplify(r, ratio=1)) <= count_ops(r)
# If ratio=oo, simplify() is always applied:
assert simplify(r, ratio=oo) is not r
def test_simplify_measure():
measure1 = lambda expr: len(str(expr))
measure2 = lambda expr: -count_ops(expr)
# Return the most complicated result
expr = (x + 1)/(x + sin(x)**2 + cos(x)**2)
assert measure1(simplify(expr, measure=measure1)) <= measure1(expr)
assert measure2(simplify(expr, measure=measure2)) <= measure2(expr)
expr2 = Eq(sin(x)**2 + cos(x)**2, 1)
assert measure1(simplify(expr2, measure=measure1)) <= measure1(expr2)
assert measure2(simplify(expr2, measure=measure2)) <= measure2(expr2)
def test_simplify_rational():
expr = 2**x*2.**y
assert simplify(expr, rational = True) == 2**(x+y)
assert simplify(expr, rational = None) == 2.0**(x+y)
assert simplify(expr, rational = False) == expr
assert simplify('0.9 - 0.8 - 0.1', rational = True) == 0
def test_simplify_issue_1308():
assert simplify(exp(Rational(-1, 2)) + exp(Rational(-3, 2))) == \
(1 + E)*exp(Rational(-3, 2))
def test_issue_5652():
assert simplify(E + exp(-E)) == exp(-E) + E
n = symbols('n', commutative=False)
assert simplify(n + n**(-n)) == n + n**(-n)
def test_simplify_fail1():
x = Symbol('x')
y = Symbol('y')
e = (x + y)**2/(-4*x*y**2 - 2*y**3 - 2*x**2*y)
assert simplify(e) == 1 / (-2*y)
def test_nthroot():
assert nthroot(90 + 34*sqrt(7), 3) == sqrt(7) + 3
q = 1 + sqrt(2) - 2*sqrt(3) + sqrt(6) + sqrt(7)
assert nthroot(expand_multinomial(q**3), 3) == q
assert nthroot(41 + 29*sqrt(2), 5) == 1 + sqrt(2)
assert nthroot(-41 - 29*sqrt(2), 5) == -1 - sqrt(2)
expr = 1320*sqrt(10) + 4216 + 2576*sqrt(6) + 1640*sqrt(15)
assert nthroot(expr, 5) == 1 + sqrt(6) + sqrt(15)
q = 1 + sqrt(2) + sqrt(3) + sqrt(5)
assert expand_multinomial(nthroot(expand_multinomial(q**5), 5)) == q
q = 1 + sqrt(2) + 7*sqrt(6) + 2*sqrt(10)
assert nthroot(expand_multinomial(q**5), 5, 8) == q
q = 1 + sqrt(2) - 2*sqrt(3) + 1171*sqrt(6)
assert nthroot(expand_multinomial(q**3), 3) == q
assert nthroot(expand_multinomial(q**6), 6) == q
def test_nthroot1():
q = 1 + sqrt(2) + sqrt(3) + S.One/10**20
p = expand_multinomial(q**5)
assert nthroot(p, 5) == q
q = 1 + sqrt(2) + sqrt(3) + S.One/10**30
p = expand_multinomial(q**5)
assert nthroot(p, 5) == q
@_both_exp_pow
def test_separatevars():
x, y, z, n = symbols('x,y,z,n')
assert separatevars(2*n*x*z + 2*x*y*z) == 2*x*z*(n + y)
assert separatevars(x*z + x*y*z) == x*z*(1 + y)
assert separatevars(pi*x*z + pi*x*y*z) == pi*x*z*(1 + y)
assert separatevars(x*y**2*sin(x) + x*sin(x)*sin(y)) == \
x*(sin(y) + y**2)*sin(x)
assert separatevars(x*exp(x + y) + x*exp(x)) == x*(1 + exp(y))*exp(x)
assert separatevars((x*(y + 1))**z).is_Pow # != x**z*(1 + y)**z
assert separatevars(1 + x + y + x*y) == (x + 1)*(y + 1)
assert separatevars(y/pi*exp(-(z - x)/cos(n))) == \
y*exp(x/cos(n))*exp(-z/cos(n))/pi
assert separatevars((x + y)*(x - y) + y**2 + 2*x + 1) == (x + 1)**2
# issue 4858
p = Symbol('p', positive=True)
assert separatevars(sqrt(p**2 + x*p**2)) == p*sqrt(1 + x)
assert separatevars(sqrt(y*(p**2 + x*p**2))) == p*sqrt(y*(1 + x))
assert separatevars(sqrt(y*(p**2 + x*p**2)), force=True) == \
p*sqrt(y)*sqrt(1 + x)
# issue 4865
assert separatevars(sqrt(x*y)).is_Pow
assert separatevars(sqrt(x*y), force=True) == sqrt(x)*sqrt(y)
# issue 4957
# any type sequence for symbols is fine
assert separatevars(((2*x + 2)*y), dict=True, symbols=()) == \
{'coeff': 1, x: 2*x + 2, y: y}
# separable
assert separatevars(((2*x + 2)*y), dict=True, symbols=[x]) == \
{'coeff': y, x: 2*x + 2}
assert separatevars(((2*x + 2)*y), dict=True, symbols=[]) == \
{'coeff': 1, x: 2*x + 2, y: y}
assert separatevars(((2*x + 2)*y), dict=True) == \
{'coeff': 1, x: 2*x + 2, y: y}
assert separatevars(((2*x + 2)*y), dict=True, symbols=None) == \
{'coeff': y*(2*x + 2)}
# not separable
assert separatevars(3, dict=True) is None
assert separatevars(2*x + y, dict=True, symbols=()) is None
assert separatevars(2*x + y, dict=True) is None
assert separatevars(2*x + y, dict=True, symbols=None) == {'coeff': 2*x + y}
# issue 4808
n, m = symbols('n,m', commutative=False)
assert separatevars(m + n*m) == (1 + n)*m
assert separatevars(x + x*n) == x*(1 + n)
# issue 4910
f = Function('f')
assert separatevars(f(x) + x*f(x)) == f(x) + x*f(x)
# a noncommutable object present
eq = x*(1 + hyper((), (), y*z))
assert separatevars(eq) == eq
s = separatevars(abs(x*y))
assert s == abs(x)*abs(y) and s.is_Mul
z = cos(1)**2 + sin(1)**2 - 1
a = abs(x*z)
s = separatevars(a)
assert not a.is_Mul and s.is_Mul and s == abs(x)*abs(z)
s = separatevars(abs(x*y*z))
assert s == abs(x)*abs(y)*abs(z)
# abs(x+y)/abs(z) would be better but we test this here to
# see that it doesn't raise
assert separatevars(abs((x+y)/z)) == abs((x+y)/z)
def test_separatevars_advanced_factor():
x, y, z = symbols('x,y,z')
assert separatevars(1 + log(x)*log(y) + log(x) + log(y)) == \
(log(x) + 1)*(log(y) + 1)
assert separatevars(1 + x - log(z) - x*log(z) - exp(y)*log(z) -
x*exp(y)*log(z) + x*exp(y) + exp(y)) == \
-((x + 1)*(log(z) - 1)*(exp(y) + 1))
x, y = symbols('x,y', positive=True)
assert separatevars(1 + log(x**log(y)) + log(x*y)) == \
(log(x) + 1)*(log(y) + 1)
def test_hypersimp():
n, k = symbols('n,k', integer=True)
assert hypersimp(factorial(k), k) == k + 1
assert hypersimp(factorial(k**2), k) is None
assert hypersimp(1/factorial(k), k) == 1/(k + 1)
assert hypersimp(2**k/factorial(k)**2, k) == 2/(k + 1)**2
assert hypersimp(binomial(n, k), k) == (n - k)/(k + 1)
assert hypersimp(binomial(n + 1, k), k) == (n - k + 1)/(k + 1)
term = (4*k + 1)*factorial(k)/factorial(2*k + 1)
assert hypersimp(term, k) == S.Half*((4*k + 5)/(3 + 14*k + 8*k**2))
term = 1/((2*k - 1)*factorial(2*k + 1))
assert hypersimp(term, k) == (k - S.Half)/((k + 1)*(2*k + 1)*(2*k + 3))
term = binomial(n, k)*(-1)**k/factorial(k)
assert hypersimp(term, k) == (k - n)/(k + 1)**2
def test_nsimplify():
x = Symbol("x")
assert nsimplify(0) == 0
assert nsimplify(-1) == -1
assert nsimplify(1) == 1
assert nsimplify(1 + x) == 1 + x
assert nsimplify(2.7) == Rational(27, 10)
assert nsimplify(1 - GoldenRatio) == (1 - sqrt(5))/2
assert nsimplify((1 + sqrt(5))/4, [GoldenRatio]) == GoldenRatio/2
assert nsimplify(2/GoldenRatio, [GoldenRatio]) == 2*GoldenRatio - 2
assert nsimplify(exp(pi*I*Rational(5, 3), evaluate=False)) == \
sympify('1/2 - sqrt(3)*I/2')
assert nsimplify(sin(pi*Rational(3, 5), evaluate=False)) == \
sympify('sqrt(sqrt(5)/8 + 5/8)')
assert nsimplify(sqrt(atan('1', evaluate=False))*(2 + I), [pi]) == \
sqrt(pi) + sqrt(pi)/2*I
assert nsimplify(2 + exp(2*atan('1/4')*I)) == sympify('49/17 + 8*I/17')
assert nsimplify(pi, tolerance=0.01) == Rational(22, 7)
assert nsimplify(pi, tolerance=0.001) == Rational(355, 113)
assert nsimplify(0.33333, tolerance=1e-4) == Rational(1, 3)
assert nsimplify(2.0**(1/3.), tolerance=0.001) == Rational(635, 504)
assert nsimplify(2.0**(1/3.), tolerance=0.001, full=True) == \
2**Rational(1, 3)
assert nsimplify(x + .5, rational=True) == S.Half + x
assert nsimplify(1/.3 + x, rational=True) == Rational(10, 3) + x
assert nsimplify(log(3).n(), rational=True) == \
sympify('109861228866811/100000000000000')
assert nsimplify(Float(0.272198261287950), [pi, log(2)]) == pi*log(2)/8
assert nsimplify(Float(0.272198261287950).n(3), [pi, log(2)]) == \
-pi/4 - log(2) + Rational(7, 4)
assert nsimplify(x/7.0) == x/7
assert nsimplify(pi/1e2) == pi/100
assert nsimplify(pi/1e2, rational=False) == pi/100.0
assert nsimplify(pi/1e-7) == 10000000*pi
assert not nsimplify(
factor(-3.0*z**2*(z**2)**(-2.5) + 3*(z**2)**(-1.5))).atoms(Float)
e = x**0.0
assert e.is_Pow and nsimplify(x**0.0) == 1
assert nsimplify(3.333333, tolerance=0.1, rational=True) == Rational(10, 3)
assert nsimplify(3.333333, tolerance=0.01, rational=True) == Rational(10, 3)
assert nsimplify(3.666666, tolerance=0.1, rational=True) == Rational(11, 3)
assert nsimplify(3.666666, tolerance=0.01, rational=True) == Rational(11, 3)
assert nsimplify(33, tolerance=10, rational=True) == Rational(33)
assert nsimplify(33.33, tolerance=10, rational=True) == Rational(30)
assert nsimplify(37.76, tolerance=10, rational=True) == Rational(40)
assert nsimplify(-203.1) == Rational(-2031, 10)
assert nsimplify(.2, tolerance=0) == Rational(1, 5)
assert nsimplify(-.2, tolerance=0) == Rational(-1, 5)
assert nsimplify(.2222, tolerance=0) == Rational(1111, 5000)
assert nsimplify(-.2222, tolerance=0) == Rational(-1111, 5000)
# issue 7211, PR 4112
assert nsimplify(S(2e-8)) == Rational(1, 50000000)
# issue 7322 direct test
assert nsimplify(1e-42, rational=True) != 0
# issue 10336
inf = Float('inf')
infs = (-oo, oo, inf, -inf)
for zi in infs:
ans = sign(zi)*oo
assert nsimplify(zi) == ans
assert nsimplify(zi + x) == x + ans
assert nsimplify(0.33333333, rational=True, rational_conversion='exact') == Rational(0.33333333)
# Make sure nsimplify on expressions uses full precision
assert nsimplify(pi.evalf(100)*x, rational_conversion='exact').evalf(100) == pi.evalf(100)*x
def test_issue_9448():
tmp = sympify("1/(1 - (-1)**(2/3) - (-1)**(1/3)) + 1/(1 + (-1)**(2/3) + (-1)**(1/3))")
assert nsimplify(tmp) == S.Half
def test_extract_minus_sign():
x = Symbol("x")
y = Symbol("y")
a = Symbol("a")
b = Symbol("b")
assert simplify(-x/-y) == x/y
assert simplify(-x/y) == -x/y
assert simplify(x/y) == x/y
assert simplify(x/-y) == -x/y
assert simplify(-x/0) == zoo*x
assert simplify(Rational(-5, 0)) is zoo
assert simplify(-a*x/(-y - b)) == a*x/(b + y)
def test_diff():
x = Symbol("x")
y = Symbol("y")
f = Function("f")
g = Function("g")
assert simplify(g(x).diff(x)*f(x).diff(x) - f(x).diff(x)*g(x).diff(x)) == 0
assert simplify(2*f(x)*f(x).diff(x) - diff(f(x)**2, x)) == 0
assert simplify(diff(1/f(x), x) + f(x).diff(x)/f(x)**2) == 0
assert simplify(f(x).diff(x, y) - f(x).diff(y, x)) == 0
def test_logcombine_1():
x, y = symbols("x,y")
a = Symbol("a")
z, w = symbols("z,w", positive=True)
b = Symbol("b", real=True)
assert logcombine(log(x) + 2*log(y)) == log(x) + 2*log(y)
assert logcombine(log(x) + 2*log(y), force=True) == log(x*y**2)
assert logcombine(a*log(w) + log(z)) == a*log(w) + log(z)
assert logcombine(b*log(z) + b*log(x)) == log(z**b) + b*log(x)
assert logcombine(b*log(z) - log(w)) == log(z**b/w)
assert logcombine(log(x)*log(z)) == log(x)*log(z)
assert logcombine(log(w)*log(x)) == log(w)*log(x)
assert logcombine(cos(-2*log(z) + b*log(w))) in [cos(log(w**b/z**2)),
cos(log(z**2/w**b))]
assert logcombine(log(log(x) - log(y)) - log(z), force=True) == \
log(log(x/y)/z)
assert logcombine((2 + I)*log(x), force=True) == (2 + I)*log(x)
assert logcombine((x**2 + log(x) - log(y))/(x*y), force=True) == \
(x**2 + log(x/y))/(x*y)
# the following could also give log(z*x**log(y**2)), what we
# are testing is that a canonical result is obtained
assert logcombine(log(x)*2*log(y) + log(z), force=True) == \
log(z*y**log(x**2))
assert logcombine((x*y + sqrt(x**4 + y**4) + log(x) - log(y))/(pi*x**Rational(2, 3)*
sqrt(y)**3), force=True) == (
x*y + sqrt(x**4 + y**4) + log(x/y))/(pi*x**Rational(2, 3)*y**Rational(3, 2))
assert logcombine(gamma(-log(x/y))*acos(-log(x/y)), force=True) == \
acos(-log(x/y))*gamma(-log(x/y))
assert logcombine(2*log(z)*log(w)*log(x) + log(z) + log(w)) == \
log(z**log(w**2))*log(x) + log(w*z)
assert logcombine(3*log(w) + 3*log(z)) == log(w**3*z**3)
assert logcombine(x*(y + 1) + log(2) + log(3)) == x*(y + 1) + log(6)
assert logcombine((x + y)*log(w) + (-x - y)*log(3)) == (x + y)*log(w/3)
# a single unknown can combine
assert logcombine(log(x) + log(2)) == log(2*x)
eq = log(abs(x)) + log(abs(y))
assert logcombine(eq) == eq
reps = {x: 0, y: 0}
assert log(abs(x)*abs(y)).subs(reps) != eq.subs(reps)
def test_logcombine_complex_coeff():
i = Integral((sin(x**2) + cos(x**3))/x, x)
assert logcombine(i, force=True) == i
assert logcombine(i + 2*log(x), force=True) == \
i + log(x**2)
def test_issue_5950():
x, y = symbols("x,y", positive=True)
assert logcombine(log(3) - log(2)) == log(Rational(3,2), evaluate=False)
assert logcombine(log(x) - log(y)) == log(x/y)
assert logcombine(log(Rational(3,2), evaluate=False) - log(2)) == \
log(Rational(3,4), evaluate=False)
def test_posify():
x = symbols('x')
assert str(posify(
x +
Symbol('p', positive=True) +
Symbol('n', negative=True))) == '(_x + n + p, {_x: x})'
eq, rep = posify(1/x)
assert log(eq).expand().subs(rep) == -log(x)
assert str(posify([x, 1 + x])) == '([_x, _x + 1], {_x: x})'
p = symbols('p', positive=True)
n = symbols('n', negative=True)
orig = [x, n, p]
modified, reps = posify(orig)
assert str(modified) == '[_x, n, p]'
assert [w.subs(reps) for w in modified] == orig
assert str(Integral(posify(1/x + y)[0], (y, 1, 3)).expand()) == \
'Integral(1/_x, (y, 1, 3)) + Integral(_y, (y, 1, 3))'
assert str(Sum(posify(1/x**n)[0], (n,1,3)).expand()) == \
'Sum(_x**(-n), (n, 1, 3))'
# issue 16438
k = Symbol('k', finite=True)
eq, rep = posify(k)
assert eq.assumptions0 == {'positive': True, 'zero': False, 'imaginary': False,
'nonpositive': False, 'commutative': True, 'hermitian': True, 'real': True, 'nonzero': True,
'nonnegative': True, 'negative': False, 'complex': True, 'finite': True,
'infinite': False, 'extended_real':True, 'extended_negative': False,
'extended_nonnegative': True, 'extended_nonpositive': False,
'extended_nonzero': True, 'extended_positive': True}
def test_issue_4194():
# simplify should call cancel
f = Function('f')
assert simplify((4*x + 6*f(y))/(2*x + 3*f(y))) == 2
@XFAIL
def test_simplify_float_vs_integer():
# Test for issue 4473:
# https://github.com/sympy/sympy/issues/4473
assert simplify(x**2.0 - x**2) == 0
assert simplify(x**2 - x**2.0) == 0
def test_as_content_primitive():
assert (x/2 + y).as_content_primitive() == (S.Half, x + 2*y)
assert (x/2 + y).as_content_primitive(clear=False) == (S.One, x/2 + y)
assert (y*(x/2 + y)).as_content_primitive() == (S.Half, y*(x + 2*y))
assert (y*(x/2 + y)).as_content_primitive(clear=False) == (S.One, y*(x/2 + y))
# although the _as_content_primitive methods do not alter the underlying structure,
# the as_content_primitive function will touch up the expression and join
# bases that would otherwise have not been joined.
assert (x*(2 + 2*x)*(3*x + 3)**2).as_content_primitive() == \
(18, x*(x + 1)**3)
assert (2 + 2*x + 2*y*(3 + 3*y)).as_content_primitive() == \
(2, x + 3*y*(y + 1) + 1)
assert ((2 + 6*x)**2).as_content_primitive() == \
(4, (3*x + 1)**2)
assert ((2 + 6*x)**(2*y)).as_content_primitive() == \
(1, (_keep_coeff(S(2), (3*x + 1)))**(2*y))
assert (5 + 10*x + 2*y*(3 + 3*y)).as_content_primitive() == \
(1, 10*x + 6*y*(y + 1) + 5)
assert (5*(x*(1 + y)) + 2*x*(3 + 3*y)).as_content_primitive() == \
(11, x*(y + 1))
assert ((5*(x*(1 + y)) + 2*x*(3 + 3*y))**2).as_content_primitive() == \
(121, x**2*(y + 1)**2)
assert (y**2).as_content_primitive() == \
(1, y**2)
assert (S.Infinity).as_content_primitive() == (1, oo)
eq = x**(2 + y)
assert (eq).as_content_primitive() == (1, eq)
assert (S.Half**(2 + x)).as_content_primitive() == (Rational(1, 4), 2**-x)
assert (Rational(-1, 2)**(2 + x)).as_content_primitive() == \
(Rational(1, 4), (Rational(-1, 2))**x)
assert (Rational(-1, 2)**(2 + x)).as_content_primitive() == \
(Rational(1, 4), Rational(-1, 2)**x)
assert (4**((1 + y)/2)).as_content_primitive() == (2, 4**(y/2))
assert (3**((1 + y)/2)).as_content_primitive() == \
(1, 3**(Mul(S.Half, 1 + y, evaluate=False)))
assert (5**Rational(3, 4)).as_content_primitive() == (1, 5**Rational(3, 4))
assert (5**Rational(7, 4)).as_content_primitive() == (5, 5**Rational(3, 4))
assert Add(z*Rational(5, 7), 0.5*x, y*Rational(3, 2), evaluate=False).as_content_primitive() == \
(Rational(1, 14), 7.0*x + 21*y + 10*z)
assert (2**Rational(3, 4) + 2**Rational(1, 4)*sqrt(3)).as_content_primitive(radical=True) == \
(1, 2**Rational(1, 4)*(sqrt(2) + sqrt(3)))
def test_signsimp():
e = x*(-x + 1) + x*(x - 1)
assert signsimp(Eq(e, 0)) is S.true
assert Abs(x - 1) == Abs(1 - x)
assert signsimp(y - x) == y - x
assert signsimp(y - x, evaluate=False) == Mul(-1, x - y, evaluate=False)
def test_besselsimp():
from sympy.functions.special.bessel import (besseli, besselj, bessely)
from sympy.integrals.transforms import cosine_transform
assert besselsimp(exp(-I*pi*y/2)*besseli(y, z*exp_polar(I*pi/2))) == \
besselj(y, z)
assert besselsimp(exp(-I*pi*a/2)*besseli(a, 2*sqrt(x)*exp_polar(I*pi/2))) == \
besselj(a, 2*sqrt(x))
assert besselsimp(sqrt(2)*sqrt(pi)*x**Rational(1, 4)*exp(I*pi/4)*exp(-I*pi*a/2) *
besseli(Rational(-1, 2), sqrt(x)*exp_polar(I*pi/2)) *
besseli(a, sqrt(x)*exp_polar(I*pi/2))/2) == \
besselj(a, sqrt(x)) * cos(sqrt(x))
assert besselsimp(besseli(Rational(-1, 2), z)) == \
sqrt(2)*cosh(z)/(sqrt(pi)*sqrt(z))
assert besselsimp(besseli(a, z*exp_polar(-I*pi/2))) == \
exp(-I*pi*a/2)*besselj(a, z)
assert cosine_transform(1/t*sin(a/t), t, y) == \
sqrt(2)*sqrt(pi)*besselj(0, 2*sqrt(a)*sqrt(y))/2
assert besselsimp(x**2*(a*(-2*besselj(5*I, x) + besselj(-2 + 5*I, x) +
besselj(2 + 5*I, x)) + b*(-2*bessely(5*I, x) + bessely(-2 + 5*I, x) +
bessely(2 + 5*I, x)))/4 + x*(a*(besselj(-1 + 5*I, x)/2 - besselj(1 + 5*I, x)/2)
+ b*(bessely(-1 + 5*I, x)/2 - bessely(1 + 5*I, x)/2)) + (x**2 + 25)*(a*besselj(5*I, x)
+ b*bessely(5*I, x))) == 0
assert besselsimp(81*x**2*(a*(besselj(Rational(-5, 3), 9*x) - 2*besselj(Rational(1, 3), 9*x) + besselj(Rational(7, 3), 9*x))
+ b*(bessely(Rational(-5, 3), 9*x) - 2*bessely(Rational(1, 3), 9*x) + bessely(Rational(7, 3), 9*x)))/4 + x*(a*(9*besselj(Rational(-2, 3), 9*x)/2
- 9*besselj(Rational(4, 3), 9*x)/2) + b*(9*bessely(Rational(-2, 3), 9*x)/2 - 9*bessely(Rational(4, 3), 9*x)/2)) +
(81*x**2 - Rational(1, 9))*(a*besselj(Rational(1, 3), 9*x) + b*bessely(Rational(1, 3), 9*x))) == 0
assert besselsimp(besselj(a-1,x) + besselj(a+1, x) - 2*a*besselj(a, x)/x) == 0
assert besselsimp(besselj(a-1,x) + besselj(a+1, x) + besselj(a, x)) == (2*a + x)*besselj(a, x)/x
assert besselsimp(x**2* besselj(a,x) + x**3*besselj(a+1, x) + besselj(a+2, x)) == \
2*a*x*besselj(a + 1, x) + x**3*besselj(a + 1, x) - x**2*besselj(a + 2, x) + 2*x*besselj(a + 1, x) + besselj(a + 2, x)
def test_Piecewise():
e1 = x*(x + y) - y*(x + y)
e2 = sin(x)**2 + cos(x)**2
e3 = expand((x + y)*y/x)
s1 = simplify(e1)
s2 = simplify(e2)
s3 = simplify(e3)
assert simplify(Piecewise((e1, x < e2), (e3, True))) == \
Piecewise((s1, x < s2), (s3, True))
def test_polymorphism():
class A(Basic):
def _eval_simplify(x, **kwargs):
return S.One
a = A(5, 2)
assert simplify(a) == 1
def test_issue_from_PR1599():
n1, n2, n3, n4 = symbols('n1 n2 n3 n4', negative=True)
assert simplify(I*sqrt(n1)) == -sqrt(-n1)
def test_issue_6811():
eq = (x + 2*y)*(2*x + 2)
assert simplify(eq) == (x + 1)*(x + 2*y)*2
# reject the 2-arg Mul -- these are a headache for test writing
assert simplify(eq.expand()) == \
2*x**2 + 4*x*y + 2*x + 4*y
def test_issue_6920():
e = [cos(x) + I*sin(x), cos(x) - I*sin(x),
cosh(x) - sinh(x), cosh(x) + sinh(x)]
ok = [exp(I*x), exp(-I*x), exp(-x), exp(x)]
# wrap in f to show that the change happens wherever ei occurs
f = Function('f')
assert [simplify(f(ei)).args[0] for ei in e] == ok
def test_issue_7001():
from sympy.abc import r, R
assert simplify(-(r*Piecewise((pi*Rational(4, 3), r <= R),
(-8*pi*R**3/(3*r**3), True)) + 2*Piecewise((pi*r*Rational(4, 3), r <= R),
(4*pi*R**3/(3*r**2), True)))/(4*pi*r)) == \
Piecewise((-1, r <= R), (0, True))
def test_inequality_no_auto_simplify():
# no simplify on creation but can be simplified
lhs = cos(x)**2 + sin(x)**2
rhs = 2
e = Lt(lhs, rhs, evaluate=False)
assert e is not S.true
assert simplify(e)
def test_issue_9398():
from sympy.core.numbers import Number
from sympy.polys.polytools import cancel
assert cancel(1e-14) != 0
assert cancel(1e-14*I) != 0
assert simplify(1e-14) != 0
assert simplify(1e-14*I) != 0
assert (I*Number(1.)*Number(10)**Number(-14)).simplify() != 0
assert cancel(1e-20) != 0
assert cancel(1e-20*I) != 0
assert simplify(1e-20) != 0
assert simplify(1e-20*I) != 0
assert cancel(1e-100) != 0
assert cancel(1e-100*I) != 0
assert simplify(1e-100) != 0
assert simplify(1e-100*I) != 0
f = Float("1e-1000")
assert cancel(f) != 0
assert cancel(f*I) != 0
assert simplify(f) != 0
assert simplify(f*I) != 0
def test_issue_9324_simplify():
M = MatrixSymbol('M', 10, 10)
e = M[0, 0] + M[5, 4] + 1304
assert simplify(e) == e
def test_issue_9817_simplify():
# simplify on trace of substituted explicit quadratic form of matrix
# expressions (a scalar) should return without errors (AttributeError)
# See issue #9817 and #9190 for the original bug more discussion on this
from sympy.matrices.expressions import Identity, trace
v = MatrixSymbol('v', 3, 1)
A = MatrixSymbol('A', 3, 3)
x = Matrix([i + 1 for i in range(3)])
X = Identity(3)
quadratic = v.T * A * v
assert simplify((trace(quadratic.as_explicit())).xreplace({v:x, A:X})) == 14
def test_issue_13474():
x = Symbol('x')
assert simplify(x + csch(sinc(1))) == x + csch(sinc(1))
@_both_exp_pow
def test_simplify_function_inverse():
# "inverse" attribute does not guarantee that f(g(x)) is x
# so this simplification should not happen automatically.
# See issue #12140
x, y = symbols('x, y')
g = Function('g')
class f(Function):
def inverse(self, argindex=1):
return g
assert simplify(f(g(x))) == f(g(x))
assert inversecombine(f(g(x))) == x
assert simplify(f(g(x)), inverse=True) == x
assert simplify(f(g(sin(x)**2 + cos(x)**2)), inverse=True) == 1
assert simplify(f(g(x, y)), inverse=True) == f(g(x, y))
assert unchanged(asin, sin(x))
assert simplify(asin(sin(x))) == asin(sin(x))
assert simplify(2*asin(sin(3*x)), inverse=True) == 6*x
assert simplify(log(exp(x))) == log(exp(x))
assert simplify(log(exp(x)), inverse=True) == x
assert simplify(exp(log(x)), inverse=True) == x
assert simplify(log(exp(x), 2), inverse=True) == x/log(2)
assert simplify(log(exp(x), 2, evaluate=False), inverse=True) == x/log(2)
def test_clear_coefficients():
from sympy.simplify.simplify import clear_coefficients
assert clear_coefficients(4*y*(6*x + 3)) == (y*(2*x + 1), 0)
assert clear_coefficients(4*y*(6*x + 3) - 2) == (y*(2*x + 1), Rational(1, 6))
assert clear_coefficients(4*y*(6*x + 3) - 2, x) == (y*(2*x + 1), x/12 + Rational(1, 6))
assert clear_coefficients(sqrt(2) - 2) == (sqrt(2), 2)
assert clear_coefficients(4*sqrt(2) - 2) == (sqrt(2), S.Half)
assert clear_coefficients(S(3), x) == (0, x - 3)
assert clear_coefficients(S.Infinity, x) == (S.Infinity, x)
assert clear_coefficients(-S.Pi, x) == (S.Pi, -x)
assert clear_coefficients(2 - S.Pi/3, x) == (pi, -3*x + 6)
def test_nc_simplify():
from sympy.simplify.simplify import nc_simplify
from sympy.matrices.expressions import MatPow, Identity
from sympy.core import Pow
from functools import reduce
a, b, c, d = symbols('a b c d', commutative = False)
x = Symbol('x')
A = MatrixSymbol("A", x, x)
B = MatrixSymbol("B", x, x)
C = MatrixSymbol("C", x, x)
D = MatrixSymbol("D", x, x)
subst = {a: A, b: B, c: C, d:D}
funcs = {Add: lambda x,y: x+y, Mul: lambda x,y: x*y }
def _to_matrix(expr):
if expr in subst:
return subst[expr]
if isinstance(expr, Pow):
return MatPow(_to_matrix(expr.args[0]), expr.args[1])
elif isinstance(expr, (Add, Mul)):
return reduce(funcs[expr.func],[_to_matrix(a) for a in expr.args])
else:
return expr*Identity(x)
def _check(expr, simplified, deep=True, matrix=True):
assert nc_simplify(expr, deep=deep) == simplified
assert expand(expr) == expand(simplified)
if matrix:
m_simp = _to_matrix(simplified).doit(inv_expand=False)
assert nc_simplify(_to_matrix(expr), deep=deep) == m_simp
_check(a*b*a*b*a*b*c*(a*b)**3*c, ((a*b)**3*c)**2)
_check(a*b*(a*b)**-2*a*b, 1)
_check(a**2*b*a*b*a*b*(a*b)**-1, a*(a*b)**2, matrix=False)
_check(b*a*b**2*a*b**2*a*b**2, b*(a*b**2)**3)
_check(a*b*a**2*b*a**2*b*a**3, (a*b*a)**3*a**2)
_check(a**2*b*a**4*b*a**4*b*a**2, (a**2*b*a**2)**3)
_check(a**3*b*a**4*b*a**4*b*a, a**3*(b*a**4)**3*a**-3)
_check(a*b*a*b + a*b*c*x*a*b*c, (a*b)**2 + x*(a*b*c)**2)
_check(a*b*a*b*c*a*b*a*b*c, ((a*b)**2*c)**2)
_check(b**-1*a**-1*(a*b)**2, a*b)
_check(a**-1*b*c**-1, (c*b**-1*a)**-1)
expr = a**3*b*a**4*b*a**4*b*a**2*b*a**2*(b*a**2)**2*b*a**2*b*a**2
for _ in range(10):
expr *= a*b
_check(expr, a**3*(b*a**4)**2*(b*a**2)**6*(a*b)**10)
_check((a*b*a*b)**2, (a*b*a*b)**2, deep=False)
_check(a*b*(c*d)**2, a*b*(c*d)**2)
expr = b**-1*(a**-1*b**-1 - a**-1*c*b**-1)**-1*a**-1
assert nc_simplify(expr) == (1-c)**-1
# commutative expressions should be returned without an error
assert nc_simplify(2*x**2) == 2*x**2
def test_issue_15965():
A = Sum(z*x**y, (x, 1, a))
anew = z*Sum(x**y, (x, 1, a))
B = Integral(x*y, x)
bdo = x**2*y/2
assert simplify(A + B) == anew + bdo
assert simplify(A) == anew
assert simplify(B) == bdo
assert simplify(B, doit=False) == y*Integral(x, x)
def test_issue_17137():
assert simplify(cos(x)**I) == cos(x)**I
assert simplify(cos(x)**(2 + 3*I)) == cos(x)**(2 + 3*I)
def test_issue_21869():
x = Symbol('x', real=True)
y = Symbol('y', real=True)
expr = And(Eq(x**2, 4), Le(x, y))
assert expr.simplify() == expr
expr = And(Eq(x**2, 4), Eq(x, 2))
assert expr.simplify() == Eq(x, 2)
expr = And(Eq(x**3, x**2), Eq(x, 1))
assert expr.simplify() == Eq(x, 1)
expr = And(Eq(sin(x), x**2), Eq(x, 0))
assert expr.simplify() == Eq(x, 0)
expr = And(Eq(x**3, x**2), Eq(x, 2))
assert expr.simplify() == S.false
expr = And(Eq(y, x**2), Eq(x, 1))
assert expr.simplify() == And(Eq(y,1), Eq(x, 1))
expr = And(Eq(y**2, 1), Eq(y, x**2), Eq(x, 1))
assert expr.simplify() == And(Eq(y,1), Eq(x, 1))
expr = And(Eq(y**2, 4), Eq(y, 2*x**2), Eq(x, 1))
assert expr.simplify() == And(Eq(y,2), Eq(x, 1))
expr = And(Eq(y**2, 4), Eq(y, x**2), Eq(x, 1))
assert expr.simplify() == S.false
def test_issue_7971_21740():
z = Integral(x, (x, 1, 1))
assert z != 0
assert simplify(z) is S.Zero
assert simplify(S.Zero) is S.Zero
z = simplify(Float(0))
assert z is not S.Zero and z == 0
@slow
def test_issue_17141_slow():
# Should not give RecursionError
assert simplify((2**acos(I+1)**2).rewrite('log')) == 2**((pi + 2*I*log(-1 +
sqrt(1 - 2*I) + I))**2/4)
def test_issue_17141():
# Check that there is no RecursionError
assert simplify(x**(1 / acos(I))) == x**(2/(pi - 2*I*log(1 + sqrt(2))))
assert simplify(acos(-I)**2*acos(I)**2) == \
log(1 + sqrt(2))**4 + pi**2*log(1 + sqrt(2))**2/2 + pi**4/16
assert simplify(2**acos(I)**2) == 2**((pi - 2*I*log(1 + sqrt(2)))**2/4)
p = 2**acos(I+1)**2
assert simplify(p) == p
def test_simplify_kroneckerdelta():
i, j = symbols("i j")
K = KroneckerDelta
assert simplify(K(i, j)) == K(i, j)
assert simplify(K(0, j)) == K(0, j)
assert simplify(K(i, 0)) == K(i, 0)
assert simplify(K(0, j).rewrite(Piecewise) * K(1, j)) == 0
assert simplify(K(1, i) + Piecewise((1, Eq(j, 2)), (0, True))) == K(1, i) + K(2, j)
# issue 17214
assert simplify(K(0, j) * K(1, j)) == 0
n = Symbol('n', integer=True)
assert simplify(K(0, n) * K(1, n)) == 0
M = Matrix(4, 4, lambda i, j: K(j - i, n) if i <= j else 0)
assert simplify(M**2) == Matrix([[K(0, n), 0, K(1, n), 0],
[0, K(0, n), 0, K(1, n)],
[0, 0, K(0, n), 0],
[0, 0, 0, K(0, n)]])
assert simplify(eye(1) * KroneckerDelta(0, n) *
KroneckerDelta(1, n)) == Matrix([[0]])
assert simplify(S.Infinity * KroneckerDelta(0, n) *
KroneckerDelta(1, n)) is S.NaN
def test_issue_17292():
assert simplify(abs(x)/abs(x**2)) == 1/abs(x)
# this is bigger than the issue: check that deep processing works
assert simplify(5*abs((x**2 - 1)/(x - 1))) == 5*Abs(x + 1)
def test_issue_19822():
expr = And(Gt(n-2, 1), Gt(n, 1))
assert simplify(expr) == Gt(n, 3)
def test_issue_18645():
expr = And(Ge(x, 3), Le(x, 3))
assert simplify(expr) == Eq(x, 3)
expr = And(Eq(x, 3), Le(x, 3))
assert simplify(expr) == Eq(x, 3)
@XFAIL
def test_issue_18642():
i = Symbol("i", integer=True)
n = Symbol("n", integer=True)
expr = And(Eq(i, 2 * n), Le(i, 2*n -1))
assert simplify(expr) == S.false
@XFAIL
def test_issue_18389():
n = Symbol("n", integer=True)
expr = Eq(n, 0) | (n >= 1)
assert simplify(expr) == Ge(n, 0)
def test_issue_8373():
x = Symbol('x', real=True)
assert simplify(Or(x < 1, x >= 1)) == S.true
def test_issue_7950():
expr = And(Eq(x, 1), Eq(x, 2))
assert simplify(expr) == S.false
def test_issue_22020():
expr = I*pi/2 -oo
assert simplify(expr) == expr
# Used to throw an error
def test_issue_19484():
assert simplify(sign(x) * Abs(x)) == x
e = x + sign(x + x**3)
assert simplify(Abs(x + x**3)*e) == x**3 + x*Abs(x**3 + x) + x
e = x**2 + sign(x**3 + 1)
assert simplify(Abs(x**3 + 1) * e) == x**3 + x**2*Abs(x**3 + 1) + 1
f = Function('f')
e = x + sign(x + f(x)**3)
assert simplify(Abs(x + f(x)**3) * e) == x*Abs(x + f(x)**3) + x + f(x)**3
def test_issue_19161():
polynomial = Poly('x**2').simplify()
assert (polynomial-x**2).simplify() == 0
def test_issue_22210():
d = Symbol('d', integer=True)
expr = 2*Derivative(sin(x), (x, d))
assert expr.simplify() == expr
|
ba0b1095fb8ae8f3a28b175e8adeb7428bec540946e49c8268f94fa748f7e4b1 | """Tests for tools for manipulation of expressions using paths. """
from sympy.simplify.epathtools import epath, EPath
from sympy.testing.pytest import raises
from sympy.core.numbers import E
from sympy.functions.elementary.trigonometric import (cos, sin)
from sympy.abc import x, y, z, t
def test_epath_select():
expr = [((x, 1, t), 2), ((3, y, 4), z)]
assert epath("/*", expr) == [((x, 1, t), 2), ((3, y, 4), z)]
assert epath("/*/*", expr) == [(x, 1, t), 2, (3, y, 4), z]
assert epath("/*/*/*", expr) == [x, 1, t, 3, y, 4]
assert epath("/*/*/*/*", expr) == []
assert epath("/[:]", expr) == [((x, 1, t), 2), ((3, y, 4), z)]
assert epath("/[:]/[:]", expr) == [(x, 1, t), 2, (3, y, 4), z]
assert epath("/[:]/[:]/[:]", expr) == [x, 1, t, 3, y, 4]
assert epath("/[:]/[:]/[:]/[:]", expr) == []
assert epath("/*/[:]", expr) == [(x, 1, t), 2, (3, y, 4), z]
assert epath("/*/[0]", expr) == [(x, 1, t), (3, y, 4)]
assert epath("/*/[1]", expr) == [2, z]
assert epath("/*/[2]", expr) == []
assert epath("/*/int", expr) == [2]
assert epath("/*/Symbol", expr) == [z]
assert epath("/*/tuple", expr) == [(x, 1, t), (3, y, 4)]
assert epath("/*/__iter__?", expr) == [(x, 1, t), (3, y, 4)]
assert epath("/*/int|tuple", expr) == [(x, 1, t), 2, (3, y, 4)]
assert epath("/*/Symbol|tuple", expr) == [(x, 1, t), (3, y, 4), z]
assert epath("/*/int|Symbol|tuple", expr) == [(x, 1, t), 2, (3, y, 4), z]
assert epath("/*/int|__iter__?", expr) == [(x, 1, t), 2, (3, y, 4)]
assert epath("/*/Symbol|__iter__?", expr) == [(x, 1, t), (3, y, 4), z]
assert epath(
"/*/int|Symbol|__iter__?", expr) == [(x, 1, t), 2, (3, y, 4), z]
assert epath("/*/[0]/int", expr) == [1, 3, 4]
assert epath("/*/[0]/Symbol", expr) == [x, t, y]
assert epath("/*/[0]/int[1:]", expr) == [1, 4]
assert epath("/*/[0]/Symbol[1:]", expr) == [t, y]
assert epath("/Symbol", x + y + z + 1) == [x, y, z]
assert epath("/*/*/Symbol", t + sin(x + 1) + cos(x + y + E)) == [x, x, y]
def test_epath_apply():
expr = [((x, 1, t), 2), ((3, y, 4), z)]
func = lambda expr: expr**2
assert epath("/*", expr, list) == [[(x, 1, t), 2], [(3, y, 4), z]]
assert epath("/*/[0]", expr, list) == [([x, 1, t], 2), ([3, y, 4], z)]
assert epath("/*/[1]", expr, func) == [((x, 1, t), 4), ((3, y, 4), z**2)]
assert epath("/*/[2]", expr, list) == expr
assert epath("/*/[0]/int", expr, func) == [((x, 1, t), 2), ((9, y, 16), z)]
assert epath("/*/[0]/Symbol", expr, func) == [((x**2, 1, t**2), 2),
((3, y**2, 4), z)]
assert epath(
"/*/[0]/int[1:]", expr, func) == [((x, 1, t), 2), ((3, y, 16), z)]
assert epath("/*/[0]/Symbol[1:]", expr, func) == [((x, 1, t**2),
2), ((3, y**2, 4), z)]
assert epath("/Symbol", x + y + z + 1, func) == x**2 + y**2 + z**2 + 1
assert epath("/*/*/Symbol", t + sin(x + 1) + cos(x + y + E), func) == \
t + sin(x**2 + 1) + cos(x**2 + y**2 + E)
def test_EPath():
assert EPath("/*/[0]")._path == "/*/[0]"
assert EPath(EPath("/*/[0]"))._path == "/*/[0]"
assert isinstance(epath("/*/[0]"), EPath) is True
assert repr(EPath("/*/[0]")) == "EPath('/*/[0]')"
raises(ValueError, lambda: EPath(""))
raises(ValueError, lambda: EPath("/"))
raises(ValueError, lambda: EPath("/|x"))
raises(ValueError, lambda: EPath("/["))
raises(ValueError, lambda: EPath("/[0]%"))
raises(NotImplementedError, lambda: EPath("Symbol"))
|
95d40b21f5d75981d814971877b78a546bafc01c12259e51ffd9dcbaddee19c2 | from functools import reduce
import itertools
from operator import add
from sympy.core.add import Add
from sympy.core.containers import Tuple
from sympy.core.function import Function
from sympy.core.mul import Mul
from sympy.core.power import Pow
from sympy.core.relational import Eq
from sympy.core.singleton import S
from sympy.core.symbol import (Symbol, symbols)
from sympy.core.sympify import sympify
from sympy.functions.elementary.exponential import exp
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.piecewise import Piecewise
from sympy.functions.elementary.trigonometric import (cos, sin)
from sympy.matrices.dense import Matrix
from sympy.polys.rootoftools import CRootOf
from sympy.series.order import O
from sympy.simplify.cse_main import cse
from sympy.simplify.simplify import signsimp
from sympy.tensor.indexed import (Idx, IndexedBase)
from sympy.core.function import count_ops
from sympy.simplify.cse_opts import sub_pre, sub_post
from sympy.functions.special.hyper import meijerg
from sympy.simplify import cse_main, cse_opts
from sympy.utilities.iterables import subsets
from sympy.testing.pytest import XFAIL, raises
from sympy.matrices import (MutableDenseMatrix, MutableSparseMatrix,
ImmutableDenseMatrix, ImmutableSparseMatrix)
from sympy.matrices.expressions import MatrixSymbol
w, x, y, z = symbols('w,x,y,z')
x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, x10, x11, x12 = symbols('x:13')
def test_numbered_symbols():
ns = cse_main.numbered_symbols(prefix='y')
assert list(itertools.islice(
ns, 0, 10)) == [Symbol('y%s' % i) for i in range(0, 10)]
ns = cse_main.numbered_symbols(prefix='y')
assert list(itertools.islice(
ns, 10, 20)) == [Symbol('y%s' % i) for i in range(10, 20)]
ns = cse_main.numbered_symbols()
assert list(itertools.islice(
ns, 0, 10)) == [Symbol('x%s' % i) for i in range(0, 10)]
# Dummy "optimization" functions for testing.
def opt1(expr):
return expr + y
def opt2(expr):
return expr*z
def test_preprocess_for_cse():
assert cse_main.preprocess_for_cse(x, [(opt1, None)]) == x + y
assert cse_main.preprocess_for_cse(x, [(None, opt1)]) == x
assert cse_main.preprocess_for_cse(x, [(None, None)]) == x
assert cse_main.preprocess_for_cse(x, [(opt1, opt2)]) == x + y
assert cse_main.preprocess_for_cse(
x, [(opt1, None), (opt2, None)]) == (x + y)*z
def test_postprocess_for_cse():
assert cse_main.postprocess_for_cse(x, [(opt1, None)]) == x
assert cse_main.postprocess_for_cse(x, [(None, opt1)]) == x + y
assert cse_main.postprocess_for_cse(x, [(None, None)]) == x
assert cse_main.postprocess_for_cse(x, [(opt1, opt2)]) == x*z
# Note the reverse order of application.
assert cse_main.postprocess_for_cse(
x, [(None, opt1), (None, opt2)]) == x*z + y
def test_cse_single():
# Simple substitution.
e = Add(Pow(x + y, 2), sqrt(x + y))
substs, reduced = cse([e])
assert substs == [(x0, x + y)]
assert reduced == [sqrt(x0) + x0**2]
subst42, (red42,) = cse([42]) # issue_15082
assert len(subst42) == 0 and red42 == 42
subst_half, (red_half,) = cse([0.5])
assert len(subst_half) == 0 and red_half == 0.5
def test_cse_single2():
# Simple substitution, test for being able to pass the expression directly
e = Add(Pow(x + y, 2), sqrt(x + y))
substs, reduced = cse(e)
assert substs == [(x0, x + y)]
assert reduced == [sqrt(x0) + x0**2]
substs, reduced = cse(Matrix([[1]]))
assert isinstance(reduced[0], Matrix)
subst42, (red42,) = cse(42) # issue 15082
assert len(subst42) == 0 and red42 == 42
subst_half, (red_half,) = cse(0.5) # issue 15082
assert len(subst_half) == 0 and red_half == 0.5
def test_cse_not_possible():
# No substitution possible.
e = Add(x, y)
substs, reduced = cse([e])
assert substs == []
assert reduced == [x + y]
# issue 6329
eq = (meijerg((1, 2), (y, 4), (5,), [], x) +
meijerg((1, 3), (y, 4), (5,), [], x))
assert cse(eq) == ([], [eq])
def test_nested_substitution():
# Substitution within a substitution.
e = Add(Pow(w*x + y, 2), sqrt(w*x + y))
substs, reduced = cse([e])
assert substs == [(x0, w*x + y)]
assert reduced == [sqrt(x0) + x0**2]
def test_subtraction_opt():
# Make sure subtraction is optimized.
e = (x - y)*(z - y) + exp((x - y)*(z - y))
substs, reduced = cse(
[e], optimizations=[(cse_opts.sub_pre, cse_opts.sub_post)])
assert substs == [(x0, (x - y)*(y - z))]
assert reduced == [-x0 + exp(-x0)]
e = -(x - y)*(z - y) + exp(-(x - y)*(z - y))
substs, reduced = cse(
[e], optimizations=[(cse_opts.sub_pre, cse_opts.sub_post)])
assert substs == [(x0, (x - y)*(y - z))]
assert reduced == [x0 + exp(x0)]
# issue 4077
n = -1 + 1/x
e = n/x/(-n)**2 - 1/n/x
assert cse(e, optimizations=[(cse_opts.sub_pre, cse_opts.sub_post)]) == \
([], [0])
assert cse(((w + x + y + z)*(w - y - z))/(w + x)**3) == \
([(x0, w + x), (x1, y + z)], [(w - x1)*(x0 + x1)/x0**3])
def test_multiple_expressions():
e1 = (x + y)*z
e2 = (x + y)*w
substs, reduced = cse([e1, e2])
assert substs == [(x0, x + y)]
assert reduced == [x0*z, x0*w]
l = [w*x*y + z, w*y]
substs, reduced = cse(l)
rsubsts, _ = cse(reversed(l))
assert substs == rsubsts
assert reduced == [z + x*x0, x0]
l = [w*x*y, w*x*y + z, w*y]
substs, reduced = cse(l)
rsubsts, _ = cse(reversed(l))
assert substs == rsubsts
assert reduced == [x1, x1 + z, x0]
l = [(x - z)*(y - z), x - z, y - z]
substs, reduced = cse(l)
rsubsts, _ = cse(reversed(l))
assert substs == [(x0, -z), (x1, x + x0), (x2, x0 + y)]
assert rsubsts == [(x0, -z), (x1, x0 + y), (x2, x + x0)]
assert reduced == [x1*x2, x1, x2]
l = [w*y + w + x + y + z, w*x*y]
assert cse(l) == ([(x0, w*y)], [w + x + x0 + y + z, x*x0])
assert cse([x + y, x + y + z]) == ([(x0, x + y)], [x0, z + x0])
assert cse([x + y, x + z]) == ([], [x + y, x + z])
assert cse([x*y, z + x*y, x*y*z + 3]) == \
([(x0, x*y)], [x0, z + x0, 3 + x0*z])
@XFAIL # CSE of non-commutative Mul terms is disabled
def test_non_commutative_cse():
A, B, C = symbols('A B C', commutative=False)
l = [A*B*C, A*C]
assert cse(l) == ([], l)
l = [A*B*C, A*B]
assert cse(l) == ([(x0, A*B)], [x0*C, x0])
# Test if CSE of non-commutative Mul terms is disabled
def test_bypass_non_commutatives():
A, B, C = symbols('A B C', commutative=False)
l = [A*B*C, A*C]
assert cse(l) == ([], l)
l = [A*B*C, A*B]
assert cse(l) == ([], l)
l = [B*C, A*B*C]
assert cse(l) == ([], l)
@XFAIL # CSE fails when replacing non-commutative sub-expressions
def test_non_commutative_order():
A, B, C = symbols('A B C', commutative=False)
x0 = symbols('x0', commutative=False)
l = [B+C, A*(B+C)]
assert cse(l) == ([(x0, B+C)], [x0, A*x0])
@XFAIL # Worked in gh-11232, but was reverted due to performance considerations
def test_issue_10228():
assert cse([x*y**2 + x*y]) == ([(x0, x*y)], [x0*y + x0])
assert cse([x + y, 2*x + y]) == ([(x0, x + y)], [x0, x + x0])
assert cse((w + 2*x + y + z, w + x + 1)) == (
[(x0, w + x)], [x0 + x + y + z, x0 + 1])
assert cse(((w + x + y + z)*(w - x))/(w + x)) == (
[(x0, w + x)], [(x0 + y + z)*(w - x)/x0])
a, b, c, d, f, g, j, m = symbols('a, b, c, d, f, g, j, m')
exprs = (d*g**2*j*m, 4*a*f*g*m, a*b*c*f**2)
assert cse(exprs) == (
[(x0, g*m), (x1, a*f)], [d*g*j*x0, 4*x0*x1, b*c*f*x1]
)
@XFAIL
def test_powers():
assert cse(x*y**2 + x*y) == ([(x0, x*y)], [x0*y + x0])
def test_issue_4498():
assert cse(w/(x - y) + z/(y - x), optimizations='basic') == \
([], [(w - z)/(x - y)])
def test_issue_4020():
assert cse(x**5 + x**4 + x**3 + x**2, optimizations='basic') \
== ([(x0, x**2)], [x0*(x**3 + x + x0 + 1)])
def test_issue_4203():
assert cse(sin(x**x)/x**x) == ([(x0, x**x)], [sin(x0)/x0])
def test_issue_6263():
e = Eq(x*(-x + 1) + x*(x - 1), 0)
assert cse(e, optimizations='basic') == ([], [True])
def test_dont_cse_tuples():
from sympy.core.function import Subs
f = Function("f")
g = Function("g")
name_val, (expr,) = cse(
Subs(f(x, y), (x, y), (0, 1))
+ Subs(g(x, y), (x, y), (0, 1)))
assert name_val == []
assert expr == (Subs(f(x, y), (x, y), (0, 1))
+ Subs(g(x, y), (x, y), (0, 1)))
name_val, (expr,) = cse(
Subs(f(x, y), (x, y), (0, x + y))
+ Subs(g(x, y), (x, y), (0, x + y)))
assert name_val == [(x0, x + y)]
assert expr == Subs(f(x, y), (x, y), (0, x0)) + \
Subs(g(x, y), (x, y), (0, x0))
def test_pow_invpow():
assert cse(1/x**2 + x**2) == \
([(x0, x**2)], [x0 + 1/x0])
assert cse(x**2 + (1 + 1/x**2)/x**2) == \
([(x0, x**2), (x1, 1/x0)], [x0 + x1*(x1 + 1)])
assert cse(1/x**2 + (1 + 1/x**2)*x**2) == \
([(x0, x**2), (x1, 1/x0)], [x0*(x1 + 1) + x1])
assert cse(cos(1/x**2) + sin(1/x**2)) == \
([(x0, x**(-2))], [sin(x0) + cos(x0)])
assert cse(cos(x**2) + sin(x**2)) == \
([(x0, x**2)], [sin(x0) + cos(x0)])
assert cse(y/(2 + x**2) + z/x**2/y) == \
([(x0, x**2)], [y/(x0 + 2) + z/(x0*y)])
assert cse(exp(x**2) + x**2*cos(1/x**2)) == \
([(x0, x**2)], [x0*cos(1/x0) + exp(x0)])
assert cse((1 + 1/x**2)/x**2) == \
([(x0, x**(-2))], [x0*(x0 + 1)])
assert cse(x**(2*y) + x**(-2*y)) == \
([(x0, x**(2*y))], [x0 + 1/x0])
def test_postprocess():
eq = (x + 1 + exp((x + 1)/(y + 1)) + cos(y + 1))
assert cse([eq, Eq(x, z + 1), z - 2, (z + 1)*(x + 1)],
postprocess=cse_main.cse_separate) == \
[[(x0, y + 1), (x2, z + 1), (x, x2), (x1, x + 1)],
[x1 + exp(x1/x0) + cos(x0), z - 2, x1*x2]]
def test_issue_4499():
# previously, this gave 16 constants
from sympy.abc import a, b
B = Function('B')
G = Function('G')
t = Tuple(*
(a, a + S.Half, 2*a, b, 2*a - b + 1, (sqrt(z)/2)**(-2*a + 1)*B(2*a -
b, sqrt(z))*B(b - 1, sqrt(z))*G(b)*G(2*a - b + 1),
sqrt(z)*(sqrt(z)/2)**(-2*a + 1)*B(b, sqrt(z))*B(2*a - b,
sqrt(z))*G(b)*G(2*a - b + 1), sqrt(z)*(sqrt(z)/2)**(-2*a + 1)*B(b - 1,
sqrt(z))*B(2*a - b + 1, sqrt(z))*G(b)*G(2*a - b + 1),
(sqrt(z)/2)**(-2*a + 1)*B(b, sqrt(z))*B(2*a - b + 1,
sqrt(z))*G(b)*G(2*a - b + 1), 1, 0, S.Half, z/2, -b + 1, -2*a + b,
-2*a))
c = cse(t)
ans = (
[(x0, 2*a), (x1, -b + x0), (x2, x1 + 1), (x3, b - 1), (x4, sqrt(z)),
(x5, B(x3, x4)), (x6, (x4/2)**(1 - x0)*G(b)*G(x2)), (x7, x6*B(x1, x4)),
(x8, B(b, x4)), (x9, x6*B(x2, x4))],
[(a, a + S.Half, x0, b, x2, x5*x7, x4*x7*x8, x4*x5*x9, x8*x9,
1, 0, S.Half, z/2, -x3, -x1, -x0)])
assert ans == c
def test_issue_6169():
r = CRootOf(x**6 - 4*x**5 - 2, 1)
assert cse(r) == ([], [r])
# and a check that the right thing is done with the new
# mechanism
assert sub_post(sub_pre((-x - y)*z - x - y)) == -z*(x + y) - x - y
def test_cse_Indexed():
len_y = 5
y = IndexedBase('y', shape=(len_y,))
x = IndexedBase('x', shape=(len_y,))
i = Idx('i', len_y-1)
expr1 = (y[i+1]-y[i])/(x[i+1]-x[i])
expr2 = 1/(x[i+1]-x[i])
replacements, reduced_exprs = cse([expr1, expr2])
assert len(replacements) > 0
def test_cse_MatrixSymbol():
# MatrixSymbols have non-Basic args, so make sure that works
A = MatrixSymbol("A", 3, 3)
assert cse(A) == ([], [A])
n = symbols('n', integer=True)
B = MatrixSymbol("B", n, n)
assert cse(B) == ([], [B])
def test_cse_MatrixExpr():
A = MatrixSymbol('A', 3, 3)
y = MatrixSymbol('y', 3, 1)
expr1 = (A.T*A).I * A * y
expr2 = (A.T*A) * A * y
replacements, reduced_exprs = cse([expr1, expr2])
assert len(replacements) > 0
replacements, reduced_exprs = cse([expr1 + expr2, expr1])
assert replacements
replacements, reduced_exprs = cse([A**2, A + A**2])
assert replacements
def test_Piecewise():
f = Piecewise((-z + x*y, Eq(y, 0)), (-z - x*y, True))
ans = cse(f)
actual_ans = ([(x0, x*y)],
[Piecewise((x0 - z, Eq(y, 0)), (-z - x0, True))])
assert ans == actual_ans
def test_ignore_order_terms():
eq = exp(x).series(x,0,3) + sin(y+x**3) - 1
assert cse(eq) == ([], [sin(x**3 + y) + x + x**2/2 + O(x**3)])
def test_name_conflict():
z1 = x0 + y
z2 = x2 + x3
l = [cos(z1) + z1, cos(z2) + z2, x0 + x2]
substs, reduced = cse(l)
assert [e.subs(reversed(substs)) for e in reduced] == l
def test_name_conflict_cust_symbols():
z1 = x0 + y
z2 = x2 + x3
l = [cos(z1) + z1, cos(z2) + z2, x0 + x2]
substs, reduced = cse(l, symbols("x:10"))
assert [e.subs(reversed(substs)) for e in reduced] == l
def test_symbols_exhausted_error():
l = cos(x+y)+x+y+cos(w+y)+sin(w+y)
sym = [x, y, z]
with raises(ValueError):
cse(l, symbols=sym)
def test_issue_7840():
# daveknippers' example
C393 = sympify( \
'Piecewise((C391 - 1.65, C390 < 0.5), (Piecewise((C391 - 1.65, \
C391 > 2.35), (C392, True)), True))'
)
C391 = sympify( \
'Piecewise((2.05*C390**(-1.03), C390 < 0.5), (2.5*C390**(-0.625), True))'
)
C393 = C393.subs('C391',C391)
# simple substitution
sub = {}
sub['C390'] = 0.703451854
sub['C392'] = 1.01417794
ss_answer = C393.subs(sub)
# cse
substitutions,new_eqn = cse(C393)
for pair in substitutions:
sub[pair[0].name] = pair[1].subs(sub)
cse_answer = new_eqn[0].subs(sub)
# both methods should be the same
assert ss_answer == cse_answer
# GitRay's example
expr = sympify(
"Piecewise((Symbol('ON'), Equality(Symbol('mode'), Symbol('ON'))), \
(Piecewise((Piecewise((Symbol('OFF'), StrictLessThan(Symbol('x'), \
Symbol('threshold'))), (Symbol('ON'), true)), Equality(Symbol('mode'), \
Symbol('AUTO'))), (Symbol('OFF'), true)), true))"
)
substitutions, new_eqn = cse(expr)
# this Piecewise should be exactly the same
assert new_eqn[0] == expr
# there should not be any replacements
assert len(substitutions) < 1
def test_issue_8891():
for cls in (MutableDenseMatrix, MutableSparseMatrix,
ImmutableDenseMatrix, ImmutableSparseMatrix):
m = cls(2, 2, [x + y, 0, 0, 0])
res = cse([x + y, m])
ans = ([(x0, x + y)], [x0, cls([[x0, 0], [0, 0]])])
assert res == ans
assert isinstance(res[1][-1], cls)
def test_issue_11230():
# a specific test that always failed
a, b, f, k, l, i = symbols('a b f k l i')
p = [a*b*f*k*l, a*i*k**2*l, f*i*k**2*l]
R, C = cse(p)
assert not any(i.is_Mul for a in C for i in a.args)
# random tests for the issue
from random import choice
from sympy.core.function import expand_mul
s = symbols('a:m')
# 35 Mul tests, none of which should ever fail
ex = [Mul(*[choice(s) for i in range(5)]) for i in range(7)]
for p in subsets(ex, 3):
p = list(p)
R, C = cse(p)
assert not any(i.is_Mul for a in C for i in a.args)
for ri in reversed(R):
for i in range(len(C)):
C[i] = C[i].subs(*ri)
assert p == C
# 35 Add tests, none of which should ever fail
ex = [Add(*[choice(s[:7]) for i in range(5)]) for i in range(7)]
for p in subsets(ex, 3):
p = list(p)
R, C = cse(p)
assert not any(i.is_Add for a in C for i in a.args)
for ri in reversed(R):
for i in range(len(C)):
C[i] = C[i].subs(*ri)
# use expand_mul to handle cases like this:
# p = [a + 2*b + 2*e, 2*b + c + 2*e, b + 2*c + 2*g]
# x0 = 2*(b + e) is identified giving a rebuilt p that
# is now `[a + 2*(b + e), c + 2*(b + e), b + 2*c + 2*g]`
assert p == [expand_mul(i) for i in C]
@XFAIL
def test_issue_11577():
def check(eq):
r, c = cse(eq)
assert eq.count_ops() >= \
len(r) + sum([i[1].count_ops() for i in r]) + \
count_ops(c)
eq = x**5*y**2 + x**5*y + x**5
assert cse(eq) == (
[(x0, x**4), (x1, x*y)], [x**5 + x0*x1*y + x0*x1])
# ([(x0, x**5*y)], [x0*y + x0 + x**5]) or
# ([(x0, x**5)], [x0*y**2 + x0*y + x0])
check(eq)
eq = x**2/(y + 1)**2 + x/(y + 1)
assert cse(eq) == (
[(x0, y + 1)], [x**2/x0**2 + x/x0])
# ([(x0, x/(y + 1))], [x0**2 + x0])
check(eq)
def test_hollow_rejection():
eq = [x + 3, x + 4]
assert cse(eq) == ([], eq)
def test_cse_ignore():
exprs = [exp(y)*(3*y + 3*sqrt(x+1)), exp(y)*(5*y + 5*sqrt(x+1))]
subst1, red1 = cse(exprs)
assert any(y in sub.free_symbols for _, sub in subst1), "cse failed to identify any term with y"
subst2, red2 = cse(exprs, ignore=(y,)) # y is not allowed in substitutions
assert not any(y in sub.free_symbols for _, sub in subst2), "Sub-expressions containing y must be ignored"
assert any(sub - sqrt(x + 1) == 0 for _, sub in subst2), "cse failed to identify sqrt(x + 1) as sub-expression"
def test_cse_ignore_issue_15002():
l = [
w*exp(x)*exp(-z),
exp(y)*exp(x)*exp(-z)
]
substs, reduced = cse(l, ignore=(x,))
rl = [e.subs(reversed(substs)) for e in reduced]
assert rl == l
def test_cse__performance():
nexprs, nterms = 3, 20
x = symbols('x:%d' % nterms)
exprs = [
reduce(add, [x[j]*(-1)**(i+j) for j in range(nterms)])
for i in range(nexprs)
]
assert (exprs[0] + exprs[1]).simplify() == 0
subst, red = cse(exprs)
assert len(subst) > 0, "exprs[0] == -exprs[2], i.e. a CSE"
for i, e in enumerate(red):
assert (e.subs(reversed(subst)) - exprs[i]).simplify() == 0
def test_issue_12070():
exprs = [x + y, 2 + x + y, x + y + z, 3 + x + y + z]
subst, red = cse(exprs)
assert 6 >= (len(subst) + sum([v.count_ops() for k, v in subst]) +
count_ops(red))
def test_issue_13000():
eq = x/(-4*x**2 + y**2)
cse_eq = cse(eq)[1][0]
assert cse_eq == eq
def test_issue_18203():
eq = CRootOf(x**5 + 11*x - 2, 0) + CRootOf(x**5 + 11*x - 2, 1)
assert cse(eq) == ([], [eq])
def test_unevaluated_mul():
eq = Mul(x + y, x + y, evaluate=False)
assert cse(eq) == ([(x0, x + y)], [x0**2])
def test_cse_release_variables():
from sympy.simplify.cse_main import cse_release_variables
_0, _1, _2, _3, _4 = symbols('_:5')
eqs = [(x + y - 1)**2, x,
x + y, (x + y)/(2*x + 1) + (x + y - 1)**2,
(2*x + 1)**(x + y)]
r, e = cse(eqs, postprocess=cse_release_variables)
# this can change in keeping with the intention of the function
assert r, e == ([
(x0, x + y), (x1, (x0 - 1)**2), (x2, 2*x + 1),
(_3, x0/x2 + x1), (_4, x2**x0), (x2, None), (_0, x1),
(x1, None), (_2, x0), (x0, None), (_1, x)], (_0, _1, _2, _3, _4))
r.reverse()
assert eqs == [i.subs(r) for i in e]
def test_cse_list():
_cse = lambda x: cse(x, list=False)
assert _cse(x) == ([], x)
assert _cse('x') == ([], 'x')
it = [x]
for c in (list, tuple, set, Tuple):
assert _cse(c(it)) == ([], c(it))
d = {x: 1}
assert _cse(d) == ([], d)
def test_issue_18991():
A = MatrixSymbol('A', 2, 2)
assert signsimp(-A * A - A) == -A * A - A
def test_unevaluated_Mul():
m = [Mul(1, 2, evaluate=False)]
assert cse(m) == ([], m)
|
511b63277f45f92c9a254fe490cbda47c2399c9457f7c408486dce70830eff88 | from sympy.core.numbers import (Rational, pi)
from sympy.core.singleton import S
from sympy.core.symbol import symbols
from sympy.functions.combinatorial.factorials import (rf, binomial, factorial)
from sympy.functions.elementary.exponential import exp
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.piecewise import Piecewise
from sympy.functions.elementary.trigonometric import (cos, sin)
from sympy.functions.special.gamma_functions import gamma
from sympy.simplify.gammasimp import gammasimp
from sympy.simplify.powsimp import powsimp
from sympy.simplify.simplify import simplify
from sympy.abc import x, y, n, k
def test_gammasimp():
R = Rational
# was part of test_combsimp_gamma() in test_combsimp.py
assert gammasimp(gamma(x)) == gamma(x)
assert gammasimp(gamma(x + 1)/x) == gamma(x)
assert gammasimp(gamma(x)/(x - 1)) == gamma(x - 1)
assert gammasimp(x*gamma(x)) == gamma(x + 1)
assert gammasimp((x + 1)*gamma(x + 1)) == gamma(x + 2)
assert gammasimp(gamma(x + y)*(x + y)) == gamma(x + y + 1)
assert gammasimp(x/gamma(x + 1)) == 1/gamma(x)
assert gammasimp((x + 1)**2/gamma(x + 2)) == (x + 1)/gamma(x + 1)
assert gammasimp(x*gamma(x) + gamma(x + 3)/(x + 2)) == \
(x + 2)*gamma(x + 1)
assert gammasimp(gamma(2*x)*x) == gamma(2*x + 1)/2
assert gammasimp(gamma(2*x)/(x - S.Half)) == 2*gamma(2*x - 1)
assert gammasimp(gamma(x)*gamma(1 - x)) == pi/sin(pi*x)
assert gammasimp(gamma(x)*gamma(-x)) == -pi/(x*sin(pi*x))
assert gammasimp(1/gamma(x + 3)/gamma(1 - x)) == \
sin(pi*x)/(pi*x*(x + 1)*(x + 2))
assert gammasimp(factorial(n + 2)) == gamma(n + 3)
assert gammasimp(binomial(n, k)) == \
gamma(n + 1)/(gamma(k + 1)*gamma(-k + n + 1))
assert powsimp(gammasimp(
gamma(x)*gamma(x + S.Half)*gamma(y)/gamma(x + y))) == \
2**(-2*x + 1)*sqrt(pi)*gamma(2*x)*gamma(y)/gamma(x + y)
assert gammasimp(1/gamma(x)/gamma(x - Rational(1, 3))/gamma(x + Rational(1, 3))) == \
3**(3*x - Rational(3, 2))/(2*pi*gamma(3*x - 1))
assert simplify(
gamma(S.Half + x/2)*gamma(1 + x/2)/gamma(1 + x)/sqrt(pi)*2**x) == 1
assert gammasimp(gamma(Rational(-1, 4))*gamma(Rational(-3, 4))) == 16*sqrt(2)*pi/3
assert powsimp(gammasimp(gamma(2*x)/gamma(x))) == \
2**(2*x - 1)*gamma(x + S.Half)/sqrt(pi)
# issue 6792
e = (-gamma(k)*gamma(k + 2) + gamma(k + 1)**2)/gamma(k)**2
assert gammasimp(e) == -k
assert gammasimp(1/e) == -1/k
e = (gamma(x) + gamma(x + 1))/gamma(x)
assert gammasimp(e) == x + 1
assert gammasimp(1/e) == 1/(x + 1)
e = (gamma(x) + gamma(x + 2))*(gamma(x - 1) + gamma(x))/gamma(x)
assert gammasimp(e) == (x**2 + x + 1)*gamma(x + 1)/(x - 1)
e = (-gamma(k)*gamma(k + 2) + gamma(k + 1)**2)/gamma(k)**2
assert gammasimp(e**2) == k**2
assert gammasimp(e**2/gamma(k + 1)) == k/gamma(k)
a = R(1, 2) + R(1, 3)
b = a + R(1, 3)
assert gammasimp(gamma(2*k)/gamma(k)*gamma(k + a)*gamma(k + b))
3*2**(2*k + 1)*3**(-3*k - 2)*sqrt(pi)*gamma(3*k + R(3, 2))/2
# issue 9699
assert gammasimp((x + 1)*factorial(x)/gamma(y)) == gamma(x + 2)/gamma(y)
assert gammasimp(rf(x + n, k)*binomial(n, k)).simplify() == Piecewise(
(gamma(n + 1)*gamma(k + n + x)/(gamma(k + 1)*gamma(n + x)*gamma(-k + n + 1)), n > -x),
((-1)**k*gamma(n + 1)*gamma(-n - x + 1)/(gamma(k + 1)*gamma(-k + n + 1)*gamma(-k - n - x + 1)), True))
A, B = symbols('A B', commutative=False)
assert gammasimp(e*B*A) == gammasimp(e)*B*A
# check iteration
assert gammasimp(gamma(2*k)/gamma(k)*gamma(-k - R(1, 2))) == (
-2**(2*k + 1)*sqrt(pi)/(2*((2*k + 1)*cos(pi*k))))
assert gammasimp(
gamma(k)*gamma(k + R(1, 3))*gamma(k + R(2, 3))/gamma(k*R(3, 2))) == (
3*2**(3*k + 1)*3**(-3*k - S.Half)*sqrt(pi)*gamma(k*R(3, 2) + S.Half)/2)
# issue 6153
assert gammasimp(gamma(Rational(1, 4))/gamma(Rational(5, 4))) == 4
# was part of test_combsimp() in test_combsimp.py
assert gammasimp(binomial(n + 2, k + S.Half)) == gamma(n + 3)/ \
(gamma(k + R(3, 2))*gamma(-k + n + R(5, 2)))
assert gammasimp(binomial(n + 2, k + 2.0)) == \
gamma(n + 3)/(gamma(k + 3.0)*gamma(-k + n + 1))
# issue 11548
assert gammasimp(binomial(0, x)) == sin(pi*x)/(pi*x)
e = gamma(n + Rational(1, 3))*gamma(n + R(2, 3))
assert gammasimp(e) == e
assert gammasimp(gamma(4*n + S.Half)/gamma(2*n - R(3, 4))) == \
2**(4*n - R(5, 2))*(8*n - 3)*gamma(2*n + R(3, 4))/sqrt(pi)
i, m = symbols('i m', integer = True)
e = gamma(exp(i))
assert gammasimp(e) == e
e = gamma(m + 3)
assert gammasimp(e) == e
e = gamma(m + 1)/(gamma(i + 1)*gamma(-i + m + 1))
assert gammasimp(e) == e
p = symbols("p", integer=True, positive=True)
assert gammasimp(gamma(-p+4)) == gamma(-p+4)
|
b91abb00623de7b2de2ce99821732a2a4b2d43294ad3dc4c6094547e54fc6beb | from sympy.core.numbers import (Rational, pi)
from sympy.functions.elementary.exponential import log
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.special.error_functions import erf
from sympy.polys.domains.finitefield import GF
from sympy.simplify.ratsimp import (ratsimp, ratsimpmodprime)
from sympy.abc import x, y, z, t, a, b, c, d, e
def test_ratsimp():
f, g = 1/x + 1/y, (x + y)/(x*y)
assert f != g and ratsimp(f) == g
f, g = 1/(1 + 1/x), 1 - 1/(x + 1)
assert f != g and ratsimp(f) == g
f, g = x/(x + y) + y/(x + y), 1
assert f != g and ratsimp(f) == g
f, g = -x - y - y**2/(x + y) + x**2/(x + y), -2*y
assert f != g and ratsimp(f) == g
f = (a*c*x*y + a*c*z - b*d*x*y - b*d*z - b*t*x*y - b*t*x - b*t*z +
e*x)/(x*y + z)
G = [a*c - b*d - b*t + (-b*t*x + e*x)/(x*y + z),
a*c - b*d - b*t - ( b*t*x - e*x)/(x*y + z)]
assert f != g and ratsimp(f) in G
A = sqrt(pi)
B = log(erf(x) - 1)
C = log(erf(x) + 1)
D = 8 - 8*erf(x)
f = A*B/D - A*C/D + A*C*erf(x)/D - A*B*erf(x)/D + 2*A/D
assert ratsimp(f) == A*B/8 - A*C/8 - A/(4*erf(x) - 4)
def test_ratsimpmodprime():
a = y**5 + x + y
b = x - y
F = [x*y**5 - x - y]
assert ratsimpmodprime(a/b, F, x, y, order='lex') == \
(-x**2 - x*y - x - y) / (-x**2 + x*y)
a = x + y**2 - 2
b = x + y**2 - y - 1
F = [x*y - 1]
assert ratsimpmodprime(a/b, F, x, y, order='lex') == \
(1 + y - x)/(y - x)
a = 5*x**3 + 21*x**2 + 4*x*y + 23*x + 12*y + 15
b = 7*x**3 - y*x**2 + 31*x**2 + 2*x*y + 15*y + 37*x + 21
F = [x**2 + y**2 - 1]
assert ratsimpmodprime(a/b, F, x, y, order='lex') == \
(1 + 5*y - 5*x)/(8*y - 6*x)
a = x*y - x - 2*y + 4
b = x + y**2 - 2*y
F = [x - 2, y - 3]
assert ratsimpmodprime(a/b, F, x, y, order='lex') == \
Rational(2, 5)
# Test a bug where denominators would be dropped
assert ratsimpmodprime(x, [y - 2*x], order='lex') == \
y/2
a = (x**5 + 2*x**4 + 2*x**3 + 2*x**2 + x + 2/x + x**(-2))
assert ratsimpmodprime(a, [x + 1], domain=GF(2)) == 1
assert ratsimpmodprime(a, [x + 1], domain=GF(3)) == -1
|
4b00fa42c7d296b11da43d9d6e470deb608f54844fe5269d8c2a652eb300a1af | from sympy.categories import (Object, Morphism, IdentityMorphism,
NamedMorphism, CompositeMorphism,
Diagram, Category)
from sympy.categories.baseclasses import Class
from sympy.testing.pytest import raises
from sympy.core.containers import (Dict, Tuple)
from sympy.sets import EmptySet
from sympy.sets.sets import FiniteSet
def test_morphisms():
A = Object("A")
B = Object("B")
C = Object("C")
D = Object("D")
# Test the base morphism.
f = NamedMorphism(A, B, "f")
assert f.domain == A
assert f.codomain == B
assert f == NamedMorphism(A, B, "f")
# Test identities.
id_A = IdentityMorphism(A)
id_B = IdentityMorphism(B)
assert id_A.domain == A
assert id_A.codomain == A
assert id_A == IdentityMorphism(A)
assert id_A != id_B
# Test named morphisms.
g = NamedMorphism(B, C, "g")
assert g.name == "g"
assert g != f
assert g == NamedMorphism(B, C, "g")
assert g != NamedMorphism(B, C, "f")
# Test composite morphisms.
assert f == CompositeMorphism(f)
k = g.compose(f)
assert k.domain == A
assert k.codomain == C
assert k.components == Tuple(f, g)
assert g * f == k
assert CompositeMorphism(f, g) == k
assert CompositeMorphism(g * f) == g * f
# Test the associativity of composition.
h = NamedMorphism(C, D, "h")
p = h * g
u = h * g * f
assert h * k == u
assert p * f == u
assert CompositeMorphism(f, g, h) == u
# Test flattening.
u2 = u.flatten("u")
assert isinstance(u2, NamedMorphism)
assert u2.name == "u"
assert u2.domain == A
assert u2.codomain == D
# Test identities.
assert f * id_A == f
assert id_B * f == f
assert id_A * id_A == id_A
assert CompositeMorphism(id_A) == id_A
# Test bad compositions.
raises(ValueError, lambda: f * g)
raises(TypeError, lambda: f.compose(None))
raises(TypeError, lambda: id_A.compose(None))
raises(TypeError, lambda: f * None)
raises(TypeError, lambda: id_A * None)
raises(TypeError, lambda: CompositeMorphism(f, None, 1))
raises(ValueError, lambda: NamedMorphism(A, B, ""))
raises(NotImplementedError, lambda: Morphism(A, B))
def test_diagram():
A = Object("A")
B = Object("B")
C = Object("C")
f = NamedMorphism(A, B, "f")
g = NamedMorphism(B, C, "g")
id_A = IdentityMorphism(A)
id_B = IdentityMorphism(B)
empty = EmptySet
# Test the addition of identities.
d1 = Diagram([f])
assert d1.objects == FiniteSet(A, B)
assert d1.hom(A, B) == (FiniteSet(f), empty)
assert d1.hom(A, A) == (FiniteSet(id_A), empty)
assert d1.hom(B, B) == (FiniteSet(id_B), empty)
assert d1 == Diagram([id_A, f])
assert d1 == Diagram([f, f])
# Test the addition of composites.
d2 = Diagram([f, g])
homAC = d2.hom(A, C)[0]
assert d2.objects == FiniteSet(A, B, C)
assert g * f in d2.premises.keys()
assert homAC == FiniteSet(g * f)
# Test equality, inequality and hash.
d11 = Diagram([f])
assert d1 == d11
assert d1 != d2
assert hash(d1) == hash(d11)
d11 = Diagram({f: "unique"})
assert d1 != d11
# Make sure that (re-)adding composites (with new properties)
# works as expected.
d = Diagram([f, g], {g * f: "unique"})
assert d.conclusions == Dict({g * f: FiniteSet("unique")})
# Check the hom-sets when there are premises and conclusions.
assert d.hom(A, C) == (FiniteSet(g * f), FiniteSet(g * f))
d = Diagram([f, g], [g * f])
assert d.hom(A, C) == (FiniteSet(g * f), FiniteSet(g * f))
# Check how the properties of composite morphisms are computed.
d = Diagram({f: ["unique", "isomorphism"], g: "unique"})
assert d.premises[g * f] == FiniteSet("unique")
# Check that conclusion morphisms with new objects are not allowed.
d = Diagram([f], [g])
assert d.conclusions == Dict({})
# Test an empty diagram.
d = Diagram()
assert d.premises == Dict({})
assert d.conclusions == Dict({})
assert d.objects == empty
# Check a SymPy Dict object.
d = Diagram(Dict({f: FiniteSet("unique", "isomorphism"), g: "unique"}))
assert d.premises[g * f] == FiniteSet("unique")
# Check the addition of components of composite morphisms.
d = Diagram([g * f])
assert f in d.premises
assert g in d.premises
# Check subdiagrams.
d = Diagram([f, g], {g * f: "unique"})
d1 = Diagram([f])
assert d.is_subdiagram(d1)
assert not d1.is_subdiagram(d)
d = Diagram([NamedMorphism(B, A, "f'")])
assert not d.is_subdiagram(d1)
assert not d1.is_subdiagram(d)
d1 = Diagram([f, g], {g * f: ["unique", "something"]})
assert not d.is_subdiagram(d1)
assert not d1.is_subdiagram(d)
d = Diagram({f: "blooh"})
d1 = Diagram({f: "bleeh"})
assert not d.is_subdiagram(d1)
assert not d1.is_subdiagram(d)
d = Diagram([f, g], {f: "unique", g * f: "veryunique"})
d1 = d.subdiagram_from_objects(FiniteSet(A, B))
assert d1 == Diagram([f], {f: "unique"})
raises(ValueError, lambda: d.subdiagram_from_objects(FiniteSet(A,
Object("D"))))
raises(ValueError, lambda: Diagram({IdentityMorphism(A): "unique"}))
def test_category():
A = Object("A")
B = Object("B")
C = Object("C")
f = NamedMorphism(A, B, "f")
g = NamedMorphism(B, C, "g")
d1 = Diagram([f, g])
d2 = Diagram([f])
objects = d1.objects | d2.objects
K = Category("K", objects, commutative_diagrams=[d1, d2])
assert K.name == "K"
assert K.objects == Class(objects)
assert K.commutative_diagrams == FiniteSet(d1, d2)
raises(ValueError, lambda: Category(""))
|
2042cfa5a7669d0c90db1e5ae6a1c2f22a2ae647d3d549c0978875bcede06ea8 | from sympy.categories.diagram_drawing import _GrowableGrid, ArrowStringDescription
from sympy.categories import (DiagramGrid, Object, NamedMorphism,
Diagram, XypicDiagramDrawer, xypic_draw_diagram)
from sympy.sets.sets import FiniteSet
def test_GrowableGrid():
grid = _GrowableGrid(1, 2)
# Check dimensions.
assert grid.width == 1
assert grid.height == 2
# Check initialization of elements.
assert grid[0, 0] is None
assert grid[1, 0] is None
# Check assignment to elements.
grid[0, 0] = 1
grid[1, 0] = "two"
assert grid[0, 0] == 1
assert grid[1, 0] == "two"
# Check appending a row.
grid.append_row()
assert grid.width == 1
assert grid.height == 3
assert grid[0, 0] == 1
assert grid[1, 0] == "two"
assert grid[2, 0] is None
# Check appending a column.
grid.append_column()
assert grid.width == 2
assert grid.height == 3
assert grid[0, 0] == 1
assert grid[1, 0] == "two"
assert grid[2, 0] is None
assert grid[0, 1] is None
assert grid[1, 1] is None
assert grid[2, 1] is None
grid = _GrowableGrid(1, 2)
grid[0, 0] = 1
grid[1, 0] = "two"
# Check prepending a row.
grid.prepend_row()
assert grid.width == 1
assert grid.height == 3
assert grid[0, 0] is None
assert grid[1, 0] == 1
assert grid[2, 0] == "two"
# Check prepending a column.
grid.prepend_column()
assert grid.width == 2
assert grid.height == 3
assert grid[0, 0] is None
assert grid[1, 0] is None
assert grid[2, 0] is None
assert grid[0, 1] is None
assert grid[1, 1] == 1
assert grid[2, 1] == "two"
def test_DiagramGrid():
# Set up some objects and morphisms.
A = Object("A")
B = Object("B")
C = Object("C")
D = Object("D")
E = Object("E")
f = NamedMorphism(A, B, "f")
g = NamedMorphism(B, C, "g")
h = NamedMorphism(D, A, "h")
k = NamedMorphism(D, B, "k")
# A one-morphism diagram.
d = Diagram([f])
grid = DiagramGrid(d)
assert grid.width == 2
assert grid.height == 1
assert grid[0, 0] == A
assert grid[0, 1] == B
assert grid.morphisms == {f: FiniteSet()}
# A triangle.
d = Diagram([f, g], {g * f: "unique"})
grid = DiagramGrid(d)
assert grid.width == 2
assert grid.height == 2
assert grid[0, 0] == A
assert grid[0, 1] == B
assert grid[1, 0] == C
assert grid[1, 1] is None
assert grid.morphisms == {f: FiniteSet(), g: FiniteSet(),
g * f: FiniteSet("unique")}
# A triangle with a "loop" morphism.
l_A = NamedMorphism(A, A, "l_A")
d = Diagram([f, g, l_A])
grid = DiagramGrid(d)
assert grid.width == 2
assert grid.height == 2
assert grid[0, 0] == A
assert grid[0, 1] == B
assert grid[1, 0] is None
assert grid[1, 1] == C
assert grid.morphisms == {f: FiniteSet(), g: FiniteSet(), l_A: FiniteSet()}
# A simple diagram.
d = Diagram([f, g, h, k])
grid = DiagramGrid(d)
assert grid.width == 3
assert grid.height == 2
assert grid[0, 0] == A
assert grid[0, 1] == B
assert grid[0, 2] == D
assert grid[1, 0] is None
assert grid[1, 1] == C
assert grid[1, 2] is None
assert grid.morphisms == {f: FiniteSet(), g: FiniteSet(), h: FiniteSet(),
k: FiniteSet()}
assert str(grid) == '[[Object("A"), Object("B"), Object("D")], ' \
'[None, Object("C"), None]]'
# A chain of morphisms.
f = NamedMorphism(A, B, "f")
g = NamedMorphism(B, C, "g")
h = NamedMorphism(C, D, "h")
k = NamedMorphism(D, E, "k")
d = Diagram([f, g, h, k])
grid = DiagramGrid(d)
assert grid.width == 3
assert grid.height == 3
assert grid[0, 0] == A
assert grid[0, 1] == B
assert grid[0, 2] is None
assert grid[1, 0] is None
assert grid[1, 1] == C
assert grid[1, 2] == D
assert grid[2, 0] is None
assert grid[2, 1] is None
assert grid[2, 2] == E
assert grid.morphisms == {f: FiniteSet(), g: FiniteSet(), h: FiniteSet(),
k: FiniteSet()}
# A square.
f = NamedMorphism(A, B, "f")
g = NamedMorphism(B, D, "g")
h = NamedMorphism(A, C, "h")
k = NamedMorphism(C, D, "k")
d = Diagram([f, g, h, k])
grid = DiagramGrid(d)
assert grid.width == 2
assert grid.height == 2
assert grid[0, 0] == A
assert grid[0, 1] == B
assert grid[1, 0] == C
assert grid[1, 1] == D
assert grid.morphisms == {f: FiniteSet(), g: FiniteSet(), h: FiniteSet(),
k: FiniteSet()}
# A strange diagram which resulted from a typo when creating a
# test for five lemma, but which allowed to stop one extra problem
# in the algorithm.
A = Object("A")
B = Object("B")
C = Object("C")
D = Object("D")
E = Object("E")
A_ = Object("A'")
B_ = Object("B'")
C_ = Object("C'")
D_ = Object("D'")
E_ = Object("E'")
f = NamedMorphism(A, B, "f")
g = NamedMorphism(B, C, "g")
h = NamedMorphism(C, D, "h")
i = NamedMorphism(D, E, "i")
# These 4 morphisms should be between primed objects.
j = NamedMorphism(A, B, "j")
k = NamedMorphism(B, C, "k")
l = NamedMorphism(C, D, "l")
m = NamedMorphism(D, E, "m")
o = NamedMorphism(A, A_, "o")
p = NamedMorphism(B, B_, "p")
q = NamedMorphism(C, C_, "q")
r = NamedMorphism(D, D_, "r")
s = NamedMorphism(E, E_, "s")
d = Diagram([f, g, h, i, j, k, l, m, o, p, q, r, s])
grid = DiagramGrid(d)
assert grid.width == 3
assert grid.height == 4
assert grid[0, 0] is None
assert grid[0, 1] == A
assert grid[0, 2] == A_
assert grid[1, 0] == C
assert grid[1, 1] == B
assert grid[1, 2] == B_
assert grid[2, 0] == C_
assert grid[2, 1] == D
assert grid[2, 2] == D_
assert grid[3, 0] is None
assert grid[3, 1] == E
assert grid[3, 2] == E_
morphisms = {}
for m in [f, g, h, i, j, k, l, m, o, p, q, r, s]:
morphisms[m] = FiniteSet()
assert grid.morphisms == morphisms
# A cube.
A1 = Object("A1")
A2 = Object("A2")
A3 = Object("A3")
A4 = Object("A4")
A5 = Object("A5")
A6 = Object("A6")
A7 = Object("A7")
A8 = Object("A8")
# The top face of the cube.
f1 = NamedMorphism(A1, A2, "f1")
f2 = NamedMorphism(A1, A3, "f2")
f3 = NamedMorphism(A2, A4, "f3")
f4 = NamedMorphism(A3, A4, "f3")
# The bottom face of the cube.
f5 = NamedMorphism(A5, A6, "f5")
f6 = NamedMorphism(A5, A7, "f6")
f7 = NamedMorphism(A6, A8, "f7")
f8 = NamedMorphism(A7, A8, "f8")
# The remaining morphisms.
f9 = NamedMorphism(A1, A5, "f9")
f10 = NamedMorphism(A2, A6, "f10")
f11 = NamedMorphism(A3, A7, "f11")
f12 = NamedMorphism(A4, A8, "f11")
d = Diagram([f1, f2, f3, f4, f5, f6, f7, f8, f9, f10, f11, f12])
grid = DiagramGrid(d)
assert grid.width == 4
assert grid.height == 3
assert grid[0, 0] is None
assert grid[0, 1] == A5
assert grid[0, 2] == A6
assert grid[0, 3] is None
assert grid[1, 0] is None
assert grid[1, 1] == A1
assert grid[1, 2] == A2
assert grid[1, 3] is None
assert grid[2, 0] == A7
assert grid[2, 1] == A3
assert grid[2, 2] == A4
assert grid[2, 3] == A8
morphisms = {}
for m in [f1, f2, f3, f4, f5, f6, f7, f8, f9, f10, f11, f12]:
morphisms[m] = FiniteSet()
assert grid.morphisms == morphisms
# A line diagram.
A = Object("A")
B = Object("B")
C = Object("C")
D = Object("D")
E = Object("E")
f = NamedMorphism(A, B, "f")
g = NamedMorphism(B, C, "g")
h = NamedMorphism(C, D, "h")
i = NamedMorphism(D, E, "i")
d = Diagram([f, g, h, i])
grid = DiagramGrid(d, layout="sequential")
assert grid.width == 5
assert grid.height == 1
assert grid[0, 0] == A
assert grid[0, 1] == B
assert grid[0, 2] == C
assert grid[0, 3] == D
assert grid[0, 4] == E
assert grid.morphisms == {f: FiniteSet(), g: FiniteSet(), h: FiniteSet(),
i: FiniteSet()}
# Test the transposed version.
grid = DiagramGrid(d, layout="sequential", transpose=True)
assert grid.width == 1
assert grid.height == 5
assert grid[0, 0] == A
assert grid[1, 0] == B
assert grid[2, 0] == C
assert grid[3, 0] == D
assert grid[4, 0] == E
assert grid.morphisms == {f: FiniteSet(), g: FiniteSet(), h: FiniteSet(),
i: FiniteSet()}
# A pullback.
m1 = NamedMorphism(A, B, "m1")
m2 = NamedMorphism(A, C, "m2")
s1 = NamedMorphism(B, D, "s1")
s2 = NamedMorphism(C, D, "s2")
f1 = NamedMorphism(E, B, "f1")
f2 = NamedMorphism(E, C, "f2")
g = NamedMorphism(E, A, "g")
d = Diagram([m1, m2, s1, s2, f1, f2], {g: "unique"})
grid = DiagramGrid(d)
assert grid.width == 3
assert grid.height == 2
assert grid[0, 0] == A
assert grid[0, 1] == B
assert grid[0, 2] == E
assert grid[1, 0] == C
assert grid[1, 1] == D
assert grid[1, 2] is None
morphisms = {g: FiniteSet("unique")}
for m in [m1, m2, s1, s2, f1, f2]:
morphisms[m] = FiniteSet()
assert grid.morphisms == morphisms
# Test the pullback with sequential layout, just for stress
# testing.
grid = DiagramGrid(d, layout="sequential")
assert grid.width == 5
assert grid.height == 1
assert grid[0, 0] == D
assert grid[0, 1] == B
assert grid[0, 2] == A
assert grid[0, 3] == C
assert grid[0, 4] == E
assert grid.morphisms == morphisms
# Test a pullback with object grouping.
grid = DiagramGrid(d, groups=FiniteSet(E, FiniteSet(A, B, C, D)))
assert grid.width == 3
assert grid.height == 2
assert grid[0, 0] == E
assert grid[0, 1] == A
assert grid[0, 2] == B
assert grid[1, 0] is None
assert grid[1, 1] == C
assert grid[1, 2] == D
assert grid.morphisms == morphisms
# Five lemma, actually.
A = Object("A")
B = Object("B")
C = Object("C")
D = Object("D")
E = Object("E")
A_ = Object("A'")
B_ = Object("B'")
C_ = Object("C'")
D_ = Object("D'")
E_ = Object("E'")
f = NamedMorphism(A, B, "f")
g = NamedMorphism(B, C, "g")
h = NamedMorphism(C, D, "h")
i = NamedMorphism(D, E, "i")
j = NamedMorphism(A_, B_, "j")
k = NamedMorphism(B_, C_, "k")
l = NamedMorphism(C_, D_, "l")
m = NamedMorphism(D_, E_, "m")
o = NamedMorphism(A, A_, "o")
p = NamedMorphism(B, B_, "p")
q = NamedMorphism(C, C_, "q")
r = NamedMorphism(D, D_, "r")
s = NamedMorphism(E, E_, "s")
d = Diagram([f, g, h, i, j, k, l, m, o, p, q, r, s])
grid = DiagramGrid(d)
assert grid.width == 5
assert grid.height == 3
assert grid[0, 0] is None
assert grid[0, 1] == A
assert grid[0, 2] == A_
assert grid[0, 3] is None
assert grid[0, 4] is None
assert grid[1, 0] == C
assert grid[1, 1] == B
assert grid[1, 2] == B_
assert grid[1, 3] == C_
assert grid[1, 4] is None
assert grid[2, 0] == D
assert grid[2, 1] == E
assert grid[2, 2] is None
assert grid[2, 3] == D_
assert grid[2, 4] == E_
morphisms = {}
for m in [f, g, h, i, j, k, l, m, o, p, q, r, s]:
morphisms[m] = FiniteSet()
assert grid.morphisms == morphisms
# Test the five lemma with object grouping.
grid = DiagramGrid(d, FiniteSet(
FiniteSet(A, B, C, D, E), FiniteSet(A_, B_, C_, D_, E_)))
assert grid.width == 6
assert grid.height == 3
assert grid[0, 0] == A
assert grid[0, 1] == B
assert grid[0, 2] is None
assert grid[0, 3] == A_
assert grid[0, 4] == B_
assert grid[0, 5] is None
assert grid[1, 0] is None
assert grid[1, 1] == C
assert grid[1, 2] == D
assert grid[1, 3] is None
assert grid[1, 4] == C_
assert grid[1, 5] == D_
assert grid[2, 0] is None
assert grid[2, 1] is None
assert grid[2, 2] == E
assert grid[2, 3] is None
assert grid[2, 4] is None
assert grid[2, 5] == E_
assert grid.morphisms == morphisms
# Test the five lemma with object grouping, but mixing containers
# to represent groups.
grid = DiagramGrid(d, [(A, B, C, D, E), {A_, B_, C_, D_, E_}])
assert grid.width == 6
assert grid.height == 3
assert grid[0, 0] == A
assert grid[0, 1] == B
assert grid[0, 2] is None
assert grid[0, 3] == A_
assert grid[0, 4] == B_
assert grid[0, 5] is None
assert grid[1, 0] is None
assert grid[1, 1] == C
assert grid[1, 2] == D
assert grid[1, 3] is None
assert grid[1, 4] == C_
assert grid[1, 5] == D_
assert grid[2, 0] is None
assert grid[2, 1] is None
assert grid[2, 2] == E
assert grid[2, 3] is None
assert grid[2, 4] is None
assert grid[2, 5] == E_
assert grid.morphisms == morphisms
# Test the five lemma with object grouping and hints.
grid = DiagramGrid(d, {
FiniteSet(A, B, C, D, E): {"layout": "sequential",
"transpose": True},
FiniteSet(A_, B_, C_, D_, E_): {"layout": "sequential",
"transpose": True}},
transpose=True)
assert grid.width == 5
assert grid.height == 2
assert grid[0, 0] == A
assert grid[0, 1] == B
assert grid[0, 2] == C
assert grid[0, 3] == D
assert grid[0, 4] == E
assert grid[1, 0] == A_
assert grid[1, 1] == B_
assert grid[1, 2] == C_
assert grid[1, 3] == D_
assert grid[1, 4] == E_
assert grid.morphisms == morphisms
# A two-triangle disconnected diagram.
f = NamedMorphism(A, B, "f")
g = NamedMorphism(B, C, "g")
f_ = NamedMorphism(A_, B_, "f")
g_ = NamedMorphism(B_, C_, "g")
d = Diagram([f, g, f_, g_], {g * f: "unique", g_ * f_: "unique"})
grid = DiagramGrid(d)
assert grid.width == 4
assert grid.height == 2
assert grid[0, 0] == A
assert grid[0, 1] == B
assert grid[0, 2] == A_
assert grid[0, 3] == B_
assert grid[1, 0] == C
assert grid[1, 1] is None
assert grid[1, 2] == C_
assert grid[1, 3] is None
assert grid.morphisms == {f: FiniteSet(), g: FiniteSet(), f_: FiniteSet(),
g_: FiniteSet(), g * f: FiniteSet("unique"),
g_ * f_: FiniteSet("unique")}
# A two-morphism disconnected diagram.
f = NamedMorphism(A, B, "f")
g = NamedMorphism(C, D, "g")
d = Diagram([f, g])
grid = DiagramGrid(d)
assert grid.width == 4
assert grid.height == 1
assert grid[0, 0] == A
assert grid[0, 1] == B
assert grid[0, 2] == C
assert grid[0, 3] == D
assert grid.morphisms == {f: FiniteSet(), g: FiniteSet()}
# Test a one-object diagram.
f = NamedMorphism(A, A, "f")
d = Diagram([f])
grid = DiagramGrid(d)
assert grid.width == 1
assert grid.height == 1
assert grid[0, 0] == A
# Test a two-object disconnected diagram.
g = NamedMorphism(B, B, "g")
d = Diagram([f, g])
grid = DiagramGrid(d)
assert grid.width == 2
assert grid.height == 1
assert grid[0, 0] == A
assert grid[0, 1] == B
def test_DiagramGrid_pseudopod():
# Test a diagram in which even growing a pseudopod does not
# eventually help.
A = Object("A")
B = Object("B")
C = Object("C")
D = Object("D")
E = Object("E")
F = Object("F")
A_ = Object("A'")
B_ = Object("B'")
C_ = Object("C'")
D_ = Object("D'")
E_ = Object("E'")
f1 = NamedMorphism(A, B, "f1")
f2 = NamedMorphism(A, C, "f2")
f3 = NamedMorphism(A, D, "f3")
f4 = NamedMorphism(A, E, "f4")
f5 = NamedMorphism(A, A_, "f5")
f6 = NamedMorphism(A, B_, "f6")
f7 = NamedMorphism(A, C_, "f7")
f8 = NamedMorphism(A, D_, "f8")
f9 = NamedMorphism(A, E_, "f9")
f10 = NamedMorphism(A, F, "f10")
d = Diagram([f1, f2, f3, f4, f5, f6, f7, f8, f9, f10])
grid = DiagramGrid(d)
assert grid.width == 5
assert grid.height == 3
assert grid[0, 0] == E
assert grid[0, 1] == C
assert grid[0, 2] == C_
assert grid[0, 3] == E_
assert grid[0, 4] == F
assert grid[1, 0] == D
assert grid[1, 1] == A
assert grid[1, 2] == A_
assert grid[1, 3] is None
assert grid[1, 4] is None
assert grid[2, 0] == D_
assert grid[2, 1] == B
assert grid[2, 2] == B_
assert grid[2, 3] is None
assert grid[2, 4] is None
morphisms = {}
for f in [f1, f2, f3, f4, f5, f6, f7, f8, f9, f10]:
morphisms[f] = FiniteSet()
assert grid.morphisms == morphisms
def test_ArrowStringDescription():
astr = ArrowStringDescription("cm", "", None, "", "", "d", "r", "_", "f")
assert str(astr) == "\\ar[dr]_{f}"
astr = ArrowStringDescription("cm", "", 12, "", "", "d", "r", "_", "f")
assert str(astr) == "\\ar[dr]_{f}"
astr = ArrowStringDescription("cm", "^", 12, "", "", "d", "r", "_", "f")
assert str(astr) == "\\ar@/^12cm/[dr]_{f}"
astr = ArrowStringDescription("cm", "", 12, "r", "", "d", "r", "_", "f")
assert str(astr) == "\\ar[dr]_{f}"
astr = ArrowStringDescription("cm", "", 12, "r", "u", "d", "r", "_", "f")
assert str(astr) == "\\ar@(r,u)[dr]_{f}"
astr = ArrowStringDescription("cm", "", 12, "r", "u", "d", "r", "_", "f")
assert str(astr) == "\\ar@(r,u)[dr]_{f}"
astr = ArrowStringDescription("cm", "", 12, "r", "u", "d", "r", "_", "f")
astr.arrow_style = "{-->}"
assert str(astr) == "\\ar@(r,u)@{-->}[dr]_{f}"
astr = ArrowStringDescription("cm", "_", 12, "", "", "d", "r", "_", "f")
astr.arrow_style = "{-->}"
assert str(astr) == "\\ar@/_12cm/@{-->}[dr]_{f}"
def test_XypicDiagramDrawer_line():
# A linear diagram.
A = Object("A")
B = Object("B")
C = Object("C")
D = Object("D")
E = Object("E")
f = NamedMorphism(A, B, "f")
g = NamedMorphism(B, C, "g")
h = NamedMorphism(C, D, "h")
i = NamedMorphism(D, E, "i")
d = Diagram([f, g, h, i])
grid = DiagramGrid(d, layout="sequential")
drawer = XypicDiagramDrawer()
assert drawer.draw(d, grid) == "\\xymatrix{\n" \
"A \\ar[r]^{f} & B \\ar[r]^{g} & C \\ar[r]^{h} & D \\ar[r]^{i} & E \n" \
"}\n"
# The same diagram, transposed.
grid = DiagramGrid(d, layout="sequential", transpose=True)
drawer = XypicDiagramDrawer()
assert drawer.draw(d, grid) == "\\xymatrix{\n" \
"A \\ar[d]^{f} \\\\\n" \
"B \\ar[d]^{g} \\\\\n" \
"C \\ar[d]^{h} \\\\\n" \
"D \\ar[d]^{i} \\\\\n" \
"E \n" \
"}\n"
def test_XypicDiagramDrawer_triangle():
# A triangle diagram.
A = Object("A")
B = Object("B")
C = Object("C")
f = NamedMorphism(A, B, "f")
g = NamedMorphism(B, C, "g")
d = Diagram([f, g], {g * f: "unique"})
grid = DiagramGrid(d)
drawer = XypicDiagramDrawer()
assert drawer.draw(d, grid) == "\\xymatrix{\n" \
"A \\ar[d]_{g\\circ f} \\ar[r]^{f} & B \\ar[ld]^{g} \\\\\n" \
"C & \n" \
"}\n"
# The same diagram, transposed.
grid = DiagramGrid(d, transpose=True)
drawer = XypicDiagramDrawer()
assert drawer.draw(d, grid) == "\\xymatrix{\n" \
"A \\ar[r]^{g\\circ f} \\ar[d]_{f} & C \\\\\n" \
"B \\ar[ru]_{g} & \n" \
"}\n"
# The same diagram, with a masked morphism.
assert drawer.draw(d, grid, masked=[g]) == "\\xymatrix{\n" \
"A \\ar[r]^{g\\circ f} \\ar[d]_{f} & C \\\\\n" \
"B & \n" \
"}\n"
# The same diagram with a formatter for "unique".
def formatter(astr):
astr.label = "\\exists !" + astr.label
astr.arrow_style = "{-->}"
drawer.arrow_formatters["unique"] = formatter
assert drawer.draw(d, grid) == "\\xymatrix{\n" \
"A \\ar@{-->}[r]^{\\exists !g\\circ f} \\ar[d]_{f} & C \\\\\n" \
"B \\ar[ru]_{g} & \n" \
"}\n"
# The same diagram with a default formatter.
def default_formatter(astr):
astr.label_displacement = "(0.45)"
drawer.default_arrow_formatter = default_formatter
assert drawer.draw(d, grid) == "\\xymatrix{\n" \
"A \\ar@{-->}[r]^(0.45){\\exists !g\\circ f} \\ar[d]_(0.45){f} & C \\\\\n" \
"B \\ar[ru]_(0.45){g} & \n" \
"}\n"
# A triangle diagram with a lot of morphisms between the same
# objects.
f1 = NamedMorphism(B, A, "f1")
f2 = NamedMorphism(A, B, "f2")
g1 = NamedMorphism(C, B, "g1")
g2 = NamedMorphism(B, C, "g2")
d = Diagram([f, f1, f2, g, g1, g2], {f1 * g1: "unique", g2 * f2: "unique"})
grid = DiagramGrid(d, transpose=True)
drawer = XypicDiagramDrawer()
assert drawer.draw(d, grid, masked=[f1*g1*g2*f2, g2*f2*f1*g1]) == \
"\\xymatrix{\n" \
"A \\ar[r]^{g_{2}\\circ f_{2}} \\ar[d]_{f} \\ar@/^3mm/[d]^{f_{2}} " \
"& C \\ar@/^3mm/[l]^{f_{1}\\circ g_{1}} \\ar@/^3mm/[ld]^{g_{1}} \\\\\n" \
"B \\ar@/^3mm/[u]^{f_{1}} \\ar[ru]_{g} \\ar@/^3mm/[ru]^{g_{2}} & \n" \
"}\n"
def test_XypicDiagramDrawer_cube():
# A cube diagram.
A1 = Object("A1")
A2 = Object("A2")
A3 = Object("A3")
A4 = Object("A4")
A5 = Object("A5")
A6 = Object("A6")
A7 = Object("A7")
A8 = Object("A8")
# The top face of the cube.
f1 = NamedMorphism(A1, A2, "f1")
f2 = NamedMorphism(A1, A3, "f2")
f3 = NamedMorphism(A2, A4, "f3")
f4 = NamedMorphism(A3, A4, "f3")
# The bottom face of the cube.
f5 = NamedMorphism(A5, A6, "f5")
f6 = NamedMorphism(A5, A7, "f6")
f7 = NamedMorphism(A6, A8, "f7")
f8 = NamedMorphism(A7, A8, "f8")
# The remaining morphisms.
f9 = NamedMorphism(A1, A5, "f9")
f10 = NamedMorphism(A2, A6, "f10")
f11 = NamedMorphism(A3, A7, "f11")
f12 = NamedMorphism(A4, A8, "f11")
d = Diagram([f1, f2, f3, f4, f5, f6, f7, f8, f9, f10, f11, f12])
grid = DiagramGrid(d)
drawer = XypicDiagramDrawer()
assert drawer.draw(d, grid) == "\\xymatrix{\n" \
"& A_{5} \\ar[r]^{f_{5}} \\ar[ldd]_{f_{6}} & A_{6} \\ar[rdd]^{f_{7}} " \
"& \\\\\n" \
"& A_{1} \\ar[r]^{f_{1}} \\ar[d]^{f_{2}} \\ar[u]^{f_{9}} & A_{2} " \
"\\ar[d]^{f_{3}} \\ar[u]_{f_{10}} & \\\\\n" \
"A_{7} \\ar@/_3mm/[rrr]_{f_{8}} & A_{3} \\ar[r]^{f_{3}} \\ar[l]_{f_{11}} " \
"& A_{4} \\ar[r]^{f_{11}} & A_{8} \n" \
"}\n"
# The same diagram, transposed.
grid = DiagramGrid(d, transpose=True)
drawer = XypicDiagramDrawer()
assert drawer.draw(d, grid) == "\\xymatrix{\n" \
"& & A_{7} \\ar@/^3mm/[ddd]^{f_{8}} \\\\\n" \
"A_{5} \\ar[d]_{f_{5}} \\ar[rru]^{f_{6}} & A_{1} \\ar[d]^{f_{1}} " \
"\\ar[r]^{f_{2}} \\ar[l]^{f_{9}} & A_{3} \\ar[d]_{f_{3}} " \
"\\ar[u]^{f_{11}} \\\\\n" \
"A_{6} \\ar[rrd]_{f_{7}} & A_{2} \\ar[r]^{f_{3}} \\ar[l]^{f_{10}} " \
"& A_{4} \\ar[d]_{f_{11}} \\\\\n" \
"& & A_{8} \n" \
"}\n"
def test_XypicDiagramDrawer_curved_and_loops():
# A simple diagram, with a curved arrow.
A = Object("A")
B = Object("B")
C = Object("C")
D = Object("D")
f = NamedMorphism(A, B, "f")
g = NamedMorphism(B, C, "g")
h = NamedMorphism(D, A, "h")
k = NamedMorphism(D, B, "k")
d = Diagram([f, g, h, k])
grid = DiagramGrid(d)
drawer = XypicDiagramDrawer()
assert drawer.draw(d, grid) == "\\xymatrix{\n" \
"A \\ar[r]_{f} & B \\ar[d]^{g} & D \\ar[l]^{k} \\ar@/_3mm/[ll]_{h} \\\\\n" \
"& C & \n" \
"}\n"
# The same diagram, transposed.
grid = DiagramGrid(d, transpose=True)
drawer = XypicDiagramDrawer()
assert drawer.draw(d, grid) == "\\xymatrix{\n" \
"A \\ar[d]^{f} & \\\\\n" \
"B \\ar[r]^{g} & C \\\\\n" \
"D \\ar[u]_{k} \\ar@/^3mm/[uu]^{h} & \n" \
"}\n"
# The same diagram, larger and rotated.
assert drawer.draw(d, grid, diagram_format="@+1cm@dr") == \
"\\xymatrix@+1cm@dr{\n" \
"A \\ar[d]^{f} & \\\\\n" \
"B \\ar[r]^{g} & C \\\\\n" \
"D \\ar[u]_{k} \\ar@/^3mm/[uu]^{h} & \n" \
"}\n"
# A simple diagram with three curved arrows.
h1 = NamedMorphism(D, A, "h1")
h2 = NamedMorphism(A, D, "h2")
k = NamedMorphism(D, B, "k")
d = Diagram([f, g, h, k, h1, h2])
grid = DiagramGrid(d)
drawer = XypicDiagramDrawer()
assert drawer.draw(d, grid) == "\\xymatrix{\n" \
"A \\ar[r]_{f} \\ar@/^3mm/[rr]^{h_{2}} & B \\ar[d]^{g} & D \\ar[l]^{k} " \
"\\ar@/_7mm/[ll]_{h} \\ar@/_11mm/[ll]_{h_{1}} \\\\\n" \
"& C & \n" \
"}\n"
# The same diagram, transposed.
grid = DiagramGrid(d, transpose=True)
drawer = XypicDiagramDrawer()
assert drawer.draw(d, grid) == "\\xymatrix{\n" \
"A \\ar[d]^{f} \\ar@/_3mm/[dd]_{h_{2}} & \\\\\n" \
"B \\ar[r]^{g} & C \\\\\n" \
"D \\ar[u]_{k} \\ar@/^7mm/[uu]^{h} \\ar@/^11mm/[uu]^{h_{1}} & \n" \
"}\n"
# The same diagram, with "loop" morphisms.
l_A = NamedMorphism(A, A, "l_A")
l_D = NamedMorphism(D, D, "l_D")
l_C = NamedMorphism(C, C, "l_C")
d = Diagram([f, g, h, k, h1, h2, l_A, l_D, l_C])
grid = DiagramGrid(d)
drawer = XypicDiagramDrawer()
assert drawer.draw(d, grid) == "\\xymatrix{\n" \
"A \\ar[r]_{f} \\ar@/^3mm/[rr]^{h_{2}} \\ar@(u,l)[]^{l_{A}} " \
"& B \\ar[d]^{g} & D \\ar[l]^{k} \\ar@/_7mm/[ll]_{h} " \
"\\ar@/_11mm/[ll]_{h_{1}} \\ar@(r,u)[]^{l_{D}} \\\\\n" \
"& C \\ar@(l,d)[]^{l_{C}} & \n" \
"}\n"
# The same diagram with "loop" morphisms, transposed.
grid = DiagramGrid(d, transpose=True)
drawer = XypicDiagramDrawer()
assert drawer.draw(d, grid) == "\\xymatrix{\n" \
"A \\ar[d]^{f} \\ar@/_3mm/[dd]_{h_{2}} \\ar@(r,u)[]^{l_{A}} & \\\\\n" \
"B \\ar[r]^{g} & C \\ar@(r,u)[]^{l_{C}} \\\\\n" \
"D \\ar[u]_{k} \\ar@/^7mm/[uu]^{h} \\ar@/^11mm/[uu]^{h_{1}} " \
"\\ar@(l,d)[]^{l_{D}} & \n" \
"}\n"
# The same diagram with two "loop" morphisms per object.
l_A_ = NamedMorphism(A, A, "n_A")
l_D_ = NamedMorphism(D, D, "n_D")
l_C_ = NamedMorphism(C, C, "n_C")
d = Diagram([f, g, h, k, h1, h2, l_A, l_D, l_C, l_A_, l_D_, l_C_])
grid = DiagramGrid(d)
drawer = XypicDiagramDrawer()
assert drawer.draw(d, grid) == "\\xymatrix{\n" \
"A \\ar[r]_{f} \\ar@/^3mm/[rr]^{h_{2}} \\ar@(u,l)[]^{l_{A}} " \
"\\ar@/^3mm/@(l,d)[]^{n_{A}} & B \\ar[d]^{g} & D \\ar[l]^{k} " \
"\\ar@/_7mm/[ll]_{h} \\ar@/_11mm/[ll]_{h_{1}} \\ar@(r,u)[]^{l_{D}} " \
"\\ar@/^3mm/@(d,r)[]^{n_{D}} \\\\\n" \
"& C \\ar@(l,d)[]^{l_{C}} \\ar@/^3mm/@(d,r)[]^{n_{C}} & \n" \
"}\n"
# The same diagram with two "loop" morphisms per object, transposed.
grid = DiagramGrid(d, transpose=True)
drawer = XypicDiagramDrawer()
assert drawer.draw(d, grid) == "\\xymatrix{\n" \
"A \\ar[d]^{f} \\ar@/_3mm/[dd]_{h_{2}} \\ar@(r,u)[]^{l_{A}} " \
"\\ar@/^3mm/@(u,l)[]^{n_{A}} & \\\\\n" \
"B \\ar[r]^{g} & C \\ar@(r,u)[]^{l_{C}} \\ar@/^3mm/@(d,r)[]^{n_{C}} \\\\\n" \
"D \\ar[u]_{k} \\ar@/^7mm/[uu]^{h} \\ar@/^11mm/[uu]^{h_{1}} " \
"\\ar@(l,d)[]^{l_{D}} \\ar@/^3mm/@(d,r)[]^{n_{D}} & \n" \
"}\n"
def test_xypic_draw_diagram():
# A linear diagram.
A = Object("A")
B = Object("B")
C = Object("C")
D = Object("D")
E = Object("E")
f = NamedMorphism(A, B, "f")
g = NamedMorphism(B, C, "g")
h = NamedMorphism(C, D, "h")
i = NamedMorphism(D, E, "i")
d = Diagram([f, g, h, i])
grid = DiagramGrid(d, layout="sequential")
drawer = XypicDiagramDrawer()
assert drawer.draw(d, grid) == xypic_draw_diagram(d, layout="sequential")
|
f23f1286720d9b4c0566f255a0bdd16a324e4bd377c5078c75f19edbd16321d7 | from sympy.core.function import diff
from sympy.core.numbers import (E, I, Rational, pi)
from sympy.core.singleton import S
from sympy.core.symbol import (Symbol, symbols)
from sympy.functions.elementary.complexes import (Abs, conjugate, im, re, sign)
from sympy.functions.elementary.exponential import log
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.trigonometric import (acos, asin, cos, sin)
from sympy.integrals.integrals import integrate
from sympy.matrices.dense import Matrix
from sympy.simplify.trigsimp import trigsimp
from sympy.algebras.quaternion import Quaternion
from sympy.testing.pytest import raises
w, x, y, z = symbols('w:z')
phi = symbols('phi')
def test_quaternion_construction():
q = Quaternion(w, x, y, z)
assert q + q == Quaternion(2*w, 2*x, 2*y, 2*z)
q2 = Quaternion.from_axis_angle((sqrt(3)/3, sqrt(3)/3, sqrt(3)/3),
pi*Rational(2, 3))
assert q2 == Quaternion(S.Half, S.Half,
S.Half, S.Half)
M = Matrix([[cos(phi), -sin(phi), 0], [sin(phi), cos(phi), 0], [0, 0, 1]])
q3 = trigsimp(Quaternion.from_rotation_matrix(M))
assert q3 == Quaternion(sqrt(2)*sqrt(cos(phi) + 1)/2, 0, 0, sqrt(2 - 2*cos(phi))*sign(sin(phi))/2)
nc = Symbol('nc', commutative=False)
raises(ValueError, lambda: Quaternion(w, x, nc, z))
def test_quaternion_axis_angle():
test_data = [ # axis, angle, expected_quaternion
((1, 0, 0), 0, (1, 0, 0, 0)),
((1, 0, 0), pi/2, (sqrt(2)/2, sqrt(2)/2, 0, 0)),
((0, 1, 0), pi/2, (sqrt(2)/2, 0, sqrt(2)/2, 0)),
((0, 0, 1), pi/2, (sqrt(2)/2, 0, 0, sqrt(2)/2)),
((1, 0, 0), pi, (0, 1, 0, 0)),
((0, 1, 0), pi, (0, 0, 1, 0)),
((0, 0, 1), pi, (0, 0, 0, 1)),
((1, 1, 1), pi, (0, 1/sqrt(3),1/sqrt(3),1/sqrt(3))),
((sqrt(3)/3, sqrt(3)/3, sqrt(3)/3), pi*2/3, (S.Half, S.Half, S.Half, S.Half))
]
for axis, angle, expected in test_data:
assert Quaternion.from_axis_angle(axis, angle) == Quaternion(*expected)
def test_quaternion_axis_angle_simplification():
result = Quaternion.from_axis_angle((1, 2, 3), asin(4))
assert result.a == cos(asin(4)/2)
assert result.b == sqrt(14)*sin(asin(4)/2)/14
assert result.c == sqrt(14)*sin(asin(4)/2)/7
assert result.d == 3*sqrt(14)*sin(asin(4)/2)/14
def test_quaternion_complex_real_addition():
a = symbols("a", complex=True)
b = symbols("b", real=True)
# This symbol is not complex:
c = symbols("c", commutative=False)
q = Quaternion(w, x, y, z)
assert a + q == Quaternion(w + re(a), x + im(a), y, z)
assert 1 + q == Quaternion(1 + w, x, y, z)
assert I + q == Quaternion(w, 1 + x, y, z)
assert b + q == Quaternion(w + b, x, y, z)
raises(ValueError, lambda: c + q)
raises(ValueError, lambda: q * c)
raises(ValueError, lambda: c * q)
assert -q == Quaternion(-w, -x, -y, -z)
q1 = Quaternion(3 + 4*I, 2 + 5*I, 0, 7 + 8*I, real_field = False)
q2 = Quaternion(1, 4, 7, 8)
assert q1 + (2 + 3*I) == Quaternion(5 + 7*I, 2 + 5*I, 0, 7 + 8*I)
assert q2 + (2 + 3*I) == Quaternion(3, 7, 7, 8)
assert q1 * (2 + 3*I) == \
Quaternion((2 + 3*I)*(3 + 4*I), (2 + 3*I)*(2 + 5*I), 0, (2 + 3*I)*(7 + 8*I))
assert q2 * (2 + 3*I) == Quaternion(-10, 11, 38, -5)
q1 = Quaternion(1, 2, 3, 4)
q0 = Quaternion(0, 0, 0, 0)
assert q1 + q0 == q1
assert q1 - q0 == q1
assert q1 - q1 == q0
def test_quaternion_evalf():
assert Quaternion(sqrt(2), 0, 0, sqrt(3)).evalf() == Quaternion(sqrt(2).evalf(), 0, 0, sqrt(3).evalf())
assert Quaternion(1/sqrt(2), 0, 0, 1/sqrt(2)).evalf() == Quaternion((1/sqrt(2)).evalf(), 0, 0, (1/sqrt(2)).evalf())
def test_quaternion_functions():
q = Quaternion(w, x, y, z)
q1 = Quaternion(1, 2, 3, 4)
q0 = Quaternion(0, 0, 0, 0)
assert conjugate(q) == Quaternion(w, -x, -y, -z)
assert q.norm() == sqrt(w**2 + x**2 + y**2 + z**2)
assert q.normalize() == Quaternion(w, x, y, z) / sqrt(w**2 + x**2 + y**2 + z**2)
assert q.inverse() == Quaternion(w, -x, -y, -z) / (w**2 + x**2 + y**2 + z**2)
assert q.inverse() == q.pow(-1)
raises(ValueError, lambda: q0.inverse())
assert q.pow(2) == Quaternion(w**2 - x**2 - y**2 - z**2, 2*w*x, 2*w*y, 2*w*z)
assert q**(2) == Quaternion(w**2 - x**2 - y**2 - z**2, 2*w*x, 2*w*y, 2*w*z)
assert q1.pow(-2) == Quaternion(Rational(-7, 225), Rational(-1, 225), Rational(-1, 150), Rational(-2, 225))
assert q1**(-2) == Quaternion(Rational(-7, 225), Rational(-1, 225), Rational(-1, 150), Rational(-2, 225))
assert q1.pow(-0.5) == NotImplemented
raises(TypeError, lambda: q1**(-0.5))
assert q1.exp() == \
Quaternion(E * cos(sqrt(29)),
2 * sqrt(29) * E * sin(sqrt(29)) / 29,
3 * sqrt(29) * E * sin(sqrt(29)) / 29,
4 * sqrt(29) * E * sin(sqrt(29)) / 29)
assert q1._ln() == \
Quaternion(log(sqrt(30)),
2 * sqrt(29) * acos(sqrt(30)/30) / 29,
3 * sqrt(29) * acos(sqrt(30)/30) / 29,
4 * sqrt(29) * acos(sqrt(30)/30) / 29)
assert q1.pow_cos_sin(2) == \
Quaternion(30 * cos(2 * acos(sqrt(30)/30)),
60 * sqrt(29) * sin(2 * acos(sqrt(30)/30)) / 29,
90 * sqrt(29) * sin(2 * acos(sqrt(30)/30)) / 29,
120 * sqrt(29) * sin(2 * acos(sqrt(30)/30)) / 29)
assert diff(Quaternion(x, x, x, x), x) == Quaternion(1, 1, 1, 1)
assert integrate(Quaternion(x, x, x, x), x) == \
Quaternion(x**2 / 2, x**2 / 2, x**2 / 2, x**2 / 2)
assert Quaternion.rotate_point((1, 1, 1), q1) == (S.One / 5, 1, S(7) / 5)
n = Symbol('n')
raises(TypeError, lambda: q1**n)
n = Symbol('n', integer=True)
raises(TypeError, lambda: q1**n)
def test_quaternion_conversions():
q1 = Quaternion(1, 2, 3, 4)
assert q1.to_axis_angle() == ((2 * sqrt(29)/29,
3 * sqrt(29)/29,
4 * sqrt(29)/29),
2 * acos(sqrt(30)/30))
assert q1.to_rotation_matrix() == Matrix([[Rational(-2, 3), Rational(2, 15), Rational(11, 15)],
[Rational(2, 3), Rational(-1, 3), Rational(2, 3)],
[Rational(1, 3), Rational(14, 15), Rational(2, 15)]])
assert q1.to_rotation_matrix((1, 1, 1)) == Matrix([[Rational(-2, 3), Rational(2, 15), Rational(11, 15), Rational(4, 5)],
[Rational(2, 3), Rational(-1, 3), Rational(2, 3), S.Zero],
[Rational(1, 3), Rational(14, 15), Rational(2, 15), Rational(-2, 5)],
[S.Zero, S.Zero, S.Zero, S.One]])
theta = symbols("theta", real=True)
q2 = Quaternion(cos(theta/2), 0, 0, sin(theta/2))
assert trigsimp(q2.to_rotation_matrix()) == Matrix([
[cos(theta), -sin(theta), 0],
[sin(theta), cos(theta), 0],
[0, 0, 1]])
assert q2.to_axis_angle() == ((0, 0, sin(theta/2)/Abs(sin(theta/2))),
2*acos(cos(theta/2)))
assert trigsimp(q2.to_rotation_matrix((1, 1, 1))) == Matrix([
[cos(theta), -sin(theta), 0, sin(theta) - cos(theta) + 1],
[sin(theta), cos(theta), 0, -sin(theta) - cos(theta) + 1],
[0, 0, 1, 0],
[0, 0, 0, 1]])
def test_quaternion_rotation_iss1593():
"""
There was a sign mistake in the definition,
of the rotation matrix. This tests that particular sign mistake.
See issue 1593 for reference.
See wikipedia
https://en.wikipedia.org/wiki/Quaternions_and_spatial_rotation#Quaternion-derived_rotation_matrix
for the correct definition
"""
q = Quaternion(cos(phi/2), sin(phi/2), 0, 0)
assert(trigsimp(q.to_rotation_matrix()) == Matrix([
[1, 0, 0],
[0, cos(phi), -sin(phi)],
[0, sin(phi), cos(phi)]]))
def test_quaternion_multiplication():
q1 = Quaternion(3 + 4*I, 2 + 5*I, 0, 7 + 8*I, real_field = False)
q2 = Quaternion(1, 2, 3, 5)
q3 = Quaternion(1, 1, 1, y)
assert Quaternion._generic_mul(4, 1) == 4
assert Quaternion._generic_mul(4, q1) == Quaternion(12 + 16*I, 8 + 20*I, 0, 28 + 32*I)
assert q2.mul(2) == Quaternion(2, 4, 6, 10)
assert q2.mul(q3) == Quaternion(-5*y - 4, 3*y - 2, 9 - 2*y, y + 4)
assert q2.mul(q3) == q2*q3
z = symbols('z', complex=True)
z_quat = Quaternion(re(z), im(z), 0, 0)
q = Quaternion(*symbols('q:4', real=True))
assert z * q == z_quat * q
assert q * z == q * z_quat
def test_issue_16318():
#for rtruediv
q0 = Quaternion(0, 0, 0, 0)
raises(ValueError, lambda: 1/q0)
#for rotate_point
q = Quaternion(1, 2, 3, 4)
(axis, angle) = q.to_axis_angle()
assert Quaternion.rotate_point((1, 1, 1), (axis, angle)) == (S.One / 5, 1, S(7) / 5)
#test for to_axis_angle
q = Quaternion(-1, 1, 1, 1)
axis = (-sqrt(3)/3, -sqrt(3)/3, -sqrt(3)/3)
angle = 2*pi/3
assert (axis, angle) == q.to_axis_angle()
|
2db472c61869f8d9e77c9da04e7d527658020509f6ae1c81ef10293a071dfeb3 | from sympy.diffgeom import Manifold, Patch, CoordSystem, Point
from sympy.core.function import Function
from sympy.core.symbol import symbols
from sympy.testing.pytest import warns_deprecated_sympy
m = Manifold('m', 2)
p = Patch('p', m)
a, b = symbols('a b')
cs = CoordSystem('cs', p, [a, b])
x, y = symbols('x y')
f = Function('f')
s1, s2 = cs.coord_functions()
v1, v2 = cs.base_vectors()
f1, f2 = cs.base_oneforms()
def test_point():
point = Point(cs, [x, y])
assert point != Point(cs, [2, y])
#TODO assert point.subs(x, 2) == Point(cs, [2, y])
#TODO assert point.free_symbols == set([x, y])
def test_subs():
assert s1.subs(s1, s2) == s2
assert v1.subs(v1, v2) == v2
assert f1.subs(f1, f2) == f2
assert (x*f(s1) + y).subs(s1, s2) == x*f(s2) + y
assert (f(s1)*v1).subs(v1, v2) == f(s1)*v2
assert (y*f(s1)*f1).subs(f1, f2) == y*f(s1)*f2
def test_deprecated():
with warns_deprecated_sympy():
cs_wname = CoordSystem('cs', p, ['a', 'b'])
assert cs_wname == cs_wname.func(*cs_wname.args)
|
8f3797c20ad209fd5d231cbe00debcaf8c0f6057e4ee25483ae6fdb8c9ac0f05 | from sympy.core import Lambda, Symbol, symbols
from sympy.diffgeom.rn import R2, R2_p, R2_r, R3_r, R3_c, R3_s, R2_origin
from sympy.diffgeom import (CoordSystem, Commutator, Differential, TensorProduct,
WedgeProduct, BaseCovarDerivativeOp, CovarDerivativeOp, LieDerivative,
covariant_order, contravariant_order, twoform_to_matrix, metric_to_Christoffel_1st,
metric_to_Christoffel_2nd, metric_to_Riemann_components,
metric_to_Ricci_components, intcurve_diffequ, intcurve_series)
from sympy.simplify import trigsimp, simplify
from sympy.functions import sqrt, atan2, sin
from sympy.matrices import Matrix
from sympy.testing.pytest import raises, nocache_fail
from sympy.testing.pytest import warns_deprecated_sympy
TP = TensorProduct
def test_coordsys_transform():
# test inverse transforms
p, q, r, s = symbols('p q r s')
rel = {('first', 'second'): [(p, q), (q, -p)]}
R2_pq = CoordSystem('first', R2_origin, [p, q], rel)
R2_rs = CoordSystem('second', R2_origin, [r, s], rel)
r, s = R2_rs.symbols
assert R2_rs.transform(R2_pq) == Matrix([[-s], [r]])
# inverse transform impossible case
a, b = symbols('a b', positive=True)
rel = {('first', 'second'): [(a,), (-a,)]}
R2_a = CoordSystem('first', R2_origin, [a], rel)
R2_b = CoordSystem('second', R2_origin, [b], rel)
# This transformation is uninvertible because there is no positive a, b satisfying a = -b
with raises(NotImplementedError):
R2_b.transform(R2_a)
# inverse transform ambiguous case
c, d = symbols('c d')
rel = {('first', 'second'): [(c,), (c**2,)]}
R2_c = CoordSystem('first', R2_origin, [c], rel)
R2_d = CoordSystem('second', R2_origin, [d], rel)
# The transform method should throw if it finds multiple inverses for a coordinate transformation.
with raises(ValueError):
R2_d.transform(R2_c)
# test indirect transformation
a, b, c, d, e, f = symbols('a, b, c, d, e, f')
rel = {('C1', 'C2'): [(a, b), (2*a, 3*b)],
('C2', 'C3'): [(c, d), (3*c, 2*d)]}
C1 = CoordSystem('C1', R2_origin, (a, b), rel)
C2 = CoordSystem('C2', R2_origin, (c, d), rel)
C3 = CoordSystem('C3', R2_origin, (e, f), rel)
a, b = C1.symbols
c, d = C2.symbols
e, f = C3.symbols
assert C2.transform(C1) == Matrix([c/2, d/3])
assert C1.transform(C3) == Matrix([6*a, 6*b])
assert C3.transform(C1) == Matrix([e/6, f/6])
assert C3.transform(C2) == Matrix([e/3, f/2])
a, b, c, d, e, f = symbols('a, b, c, d, e, f')
rel = {('C1', 'C2'): [(a, b), (2*a, 3*b + 1)],
('C3', 'C2'): [(e, f), (-e - 2, 2*f)]}
C1 = CoordSystem('C1', R2_origin, (a, b), rel)
C2 = CoordSystem('C2', R2_origin, (c, d), rel)
C3 = CoordSystem('C3', R2_origin, (e, f), rel)
a, b = C1.symbols
c, d = C2.symbols
e, f = C3.symbols
assert C2.transform(C1) == Matrix([c/2, (d - 1)/3])
assert C1.transform(C3) == Matrix([-2*a - 2, (3*b + 1)/2])
assert C3.transform(C1) == Matrix([-e/2 - 1, (2*f - 1)/3])
assert C3.transform(C2) == Matrix([-e - 2, 2*f])
# old signature uses Lambda
a, b, c, d, e, f = symbols('a, b, c, d, e, f')
rel = {('C1', 'C2'): Lambda((a, b), (2*a, 3*b + 1)),
('C3', 'C2'): Lambda((e, f), (-e - 2, 2*f))}
C1 = CoordSystem('C1', R2_origin, (a, b), rel)
C2 = CoordSystem('C2', R2_origin, (c, d), rel)
C3 = CoordSystem('C3', R2_origin, (e, f), rel)
a, b = C1.symbols
c, d = C2.symbols
e, f = C3.symbols
assert C2.transform(C1) == Matrix([c/2, (d - 1)/3])
assert C1.transform(C3) == Matrix([-2*a - 2, (3*b + 1)/2])
assert C3.transform(C1) == Matrix([-e/2 - 1, (2*f - 1)/3])
assert C3.transform(C2) == Matrix([-e - 2, 2*f])
def test_R2():
x0, y0, r0, theta0 = symbols('x0, y0, r0, theta0', real=True)
point_r = R2_r.point([x0, y0])
point_p = R2_p.point([r0, theta0])
# r**2 = x**2 + y**2
assert (R2.r**2 - R2.x**2 - R2.y**2).rcall(point_r) == 0
assert trigsimp( (R2.r**2 - R2.x**2 - R2.y**2).rcall(point_p) ) == 0
assert trigsimp(R2.e_r(R2.x**2 + R2.y**2).rcall(point_p).doit()) == 2*r0
# polar->rect->polar == Id
a, b = symbols('a b', positive=True)
m = Matrix([[a], [b]])
#TODO assert m == R2_r.transform(R2_p, R2_p.transform(R2_r, [a, b])).applyfunc(simplify)
assert m == R2_p.transform(R2_r, R2_r.transform(R2_p, m)).applyfunc(simplify)
# deprecated method
with warns_deprecated_sympy():
assert m == R2_p.coord_tuple_transform_to(
R2_r, R2_r.coord_tuple_transform_to(R2_p, m)).applyfunc(simplify)
def test_R3():
a, b, c = symbols('a b c', positive=True)
m = Matrix([[a], [b], [c]])
assert m == R3_c.transform(R3_r, R3_r.transform(R3_c, m)).applyfunc(simplify)
#TODO assert m == R3_r.transform(R3_c, R3_c.transform(R3_r, m)).applyfunc(simplify)
assert m == R3_s.transform(
R3_r, R3_r.transform(R3_s, m)).applyfunc(simplify)
#TODO assert m == R3_r.transform(R3_s, R3_s.transform(R3_r, m)).applyfunc(simplify)
assert m == R3_s.transform(
R3_c, R3_c.transform(R3_s, m)).applyfunc(simplify)
#TODO assert m == R3_c.transform(R3_s, R3_s.transform(R3_c, m)).applyfunc(simplify)
with warns_deprecated_sympy():
assert m == R3_c.coord_tuple_transform_to(
R3_r, R3_r.coord_tuple_transform_to(R3_c, m)).applyfunc(simplify)
#TODO assert m == R3_r.coord_tuple_transform_to(R3_c, R3_c.coord_tuple_transform_to(R3_r, m)).applyfunc(simplify)
assert m == R3_s.coord_tuple_transform_to(
R3_r, R3_r.coord_tuple_transform_to(R3_s, m)).applyfunc(simplify)
#TODO assert m == R3_r.coord_tuple_transform_to(R3_s, R3_s.coord_tuple_transform_to(R3_r, m)).applyfunc(simplify)
assert m == R3_s.coord_tuple_transform_to(
R3_c, R3_c.coord_tuple_transform_to(R3_s, m)).applyfunc(simplify)
#TODO assert m == R3_c.coord_tuple_transform_to(R3_s, R3_s.coord_tuple_transform_to(R3_c, m)).applyfunc(simplify)
def test_CoordinateSymbol():
x, y = R2_r.symbols
r, theta = R2_p.symbols
assert y.rewrite(R2_p) == r*sin(theta)
def test_point():
x, y = symbols('x, y')
p = R2_r.point([x, y])
assert p.free_symbols == {x, y}
assert p.coords(R2_r) == p.coords() == Matrix([x, y])
assert p.coords(R2_p) == Matrix([sqrt(x**2 + y**2), atan2(y, x)])
def test_commutator():
assert Commutator(R2.e_x, R2.e_y) == 0
assert Commutator(R2.x*R2.e_x, R2.x*R2.e_x) == 0
assert Commutator(R2.x*R2.e_x, R2.x*R2.e_y) == R2.x*R2.e_y
c = Commutator(R2.e_x, R2.e_r)
assert c(R2.x) == R2.y*(R2.x**2 + R2.y**2)**(-1)*sin(R2.theta)
def test_differential():
xdy = R2.x*R2.dy
dxdy = Differential(xdy)
assert xdy.rcall(None) == xdy
assert dxdy(R2.e_x, R2.e_y) == 1
assert dxdy(R2.e_x, R2.x*R2.e_y) == R2.x
assert Differential(dxdy) == 0
def test_products():
assert TensorProduct(
R2.dx, R2.dy)(R2.e_x, R2.e_y) == R2.dx(R2.e_x)*R2.dy(R2.e_y) == 1
assert TensorProduct(R2.dx, R2.dy)(None, R2.e_y) == R2.dx
assert TensorProduct(R2.dx, R2.dy)(R2.e_x, None) == R2.dy
assert TensorProduct(R2.dx, R2.dy)(R2.e_x) == R2.dy
assert TensorProduct(R2.x, R2.dx) == R2.x*R2.dx
assert TensorProduct(
R2.e_x, R2.e_y)(R2.x, R2.y) == R2.e_x(R2.x) * R2.e_y(R2.y) == 1
assert TensorProduct(R2.e_x, R2.e_y)(None, R2.y) == R2.e_x
assert TensorProduct(R2.e_x, R2.e_y)(R2.x, None) == R2.e_y
assert TensorProduct(R2.e_x, R2.e_y)(R2.x) == R2.e_y
assert TensorProduct(R2.x, R2.e_x) == R2.x * R2.e_x
assert TensorProduct(
R2.dx, R2.e_y)(R2.e_x, R2.y) == R2.dx(R2.e_x) * R2.e_y(R2.y) == 1
assert TensorProduct(R2.dx, R2.e_y)(None, R2.y) == R2.dx
assert TensorProduct(R2.dx, R2.e_y)(R2.e_x, None) == R2.e_y
assert TensorProduct(R2.dx, R2.e_y)(R2.e_x) == R2.e_y
assert TensorProduct(R2.x, R2.e_x) == R2.x * R2.e_x
assert TensorProduct(
R2.e_x, R2.dy)(R2.x, R2.e_y) == R2.e_x(R2.x) * R2.dy(R2.e_y) == 1
assert TensorProduct(R2.e_x, R2.dy)(None, R2.e_y) == R2.e_x
assert TensorProduct(R2.e_x, R2.dy)(R2.x, None) == R2.dy
assert TensorProduct(R2.e_x, R2.dy)(R2.x) == R2.dy
assert TensorProduct(R2.e_y,R2.e_x)(R2.x**2 + R2.y**2,R2.x**2 + R2.y**2) == 4*R2.x*R2.y
assert WedgeProduct(R2.dx, R2.dy)(R2.e_x, R2.e_y) == 1
assert WedgeProduct(R2.e_x, R2.e_y)(R2.x, R2.y) == 1
def test_lie_derivative():
assert LieDerivative(R2.e_x, R2.y) == R2.e_x(R2.y) == 0
assert LieDerivative(R2.e_x, R2.x) == R2.e_x(R2.x) == 1
assert LieDerivative(R2.e_x, R2.e_x) == Commutator(R2.e_x, R2.e_x) == 0
assert LieDerivative(R2.e_x, R2.e_r) == Commutator(R2.e_x, R2.e_r)
assert LieDerivative(R2.e_x + R2.e_y, R2.x) == 1
assert LieDerivative(
R2.e_x, TensorProduct(R2.dx, R2.dy))(R2.e_x, R2.e_y) == 0
@nocache_fail
def test_covar_deriv():
ch = metric_to_Christoffel_2nd(TP(R2.dx, R2.dx) + TP(R2.dy, R2.dy))
cvd = BaseCovarDerivativeOp(R2_r, 0, ch)
assert cvd(R2.x) == 1
# This line fails if the cache is disabled:
assert cvd(R2.x*R2.e_x) == R2.e_x
cvd = CovarDerivativeOp(R2.x*R2.e_x, ch)
assert cvd(R2.x) == R2.x
assert cvd(R2.x*R2.e_x) == R2.x*R2.e_x
def test_intcurve_diffequ():
t = symbols('t')
start_point = R2_r.point([1, 0])
vector_field = -R2.y*R2.e_x + R2.x*R2.e_y
equations, init_cond = intcurve_diffequ(vector_field, t, start_point)
assert str(equations) == '[f_1(t) + Derivative(f_0(t), t), -f_0(t) + Derivative(f_1(t), t)]'
assert str(init_cond) == '[f_0(0) - 1, f_1(0)]'
equations, init_cond = intcurve_diffequ(vector_field, t, start_point, R2_p)
assert str(
equations) == '[Derivative(f_0(t), t), Derivative(f_1(t), t) - 1]'
assert str(init_cond) == '[f_0(0) - 1, f_1(0)]'
def test_helpers_and_coordinate_dependent():
one_form = R2.dr + R2.dx
two_form = Differential(R2.x*R2.dr + R2.r*R2.dx)
three_form = Differential(
R2.y*two_form) + Differential(R2.x*Differential(R2.r*R2.dr))
metric = TensorProduct(R2.dx, R2.dx) + TensorProduct(R2.dy, R2.dy)
metric_ambig = TensorProduct(R2.dx, R2.dx) + TensorProduct(R2.dr, R2.dr)
misform_a = TensorProduct(R2.dr, R2.dr) + R2.dr
misform_b = R2.dr**4
misform_c = R2.dx*R2.dy
twoform_not_sym = TensorProduct(R2.dx, R2.dx) + TensorProduct(R2.dx, R2.dy)
twoform_not_TP = WedgeProduct(R2.dx, R2.dy)
one_vector = R2.e_x + R2.e_y
two_vector = TensorProduct(R2.e_x, R2.e_y)
three_vector = TensorProduct(R2.e_x, R2.e_y, R2.e_x)
two_wp = WedgeProduct(R2.e_x,R2.e_y)
assert covariant_order(one_form) == 1
assert covariant_order(two_form) == 2
assert covariant_order(three_form) == 3
assert covariant_order(two_form + metric) == 2
assert covariant_order(two_form + metric_ambig) == 2
assert covariant_order(two_form + twoform_not_sym) == 2
assert covariant_order(two_form + twoform_not_TP) == 2
assert contravariant_order(one_vector) == 1
assert contravariant_order(two_vector) == 2
assert contravariant_order(three_vector) == 3
assert contravariant_order(two_vector + two_wp) == 2
raises(ValueError, lambda: covariant_order(misform_a))
raises(ValueError, lambda: covariant_order(misform_b))
raises(ValueError, lambda: covariant_order(misform_c))
assert twoform_to_matrix(metric) == Matrix([[1, 0], [0, 1]])
assert twoform_to_matrix(twoform_not_sym) == Matrix([[1, 0], [1, 0]])
assert twoform_to_matrix(twoform_not_TP) == Matrix([[0, -1], [1, 0]])
raises(ValueError, lambda: twoform_to_matrix(one_form))
raises(ValueError, lambda: twoform_to_matrix(three_form))
raises(ValueError, lambda: twoform_to_matrix(metric_ambig))
raises(ValueError, lambda: metric_to_Christoffel_1st(twoform_not_sym))
raises(ValueError, lambda: metric_to_Christoffel_2nd(twoform_not_sym))
raises(ValueError, lambda: metric_to_Riemann_components(twoform_not_sym))
raises(ValueError, lambda: metric_to_Ricci_components(twoform_not_sym))
def test_correct_arguments():
raises(ValueError, lambda: R2.e_x(R2.e_x))
raises(ValueError, lambda: R2.e_x(R2.dx))
raises(ValueError, lambda: Commutator(R2.e_x, R2.x))
raises(ValueError, lambda: Commutator(R2.dx, R2.e_x))
raises(ValueError, lambda: Differential(Differential(R2.e_x)))
raises(ValueError, lambda: R2.dx(R2.x))
raises(ValueError, lambda: LieDerivative(R2.dx, R2.dx))
raises(ValueError, lambda: LieDerivative(R2.x, R2.dx))
raises(ValueError, lambda: CovarDerivativeOp(R2.dx, []))
raises(ValueError, lambda: CovarDerivativeOp(R2.x, []))
a = Symbol('a')
raises(ValueError, lambda: intcurve_series(R2.dx, a, R2_r.point([1, 2])))
raises(ValueError, lambda: intcurve_series(R2.x, a, R2_r.point([1, 2])))
raises(ValueError, lambda: intcurve_diffequ(R2.dx, a, R2_r.point([1, 2])))
raises(ValueError, lambda: intcurve_diffequ(R2.x, a, R2_r.point([1, 2])))
raises(ValueError, lambda: contravariant_order(R2.e_x + R2.dx))
raises(ValueError, lambda: covariant_order(R2.e_x + R2.dx))
raises(ValueError, lambda: contravariant_order(R2.e_x*R2.e_y))
raises(ValueError, lambda: covariant_order(R2.dx*R2.dy))
def test_simplify():
x, y = R2_r.coord_functions()
dx, dy = R2_r.base_oneforms()
ex, ey = R2_r.base_vectors()
assert simplify(x) == x
assert simplify(x*y) == x*y
assert simplify(dx*dy) == dx*dy
assert simplify(ex*ey) == ex*ey
assert ((1-x)*dx)/(1-x)**2 == dx/(1-x)
def test_issue_17917():
X = R2.x*R2.e_x - R2.y*R2.e_y
Y = (R2.x**2 + R2.y**2)*R2.e_x - R2.x*R2.y*R2.e_y
assert LieDerivative(X, Y).expand() == (
R2.x**2*R2.e_x - 3*R2.y**2*R2.e_x - R2.x*R2.y*R2.e_y)
|
738c5027f6c14b8c6b323de97f1d4cb37a02dbf2f0b89b8d617359c6cf9c546f | r'''
unit test describing the hyperbolic half-plane with the Poincare metric. This
is a basic model of hyperbolic geometry on the (positive) half-space
{(x,y) \in R^2 | y > 0}
with the Riemannian metric
ds^2 = (dx^2 + dy^2)/y^2
It has constant negative scalar curvature = -2
https://en.wikipedia.org/wiki/Poincare_half-plane_model
'''
from sympy.matrices.dense import diag
from sympy.diffgeom import (twoform_to_matrix,
metric_to_Christoffel_1st, metric_to_Christoffel_2nd,
metric_to_Riemann_components, metric_to_Ricci_components)
import sympy.diffgeom.rn
from sympy.tensor.array import ImmutableDenseNDimArray
def test_H2():
TP = sympy.diffgeom.TensorProduct
R2 = sympy.diffgeom.rn.R2
y = R2.y
dy = R2.dy
dx = R2.dx
g = (TP(dx, dx) + TP(dy, dy))*y**(-2)
automat = twoform_to_matrix(g)
mat = diag(y**(-2), y**(-2))
assert mat == automat
gamma1 = metric_to_Christoffel_1st(g)
assert gamma1[0, 0, 0] == 0
assert gamma1[0, 0, 1] == -y**(-3)
assert gamma1[0, 1, 0] == -y**(-3)
assert gamma1[0, 1, 1] == 0
assert gamma1[1, 1, 1] == -y**(-3)
assert gamma1[1, 1, 0] == 0
assert gamma1[1, 0, 1] == 0
assert gamma1[1, 0, 0] == y**(-3)
gamma2 = metric_to_Christoffel_2nd(g)
assert gamma2[0, 0, 0] == 0
assert gamma2[0, 0, 1] == -y**(-1)
assert gamma2[0, 1, 0] == -y**(-1)
assert gamma2[0, 1, 1] == 0
assert gamma2[1, 1, 1] == -y**(-1)
assert gamma2[1, 1, 0] == 0
assert gamma2[1, 0, 1] == 0
assert gamma2[1, 0, 0] == y**(-1)
Rm = metric_to_Riemann_components(g)
assert Rm[0, 0, 0, 0] == 0
assert Rm[0, 0, 0, 1] == 0
assert Rm[0, 0, 1, 0] == 0
assert Rm[0, 0, 1, 1] == 0
assert Rm[0, 1, 0, 0] == 0
assert Rm[0, 1, 0, 1] == -y**(-2)
assert Rm[0, 1, 1, 0] == y**(-2)
assert Rm[0, 1, 1, 1] == 0
assert Rm[1, 0, 0, 0] == 0
assert Rm[1, 0, 0, 1] == y**(-2)
assert Rm[1, 0, 1, 0] == -y**(-2)
assert Rm[1, 0, 1, 1] == 0
assert Rm[1, 1, 0, 0] == 0
assert Rm[1, 1, 0, 1] == 0
assert Rm[1, 1, 1, 0] == 0
assert Rm[1, 1, 1, 1] == 0
Ric = metric_to_Ricci_components(g)
assert Ric[0, 0] == -y**(-2)
assert Ric[0, 1] == 0
assert Ric[1, 0] == 0
assert Ric[0, 0] == -y**(-2)
assert Ric == ImmutableDenseNDimArray([-y**(-2), 0, 0, -y**(-2)], (2, 2))
## scalar curvature is -2
#TODO - it would be nice to have index contraction built-in
R = (Ric[0, 0] + Ric[1, 1])*y**2
assert R == -2
## Gauss curvature is -1
assert R/2 == -1
|
af6d3a9fc60cd03d6f14fd2f76351a011ed04699945b0f159aa48c17187c154f | import os
import tempfile
from sympy.core.symbol import (Symbol, symbols)
from sympy.codegen.ast import (
Assignment, Print, Declaration, FunctionDefinition, Return, real,
FunctionCall, Variable, Element, integer
)
from sympy.codegen.fnodes import (
allocatable, ArrayConstructor, isign, dsign, cmplx, kind, literal_dp,
Program, Module, use, Subroutine, dimension, assumed_extent, ImpliedDoLoop,
intent_out, size, Do, SubroutineCall, sum_, array, bind_C
)
from sympy.codegen.futils import render_as_module
from sympy.core.expr import unchanged
from sympy.external import import_module
from sympy.printing.codeprinter import fcode
from sympy.utilities._compilation import has_fortran, compile_run_strings, compile_link_import_strings
from sympy.utilities._compilation.util import may_xfail
from sympy.testing.pytest import skip, XFAIL
cython = import_module('cython')
np = import_module('numpy')
def test_size():
x = Symbol('x', real=True)
sx = size(x)
assert fcode(sx, source_format='free') == 'size(x)'
@may_xfail
def test_size_assumed_shape():
if not has_fortran():
skip("No fortran compiler found.")
a = Symbol('a', real=True)
body = [Return((sum_(a**2)/size(a))**.5)]
arr = array(a, dim=[':'], intent='in')
fd = FunctionDefinition(real, 'rms', [arr], body)
render_as_module([fd], 'mod_rms')
(stdout, stderr), info = compile_run_strings([
('rms.f90', render_as_module([fd], 'mod_rms')),
('main.f90', (
'program myprog\n'
'use mod_rms, only: rms\n'
'real*8, dimension(4), parameter :: x = [4, 2, 2, 2]\n'
'print *, dsqrt(7d0) - rms(x)\n'
'end program\n'
))
], clean=True)
assert '0.00000' in stdout
assert stderr == ''
assert info['exit_status'] == os.EX_OK
@XFAIL # https://github.com/sympy/sympy/issues/20265
@may_xfail
def test_ImpliedDoLoop():
if not has_fortran():
skip("No fortran compiler found.")
a, i = symbols('a i', integer=True)
idl = ImpliedDoLoop(i**3, i, -3, 3, 2)
ac = ArrayConstructor([-28, idl, 28])
a = array(a, dim=[':'], attrs=[allocatable])
prog = Program('idlprog', [
a.as_Declaration(),
Assignment(a, ac),
Print([a])
])
fsrc = fcode(prog, standard=2003, source_format='free')
(stdout, stderr), info = compile_run_strings([('main.f90', fsrc)], clean=True)
for numstr in '-28 -27 -1 1 27 28'.split():
assert numstr in stdout
assert stderr == ''
assert info['exit_status'] == os.EX_OK
@may_xfail
def test_Program():
x = Symbol('x', real=True)
vx = Variable.deduced(x, 42)
decl = Declaration(vx)
prnt = Print([x, x+1])
prog = Program('foo', [decl, prnt])
if not has_fortran():
skip("No fortran compiler found.")
(stdout, stderr), info = compile_run_strings([('main.f90', fcode(prog, standard=90))], clean=True)
assert '42' in stdout
assert '43' in stdout
assert stderr == ''
assert info['exit_status'] == os.EX_OK
@may_xfail
def test_Module():
x = Symbol('x', real=True)
v_x = Variable.deduced(x)
sq = FunctionDefinition(real, 'sqr', [v_x], [Return(x**2)])
mod_sq = Module('mod_sq', [], [sq])
sq_call = FunctionCall('sqr', [42.])
prg_sq = Program('foobar', [
use('mod_sq', only=['sqr']),
Print(['"Square of 42 = "', sq_call])
])
if not has_fortran():
skip("No fortran compiler found.")
(stdout, stderr), info = compile_run_strings([
('mod_sq.f90', fcode(mod_sq, standard=90)),
('main.f90', fcode(prg_sq, standard=90))
], clean=True)
assert '42' in stdout
assert str(42**2) in stdout
assert stderr == ''
@XFAIL # https://github.com/sympy/sympy/issues/20265
@may_xfail
def test_Subroutine():
# Code to generate the subroutine in the example from
# http://www.fortran90.org/src/best-practices.html#arrays
r = Symbol('r', real=True)
i = Symbol('i', integer=True)
v_r = Variable.deduced(r, attrs=(dimension(assumed_extent), intent_out))
v_i = Variable.deduced(i)
v_n = Variable('n', integer)
do_loop = Do([
Assignment(Element(r, [i]), literal_dp(1)/i**2)
], i, 1, v_n)
sub = Subroutine("f", [v_r], [
Declaration(v_n),
Declaration(v_i),
Assignment(v_n, size(r)),
do_loop
])
x = Symbol('x', real=True)
v_x3 = Variable.deduced(x, attrs=[dimension(3)])
mod = Module('mymod', definitions=[sub])
prog = Program('foo', [
use(mod, only=[sub]),
Declaration(v_x3),
SubroutineCall(sub, [v_x3]),
Print([sum_(v_x3), v_x3])
])
if not has_fortran():
skip("No fortran compiler found.")
(stdout, stderr), info = compile_run_strings([
('a.f90', fcode(mod, standard=90)),
('b.f90', fcode(prog, standard=90))
], clean=True)
ref = [1.0/i**2 for i in range(1, 4)]
assert str(sum(ref))[:-3] in stdout
for _ in ref:
assert str(_)[:-3] in stdout
assert stderr == ''
def test_isign():
x = Symbol('x', integer=True)
assert unchanged(isign, 1, x)
assert fcode(isign(1, x), standard=95, source_format='free') == 'isign(1, x)'
def test_dsign():
x = Symbol('x')
assert unchanged(dsign, 1, x)
assert fcode(dsign(literal_dp(1), x), standard=95, source_format='free') == 'dsign(1d0, x)'
def test_cmplx():
x = Symbol('x')
assert unchanged(cmplx, 1, x)
def test_kind():
x = Symbol('x')
assert unchanged(kind, x)
def test_literal_dp():
assert fcode(literal_dp(0), source_format='free') == '0d0'
@may_xfail
def test_bind_C():
if not has_fortran():
skip("No fortran compiler found.")
if not cython:
skip("Cython not found.")
if not np:
skip("NumPy not found.")
a = Symbol('a', real=True)
s = Symbol('s', integer=True)
body = [Return((sum_(a**2)/s)**.5)]
arr = array(a, dim=[s], intent='in')
fd = FunctionDefinition(real, 'rms', [arr, s], body, attrs=[bind_C('rms')])
f_mod = render_as_module([fd], 'mod_rms')
with tempfile.TemporaryDirectory() as folder:
mod, info = compile_link_import_strings([
('rms.f90', f_mod),
('_rms.pyx', (
"#cython: language_level={}\n".format("3") +
"cdef extern double rms(double*, int*)\n"
"def py_rms(double[::1] x):\n"
" cdef int s = x.size\n"
" return rms(&x[0], &s)\n"))
], build_dir=folder)
assert abs(mod.py_rms(np.array([2., 4., 2., 2.])) - 7**0.5) < 1e-14
|
a9fc0f8530396266917d7078a50bfb93e016fa17458071baef90ba5c958573fd | from itertools import product
from sympy.core.symbol import symbols
from sympy.functions.elementary.trigonometric import cos
from sympy.core.numbers import pi
from sympy.codegen.scipy_nodes import cosm1
x, y, z = symbols('x y z')
def test_cosm1():
cm1_xy = cosm1(x*y)
ref_xy = cos(x*y) - 1
for wrt, deriv_order in product([x, y, z], range(0, 3)):
assert (
cm1_xy.diff(wrt, deriv_order) -
ref_xy.diff(wrt, deriv_order)
).rewrite(cos).simplify() == 0
expr_minus2 = cosm1(pi)
assert expr_minus2.rewrite(cos) == -2
assert cosm1(3.14).simplify() == cosm1(3.14) # cannot simplify with 3.14
|
499a4e5336a16ff6c939c783d032dd99e8b0fa3377ece3e67f94d1a757724603 | import math
from sympy.core.symbol import symbols
from sympy.functions.elementary.exponential import exp
from sympy.codegen.rewriting import optimize
from sympy.codegen.approximations import SumApprox, SeriesApprox
def test_SumApprox_trivial():
x = symbols('x')
expr1 = 1 + x
sum_approx = SumApprox(bounds={x: (-1e-20, 1e-20)}, reltol=1e-16)
apx1 = optimize(expr1, [sum_approx])
assert apx1 - 1 == 0
def test_SumApprox_monotone_terms():
x, y, z = symbols('x y z')
expr1 = exp(z)*(x**2 + y**2 + 1)
bnds1 = {x: (0, 1e-3), y: (100, 1000)}
sum_approx_m2 = SumApprox(bounds=bnds1, reltol=1e-2)
sum_approx_m5 = SumApprox(bounds=bnds1, reltol=1e-5)
sum_approx_m11 = SumApprox(bounds=bnds1, reltol=1e-11)
assert (optimize(expr1, [sum_approx_m2])/exp(z) - (y**2)).simplify() == 0
assert (optimize(expr1, [sum_approx_m5])/exp(z) - (y**2 + 1)).simplify() == 0
assert (optimize(expr1, [sum_approx_m11])/exp(z) - (y**2 + 1 + x**2)).simplify() == 0
def test_SeriesApprox_trivial():
x, z = symbols('x z')
for factor in [1, exp(z)]:
x = symbols('x')
expr1 = exp(x)*factor
bnds1 = {x: (-1, 1)}
series_approx_50 = SeriesApprox(bounds=bnds1, reltol=0.50)
series_approx_10 = SeriesApprox(bounds=bnds1, reltol=0.10)
series_approx_05 = SeriesApprox(bounds=bnds1, reltol=0.05)
c = (bnds1[x][1] + bnds1[x][0])/2 # 0.0
f0 = math.exp(c) # 1.0
ref_50 = f0 + x + x**2/2
ref_10 = f0 + x + x**2/2 + x**3/6
ref_05 = f0 + x + x**2/2 + x**3/6 + x**4/24
res_50 = optimize(expr1, [series_approx_50])
res_10 = optimize(expr1, [series_approx_10])
res_05 = optimize(expr1, [series_approx_05])
assert (res_50/factor - ref_50).simplify() == 0
assert (res_10/factor - ref_10).simplify() == 0
assert (res_05/factor - ref_05).simplify() == 0
max_ord3 = SeriesApprox(bounds=bnds1, reltol=0.05, max_order=3)
assert optimize(expr1, [max_ord3]) == expr1
|
8dc6e1c964d1c0c3f84661d373ecab9f9c355bd69da585e400fc5182a03589e4 | import math
from sympy.core.containers import Tuple
from sympy.core.numbers import nan, oo, Float, Integer
from sympy.core.relational import Lt
from sympy.core.symbol import symbols, Symbol
from sympy.functions.elementary.trigonometric import sin
from sympy.matrices.dense import Matrix
from sympy.matrices.expressions.matexpr import MatrixSymbol
from sympy.sets.fancysets import Range
from sympy.tensor.indexed import Idx, IndexedBase
from sympy.testing.pytest import raises
from sympy.codegen.ast import (
Assignment, Attribute, aug_assign, CodeBlock, For, Type, Variable, Pointer, Declaration,
AddAugmentedAssignment, SubAugmentedAssignment, MulAugmentedAssignment,
DivAugmentedAssignment, ModAugmentedAssignment, value_const, pointer_const,
integer, real, complex_, int8, uint8, float16 as f16, float32 as f32,
float64 as f64, float80 as f80, float128 as f128, complex64 as c64, complex128 as c128,
While, Scope, String, Print, QuotedString, FunctionPrototype, FunctionDefinition, Return,
FunctionCall, untyped, IntBaseType, intc, Node, none, NoneToken, Token, Comment
)
x, y, z, t, x0, x1, x2, a, b = symbols("x, y, z, t, x0, x1, x2, a, b")
n = symbols("n", integer=True)
A = MatrixSymbol('A', 3, 1)
mat = Matrix([1, 2, 3])
B = IndexedBase('B')
i = Idx("i", n)
A22 = MatrixSymbol('A22',2,2)
B22 = MatrixSymbol('B22',2,2)
def test_Assignment():
# Here we just do things to show they don't error
Assignment(x, y)
Assignment(x, 0)
Assignment(A, mat)
Assignment(A[1,0], 0)
Assignment(A[1,0], x)
Assignment(B[i], x)
Assignment(B[i], 0)
a = Assignment(x, y)
assert a.func(*a.args) == a
assert a.op == ':='
# Here we test things to show that they error
# Matrix to scalar
raises(ValueError, lambda: Assignment(B[i], A))
raises(ValueError, lambda: Assignment(B[i], mat))
raises(ValueError, lambda: Assignment(x, mat))
raises(ValueError, lambda: Assignment(x, A))
raises(ValueError, lambda: Assignment(A[1,0], mat))
# Scalar to matrix
raises(ValueError, lambda: Assignment(A, x))
raises(ValueError, lambda: Assignment(A, 0))
# Non-atomic lhs
raises(TypeError, lambda: Assignment(mat, A))
raises(TypeError, lambda: Assignment(0, x))
raises(TypeError, lambda: Assignment(x*x, 1))
raises(TypeError, lambda: Assignment(A + A, mat))
raises(TypeError, lambda: Assignment(B, 0))
def test_AugAssign():
# Here we just do things to show they don't error
aug_assign(x, '+', y)
aug_assign(x, '+', 0)
aug_assign(A, '+', mat)
aug_assign(A[1, 0], '+', 0)
aug_assign(A[1, 0], '+', x)
aug_assign(B[i], '+', x)
aug_assign(B[i], '+', 0)
# Check creation via aug_assign vs constructor
for binop, cls in [
('+', AddAugmentedAssignment),
('-', SubAugmentedAssignment),
('*', MulAugmentedAssignment),
('/', DivAugmentedAssignment),
('%', ModAugmentedAssignment),
]:
a = aug_assign(x, binop, y)
b = cls(x, y)
assert a.func(*a.args) == a == b
assert a.binop == binop
assert a.op == binop + '='
# Here we test things to show that they error
# Matrix to scalar
raises(ValueError, lambda: aug_assign(B[i], '+', A))
raises(ValueError, lambda: aug_assign(B[i], '+', mat))
raises(ValueError, lambda: aug_assign(x, '+', mat))
raises(ValueError, lambda: aug_assign(x, '+', A))
raises(ValueError, lambda: aug_assign(A[1, 0], '+', mat))
# Scalar to matrix
raises(ValueError, lambda: aug_assign(A, '+', x))
raises(ValueError, lambda: aug_assign(A, '+', 0))
# Non-atomic lhs
raises(TypeError, lambda: aug_assign(mat, '+', A))
raises(TypeError, lambda: aug_assign(0, '+', x))
raises(TypeError, lambda: aug_assign(x * x, '+', 1))
raises(TypeError, lambda: aug_assign(A + A, '+', mat))
raises(TypeError, lambda: aug_assign(B, '+', 0))
def test_Assignment_printing():
assignment_classes = [
Assignment,
AddAugmentedAssignment,
SubAugmentedAssignment,
MulAugmentedAssignment,
DivAugmentedAssignment,
ModAugmentedAssignment,
]
pairs = [
(x, 2 * y + 2),
(B[i], x),
(A22, B22),
(A[0, 0], x),
]
for cls in assignment_classes:
for lhs, rhs in pairs:
a = cls(lhs, rhs)
assert repr(a) == '%s(%s, %s)' % (cls.__name__, repr(lhs), repr(rhs))
def test_CodeBlock():
c = CodeBlock(Assignment(x, 1), Assignment(y, x + 1))
assert c.func(*c.args) == c
assert c.left_hand_sides == Tuple(x, y)
assert c.right_hand_sides == Tuple(1, x + 1)
def test_CodeBlock_topological_sort():
assignments = [
Assignment(x, y + z),
Assignment(z, 1),
Assignment(t, x),
Assignment(y, 2),
]
ordered_assignments = [
# Note that the unrelated z=1 and y=2 are kept in that order
Assignment(z, 1),
Assignment(y, 2),
Assignment(x, y + z),
Assignment(t, x),
]
c1 = CodeBlock.topological_sort(assignments)
assert c1 == CodeBlock(*ordered_assignments)
# Cycle
invalid_assignments = [
Assignment(x, y + z),
Assignment(z, 1),
Assignment(y, x),
Assignment(y, 2),
]
raises(ValueError, lambda: CodeBlock.topological_sort(invalid_assignments))
# Free symbols
free_assignments = [
Assignment(x, y + z),
Assignment(z, a * b),
Assignment(t, x),
Assignment(y, b + 3),
]
free_assignments_ordered = [
Assignment(z, a * b),
Assignment(y, b + 3),
Assignment(x, y + z),
Assignment(t, x),
]
c2 = CodeBlock.topological_sort(free_assignments)
assert c2 == CodeBlock(*free_assignments_ordered)
def test_CodeBlock_free_symbols():
c1 = CodeBlock(
Assignment(x, y + z),
Assignment(z, 1),
Assignment(t, x),
Assignment(y, 2),
)
assert c1.free_symbols == set()
c2 = CodeBlock(
Assignment(x, y + z),
Assignment(z, a * b),
Assignment(t, x),
Assignment(y, b + 3),
)
assert c2.free_symbols == {a, b}
def test_CodeBlock_cse():
c1 = CodeBlock(
Assignment(y, 1),
Assignment(x, sin(y)),
Assignment(z, sin(y)),
Assignment(t, x*z),
)
assert c1.cse() == CodeBlock(
Assignment(y, 1),
Assignment(x0, sin(y)),
Assignment(x, x0),
Assignment(z, x0),
Assignment(t, x*z),
)
# Multiple assignments to same symbol not supported
raises(NotImplementedError, lambda: CodeBlock(
Assignment(x, 1),
Assignment(y, 1), Assignment(y, 2)
).cse())
# Check auto-generated symbols do not collide with existing ones
c2 = CodeBlock(
Assignment(x0, sin(y) + 1),
Assignment(x1, 2 * sin(y)),
Assignment(z, x * y),
)
assert c2.cse() == CodeBlock(
Assignment(x2, sin(y)),
Assignment(x0, x2 + 1),
Assignment(x1, 2 * x2),
Assignment(z, x * y),
)
def test_CodeBlock_cse__issue_14118():
# see https://github.com/sympy/sympy/issues/14118
c = CodeBlock(
Assignment(A22, Matrix([[x, sin(y)],[3, 4]])),
Assignment(B22, Matrix([[sin(y), 2*sin(y)], [sin(y)**2, 7]]))
)
assert c.cse() == CodeBlock(
Assignment(x0, sin(y)),
Assignment(A22, Matrix([[x, x0],[3, 4]])),
Assignment(B22, Matrix([[x0, 2*x0], [x0**2, 7]]))
)
def test_For():
f = For(n, Range(0, 3), (Assignment(A[n, 0], x + n), aug_assign(x, '+', y)))
f = For(n, (1, 2, 3, 4, 5), (Assignment(A[n, 0], x + n),))
assert f.func(*f.args) == f
raises(TypeError, lambda: For(n, x, (x + y,)))
def test_none():
assert none.is_Atom
assert none == none
class Foo(Token):
pass
foo = Foo()
assert foo != none
assert none == None
assert none == NoneToken()
assert none.func(*none.args) == none
def test_String():
st = String('foobar')
assert st.is_Atom
assert st == String('foobar')
assert st.text == 'foobar'
assert st.func(**st.kwargs()) == st
class Signifier(String):
pass
si = Signifier('foobar')
assert si != st
assert si.text == st.text
s = String('foo')
assert str(s) == 'foo'
assert repr(s) == "String('foo')"
def test_Comment():
c = Comment('foobar')
assert c.text == 'foobar'
assert str(c) == 'foobar'
def test_Node():
n = Node()
assert n == Node()
assert n.func(*n.args) == n
def test_Type():
t = Type('MyType')
assert len(t.args) == 1
assert t.name == String('MyType')
assert str(t) == 'MyType'
assert repr(t) == "Type(String('MyType'))"
assert Type(t) == t
assert t.func(*t.args) == t
t1 = Type('t1')
t2 = Type('t2')
assert t1 != t2
assert t1 == t1 and t2 == t2
t1b = Type('t1')
assert t1 == t1b
assert t2 != t1b
def test_Type__from_expr():
assert Type.from_expr(i) == integer
u = symbols('u', real=True)
assert Type.from_expr(u) == real
assert Type.from_expr(n) == integer
assert Type.from_expr(3) == integer
assert Type.from_expr(3.0) == real
assert Type.from_expr(3+1j) == complex_
raises(ValueError, lambda: Type.from_expr(sum))
def test_Type__cast_check__integers():
# Rounding
raises(ValueError, lambda: integer.cast_check(3.5))
assert integer.cast_check('3') == 3
assert integer.cast_check(Float('3.0000000000000000000')) == 3
assert integer.cast_check(Float('3.0000000000000000001')) == 3 # unintuitive maybe?
# Range
assert int8.cast_check(127.0) == 127
raises(ValueError, lambda: int8.cast_check(128))
assert int8.cast_check(-128) == -128
raises(ValueError, lambda: int8.cast_check(-129))
assert uint8.cast_check(0) == 0
assert uint8.cast_check(128) == 128
raises(ValueError, lambda: uint8.cast_check(256.0))
raises(ValueError, lambda: uint8.cast_check(-1))
def test_Attribute():
noexcept = Attribute('noexcept')
assert noexcept == Attribute('noexcept')
alignas16 = Attribute('alignas', [16])
alignas32 = Attribute('alignas', [32])
assert alignas16 != alignas32
assert alignas16.func(*alignas16.args) == alignas16
def test_Variable():
v = Variable(x, type=real)
assert v == Variable(v)
assert v == Variable('x', type=real)
assert v.symbol == x
assert v.type == real
assert value_const not in v.attrs
assert v.func(*v.args) == v
assert str(v) == 'Variable(x, type=real)'
w = Variable(y, f32, attrs={value_const})
assert w.symbol == y
assert w.type == f32
assert value_const in w.attrs
assert w.func(*w.args) == w
v_n = Variable(n, type=Type.from_expr(n))
assert v_n.type == integer
assert v_n.func(*v_n.args) == v_n
v_i = Variable(i, type=Type.from_expr(n))
assert v_i.type == integer
assert v_i != v_n
a_i = Variable.deduced(i)
assert a_i.type == integer
assert Variable.deduced(Symbol('x', real=True)).type == real
assert a_i.func(*a_i.args) == a_i
v_n2 = Variable.deduced(n, value=3.5, cast_check=False)
assert v_n2.func(*v_n2.args) == v_n2
assert abs(v_n2.value - 3.5) < 1e-15
raises(ValueError, lambda: Variable.deduced(n, value=3.5, cast_check=True))
v_n3 = Variable.deduced(n)
assert v_n3.type == integer
assert str(v_n3) == 'Variable(n, type=integer)'
assert Variable.deduced(z, value=3).type == integer
assert Variable.deduced(z, value=3.0).type == real
assert Variable.deduced(z, value=3.0+1j).type == complex_
def test_Pointer():
p = Pointer(x)
assert p.symbol == x
assert p.type == untyped
assert value_const not in p.attrs
assert pointer_const not in p.attrs
assert p.func(*p.args) == p
u = symbols('u', real=True)
pu = Pointer(u, type=Type.from_expr(u), attrs={value_const, pointer_const})
assert pu.symbol is u
assert pu.type == real
assert value_const in pu.attrs
assert pointer_const in pu.attrs
assert pu.func(*pu.args) == pu
i = symbols('i', integer=True)
deref = pu[i]
assert deref.indices == (i,)
def test_Declaration():
u = symbols('u', real=True)
vu = Variable(u, type=Type.from_expr(u))
assert Declaration(vu).variable.type == real
vn = Variable(n, type=Type.from_expr(n))
assert Declaration(vn).variable.type == integer
# PR 19107, does not allow comparison between expressions and Basic
# lt = StrictLessThan(vu, vn)
# assert isinstance(lt, StrictLessThan)
vuc = Variable(u, Type.from_expr(u), value=3.0, attrs={value_const})
assert value_const in vuc.attrs
assert pointer_const not in vuc.attrs
decl = Declaration(vuc)
assert decl.variable == vuc
assert isinstance(decl.variable.value, Float)
assert decl.variable.value == 3.0
assert decl.func(*decl.args) == decl
assert vuc.as_Declaration() == decl
assert vuc.as_Declaration(value=None, attrs=None) == Declaration(vu)
vy = Variable(y, type=integer, value=3)
decl2 = Declaration(vy)
assert decl2.variable == vy
assert decl2.variable.value == Integer(3)
vi = Variable(i, type=Type.from_expr(i), value=3.0)
decl3 = Declaration(vi)
assert decl3.variable.type == integer
assert decl3.variable.value == 3.0
raises(ValueError, lambda: Declaration(vi, 42))
def test_IntBaseType():
assert intc.name == String('intc')
assert intc.args == (intc.name,)
assert str(IntBaseType('a').name) == 'a'
def test_FloatType():
assert f16.dig == 3
assert f32.dig == 6
assert f64.dig == 15
assert f80.dig == 18
assert f128.dig == 33
assert f16.decimal_dig == 5
assert f32.decimal_dig == 9
assert f64.decimal_dig == 17
assert f80.decimal_dig == 21
assert f128.decimal_dig == 36
assert f16.max_exponent == 16
assert f32.max_exponent == 128
assert f64.max_exponent == 1024
assert f80.max_exponent == 16384
assert f128.max_exponent == 16384
assert f16.min_exponent == -13
assert f32.min_exponent == -125
assert f64.min_exponent == -1021
assert f80.min_exponent == -16381
assert f128.min_exponent == -16381
assert abs(f16.eps / Float('0.00097656', precision=16) - 1) < 0.1*10**-f16.dig
assert abs(f32.eps / Float('1.1920929e-07', precision=32) - 1) < 0.1*10**-f32.dig
assert abs(f64.eps / Float('2.2204460492503131e-16', precision=64) - 1) < 0.1*10**-f64.dig
assert abs(f80.eps / Float('1.08420217248550443401e-19', precision=80) - 1) < 0.1*10**-f80.dig
assert abs(f128.eps / Float(' 1.92592994438723585305597794258492732e-34', precision=128) - 1) < 0.1*10**-f128.dig
assert abs(f16.max / Float('65504', precision=16) - 1) < .1*10**-f16.dig
assert abs(f32.max / Float('3.40282347e+38', precision=32) - 1) < 0.1*10**-f32.dig
assert abs(f64.max / Float('1.79769313486231571e+308', precision=64) - 1) < 0.1*10**-f64.dig # cf. np.finfo(np.float64).max
assert abs(f80.max / Float('1.18973149535723176502e+4932', precision=80) - 1) < 0.1*10**-f80.dig
assert abs(f128.max / Float('1.18973149535723176508575932662800702e+4932', precision=128) - 1) < 0.1*10**-f128.dig
# cf. np.finfo(np.float32).tiny
assert abs(f16.tiny / Float('6.1035e-05', precision=16) - 1) < 0.1*10**-f16.dig
assert abs(f32.tiny / Float('1.17549435e-38', precision=32) - 1) < 0.1*10**-f32.dig
assert abs(f64.tiny / Float('2.22507385850720138e-308', precision=64) - 1) < 0.1*10**-f64.dig
assert abs(f80.tiny / Float('3.36210314311209350626e-4932', precision=80) - 1) < 0.1*10**-f80.dig
assert abs(f128.tiny / Float('3.3621031431120935062626778173217526e-4932', precision=128) - 1) < 0.1*10**-f128.dig
assert f64.cast_check(0.5) == 0.5
assert abs(f64.cast_check(3.7) - 3.7) < 3e-17
assert isinstance(f64.cast_check(3), (Float, float))
assert f64.cast_nocheck(oo) == float('inf')
assert f64.cast_nocheck(-oo) == float('-inf')
assert f64.cast_nocheck(float(oo)) == float('inf')
assert f64.cast_nocheck(float(-oo)) == float('-inf')
assert math.isnan(f64.cast_nocheck(nan))
assert f32 != f64
assert f64 == f64.func(*f64.args)
def test_Type__cast_check__floating_point():
raises(ValueError, lambda: f32.cast_check(123.45678949))
raises(ValueError, lambda: f32.cast_check(12.345678949))
raises(ValueError, lambda: f32.cast_check(1.2345678949))
raises(ValueError, lambda: f32.cast_check(.12345678949))
assert abs(123.456789049 - f32.cast_check(123.456789049) - 4.9e-8) < 1e-8
assert abs(0.12345678904 - f32.cast_check(0.12345678904) - 4e-11) < 1e-11
dcm21 = Float('0.123456789012345670499') # 21 decimals
assert abs(dcm21 - f64.cast_check(dcm21) - 4.99e-19) < 1e-19
f80.cast_check(Float('0.12345678901234567890103', precision=88))
raises(ValueError, lambda: f80.cast_check(Float('0.12345678901234567890149', precision=88)))
v10 = 12345.67894
raises(ValueError, lambda: f32.cast_check(v10))
assert abs(Float(str(v10), precision=64+8) - f64.cast_check(v10)) < v10*1e-16
assert abs(f32.cast_check(2147483647) - 2147483650) < 1
def test_Type__cast_check__complex_floating_point():
val9_11 = 123.456789049 + 0.123456789049j
raises(ValueError, lambda: c64.cast_check(.12345678949 + .12345678949j))
assert abs(val9_11 - c64.cast_check(val9_11) - 4.9e-8) < 1e-8
dcm21 = Float('0.123456789012345670499') + 1e-20j # 21 decimals
assert abs(dcm21 - c128.cast_check(dcm21) - 4.99e-19) < 1e-19
v19 = Float('0.1234567890123456749') + 1j*Float('0.1234567890123456749')
raises(ValueError, lambda: c128.cast_check(v19))
def test_While():
xpp = AddAugmentedAssignment(x, 1)
whl1 = While(x < 2, [xpp])
assert whl1.condition.args[0] == x
assert whl1.condition.args[1] == 2
assert whl1.condition == Lt(x, 2, evaluate=False)
assert whl1.body.args == (xpp,)
assert whl1.func(*whl1.args) == whl1
cblk = CodeBlock(AddAugmentedAssignment(x, 1))
whl2 = While(x < 2, cblk)
assert whl1 == whl2
assert whl1 != While(x < 3, [xpp])
def test_Scope():
assign = Assignment(x, y)
incr = AddAugmentedAssignment(x, 1)
scp = Scope([assign, incr])
cblk = CodeBlock(assign, incr)
assert scp.body == cblk
assert scp == Scope(cblk)
assert scp != Scope([incr, assign])
assert scp.func(*scp.args) == scp
def test_Print():
fmt = "%d %.3f"
ps = Print([n, x], fmt)
assert str(ps.format_string) == fmt
assert ps.print_args == Tuple(n, x)
assert ps.args == (Tuple(n, x), QuotedString(fmt), none)
assert ps == Print((n, x), fmt)
assert ps != Print([x, n], fmt)
assert ps.func(*ps.args) == ps
ps2 = Print([n, x])
assert ps2 == Print([n, x])
assert ps2 != ps
assert ps2.format_string == None
def test_FunctionPrototype_and_FunctionDefinition():
vx = Variable(x, type=real)
vn = Variable(n, type=integer)
fp1 = FunctionPrototype(real, 'power', [vx, vn])
assert fp1.return_type == real
assert fp1.name == String('power')
assert fp1.parameters == Tuple(vx, vn)
assert fp1 == FunctionPrototype(real, 'power', [vx, vn])
assert fp1 != FunctionPrototype(real, 'power', [vn, vx])
assert fp1.func(*fp1.args) == fp1
body = [Assignment(x, x**n), Return(x)]
fd1 = FunctionDefinition(real, 'power', [vx, vn], body)
assert fd1.return_type == real
assert str(fd1.name) == 'power'
assert fd1.parameters == Tuple(vx, vn)
assert fd1.body == CodeBlock(*body)
assert fd1 == FunctionDefinition(real, 'power', [vx, vn], body)
assert fd1 != FunctionDefinition(real, 'power', [vx, vn], body[::-1])
assert fd1.func(*fd1.args) == fd1
fp2 = FunctionPrototype.from_FunctionDefinition(fd1)
assert fp2 == fp1
fd2 = FunctionDefinition.from_FunctionPrototype(fp1, body)
assert fd2 == fd1
def test_Return():
rs = Return(x)
assert rs.args == (x,)
assert rs == Return(x)
assert rs != Return(y)
assert rs.func(*rs.args) == rs
def test_FunctionCall():
fc = FunctionCall('power', (x, 3))
assert fc.function_args[0] == x
assert fc.function_args[1] == 3
assert len(fc.function_args) == 2
assert isinstance(fc.function_args[1], Integer)
assert fc == FunctionCall('power', (x, 3))
assert fc != FunctionCall('power', (3, x))
assert fc != FunctionCall('Power', (x, 3))
assert fc.func(*fc.args) == fc
fc2 = FunctionCall('fma', [2, 3, 4])
assert len(fc2.function_args) == 3
assert fc2.function_args[0] == 2
assert fc2.function_args[1] == 3
assert fc2.function_args[2] == 4
assert str(fc2) in ( # not sure if QuotedString is a better default...
'FunctionCall(fma, function_args=(2, 3, 4))',
'FunctionCall("fma", function_args=(2, 3, 4))',
)
def test_ast_replace():
x = Variable('x', real)
y = Variable('y', real)
n = Variable('n', integer)
pwer = FunctionDefinition(real, 'pwer', [x, n], [pow(x.symbol, n.symbol)])
pname = pwer.name
pcall = FunctionCall('pwer', [y, 3])
tree1 = CodeBlock(pwer, pcall)
assert str(tree1.args[0].name) == 'pwer'
assert str(tree1.args[1].name) == 'pwer'
for a, b in zip(tree1, [pwer, pcall]):
assert a == b
tree2 = tree1.replace(pname, String('power'))
assert str(tree1.args[0].name) == 'pwer'
assert str(tree1.args[1].name) == 'pwer'
assert str(tree2.args[0].name) == 'power'
assert str(tree2.args[1].name) == 'power'
|
bdec849ea7957ed22c80a9531bfc4c98259c58f2c379257f3a90047a485fbe94 | import tempfile
from sympy.core.numbers import pi
from sympy.core.power import Pow
from sympy.core.singleton import S
from sympy.core.symbol import Symbol
from sympy.functions.elementary.complexes import Abs
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.trigonometric import (cos, sin, sinc)
from sympy.matrices.expressions.matexpr import MatrixSymbol
from sympy.assumptions import assuming, Q
from sympy.external import import_module
from sympy.printing.codeprinter import ccode
from sympy.codegen.matrix_nodes import MatrixSolve
from sympy.codegen.cfunctions import log2, exp2, expm1, log1p
from sympy.codegen.numpy_nodes import logaddexp, logaddexp2
from sympy.codegen.scipy_nodes import cosm1
from sympy.codegen.rewriting import (
optimize, cosm1_opt, log2_opt, exp2_opt, expm1_opt, log1p_opt, optims_c99,
create_expand_pow_optimization, matinv_opt, logaddexp_opt, logaddexp2_opt,
optims_numpy, sinc_opts, FuncMinusOneOptim
)
from sympy.testing.pytest import XFAIL, skip
from sympy.utilities._compilation import compile_link_import_strings, has_c
from sympy.utilities._compilation.util import may_xfail
cython = import_module('cython')
def test_log2_opt():
x = Symbol('x')
expr1 = 7*log(3*x + 5)/(log(2))
opt1 = optimize(expr1, [log2_opt])
assert opt1 == 7*log2(3*x + 5)
assert opt1.rewrite(log) == expr1
expr2 = 3*log(5*x + 7)/(13*log(2))
opt2 = optimize(expr2, [log2_opt])
assert opt2 == 3*log2(5*x + 7)/13
assert opt2.rewrite(log) == expr2
expr3 = log(x)/log(2)
opt3 = optimize(expr3, [log2_opt])
assert opt3 == log2(x)
assert opt3.rewrite(log) == expr3
expr4 = log(x)/log(2) + log(x+1)
opt4 = optimize(expr4, [log2_opt])
assert opt4 == log2(x) + log(2)*log2(x+1)
assert opt4.rewrite(log) == expr4
expr5 = log(17)
opt5 = optimize(expr5, [log2_opt])
assert opt5 == expr5
expr6 = log(x + 3)/log(2)
opt6 = optimize(expr6, [log2_opt])
assert str(opt6) == 'log2(x + 3)'
assert opt6.rewrite(log) == expr6
def test_exp2_opt():
x = Symbol('x')
expr1 = 1 + 2**x
opt1 = optimize(expr1, [exp2_opt])
assert opt1 == 1 + exp2(x)
assert opt1.rewrite(Pow) == expr1
expr2 = 1 + 3**x
assert expr2 == optimize(expr2, [exp2_opt])
def test_expm1_opt():
x = Symbol('x')
expr1 = exp(x) - 1
opt1 = optimize(expr1, [expm1_opt])
assert expm1(x) - opt1 == 0
assert opt1.rewrite(exp) == expr1
expr2 = 3*exp(x) - 3
opt2 = optimize(expr2, [expm1_opt])
assert 3*expm1(x) == opt2
assert opt2.rewrite(exp) == expr2
expr3 = 3*exp(x) - 5
opt3 = optimize(expr3, [expm1_opt])
assert 3*expm1(x) - 2 == opt3
assert opt3.rewrite(exp) == expr3
expm1_opt_non_opportunistic = FuncMinusOneOptim(exp, expm1, opportunistic=False)
assert expr3 == optimize(expr3, [expm1_opt_non_opportunistic])
assert opt1 == optimize(expr1, [expm1_opt_non_opportunistic])
assert opt2 == optimize(expr2, [expm1_opt_non_opportunistic])
expr4 = 3*exp(x) + log(x) - 3
opt4 = optimize(expr4, [expm1_opt])
assert 3*expm1(x) + log(x) == opt4
assert opt4.rewrite(exp) == expr4
expr5 = 3*exp(2*x) - 3
opt5 = optimize(expr5, [expm1_opt])
assert 3*expm1(2*x) == opt5
assert opt5.rewrite(exp) == expr5
expr6 = (2*exp(x) + 1)/(exp(x) + 1) + 1
opt6 = optimize(expr6, [expm1_opt])
assert opt6.count_ops() <= expr6.count_ops()
def ev(e):
return e.subs(x, 3).evalf()
assert abs(ev(expr6) - ev(opt6)) < 1e-15
y = Symbol('y')
expr7 = (2*exp(x) - 1)/(1 - exp(y)) - 1/(1-exp(y))
opt7 = optimize(expr7, [expm1_opt])
assert -2*expm1(x)/expm1(y) == opt7
assert (opt7.rewrite(exp) - expr7).factor() == 0
expr8 = (1+exp(x))**2 - 4
opt8 = optimize(expr8, [expm1_opt])
tgt8a = (exp(x) + 3)*expm1(x)
tgt8b = 2*expm1(x) + expm1(2*x)
# Both tgt8a & tgt8b seem to give full precision (~16 digits for double)
# for x=1e-7 (compare with expr8 which only achieves ~8 significant digits).
# If we can show that either tgt8a or tgt8b is preferable, we can
# change this test to ensure the preferable version is returned.
assert (tgt8a - tgt8b).rewrite(exp).factor() == 0
assert opt8 in (tgt8a, tgt8b)
assert (opt8.rewrite(exp) - expr8).factor() == 0
expr9 = sin(expr8)
opt9 = optimize(expr9, [expm1_opt])
tgt9a = sin(tgt8a)
tgt9b = sin(tgt8b)
assert opt9 in (tgt9a, tgt9b)
assert (opt9.rewrite(exp) - expr9.rewrite(exp)).factor().is_zero
def test_expm1_two_exp_terms():
x, y = map(Symbol, 'x y'.split())
expr1 = exp(x) + exp(y) - 2
opt1 = optimize(expr1, [expm1_opt])
assert opt1 == expm1(x) + expm1(y)
def test_cosm1_opt():
x = Symbol('x')
expr1 = cos(x) - 1
opt1 = optimize(expr1, [cosm1_opt])
assert cosm1(x) - opt1 == 0
assert opt1.rewrite(cos) == expr1
expr2 = 3*cos(x) - 3
opt2 = optimize(expr2, [cosm1_opt])
assert 3*cosm1(x) == opt2
assert opt2.rewrite(cos) == expr2
expr3 = 3*cos(x) - 5
opt3 = optimize(expr3, [cosm1_opt])
assert 3*cosm1(x) - 2 == opt3
assert opt3.rewrite(cos) == expr3
cosm1_opt_non_opportunistic = FuncMinusOneOptim(cos, cosm1, opportunistic=False)
assert expr3 == optimize(expr3, [cosm1_opt_non_opportunistic])
assert opt1 == optimize(expr1, [cosm1_opt_non_opportunistic])
assert opt2 == optimize(expr2, [cosm1_opt_non_opportunistic])
expr4 = 3*cos(x) + log(x) - 3
opt4 = optimize(expr4, [cosm1_opt])
assert 3*cosm1(x) + log(x) == opt4
assert opt4.rewrite(cos) == expr4
expr5 = 3*cos(2*x) - 3
opt5 = optimize(expr5, [cosm1_opt])
assert 3*cosm1(2*x) == opt5
assert opt5.rewrite(cos) == expr5
expr6 = 2 - 2*cos(x)
opt6 = optimize(expr6, [cosm1_opt])
assert -2*cosm1(x) == opt6
assert opt6.rewrite(cos) == expr6
def test_cosm1_two_cos_terms():
x, y = map(Symbol, 'x y'.split())
expr1 = cos(x) + cos(y) - 2
opt1 = optimize(expr1, [cosm1_opt])
assert opt1 == cosm1(x) + cosm1(y)
def test_expm1_cosm1_mixed():
x = Symbol('x')
expr1 = exp(x) + cos(x) - 2
opt1 = optimize(expr1, [expm1_opt, cosm1_opt])
assert opt1 == cosm1(x) + expm1(x)
def test_log1p_opt():
x = Symbol('x')
expr1 = log(x + 1)
opt1 = optimize(expr1, [log1p_opt])
assert log1p(x) - opt1 == 0
assert opt1.rewrite(log) == expr1
expr2 = log(3*x + 3)
opt2 = optimize(expr2, [log1p_opt])
assert log1p(x) + log(3) == opt2
assert (opt2.rewrite(log) - expr2).simplify() == 0
expr3 = log(2*x + 1)
opt3 = optimize(expr3, [log1p_opt])
assert log1p(2*x) - opt3 == 0
assert opt3.rewrite(log) == expr3
expr4 = log(x+3)
opt4 = optimize(expr4, [log1p_opt])
assert str(opt4) == 'log(x + 3)'
def test_optims_c99():
x = Symbol('x')
expr1 = 2**x + log(x)/log(2) + log(x + 1) + exp(x) - 1
opt1 = optimize(expr1, optims_c99).simplify()
assert opt1 == exp2(x) + log2(x) + log1p(x) + expm1(x)
assert opt1.rewrite(exp).rewrite(log).rewrite(Pow) == expr1
expr2 = log(x)/log(2) + log(x + 1)
opt2 = optimize(expr2, optims_c99)
assert opt2 == log2(x) + log1p(x)
assert opt2.rewrite(log) == expr2
expr3 = log(x)/log(2) + log(17*x + 17)
opt3 = optimize(expr3, optims_c99)
delta3 = opt3 - (log2(x) + log(17) + log1p(x))
assert delta3 == 0
assert (opt3.rewrite(log) - expr3).simplify() == 0
expr4 = 2**x + 3*log(5*x + 7)/(13*log(2)) + 11*exp(x) - 11 + log(17*x + 17)
opt4 = optimize(expr4, optims_c99).simplify()
delta4 = opt4 - (exp2(x) + 3*log2(5*x + 7)/13 + 11*expm1(x) + log(17) + log1p(x))
assert delta4 == 0
assert (opt4.rewrite(exp).rewrite(log).rewrite(Pow) - expr4).simplify() == 0
expr5 = 3*exp(2*x) - 3
opt5 = optimize(expr5, optims_c99)
delta5 = opt5 - 3*expm1(2*x)
assert delta5 == 0
assert opt5.rewrite(exp) == expr5
expr6 = exp(2*x) - 3
opt6 = optimize(expr6, optims_c99)
assert opt6 in (expm1(2*x) - 2, expr6) # expm1(2*x) - 2 is not better or worse
expr7 = log(3*x + 3)
opt7 = optimize(expr7, optims_c99)
delta7 = opt7 - (log(3) + log1p(x))
assert delta7 == 0
assert (opt7.rewrite(log) - expr7).simplify() == 0
expr8 = log(2*x + 3)
opt8 = optimize(expr8, optims_c99)
assert opt8 == expr8
def test_create_expand_pow_optimization():
cc = lambda x: ccode(
optimize(x, [create_expand_pow_optimization(4)]))
x = Symbol('x')
assert cc(x**4) == 'x*x*x*x'
assert cc(x**4 + x**2) == 'x*x + x*x*x*x'
assert cc(x**5 + x**4) == 'pow(x, 5) + x*x*x*x'
assert cc(sin(x)**4) == 'pow(sin(x), 4)'
# gh issue 15335
assert cc(x**(-4)) == '1.0/(x*x*x*x)'
assert cc(x**(-5)) == 'pow(x, -5)'
assert cc(-x**4) == '-(x*x*x*x)'
assert cc(x**4 - x**2) == '-(x*x) + x*x*x*x'
i = Symbol('i', integer=True)
assert cc(x**i - x**2) == 'pow(x, i) - (x*x)'
y = Symbol('y', real=True)
assert cc(Abs(exp(y**4))) == "exp(y*y*y*y)"
# gh issue 20753
cc2 = lambda x: ccode(optimize(x, [create_expand_pow_optimization(
4, base_req=lambda b: b.is_Function)]))
assert cc2(x**3 + sin(x)**3) == "pow(x, 3) + sin(x)*sin(x)*sin(x)"
def test_matsolve():
n = Symbol('n', integer=True)
A = MatrixSymbol('A', n, n)
x = MatrixSymbol('x', n, 1)
with assuming(Q.fullrank(A)):
assert optimize(A**(-1) * x, [matinv_opt]) == MatrixSolve(A, x)
assert optimize(A**(-1) * x + x, [matinv_opt]) == MatrixSolve(A, x) + x
def test_logaddexp_opt():
x, y = map(Symbol, 'x y'.split())
expr1 = log(exp(x) + exp(y))
opt1 = optimize(expr1, [logaddexp_opt])
assert logaddexp(x, y) - opt1 == 0
assert logaddexp(y, x) - opt1 == 0
assert opt1.rewrite(log) == expr1
def test_logaddexp2_opt():
x, y = map(Symbol, 'x y'.split())
expr1 = log(2**x + 2**y)/log(2)
opt1 = optimize(expr1, [logaddexp2_opt])
assert logaddexp2(x, y) - opt1 == 0
assert logaddexp2(y, x) - opt1 == 0
assert opt1.rewrite(log) == expr1
def test_sinc_opts():
def check(d):
for k, v in d.items():
assert optimize(k, sinc_opts) == v
x = Symbol('x')
check({
sin(x)/x : sinc(x),
sin(2*x)/(2*x) : sinc(2*x),
sin(3*x)/x : 3*sinc(3*x),
x*sin(x) : x*sin(x)
})
y = Symbol('y')
check({
sin(x*y)/(x*y) : sinc(x*y),
y*sin(x/y)/x : sinc(x/y),
sin(sin(x))/sin(x) : sinc(sin(x)),
sin(3*sin(x))/sin(x) : 3*sinc(3*sin(x)),
sin(x)/y : sin(x)/y
})
def test_optims_numpy():
def check(d):
for k, v in d.items():
assert optimize(k, optims_numpy) == v
x = Symbol('x')
check({
sin(2*x)/(2*x) + exp(2*x) - 1: sinc(2*x) + expm1(2*x),
log(x+3)/log(2) + log(x**2 + 1): log1p(x**2) + log2(x+3)
})
@XFAIL # room for improvement, ideally this test case should pass.
def test_optims_numpy_TODO():
def check(d):
for k, v in d.items():
assert optimize(k, optims_numpy) == v
x, y = map(Symbol, 'x y'.split())
check({
log(x*y)*sin(x*y)*log(x*y+1)/(log(2)*x*y): log2(x*y)*sinc(x*y)*log1p(x*y),
exp(x*sin(y)/y) - 1: expm1(x*sinc(y))
})
@may_xfail
def test_compiled_ccode_with_rewriting():
if not cython:
skip("cython not installed.")
if not has_c():
skip("No C compiler found.")
x = Symbol('x')
about_two = 2**(58/S(117))*3**(97/S(117))*5**(4/S(39))*7**(92/S(117))/S(30)*pi
# about_two: 1.999999999999581826
unchanged = 2*exp(x) - about_two
xval = S(10)**-11
ref = unchanged.subs(x, xval).n(19) # 2.0418173913673213e-11
rewritten = optimize(2*exp(x) - about_two, [expm1_opt])
# Unfortunately, we need to call ``.n()`` on our expressions before we hand them
# to ``ccode``, and we need to request a large number of significant digits.
# In this test, results converged for double precision when the following number
# of significant digits were chosen:
NUMBER_OF_DIGITS = 25 # TODO: this should ideally be automatically handled.
func_c = '''
#include <math.h>
double func_unchanged(double x) {
return %(unchanged)s;
}
double func_rewritten(double x) {
return %(rewritten)s;
}
''' % dict(unchanged=ccode(unchanged.n(NUMBER_OF_DIGITS)),
rewritten=ccode(rewritten.n(NUMBER_OF_DIGITS)))
func_pyx = '''
#cython: language_level=3
cdef extern double func_unchanged(double)
cdef extern double func_rewritten(double)
def py_unchanged(x):
return func_unchanged(x)
def py_rewritten(x):
return func_rewritten(x)
'''
with tempfile.TemporaryDirectory() as folder:
mod, info = compile_link_import_strings(
[('func.c', func_c), ('_func.pyx', func_pyx)],
build_dir=folder, compile_kwargs=dict(std='c99')
)
err_rewritten = abs(mod.py_rewritten(1e-11) - ref)
err_unchanged = abs(mod.py_unchanged(1e-11) - ref)
assert 1e-27 < err_rewritten < 1e-25 # highly accurate.
assert 1e-19 < err_unchanged < 1e-16 # quite poor.
# Tolerances used above were determined as follows:
# >>> no_opt = unchanged.subs(x, xval.evalf()).evalf()
# >>> with_opt = rewritten.n(25).subs(x, 1e-11).evalf()
# >>> with_opt - ref, no_opt - ref
# (1.1536301877952077e-26, 1.6547074214222335e-18)
|
7dabbccc0accecf084240348d5d91954d48ce298c23174bb61f94d20c3643297 | from itertools import product
from sympy.core.singleton import S
from sympy.core.symbol import symbols
from sympy.functions.elementary.exponential import (exp, log)
from sympy.printing.repr import srepr
from sympy.codegen.numpy_nodes import logaddexp, logaddexp2
x, y, z = symbols('x y z')
def test_logaddexp():
lae_xy = logaddexp(x, y)
ref_xy = log(exp(x) + exp(y))
for wrt, deriv_order in product([x, y, z], range(0, 3)):
assert (
lae_xy.diff(wrt, deriv_order) -
ref_xy.diff(wrt, deriv_order)
).rewrite(log).simplify() == 0
one_third_e = 1*exp(1)/3
two_thirds_e = 2*exp(1)/3
logThirdE = log(one_third_e)
logTwoThirdsE = log(two_thirds_e)
lae_sum_to_e = logaddexp(logThirdE, logTwoThirdsE)
assert lae_sum_to_e.rewrite(log) == 1
assert lae_sum_to_e.simplify() == 1
was = logaddexp(2, 3)
assert srepr(was) == srepr(was.simplify()) # cannot simplify with 2, 3
def test_logaddexp2():
lae2_xy = logaddexp2(x, y)
ref2_xy = log(2**x + 2**y)/log(2)
for wrt, deriv_order in product([x, y, z], range(0, 3)):
assert (
lae2_xy.diff(wrt, deriv_order) -
ref2_xy.diff(wrt, deriv_order)
).rewrite(log).cancel() == 0
def lb(x):
return log(x)/log(2)
two_thirds = S.One*2/3
four_thirds = 2*two_thirds
lbTwoThirds = lb(two_thirds)
lbFourThirds = lb(four_thirds)
lae2_sum_to_2 = logaddexp2(lbTwoThirds, lbFourThirds)
assert lae2_sum_to_2.rewrite(log) == 1
assert lae2_sum_to_2.simplify() == 1
was = logaddexp2(x, y)
assert srepr(was) == srepr(was.simplify()) # cannot simplify with x, y
|
eb60609cd8852e8b4265715046600ce0b4cf9cb5c2bd12535c7078b48be64f01 | from sympy.core.numbers import (Rational, pi)
from sympy.core.singleton import S
from sympy.core.symbol import (Symbol, symbols)
from sympy.functions.elementary.exponential import (exp, log)
from sympy.codegen.cfunctions import (
expm1, log1p, exp2, log2, fma, log10, Sqrt, Cbrt, hypot
)
from sympy.core.function import expand_log
def test_expm1():
# Eval
assert expm1(0) == 0
x = Symbol('x', real=True, finite=True)
# Expand and rewrite
assert expm1(x).expand(func=True) - exp(x) == -1
assert expm1(x).rewrite('tractable') - exp(x) == -1
assert expm1(x).rewrite('exp') - exp(x) == -1
# Precision
assert not ((exp(1e-10).evalf() - 1) - 1e-10 - 5e-21) < 1e-22 # for comparison
assert abs(expm1(1e-10).evalf() - 1e-10 - 5e-21) < 1e-22
# Properties
assert expm1(x).is_real
assert expm1(x).is_finite
# Diff
assert expm1(42*x).diff(x) - 42*exp(42*x) == 0
assert expm1(42*x).diff(x) - expm1(42*x).expand(func=True).diff(x) == 0
def test_log1p():
# Eval
assert log1p(0) == 0
d = S(10)
assert expand_log(log1p(d**-1000) - log(d**1000 + 1) + log(d**1000)) == 0
x = Symbol('x', real=True, finite=True)
# Expand and rewrite
assert log1p(x).expand(func=True) - log(x + 1) == 0
assert log1p(x).rewrite('tractable') - log(x + 1) == 0
assert log1p(x).rewrite('log') - log(x + 1) == 0
# Precision
assert not abs(log(1e-99 + 1).evalf() - 1e-99) < 1e-100 # for comparison
assert abs(expand_log(log1p(1e-99)).evalf() - 1e-99) < 1e-100
# Properties
assert log1p(-2**Rational(-1, 2)).is_real
assert not log1p(-1).is_finite
assert log1p(pi).is_finite
assert not log1p(x).is_positive
assert log1p(Symbol('y', positive=True)).is_positive
assert not log1p(x).is_zero
assert log1p(Symbol('z', zero=True)).is_zero
assert not log1p(x).is_nonnegative
assert log1p(Symbol('o', nonnegative=True)).is_nonnegative
# Diff
assert log1p(42*x).diff(x) - 42/(42*x + 1) == 0
assert log1p(42*x).diff(x) - log1p(42*x).expand(func=True).diff(x) == 0
def test_exp2():
# Eval
assert exp2(2) == 4
x = Symbol('x', real=True, finite=True)
# Expand
assert exp2(x).expand(func=True) - 2**x == 0
# Diff
assert exp2(42*x).diff(x) - 42*exp2(42*x)*log(2) == 0
assert exp2(42*x).diff(x) - exp2(42*x).diff(x) == 0
def test_log2():
# Eval
assert log2(8) == 3
assert log2(pi) != log(pi)/log(2) # log2 should *save* (CPU) instructions
x = Symbol('x', real=True, finite=True)
assert log2(x) != log(x)/log(2)
assert log2(2**x) == x
# Expand
assert log2(x).expand(func=True) - log(x)/log(2) == 0
# Diff
assert log2(42*x).diff() - 1/(log(2)*x) == 0
assert log2(42*x).diff() - log2(42*x).expand(func=True).diff(x) == 0
def test_fma():
x, y, z = symbols('x y z')
# Expand
assert fma(x, y, z).expand(func=True) - x*y - z == 0
expr = fma(17*x, 42*y, 101*z)
# Diff
assert expr.diff(x) - expr.expand(func=True).diff(x) == 0
assert expr.diff(y) - expr.expand(func=True).diff(y) == 0
assert expr.diff(z) - expr.expand(func=True).diff(z) == 0
assert expr.diff(x) - 17*42*y == 0
assert expr.diff(y) - 17*42*x == 0
assert expr.diff(z) - 101 == 0
def test_log10():
x = Symbol('x')
# Expand
assert log10(x).expand(func=True) - log(x)/log(10) == 0
# Diff
assert log10(42*x).diff(x) - 1/(log(10)*x) == 0
assert log10(42*x).diff(x) - log10(42*x).expand(func=True).diff(x) == 0
def test_Cbrt():
x = Symbol('x')
# Expand
assert Cbrt(x).expand(func=True) - x**Rational(1, 3) == 0
# Diff
assert Cbrt(42*x).diff(x) - 42*(42*x)**(Rational(1, 3) - 1)/3 == 0
assert Cbrt(42*x).diff(x) - Cbrt(42*x).expand(func=True).diff(x) == 0
def test_Sqrt():
x = Symbol('x')
# Expand
assert Sqrt(x).expand(func=True) - x**S.Half == 0
# Diff
assert Sqrt(42*x).diff(x) - 42*(42*x)**(S.Half - 1)/2 == 0
assert Sqrt(42*x).diff(x) - Sqrt(42*x).expand(func=True).diff(x) == 0
def test_hypot():
x, y = symbols('x y')
# Expand
assert hypot(x, y).expand(func=True) - (x**2 + y**2)**S.Half == 0
# Diff
assert hypot(17*x, 42*y).diff(x).expand(func=True) - hypot(17*x, 42*y).expand(func=True).diff(x) == 0
assert hypot(17*x, 42*y).diff(y).expand(func=True) - hypot(17*x, 42*y).expand(func=True).diff(y) == 0
assert hypot(17*x, 42*y).diff(x).expand(func=True) - 2*17*17*x*((17*x)**2 + (42*y)**2)**Rational(-1, 2)/2 == 0
assert hypot(17*x, 42*y).diff(y).expand(func=True) - 2*42*42*y*((17*x)**2 + (42*y)**2)**Rational(-1, 2)/2 == 0
|
1aca35f0a2b34b003ed401c2e794a01cf01f1f51ab19408668de9047b8ae10ed | from sympy.core.symbol import symbols
from sympy.codegen.pynodes import List
def test_List():
l = List(2, 3, 4)
assert l == List(2, 3, 4)
assert str(l) == "[2, 3, 4]"
x, y, z = symbols('x y z')
l = List(x**2,y**3,z**4)
# contrary to python's built-in list, we can call e.g. "replace" on List.
m = l.replace(lambda arg: arg.is_Pow and arg.exp>2, lambda p: p.base-p.exp)
assert m == [x**2, y-3, z-4]
|
80d2d21aabf4882bed727e327178bfb34fc405d044e5d8f9ef6e5225118c4ed9 | """
General binary relations.
"""
from typing import Optional
from sympy.core.singleton import S
from sympy.assumptions import AppliedPredicate, ask, Predicate, Q # type: ignore
from sympy.core.kind import BooleanKind
from sympy.core.relational import Eq, Ne, Gt, Lt, Ge, Le
from sympy.logic.boolalg import conjuncts, Not
__all__ = ["BinaryRelation", "AppliedBinaryRelation"]
class BinaryRelation(Predicate):
"""
Base class for all binary relational predicates.
Explanation
===========
Binary relation takes two arguments and returns ``AppliedBinaryRelation``
instance. To evaluate it to boolean value, use :obj:`~.ask()` or
:obj:`~.refine()` function.
You can add support for new types by registering the handler to dispatcher.
See :obj:`~.Predicate()` for more information about predicate dispatching.
Examples
========
Applying and evaluating to boolean value:
>>> from sympy import Q, ask, sin, cos
>>> from sympy.abc import x
>>> Q.eq(sin(x)**2+cos(x)**2, 1)
Q.eq(sin(x)**2 + cos(x)**2, 1)
>>> ask(_)
True
You can define a new binary relation by subclassing and dispatching.
Here, we define a relation $R$ such that $x R y$ returns true if
$x = y + 1$.
>>> from sympy import ask, Number, Q
>>> from sympy.assumptions import BinaryRelation
>>> class MyRel(BinaryRelation):
... name = "R"
... is_reflexive = False
>>> Q.R = MyRel()
>>> @Q.R.register(Number, Number)
... def _(n1, n2, assumptions):
... return ask(Q.zero(n1 - n2 - 1), assumptions)
>>> Q.R(2, 1)
Q.R(2, 1)
Now, we can use ``ask()`` to evaluate it to boolean value.
>>> ask(Q.R(2, 1))
True
>>> ask(Q.R(1, 2))
False
``Q.R`` returns ``False`` with minimum cost if two arguments have same
structure because it is antireflexive relation [1] by
``is_reflexive = False``.
>>> ask(Q.R(x, x))
False
References
==========
.. [1] https://en.wikipedia.org/wiki/Reflexive_relation
"""
is_reflexive: Optional[bool] = None
is_symmetric: Optional[bool] = None
def __call__(self, *args):
if not len(args) == 2:
raise ValueError("Binary relation takes two arguments, but got %s." % len(args))
return AppliedBinaryRelation(self, *args)
@property
def reversed(self):
if self.is_symmetric:
return self
return None
@property
def negated(self):
return None
def _compare_reflexive(self, lhs, rhs):
# quick exit for structurally same arguments
# do not check != here because it cannot catch the
# equivalent arguements with different structures.
# reflexivity does not hold to NaN
if lhs is S.NaN or rhs is S.NaN:
return None
reflexive = self.is_reflexive
if reflexive is None:
pass
elif reflexive and (lhs == rhs):
return True
elif not reflexive and (lhs == rhs):
return False
return None
def eval(self, args, assumptions=True):
# quick exit for structurally same arguments
ret = self._compare_reflexive(*args)
if ret is not None:
return ret
# don't perform simplify on args here. (done by AppliedBinaryRelation._eval_ask)
# evaluate by multipledispatch
lhs, rhs = args
ret = self.handler(lhs, rhs, assumptions=assumptions)
if ret is not None:
return ret
# check reversed order if the relation is reflexive
if self.is_reflexive:
types = (type(lhs), type(rhs))
if self.handler.dispatch(*types) is not self.handler.dispatch(*reversed(types)):
ret = self.handler(rhs, lhs, assumptions=assumptions)
return ret
class AppliedBinaryRelation(AppliedPredicate):
"""
The class of expressions resulting from applying ``BinaryRelation``
to the arguments.
"""
@property
def lhs(self):
"""The left-hand side of the relation."""
return self.arguments[0]
@property
def rhs(self):
"""The right-hand side of the relation."""
return self.arguments[1]
@property
def reversed(self):
"""
Try to return the relationship with sides reversed.
"""
revfunc = self.function.reversed
if revfunc is None:
return self
return revfunc(self.rhs, self.lhs)
@property
def reversedsign(self):
"""
Try to return the relationship with signs reversed.
"""
revfunc = self.function.reversed
if revfunc is None:
return self
if not any(side.kind is BooleanKind for side in self.arguments):
return revfunc(-self.lhs, -self.rhs)
return self
@property
def negated(self):
neg_rel = self.function.negated
if neg_rel is None:
return Not(self, evaluate=False)
return neg_rel(*self.arguments)
def _eval_ask(self, assumptions):
conj_assumps = set()
binrelpreds = {Eq: Q.eq, Ne: Q.ne, Gt: Q.gt, Lt: Q.lt, Ge: Q.ge, Le: Q.le}
for a in conjuncts(assumptions):
if a.func in binrelpreds:
conj_assumps.add(binrelpreds[a.func](*a.args))
else:
conj_assumps.add(a)
# After CNF in assumptions module is modified to take polyadic
# predicate, this will be removed
if any(rel in conj_assumps for rel in (self, self.reversed)):
return True
neg_rels = (self.negated, self.reversed.negated, Not(self, evaluate=False),
Not(self.reversed, evaluate=False))
if any(rel in conj_assumps for rel in neg_rels):
return False
# evaluation using multipledispatching
ret = self.function.eval(self.arguments, assumptions)
if ret is not None:
return ret
# simplify the args and try again
args = tuple(a.simplify() for a in self.arguments)
return self.function.eval(args, assumptions)
def __bool__(self):
ret = ask(self)
if ret is None:
raise TypeError("Cannot determine truth value of %s" % self)
return ret
|
922efc1d21cdbc3e90f4b2ec37c98d84a759949c8983792b91c45e219f865028 | from sympy.assumptions import Predicate, AppliedPredicate, Q
from sympy.core.relational import Eq, Ne, Gt, Lt, Ge, Le
from sympy.multipledispatch import Dispatcher
class CommutativePredicate(Predicate):
"""
Commutative predicate.
Explanation
===========
``ask(Q.commutative(x))`` is true iff ``x`` commutes with any other
object with respect to multiplication operation.
"""
# TODO: Add examples
name = 'commutative'
handler = Dispatcher("CommutativeHandler", doc="Handler for key 'commutative'.")
binrelpreds = {Eq: Q.eq, Ne: Q.ne, Gt: Q.gt, Lt: Q.lt, Ge: Q.ge, Le: Q.le}
class IsTruePredicate(Predicate):
"""
Generic predicate.
Explanation
===========
``ask(Q.is_true(x))`` is true iff ``x`` is true. This only makes
sense if ``x`` is a boolean object.
Examples
========
>>> from sympy import ask, Q
>>> from sympy.abc import x, y
>>> ask(Q.is_true(True))
True
Wrapping another applied predicate just returns the applied predicate.
>>> Q.is_true(Q.even(x))
Q.even(x)
Wrapping binary relation classes in SymPy core returns applied binary
relational predicates.
>>> from sympy import Eq, Gt
>>> Q.is_true(Eq(x, y))
Q.eq(x, y)
>>> Q.is_true(Gt(x, y))
Q.gt(x, y)
Notes
=====
This class is designed to wrap the boolean objects so that they can
behave as if they are applied predicates. Consequently, wrapping another
applied predicate is unnecessary and thus it just returns the argument.
Also, binary relation classes in SymPy core have binary predicates to
represent themselves and thus wrapping them with ``Q.is_true`` converts them
to these applied predicates.
"""
name = 'is_true'
handler = Dispatcher(
"IsTrueHandler",
doc="Wrapper allowing to query the truth value of a boolean expression."
)
def __call__(self, arg):
# No need to wrap another predicate
if isinstance(arg, AppliedPredicate):
return arg
# Convert relational predicates instead of wrapping them
if getattr(arg, "is_Relational", False):
pred = binrelpreds[arg.func]
return pred(*arg.args)
return super().__call__(arg)
|
f2dc4228fe79a651a40ab3bdc613b534c032c34e6e160f5b9cfb382a90ef72ac | from sympy.assumptions import Predicate
from sympy.multipledispatch import Dispatcher
class SquarePredicate(Predicate):
"""
Square matrix predicate.
Explanation
===========
``Q.square(x)`` is true iff ``x`` is a square matrix. A square matrix
is a matrix with the same number of rows and columns.
Examples
========
>>> from sympy import Q, ask, MatrixSymbol, ZeroMatrix, Identity
>>> X = MatrixSymbol('X', 2, 2)
>>> Y = MatrixSymbol('X', 2, 3)
>>> ask(Q.square(X))
True
>>> ask(Q.square(Y))
False
>>> ask(Q.square(ZeroMatrix(3, 3)))
True
>>> ask(Q.square(Identity(3)))
True
References
==========
.. [1] https://en.wikipedia.org/wiki/Square_matrix
"""
name = 'square'
handler = Dispatcher("SquareHandler", doc="Handler for Q.square.")
class SymmetricPredicate(Predicate):
"""
Symmetric matrix predicate.
Explanation
===========
``Q.symmetric(x)`` is true iff ``x`` is a square matrix and is equal to
its transpose. Every square diagonal matrix is a symmetric matrix.
Examples
========
>>> from sympy import Q, ask, MatrixSymbol
>>> X = MatrixSymbol('X', 2, 2)
>>> Y = MatrixSymbol('Y', 2, 3)
>>> Z = MatrixSymbol('Z', 2, 2)
>>> ask(Q.symmetric(X*Z), Q.symmetric(X) & Q.symmetric(Z))
True
>>> ask(Q.symmetric(X + Z), Q.symmetric(X) & Q.symmetric(Z))
True
>>> ask(Q.symmetric(Y))
False
References
==========
.. [1] https://en.wikipedia.org/wiki/Symmetric_matrix
"""
# TODO: Add handlers to make these keys work with
# actual matrices and add more examples in the docstring.
name = 'symmetric'
handler = Dispatcher("SymmetricHandler", doc="Handler for Q.symmetric.")
class InvertiblePredicate(Predicate):
"""
Invertible matrix predicate.
Explanation
===========
``Q.invertible(x)`` is true iff ``x`` is an invertible matrix.
A square matrix is called invertible only if its determinant is 0.
Examples
========
>>> from sympy import Q, ask, MatrixSymbol
>>> X = MatrixSymbol('X', 2, 2)
>>> Y = MatrixSymbol('Y', 2, 3)
>>> Z = MatrixSymbol('Z', 2, 2)
>>> ask(Q.invertible(X*Y), Q.invertible(X))
False
>>> ask(Q.invertible(X*Z), Q.invertible(X) & Q.invertible(Z))
True
>>> ask(Q.invertible(X), Q.fullrank(X) & Q.square(X))
True
References
==========
.. [1] https://en.wikipedia.org/wiki/Invertible_matrix
"""
name = 'invertible'
handler = Dispatcher("InvertibleHandler", doc="Handler for Q.invertible.")
class OrthogonalPredicate(Predicate):
"""
Orthogonal matrix predicate.
Explanation
===========
``Q.orthogonal(x)`` is true iff ``x`` is an orthogonal matrix.
A square matrix ``M`` is an orthogonal matrix if it satisfies
``M^TM = MM^T = I`` where ``M^T`` is the transpose matrix of
``M`` and ``I`` is an identity matrix. Note that an orthogonal
matrix is necessarily invertible.
Examples
========
>>> from sympy import Q, ask, MatrixSymbol, Identity
>>> X = MatrixSymbol('X', 2, 2)
>>> Y = MatrixSymbol('Y', 2, 3)
>>> Z = MatrixSymbol('Z', 2, 2)
>>> ask(Q.orthogonal(Y))
False
>>> ask(Q.orthogonal(X*Z*X), Q.orthogonal(X) & Q.orthogonal(Z))
True
>>> ask(Q.orthogonal(Identity(3)))
True
>>> ask(Q.invertible(X), Q.orthogonal(X))
True
References
==========
.. [1] https://en.wikipedia.org/wiki/Orthogonal_matrix
"""
name = 'orthogonal'
handler = Dispatcher("OrthogonalHandler", doc="Handler for key 'orthogonal'.")
class UnitaryPredicate(Predicate):
"""
Unitary matrix predicate.
Explanation
===========
``Q.unitary(x)`` is true iff ``x`` is a unitary matrix.
Unitary matrix is an analogue to orthogonal matrix. A square
matrix ``M`` with complex elements is unitary if :math:``M^TM = MM^T= I``
where :math:``M^T`` is the conjugate transpose matrix of ``M``.
Examples
========
>>> from sympy import Q, ask, MatrixSymbol, Identity
>>> X = MatrixSymbol('X', 2, 2)
>>> Y = MatrixSymbol('Y', 2, 3)
>>> Z = MatrixSymbol('Z', 2, 2)
>>> ask(Q.unitary(Y))
False
>>> ask(Q.unitary(X*Z*X), Q.unitary(X) & Q.unitary(Z))
True
>>> ask(Q.unitary(Identity(3)))
True
References
==========
.. [1] https://en.wikipedia.org/wiki/Unitary_matrix
"""
name = 'unitary'
handler = Dispatcher("UnitaryHandler", doc="Handler for key 'unitary'.")
class FullRankPredicate(Predicate):
"""
Fullrank matrix predicate.
Explanation
===========
``Q.fullrank(x)`` is true iff ``x`` is a full rank matrix.
A matrix is full rank if all rows and columns of the matrix
are linearly independent. A square matrix is full rank iff
its determinant is nonzero.
Examples
========
>>> from sympy import Q, ask, MatrixSymbol, ZeroMatrix, Identity
>>> X = MatrixSymbol('X', 2, 2)
>>> ask(Q.fullrank(X.T), Q.fullrank(X))
True
>>> ask(Q.fullrank(ZeroMatrix(3, 3)))
False
>>> ask(Q.fullrank(Identity(3)))
True
"""
name = 'fullrank'
handler = Dispatcher("FullRankHandler", doc="Handler for key 'fullrank'.")
class PositiveDefinitePredicate(Predicate):
r"""
Positive definite matrix predicate.
Explanation
===========
If $M$ is a :math:`n \times n` symmetric real matrix, it is said
to be positive definite if :math:`Z^TMZ` is positive for
every non-zero column vector $Z$ of $n$ real numbers.
Examples
========
>>> from sympy import Q, ask, MatrixSymbol, Identity
>>> X = MatrixSymbol('X', 2, 2)
>>> Y = MatrixSymbol('Y', 2, 3)
>>> Z = MatrixSymbol('Z', 2, 2)
>>> ask(Q.positive_definite(Y))
False
>>> ask(Q.positive_definite(Identity(3)))
True
>>> ask(Q.positive_definite(X + Z), Q.positive_definite(X) &
... Q.positive_definite(Z))
True
References
==========
.. [1] https://en.wikipedia.org/wiki/Positive-definite_matrix
"""
name = "positive_definite"
handler = Dispatcher("PositiveDefiniteHandler", doc="Handler for key 'positive_definite'.")
class UpperTriangularPredicate(Predicate):
"""
Upper triangular matrix predicate.
Explanation
===========
A matrix $M$ is called upper triangular matrix if :math:`M_{ij}=0`
for :math:`i<j`.
Examples
========
>>> from sympy import Q, ask, ZeroMatrix, Identity
>>> ask(Q.upper_triangular(Identity(3)))
True
>>> ask(Q.upper_triangular(ZeroMatrix(3, 3)))
True
References
==========
.. [1] http://mathworld.wolfram.com/UpperTriangularMatrix.html
"""
name = "upper_triangular"
handler = Dispatcher("UpperTriangularHandler", doc="Handler for key 'upper_triangular'.")
class LowerTriangularPredicate(Predicate):
"""
Lower triangular matrix predicate.
Explanation
===========
A matrix $M$ is called lower triangular matrix if :math:`M_{ij}=0`
for :math:`i>j`.
Examples
========
>>> from sympy import Q, ask, ZeroMatrix, Identity
>>> ask(Q.lower_triangular(Identity(3)))
True
>>> ask(Q.lower_triangular(ZeroMatrix(3, 3)))
True
References
==========
.. [1] http://mathworld.wolfram.com/LowerTriangularMatrix.html
"""
name = "lower_triangular"
handler = Dispatcher("LowerTriangularHandler", doc="Handler for key 'lower_triangular'.")
class DiagonalPredicate(Predicate):
"""
Diagonal matrix predicate.
Explanation
===========
``Q.diagonal(x)`` is true iff ``x`` is a diagonal matrix. A diagonal
matrix is a matrix in which the entries outside the main diagonal
are all zero.
Examples
========
>>> from sympy import Q, ask, MatrixSymbol, ZeroMatrix
>>> X = MatrixSymbol('X', 2, 2)
>>> ask(Q.diagonal(ZeroMatrix(3, 3)))
True
>>> ask(Q.diagonal(X), Q.lower_triangular(X) &
... Q.upper_triangular(X))
True
References
==========
.. [1] https://en.wikipedia.org/wiki/Diagonal_matrix
"""
name = "diagonal"
handler = Dispatcher("DiagonalHandler", doc="Handler for key 'diagonal'.")
class IntegerElementsPredicate(Predicate):
"""
Integer elements matrix predicate.
Explanation
===========
``Q.integer_elements(x)`` is true iff all the elements of ``x``
are integers.
Examples
========
>>> from sympy import Q, ask, MatrixSymbol
>>> X = MatrixSymbol('X', 4, 4)
>>> ask(Q.integer(X[1, 2]), Q.integer_elements(X))
True
"""
name = "integer_elements"
handler = Dispatcher("IntegerElementsHandler", doc="Handler for key 'integer_elements'.")
class RealElementsPredicate(Predicate):
"""
Real elements matrix predicate.
Explanation
===========
``Q.real_elements(x)`` is true iff all the elements of ``x``
are real numbers.
Examples
========
>>> from sympy import Q, ask, MatrixSymbol
>>> X = MatrixSymbol('X', 4, 4)
>>> ask(Q.real(X[1, 2]), Q.real_elements(X))
True
"""
name = "real_elements"
handler = Dispatcher("RealElementsHandler", doc="Handler for key 'real_elements'.")
class ComplexElementsPredicate(Predicate):
"""
Complex elements matrix predicate.
Explanation
===========
``Q.complex_elements(x)`` is true iff all the elements of ``x``
are complex numbers.
Examples
========
>>> from sympy import Q, ask, MatrixSymbol
>>> X = MatrixSymbol('X', 4, 4)
>>> ask(Q.complex(X[1, 2]), Q.complex_elements(X))
True
>>> ask(Q.complex_elements(X), Q.integer_elements(X))
True
"""
name = "complex_elements"
handler = Dispatcher("ComplexElementsHandler", doc="Handler for key 'complex_elements'.")
class SingularPredicate(Predicate):
"""
Singular matrix predicate.
A matrix is singular iff the value of its determinant is 0.
Examples
========
>>> from sympy import Q, ask, MatrixSymbol
>>> X = MatrixSymbol('X', 4, 4)
>>> ask(Q.singular(X), Q.invertible(X))
False
>>> ask(Q.singular(X), ~Q.invertible(X))
True
References
==========
.. [1] http://mathworld.wolfram.com/SingularMatrix.html
"""
name = "singular"
handler = Dispatcher("SingularHandler", doc="Predicate fore key 'singular'.")
class NormalPredicate(Predicate):
"""
Normal matrix predicate.
A matrix is normal if it commutes with its conjugate transpose.
Examples
========
>>> from sympy import Q, ask, MatrixSymbol
>>> X = MatrixSymbol('X', 4, 4)
>>> ask(Q.normal(X), Q.unitary(X))
True
References
==========
.. [1] https://en.wikipedia.org/wiki/Normal_matrix
"""
name = "normal"
handler = Dispatcher("NormalHandler", doc="Predicate fore key 'normal'.")
class TriangularPredicate(Predicate):
"""
Triangular matrix predicate.
Explanation
===========
``Q.triangular(X)`` is true if ``X`` is one that is either lower
triangular or upper triangular.
Examples
========
>>> from sympy import Q, ask, MatrixSymbol
>>> X = MatrixSymbol('X', 4, 4)
>>> ask(Q.triangular(X), Q.upper_triangular(X))
True
>>> ask(Q.triangular(X), Q.lower_triangular(X))
True
References
==========
.. [1] https://en.wikipedia.org/wiki/Triangular_matrix
"""
name = "triangular"
handler = Dispatcher("TriangularHandler", doc="Predicate fore key 'triangular'.")
class UnitTriangularPredicate(Predicate):
"""
Unit triangular matrix predicate.
Explanation
===========
A unit triangular matrix is a triangular matrix with 1s
on the diagonal.
Examples
========
>>> from sympy import Q, ask, MatrixSymbol
>>> X = MatrixSymbol('X', 4, 4)
>>> ask(Q.triangular(X), Q.unit_triangular(X))
True
"""
name = "unit_triangular"
handler = Dispatcher("UnitTriangularHandler", doc="Predicate fore key 'unit_triangular'.")
|
d1c4ee0fdd0213f5d249fe797ff63ed344e7c675dce94c4c54d227c528294f88 | from sympy.assumptions import Predicate
from sympy.multipledispatch import Dispatcher
class IntegerPredicate(Predicate):
"""
Integer predicate.
Explanation
===========
``Q.integer(x)`` is true iff ``x`` belongs to the set of integer
numbers.
Examples
========
>>> from sympy import Q, ask, S
>>> ask(Q.integer(5))
True
>>> ask(Q.integer(S(1)/2))
False
References
==========
.. [1] https://en.wikipedia.org/wiki/Integer
"""
name = 'integer'
handler = Dispatcher(
"IntegerHandler",
doc=("Handler for Q.integer.\n\n"
"Test that an expression belongs to the field of integer numbers.")
)
class RationalPredicate(Predicate):
"""
Rational number predicate.
Explanation
===========
``Q.rational(x)`` is true iff ``x`` belongs to the set of
rational numbers.
Examples
========
>>> from sympy import ask, Q, pi, S
>>> ask(Q.rational(0))
True
>>> ask(Q.rational(S(1)/2))
True
>>> ask(Q.rational(pi))
False
References
==========
.. [1] https://en.wikipedia.org/wiki/Rational_number
"""
name = 'rational'
handler = Dispatcher(
"RationalHandler",
doc=("Handler for Q.rational.\n\n"
"Test that an expression belongs to the field of rational numbers.")
)
class IrrationalPredicate(Predicate):
"""
Irrational number predicate.
Explanation
===========
``Q.irrational(x)`` is true iff ``x`` is any real number that
cannot be expressed as a ratio of integers.
Examples
========
>>> from sympy import ask, Q, pi, S, I
>>> ask(Q.irrational(0))
False
>>> ask(Q.irrational(S(1)/2))
False
>>> ask(Q.irrational(pi))
True
>>> ask(Q.irrational(I))
False
References
==========
.. [1] https://en.wikipedia.org/wiki/Irrational_number
"""
name = 'irrational'
handler = Dispatcher(
"IrrationalHandler",
doc=("Handler for Q.irrational.\n\n"
"Test that an expression is irrational numbers.")
)
class RealPredicate(Predicate):
r"""
Real number predicate.
Explanation
===========
``Q.real(x)`` is true iff ``x`` is a real number, i.e., it is in the
interval `(-\infty, \infty)`. Note that, in particular the
infinities are not real. Use ``Q.extended_real`` if you want to
consider those as well.
A few important facts about reals:
- Every real number is positive, negative, or zero. Furthermore,
because these sets are pairwise disjoint, each real number is
exactly one of those three.
- Every real number is also complex.
- Every real number is finite.
- Every real number is either rational or irrational.
- Every real number is either algebraic or transcendental.
- The facts ``Q.negative``, ``Q.zero``, ``Q.positive``,
``Q.nonnegative``, ``Q.nonpositive``, ``Q.nonzero``,
``Q.integer``, ``Q.rational``, and ``Q.irrational`` all imply
``Q.real``, as do all facts that imply those facts.
- The facts ``Q.algebraic``, and ``Q.transcendental`` do not imply
``Q.real``; they imply ``Q.complex``. An algebraic or
transcendental number may or may not be real.
- The "non" facts (i.e., ``Q.nonnegative``, ``Q.nonzero``,
``Q.nonpositive`` and ``Q.noninteger``) are not equivalent to
not the fact, but rather, not the fact *and* ``Q.real``.
For example, ``Q.nonnegative`` means ``~Q.negative & Q.real``.
So for example, ``I`` is not nonnegative, nonzero, or
nonpositive.
Examples
========
>>> from sympy import Q, ask, symbols
>>> x = symbols('x')
>>> ask(Q.real(x), Q.positive(x))
True
>>> ask(Q.real(0))
True
References
==========
.. [1] https://en.wikipedia.org/wiki/Real_number
"""
name = 'real'
handler = Dispatcher(
"RealHandler",
doc=("Handler for Q.real.\n\n"
"Test that an expression belongs to the field of real numbers.")
)
class ExtendedRealPredicate(Predicate):
r"""
Extended real predicate.
Explanation
===========
``Q.extended_real(x)`` is true iff ``x`` is a real number or
`\{-\infty, \infty\}`.
See documentation of ``Q.real`` for more information about related
facts.
Examples
========
>>> from sympy import ask, Q, oo, I
>>> ask(Q.extended_real(1))
True
>>> ask(Q.extended_real(I))
False
>>> ask(Q.extended_real(oo))
True
"""
name = 'extended_real'
handler = Dispatcher(
"ExtendedRealHandler",
doc=("Handler for Q.extended_real.\n\n"
"Test that an expression belongs to the field of extended real\n"
"numbers, that is real numbers union {Infinity, -Infinity}.")
)
class HermitianPredicate(Predicate):
"""
Hermitian predicate.
Explanation
===========
``ask(Q.hermitian(x))`` is true iff ``x`` belongs to the set of
Hermitian operators.
References
==========
.. [1] http://mathworld.wolfram.com/HermitianOperator.html
"""
# TODO: Add examples
name = 'hermitian'
handler = Dispatcher(
"HermitianHandler",
doc=("Handler for Q.hermitian.\n\n"
"Test that an expression belongs to the field of Hermitian operators.")
)
class ComplexPredicate(Predicate):
"""
Complex number predicate.
Explanation
===========
``Q.complex(x)`` is true iff ``x`` belongs to the set of complex
numbers. Note that every complex number is finite.
Examples
========
>>> from sympy import Q, Symbol, ask, I, oo
>>> x = Symbol('x')
>>> ask(Q.complex(0))
True
>>> ask(Q.complex(2 + 3*I))
True
>>> ask(Q.complex(oo))
False
References
==========
.. [1] https://en.wikipedia.org/wiki/Complex_number
"""
name = 'complex'
handler = Dispatcher(
"ComplexHandler",
doc=("Handler for Q.complex.\n\n"
"Test that an expression belongs to the field of complex numbers.")
)
class ImaginaryPredicate(Predicate):
"""
Imaginary number predicate.
Explanation
===========
``Q.imaginary(x)`` is true iff ``x`` can be written as a real
number multiplied by the imaginary unit ``I``. Please note that ``0``
is not considered to be an imaginary number.
Examples
========
>>> from sympy import Q, ask, I
>>> ask(Q.imaginary(3*I))
True
>>> ask(Q.imaginary(2 + 3*I))
False
>>> ask(Q.imaginary(0))
False
References
==========
.. [1] https://en.wikipedia.org/wiki/Imaginary_number
"""
name = 'imaginary'
handler = Dispatcher(
"ImaginaryHandler",
doc=("Handler for Q.imaginary.\n\n"
"Test that an expression belongs to the field of imaginary numbers,\n"
"that is, numbers in the form x*I, where x is real.")
)
class AntihermitianPredicate(Predicate):
"""
Antihermitian predicate.
Explanation
===========
``Q.antihermitian(x)`` is true iff ``x`` belongs to the field of
antihermitian operators, i.e., operators in the form ``x*I``, where
``x`` is Hermitian.
References
==========
.. [1] http://mathworld.wolfram.com/HermitianOperator.html
"""
# TODO: Add examples
name = 'antihermitian'
handler = Dispatcher(
"AntiHermitianHandler",
doc=("Handler for Q.antihermitian.\n\n"
"Test that an expression belongs to the field of anti-Hermitian\n"
"operators, that is, operators in the form x*I, where x is Hermitian.")
)
class AlgebraicPredicate(Predicate):
r"""
Algebraic number predicate.
Explanation
===========
``Q.algebraic(x)`` is true iff ``x`` belongs to the set of
algebraic numbers. ``x`` is algebraic if there is some polynomial
in ``p(x)\in \mathbb\{Q\}[x]`` such that ``p(x) = 0``.
Examples
========
>>> from sympy import ask, Q, sqrt, I, pi
>>> ask(Q.algebraic(sqrt(2)))
True
>>> ask(Q.algebraic(I))
True
>>> ask(Q.algebraic(pi))
False
References
==========
.. [1] https://en.wikipedia.org/wiki/Algebraic_number
"""
name = 'algebraic'
AlgebraicHandler = Dispatcher(
"AlgebraicHandler",
doc="""Handler for Q.algebraic key."""
)
class TranscendentalPredicate(Predicate):
"""
Transcedental number predicate.
Explanation
===========
``Q.transcendental(x)`` is true iff ``x`` belongs to the set of
transcendental numbers. A transcendental number is a real
or complex number that is not algebraic.
"""
# TODO: Add examples
name = 'transcendental'
handler = Dispatcher(
"Transcendental",
doc="""Handler for Q.transcendental key."""
)
|
627bb641a5c1274e08eae9a3fa1a6ffcebbc50648c6a0ee279d7b925dd3ab0f7 | """
Handlers for keys related to number theory: prime, even, odd, etc.
"""
from sympy.assumptions import Q, ask
from sympy.core import Add, Basic, Expr, Float, Mul, Pow, S
from sympy.core.numbers import (ImaginaryUnit, Infinity, Integer, NaN,
NegativeInfinity, NumberSymbol, Rational)
from sympy.functions import Abs, im, re
from sympy.ntheory import isprime
from sympy.multipledispatch import MDNotImplementedError
from ..predicates.ntheory import (PrimePredicate, CompositePredicate,
EvenPredicate, OddPredicate)
# PrimePredicate
def _PrimePredicate_number(expr, assumptions):
# helper method
exact = not expr.atoms(Float)
try:
i = int(expr.round())
if (expr - i).equals(0) is False:
raise TypeError
except TypeError:
return False
if exact:
return isprime(i)
# when not exact, we won't give a True or False
# since the number represents an approximate value
@PrimePredicate.register(Expr) # type: ignore
def _(expr, assumptions):
ret = expr.is_prime
if ret is None:
raise MDNotImplementedError
return ret
@PrimePredicate.register(Basic) # type: ignore
def _(expr, assumptions):
if expr.is_number:
return _PrimePredicate_number(expr, assumptions)
@PrimePredicate.register(Mul) # type: ignore
def _(expr, assumptions):
if expr.is_number:
return _PrimePredicate_number(expr, assumptions)
for arg in expr.args:
if not ask(Q.integer(arg), assumptions):
return None
for arg in expr.args:
if arg.is_number and arg.is_composite:
return False
@PrimePredicate.register(Pow) # type: ignore
def _(expr, assumptions):
"""
Integer**Integer -> !Prime
"""
if expr.is_number:
return _PrimePredicate_number(expr, assumptions)
if ask(Q.integer(expr.exp), assumptions) and \
ask(Q.integer(expr.base), assumptions):
return False
@PrimePredicate.register(Integer) # type: ignore
def _(expr, assumptions):
return isprime(expr)
@PrimePredicate.register_many(Rational, Infinity, NegativeInfinity, ImaginaryUnit) # type: ignore
def _(expr, assumptions):
return False
@PrimePredicate.register(Float) # type: ignore
def _(expr, assumptions):
return _PrimePredicate_number(expr, assumptions)
@PrimePredicate.register(NumberSymbol) # type: ignore
def _(expr, assumptions):
return _PrimePredicate_number(expr, assumptions)
@PrimePredicate.register(NaN) # type: ignore
def _(expr, assumptions):
return None
# CompositePredicate
@CompositePredicate.register(Expr) # type: ignore
def _(expr, assumptions):
ret = expr.is_composite
if ret is None:
raise MDNotImplementedError
return ret
@CompositePredicate.register(Basic) # type: ignore
def _(expr, assumptions):
_positive = ask(Q.positive(expr), assumptions)
if _positive:
_integer = ask(Q.integer(expr), assumptions)
if _integer:
_prime = ask(Q.prime(expr), assumptions)
if _prime is None:
return
# Positive integer which is not prime is not
# necessarily composite
if expr.equals(1):
return False
return not _prime
else:
return _integer
else:
return _positive
# EvenPredicate
def _EvenPredicate_number(expr, assumptions):
# helper method
try:
i = int(expr.round())
if not (expr - i).equals(0):
raise TypeError
except TypeError:
return False
if isinstance(expr, (float, Float)):
return False
return i % 2 == 0
@EvenPredicate.register(Expr) # type: ignore
def _(expr, assumptions):
ret = expr.is_even
if ret is None:
raise MDNotImplementedError
return ret
@EvenPredicate.register(Basic) # type: ignore
def _(expr, assumptions):
if expr.is_number:
return _EvenPredicate_number(expr, assumptions)
@EvenPredicate.register(Mul) # type: ignore
def _(expr, assumptions):
"""
Even * Integer -> Even
Even * Odd -> Even
Integer * Odd -> ?
Odd * Odd -> Odd
Even * Even -> Even
Integer * Integer -> Even if Integer + Integer = Odd
otherwise -> ?
"""
if expr.is_number:
return _EvenPredicate_number(expr, assumptions)
even, odd, irrational, acc = False, 0, False, 1
for arg in expr.args:
# check for all integers and at least one even
if ask(Q.integer(arg), assumptions):
if ask(Q.even(arg), assumptions):
even = True
elif ask(Q.odd(arg), assumptions):
odd += 1
elif not even and acc != 1:
if ask(Q.odd(acc + arg), assumptions):
even = True
elif ask(Q.irrational(arg), assumptions):
# one irrational makes the result False
# two makes it undefined
if irrational:
break
irrational = True
else:
break
acc = arg
else:
if irrational:
return False
if even:
return True
if odd == len(expr.args):
return False
@EvenPredicate.register(Add) # type: ignore
def _(expr, assumptions):
"""
Even + Odd -> Odd
Even + Even -> Even
Odd + Odd -> Even
"""
if expr.is_number:
return _EvenPredicate_number(expr, assumptions)
_result = True
for arg in expr.args:
if ask(Q.even(arg), assumptions):
pass
elif ask(Q.odd(arg), assumptions):
_result = not _result
else:
break
else:
return _result
@EvenPredicate.register(Pow) # type: ignore
def _(expr, assumptions):
if expr.is_number:
return _EvenPredicate_number(expr, assumptions)
if ask(Q.integer(expr.exp), assumptions):
if ask(Q.positive(expr.exp), assumptions):
return ask(Q.even(expr.base), assumptions)
elif ask(~Q.negative(expr.exp) & Q.odd(expr.base), assumptions):
return False
elif expr.base is S.NegativeOne:
return False
@EvenPredicate.register(Integer) # type: ignore
def _(expr, assumptions):
return not bool(expr.p & 1)
@EvenPredicate.register_many(Rational, Infinity, NegativeInfinity, ImaginaryUnit) # type: ignore
def _(expr, assumptions):
return False
@EvenPredicate.register(NumberSymbol) # type: ignore
def _(expr, assumptions):
return _EvenPredicate_number(expr, assumptions)
@EvenPredicate.register(Abs) # type: ignore
def _(expr, assumptions):
if ask(Q.real(expr.args[0]), assumptions):
return ask(Q.even(expr.args[0]), assumptions)
@EvenPredicate.register(re) # type: ignore
def _(expr, assumptions):
if ask(Q.real(expr.args[0]), assumptions):
return ask(Q.even(expr.args[0]), assumptions)
@EvenPredicate.register(im) # type: ignore
def _(expr, assumptions):
if ask(Q.real(expr.args[0]), assumptions):
return True
@EvenPredicate.register(NaN) # type: ignore
def _(expr, assumptions):
return None
# OddPredicate
@OddPredicate.register(Expr) # type: ignore
def _(expr, assumptions):
ret = expr.is_odd
if ret is None:
raise MDNotImplementedError
return ret
@OddPredicate.register(Basic) # type: ignore
def _(expr, assumptions):
_integer = ask(Q.integer(expr), assumptions)
if _integer:
_even = ask(Q.even(expr), assumptions)
if _even is None:
return None
return not _even
return _integer
|
a6f3dc57fbac742f9ec458cd6941e6056ac467e7b0379e34d12c371bd6cee58a | """
This module contains query handlers responsible for calculus queries:
infinitesimal, finite, etc.
"""
from sympy.assumptions import Q, ask
from sympy.core import Add, Mul, Pow, Symbol
from sympy.core.numbers import (NegativeInfinity, GoldenRatio,
Infinity, Exp1, ComplexInfinity, ImaginaryUnit, NaN, Number, Pi, E,
TribonacciConstant)
from sympy.functions import cos, exp, log, sign, sin
from sympy.logic.boolalg import conjuncts
from ..predicates.calculus import (FinitePredicate, InfinitePredicate,
PositiveInfinitePredicate, NegativeInfinitePredicate)
# FinitePredicate
@FinitePredicate.register(Symbol) # type: ignore
def _(expr, assumptions):
"""
Handles Symbol.
"""
if expr.is_finite is not None:
return expr.is_finite
if Q.finite(expr) in conjuncts(assumptions):
return True
return None
@FinitePredicate.register(Add) # type: ignore
def _(expr, assumptions):
"""
Return True if expr is bounded, False if not and None if unknown.
Truth Table:
+-------+-----+-----------+-----------+
| | | | |
| | B | U | ? |
| | | | |
+-------+-----+---+---+---+---+---+---+
| | | | | | | | |
| | |'+'|'-'|'x'|'+'|'-'|'x'|
| | | | | | | | |
+-------+-----+---+---+---+---+---+---+
| | | | |
| B | B | U | ? |
| | | | |
+---+---+-----+---+---+---+---+---+---+
| | | | | | | | | |
| |'+'| | U | ? | ? | U | ? | ? |
| | | | | | | | | |
| +---+-----+---+---+---+---+---+---+
| | | | | | | | | |
| U |'-'| | ? | U | ? | ? | U | ? |
| | | | | | | | | |
| +---+-----+---+---+---+---+---+---+
| | | | | |
| |'x'| | ? | ? |
| | | | | |
+---+---+-----+---+---+---+---+---+---+
| | | | |
| ? | | | ? |
| | | | |
+-------+-----+-----------+---+---+---+
* 'B' = Bounded
* 'U' = Unbounded
* '?' = unknown boundedness
* '+' = positive sign
* '-' = negative sign
* 'x' = sign unknown
* All Bounded -> True
* 1 Unbounded and the rest Bounded -> False
* >1 Unbounded, all with same known sign -> False
* Any Unknown and unknown sign -> None
* Else -> None
When the signs are not the same you can have an undefined
result as in oo - oo, hence 'bounded' is also undefined.
"""
sign = -1 # sign of unknown or infinite
result = True
for arg in expr.args:
_bounded = ask(Q.finite(arg), assumptions)
if _bounded:
continue
s = ask(Q.extended_positive(arg), assumptions)
# if there has been more than one sign or if the sign of this arg
# is None and Bounded is None or there was already
# an unknown sign, return None
if sign != -1 and s != sign or \
s is None and None in (_bounded, sign):
return None
else:
sign = s
# once False, do not change
if result is not False:
result = _bounded
return result
@FinitePredicate.register(Mul) # type: ignore
def _(expr, assumptions):
"""
Return True if expr is bounded, False if not and None if unknown.
Truth Table:
+---+---+---+--------+
| | | | |
| | B | U | ? |
| | | | |
+---+---+---+---+----+
| | | | | |
| | | | s | /s |
| | | | | |
+---+---+---+---+----+
| | | | |
| B | B | U | ? |
| | | | |
+---+---+---+---+----+
| | | | | |
| U | | U | U | ? |
| | | | | |
+---+---+---+---+----+
| | | | |
| ? | | | ? |
| | | | |
+---+---+---+---+----+
* B = Bounded
* U = Unbounded
* ? = unknown boundedness
* s = signed (hence nonzero)
* /s = not signed
"""
result = True
for arg in expr.args:
_bounded = ask(Q.finite(arg), assumptions)
if _bounded:
continue
elif _bounded is None:
if result is None:
return None
if ask(Q.extended_nonzero(arg), assumptions) is None:
return None
if result is not False:
result = None
else:
result = False
return result
@FinitePredicate.register(Pow) # type: ignore
def _(expr, assumptions):
"""
* Unbounded ** NonZero -> Unbounded
* Bounded ** Bounded -> Bounded
* Abs()<=1 ** Positive -> Bounded
* Abs()>=1 ** Negative -> Bounded
* Otherwise unknown
"""
if expr.base == E:
return ask(Q.finite(expr.exp), assumptions)
base_bounded = ask(Q.finite(expr.base), assumptions)
exp_bounded = ask(Q.finite(expr.exp), assumptions)
if base_bounded is None and exp_bounded is None: # Common Case
return None
if base_bounded is False and ask(Q.extended_nonzero(expr.exp), assumptions):
return False
if base_bounded and exp_bounded:
return True
if (abs(expr.base) <= 1) == True and ask(Q.extended_positive(expr.exp), assumptions):
return True
if (abs(expr.base) >= 1) == True and ask(Q.extended_negative(expr.exp), assumptions):
return True
if (abs(expr.base) >= 1) == True and exp_bounded is False:
return False
return None
@FinitePredicate.register(exp) # type: ignore
def _(expr, assumptions):
return ask(Q.finite(expr.exp), assumptions)
@FinitePredicate.register(log) # type: ignore
def _(expr, assumptions):
# After complex -> finite fact is registered to new assumption system,
# querying Q.infinite may be removed.
if ask(Q.infinite(expr.args[0]), assumptions):
return False
return ask(~Q.zero(expr.args[0]), assumptions)
@FinitePredicate.register_many(cos, sin, Number, Pi, Exp1, GoldenRatio, # type: ignore
TribonacciConstant, ImaginaryUnit, sign)
def _(expr, assumptions):
return True
@FinitePredicate.register_many(ComplexInfinity, Infinity, NegativeInfinity) # type: ignore
def _(expr, assumptions):
return False
@FinitePredicate.register(NaN) # type: ignore
def _(expr, assumptions):
return None
# InfinitePredicate
@InfinitePredicate.register_many(ComplexInfinity, Infinity, NegativeInfinity) # type: ignore
def _(expr, assumptions):
return True
# PositiveInfinitePredicate
@PositiveInfinitePredicate.register(Infinity) # type: ignore
def _(expr, assumptions):
return True
@PositiveInfinitePredicate.register_many(NegativeInfinity, ComplexInfinity) # type: ignore
def _(expr, assumptions):
return False
# NegativeInfinitePredicate
@NegativeInfinitePredicate.register(NegativeInfinity) # type: ignore
def _(expr, assumptions):
return True
@NegativeInfinitePredicate.register_many(Infinity, ComplexInfinity) # type: ignore
def _(expr, assumptions):
return False
|
f85d6fcb23e7779dbf12b9c78c73b3caa85983582eeeb7f431d3ec9e504ae762 | """
This module defines base class for handlers and some core handlers:
``Q.commutative`` and ``Q.is_true``.
"""
from sympy.assumptions import Q, ask, AppliedPredicate
from sympy.core import Basic, Symbol
from sympy.core.logic import _fuzzy_group
from sympy.core.numbers import NaN, Number
from sympy.logic.boolalg import (And, BooleanTrue, BooleanFalse, conjuncts,
Equivalent, Implies, Not, Or)
from sympy.utilities.exceptions import SymPyDeprecationWarning
from ..predicates.common import CommutativePredicate, IsTruePredicate
class AskHandler:
"""Base class that all Ask Handlers must inherit."""
def __new__(cls, *args, **kwargs):
SymPyDeprecationWarning(
feature="AskHandler() class",
useinstead="multipledispatch handler",
issue=20873,
deprecated_since_version="1.8"
).warn()
return super().__new__(cls, *args, **kwargs)
class CommonHandler(AskHandler):
# Deprecated
"""Defines some useful methods common to most Handlers. """
@staticmethod
def AlwaysTrue(expr, assumptions):
return True
@staticmethod
def AlwaysFalse(expr, assumptions):
return False
@staticmethod
def AlwaysNone(expr, assumptions):
return None
NaN = AlwaysFalse
# CommutativePredicate
@CommutativePredicate.register(Symbol) # type: ignore
def _(expr, assumptions):
"""Objects are expected to be commutative unless otherwise stated"""
assumps = conjuncts(assumptions)
if expr.is_commutative is not None:
return expr.is_commutative and not ~Q.commutative(expr) in assumps
if Q.commutative(expr) in assumps:
return True
elif ~Q.commutative(expr) in assumps:
return False
return True
@CommutativePredicate.register(Basic) # type: ignore
def _(expr, assumptions):
for arg in expr.args:
if not ask(Q.commutative(arg), assumptions):
return False
return True
@CommutativePredicate.register(Number) # type: ignore
def _(expr, assumptions):
return True
@CommutativePredicate.register(NaN) # type: ignore
def _(expr, assumptions):
return True
# IsTruePredicate
@IsTruePredicate.register(bool) # type: ignore
def _(expr, assumptions):
return expr
@IsTruePredicate.register(BooleanTrue) # type: ignore
def _(expr, assumptions):
return True
@IsTruePredicate.register(BooleanFalse) # type: ignore
def _(expr, assumptions):
return False
@IsTruePredicate.register(AppliedPredicate) # type: ignore
def _(expr, assumptions):
return ask(expr, assumptions)
@IsTruePredicate.register(Not) # type: ignore
def _(expr, assumptions):
arg = expr.args[0]
if arg.is_Symbol:
# symbol used as abstract boolean object
return None
value = ask(arg, assumptions=assumptions)
if value in (True, False):
return not value
else:
return None
@IsTruePredicate.register(Or) # type: ignore
def _(expr, assumptions):
result = False
for arg in expr.args:
p = ask(arg, assumptions=assumptions)
if p is True:
return True
if p is None:
result = None
return result
@IsTruePredicate.register(And) # type: ignore
def _(expr, assumptions):
result = True
for arg in expr.args:
p = ask(arg, assumptions=assumptions)
if p is False:
return False
if p is None:
result = None
return result
@IsTruePredicate.register(Implies) # type: ignore
def _(expr, assumptions):
p, q = expr.args
return ask(~p | q, assumptions=assumptions)
@IsTruePredicate.register(Equivalent) # type: ignore
def _(expr, assumptions):
p, q = expr.args
pt = ask(p, assumptions=assumptions)
if pt is None:
return None
qt = ask(q, assumptions=assumptions)
if qt is None:
return None
return pt == qt
#### Helper methods
def test_closed_group(expr, assumptions, key):
"""
Test for membership in a group with respect
to the current operation.
"""
return _fuzzy_group(
(ask(key(a), assumptions) for a in expr.args), quick_exit=True)
|
8d018b79ad9c436e420638d93df6a8a7344a13fc8bf7d6302ce94ea9677119a9 | """
This module contains query handlers responsible for Matrices queries:
Square, Symmetric, Invertible etc.
"""
from sympy.logic.boolalg import conjuncts
from sympy.assumptions import Q, ask
from sympy.assumptions.handlers import test_closed_group
from sympy.matrices import MatrixBase
from sympy.matrices.expressions import (BlockMatrix, BlockDiagMatrix, Determinant,
DiagMatrix, DiagonalMatrix, HadamardProduct, Identity, Inverse, MatAdd, MatMul,
MatPow, MatrixExpr, MatrixSlice, MatrixSymbol, OneMatrix, Trace, Transpose,
ZeroMatrix)
from sympy.matrices.expressions.factorizations import Factorization
from sympy.matrices.expressions.fourier import DFT
from sympy.core.logic import fuzzy_and
from sympy.utilities.iterables import sift
from sympy.core import Basic
from ..predicates.matrices import (SquarePredicate, SymmetricPredicate,
InvertiblePredicate, OrthogonalPredicate, UnitaryPredicate,
FullRankPredicate, PositiveDefinitePredicate, UpperTriangularPredicate,
LowerTriangularPredicate, DiagonalPredicate, IntegerElementsPredicate,
RealElementsPredicate, ComplexElementsPredicate)
def _Factorization(predicate, expr, assumptions):
if predicate in expr.predicates:
return True
# SquarePredicate
@SquarePredicate.register(MatrixExpr) # type: ignore
def _(expr, assumptions):
return expr.shape[0] == expr.shape[1]
# SymmetricPredicate
@SymmetricPredicate.register(MatMul) # type: ignore
def _(expr, assumptions):
factor, mmul = expr.as_coeff_mmul()
if all(ask(Q.symmetric(arg), assumptions) for arg in mmul.args):
return True
# TODO: implement sathandlers system for the matrices.
# Now it duplicates the general fact: Implies(Q.diagonal, Q.symmetric).
if ask(Q.diagonal(expr), assumptions):
return True
if len(mmul.args) >= 2 and mmul.args[0] == mmul.args[-1].T:
if len(mmul.args) == 2:
return True
return ask(Q.symmetric(MatMul(*mmul.args[1:-1])), assumptions)
@SymmetricPredicate.register(MatPow) # type: ignore
def _(expr, assumptions):
# only for integer powers
base, exp = expr.args
int_exp = ask(Q.integer(exp), assumptions)
if not int_exp:
return None
non_negative = ask(~Q.negative(exp), assumptions)
if (non_negative or non_negative == False
and ask(Q.invertible(base), assumptions)):
return ask(Q.symmetric(base), assumptions)
return None
@SymmetricPredicate.register(MatAdd) # type: ignore
def _(expr, assumptions):
return all(ask(Q.symmetric(arg), assumptions) for arg in expr.args)
@SymmetricPredicate.register(MatrixSymbol) # type: ignore
def _(expr, assumptions):
if not expr.is_square:
return False
# TODO: implement sathandlers system for the matrices.
# Now it duplicates the general fact: Implies(Q.diagonal, Q.symmetric).
if ask(Q.diagonal(expr), assumptions):
return True
if Q.symmetric(expr) in conjuncts(assumptions):
return True
@SymmetricPredicate.register_many(OneMatrix, ZeroMatrix) # type: ignore
def _(expr, assumptions):
return ask(Q.square(expr), assumptions)
@SymmetricPredicate.register_many(Inverse, Transpose) # type: ignore
def _(expr, assumptions):
return ask(Q.symmetric(expr.arg), assumptions)
@SymmetricPredicate.register(MatrixSlice) # type: ignore
def _(expr, assumptions):
# TODO: implement sathandlers system for the matrices.
# Now it duplicates the general fact: Implies(Q.diagonal, Q.symmetric).
if ask(Q.diagonal(expr), assumptions):
return True
if not expr.on_diag:
return None
else:
return ask(Q.symmetric(expr.parent), assumptions)
@SymmetricPredicate.register(Identity) # type: ignore
def _(expr, assumptions):
return True
# InvertiblePredicate
@InvertiblePredicate.register(MatMul) # type: ignore
def _(expr, assumptions):
factor, mmul = expr.as_coeff_mmul()
if all(ask(Q.invertible(arg), assumptions) for arg in mmul.args):
return True
if any(ask(Q.invertible(arg), assumptions) is False
for arg in mmul.args):
return False
@InvertiblePredicate.register(MatPow) # type: ignore
def _(expr, assumptions):
# only for integer powers
base, exp = expr.args
int_exp = ask(Q.integer(exp), assumptions)
if not int_exp:
return None
if exp.is_negative == False:
return ask(Q.invertible(base), assumptions)
return None
@InvertiblePredicate.register(MatAdd) # type: ignore
def _(expr, assumptions):
return None
@InvertiblePredicate.register(MatrixSymbol) # type: ignore
def _(expr, assumptions):
if not expr.is_square:
return False
if Q.invertible(expr) in conjuncts(assumptions):
return True
@InvertiblePredicate.register_many(Identity, Inverse) # type: ignore
def _(expr, assumptions):
return True
@InvertiblePredicate.register(ZeroMatrix) # type: ignore
def _(expr, assumptions):
return False
@InvertiblePredicate.register(OneMatrix) # type: ignore
def _(expr, assumptions):
return expr.shape[0] == 1 and expr.shape[1] == 1
@InvertiblePredicate.register(Transpose) # type: ignore
def _(expr, assumptions):
return ask(Q.invertible(expr.arg), assumptions)
@InvertiblePredicate.register(MatrixSlice) # type: ignore
def _(expr, assumptions):
if not expr.on_diag:
return None
else:
return ask(Q.invertible(expr.parent), assumptions)
@InvertiblePredicate.register(MatrixBase) # type: ignore
def _(expr, assumptions):
if not expr.is_square:
return False
return expr.rank() == expr.rows
@InvertiblePredicate.register(MatrixExpr) # type: ignore
def _(expr, assumptions):
if not expr.is_square:
return False
return None
@InvertiblePredicate.register(BlockMatrix) # type: ignore
def _(expr, assumptions):
from sympy.matrices.expressions.blockmatrix import reblock_2x2
if not expr.is_square:
return False
if expr.blockshape == (1, 1):
return ask(Q.invertible(expr.blocks[0, 0]), assumptions)
expr = reblock_2x2(expr)
if expr.blockshape == (2, 2):
[[A, B], [C, D]] = expr.blocks.tolist()
if ask(Q.invertible(A), assumptions) == True:
invertible = ask(Q.invertible(D - C * A.I * B), assumptions)
if invertible is not None:
return invertible
if ask(Q.invertible(B), assumptions) == True:
invertible = ask(Q.invertible(C - D * B.I * A), assumptions)
if invertible is not None:
return invertible
if ask(Q.invertible(C), assumptions) == True:
invertible = ask(Q.invertible(B - A * C.I * D), assumptions)
if invertible is not None:
return invertible
if ask(Q.invertible(D), assumptions) == True:
invertible = ask(Q.invertible(A - B * D.I * C), assumptions)
if invertible is not None:
return invertible
return None
@InvertiblePredicate.register(BlockDiagMatrix) # type: ignore
def _(expr, assumptions):
if expr.rowblocksizes != expr.colblocksizes:
return None
return fuzzy_and([ask(Q.invertible(a), assumptions) for a in expr.diag])
# OrthogonalPredicate
@OrthogonalPredicate.register(MatMul) # type: ignore
def _(expr, assumptions):
factor, mmul = expr.as_coeff_mmul()
if (all(ask(Q.orthogonal(arg), assumptions) for arg in mmul.args) and
factor == 1):
return True
if any(ask(Q.invertible(arg), assumptions) is False
for arg in mmul.args):
return False
@OrthogonalPredicate.register(MatPow) # type: ignore
def _(expr, assumptions):
# only for integer powers
base, exp = expr.args
int_exp = ask(Q.integer(exp), assumptions)
if int_exp:
return ask(Q.orthogonal(base), assumptions)
return None
@OrthogonalPredicate.register(MatAdd) # type: ignore
def _(expr, assumptions):
if (len(expr.args) == 1 and
ask(Q.orthogonal(expr.args[0]), assumptions)):
return True
@OrthogonalPredicate.register(MatrixSymbol) # type: ignore
def _(expr, assumptions):
if (not expr.is_square or
ask(Q.invertible(expr), assumptions) is False):
return False
if Q.orthogonal(expr) in conjuncts(assumptions):
return True
@OrthogonalPredicate.register(Identity) # type: ignore
def _(expr, assumptions):
return True
@OrthogonalPredicate.register(ZeroMatrix) # type: ignore
def _(expr, assumptions):
return False
@OrthogonalPredicate.register_many(Inverse, Transpose) # type: ignore
def _(expr, assumptions):
return ask(Q.orthogonal(expr.arg), assumptions)
@OrthogonalPredicate.register(MatrixSlice) # type: ignore
def _(expr, assumptions):
if not expr.on_diag:
return None
else:
return ask(Q.orthogonal(expr.parent), assumptions)
@OrthogonalPredicate.register(Factorization) # type: ignore
def _(expr, assumptions):
return _Factorization(Q.orthogonal, expr, assumptions)
# UnitaryPredicate
@UnitaryPredicate.register(MatMul) # type: ignore
def _(expr, assumptions):
factor, mmul = expr.as_coeff_mmul()
if (all(ask(Q.unitary(arg), assumptions) for arg in mmul.args) and
abs(factor) == 1):
return True
if any(ask(Q.invertible(arg), assumptions) is False
for arg in mmul.args):
return False
@UnitaryPredicate.register(MatPow) # type: ignore
def _(expr, assumptions):
# only for integer powers
base, exp = expr.args
int_exp = ask(Q.integer(exp), assumptions)
if int_exp:
return ask(Q.unitary(base), assumptions)
return None
@UnitaryPredicate.register(MatrixSymbol) # type: ignore
def _(expr, assumptions):
if (not expr.is_square or
ask(Q.invertible(expr), assumptions) is False):
return False
if Q.unitary(expr) in conjuncts(assumptions):
return True
@UnitaryPredicate.register_many(Inverse, Transpose) # type: ignore
def _(expr, assumptions):
return ask(Q.unitary(expr.arg), assumptions)
@UnitaryPredicate.register(MatrixSlice) # type: ignore
def _(expr, assumptions):
if not expr.on_diag:
return None
else:
return ask(Q.unitary(expr.parent), assumptions)
@UnitaryPredicate.register_many(DFT, Identity) # type: ignore
def _(expr, assumptions):
return True
@UnitaryPredicate.register(ZeroMatrix) # type: ignore
def _(expr, assumptions):
return False
@UnitaryPredicate.register(Factorization) # type: ignore
def _(expr, assumptions):
return _Factorization(Q.unitary, expr, assumptions)
# FullRankPredicate
@FullRankPredicate.register(MatMul) # type: ignore
def _(expr, assumptions):
if all(ask(Q.fullrank(arg), assumptions) for arg in expr.args):
return True
@FullRankPredicate.register(MatPow) # type: ignore
def _(expr, assumptions):
# only for integer powers
base, exp = expr.args
int_exp = ask(Q.integer(exp), assumptions)
if int_exp and ask(~Q.negative(exp), assumptions):
return ask(Q.fullrank(base), assumptions)
return None
@FullRankPredicate.register(Identity) # type: ignore
def _(expr, assumptions):
return True
@FullRankPredicate.register(ZeroMatrix) # type: ignore
def _(expr, assumptions):
return False
@FullRankPredicate.register(OneMatrix) # type: ignore
def _(expr, assumptions):
return expr.shape[0] == 1 and expr.shape[1] == 1
@FullRankPredicate.register_many(Inverse, Transpose) # type: ignore
def _(expr, assumptions):
return ask(Q.fullrank(expr.arg), assumptions)
@FullRankPredicate.register(MatrixSlice) # type: ignore
def _(expr, assumptions):
if ask(Q.orthogonal(expr.parent), assumptions):
return True
# PositiveDefinitePredicate
@PositiveDefinitePredicate.register(MatMul) # type: ignore
def _(expr, assumptions):
factor, mmul = expr.as_coeff_mmul()
if (all(ask(Q.positive_definite(arg), assumptions)
for arg in mmul.args) and factor > 0):
return True
if (len(mmul.args) >= 2
and mmul.args[0] == mmul.args[-1].T
and ask(Q.fullrank(mmul.args[0]), assumptions)):
return ask(Q.positive_definite(
MatMul(*mmul.args[1:-1])), assumptions)
@PositiveDefinitePredicate.register(MatPow) # type: ignore
def _(expr, assumptions):
# a power of a positive definite matrix is positive definite
if ask(Q.positive_definite(expr.args[0]), assumptions):
return True
@PositiveDefinitePredicate.register(MatAdd) # type: ignore
def _(expr, assumptions):
if all(ask(Q.positive_definite(arg), assumptions)
for arg in expr.args):
return True
@PositiveDefinitePredicate.register(MatrixSymbol) # type: ignore
def _(expr, assumptions):
if not expr.is_square:
return False
if Q.positive_definite(expr) in conjuncts(assumptions):
return True
@PositiveDefinitePredicate.register(Identity) # type: ignore
def _(expr, assumptions):
return True
@PositiveDefinitePredicate.register(ZeroMatrix) # type: ignore
def _(expr, assumptions):
return False
@PositiveDefinitePredicate.register(OneMatrix) # type: ignore
def _(expr, assumptions):
return expr.shape[0] == 1 and expr.shape[1] == 1
@PositiveDefinitePredicate.register_many(Inverse, Transpose) # type: ignore
def _(expr, assumptions):
return ask(Q.positive_definite(expr.arg), assumptions)
@PositiveDefinitePredicate.register(MatrixSlice) # type: ignore
def _(expr, assumptions):
if not expr.on_diag:
return None
else:
return ask(Q.positive_definite(expr.parent), assumptions)
# UpperTriangularPredicate
@UpperTriangularPredicate.register(MatMul) # type: ignore
def _(expr, assumptions):
factor, matrices = expr.as_coeff_matrices()
if all(ask(Q.upper_triangular(m), assumptions) for m in matrices):
return True
@UpperTriangularPredicate.register(MatAdd) # type: ignore
def _(expr, assumptions):
if all(ask(Q.upper_triangular(arg), assumptions) for arg in expr.args):
return True
@UpperTriangularPredicate.register(MatPow) # type: ignore
def _(expr, assumptions):
# only for integer powers
base, exp = expr.args
int_exp = ask(Q.integer(exp), assumptions)
if not int_exp:
return None
non_negative = ask(~Q.negative(exp), assumptions)
if (non_negative or non_negative == False
and ask(Q.invertible(base), assumptions)):
return ask(Q.upper_triangular(base), assumptions)
return None
@UpperTriangularPredicate.register(MatrixSymbol) # type: ignore
def _(expr, assumptions):
if Q.upper_triangular(expr) in conjuncts(assumptions):
return True
@UpperTriangularPredicate.register_many(Identity, ZeroMatrix) # type: ignore
def _(expr, assumptions):
return True
@UpperTriangularPredicate.register(OneMatrix) # type: ignore
def _(expr, assumptions):
return expr.shape[0] == 1 and expr.shape[1] == 1
@UpperTriangularPredicate.register(Transpose) # type: ignore
def _(expr, assumptions):
return ask(Q.lower_triangular(expr.arg), assumptions)
@UpperTriangularPredicate.register(Inverse) # type: ignore
def _(expr, assumptions):
return ask(Q.upper_triangular(expr.arg), assumptions)
@UpperTriangularPredicate.register(MatrixSlice) # type: ignore
def _(expr, assumptions):
if not expr.on_diag:
return None
else:
return ask(Q.upper_triangular(expr.parent), assumptions)
@UpperTriangularPredicate.register(Factorization) # type: ignore
def _(expr, assumptions):
return _Factorization(Q.upper_triangular, expr, assumptions)
# LowerTriangularPredicate
@LowerTriangularPredicate.register(MatMul) # type: ignore
def _(expr, assumptions):
factor, matrices = expr.as_coeff_matrices()
if all(ask(Q.lower_triangular(m), assumptions) for m in matrices):
return True
@LowerTriangularPredicate.register(MatAdd) # type: ignore
def _(expr, assumptions):
if all(ask(Q.lower_triangular(arg), assumptions) for arg in expr.args):
return True
@LowerTriangularPredicate.register(MatPow) # type: ignore
def _(expr, assumptions):
# only for integer powers
base, exp = expr.args
int_exp = ask(Q.integer(exp), assumptions)
if not int_exp:
return None
non_negative = ask(~Q.negative(exp), assumptions)
if (non_negative or non_negative == False
and ask(Q.invertible(base), assumptions)):
return ask(Q.lower_triangular(base), assumptions)
return None
@LowerTriangularPredicate.register(MatrixSymbol) # type: ignore
def _(expr, assumptions):
if Q.lower_triangular(expr) in conjuncts(assumptions):
return True
@LowerTriangularPredicate.register_many(Identity, ZeroMatrix) # type: ignore
def _(expr, assumptions):
return True
@LowerTriangularPredicate.register(OneMatrix) # type: ignore
def _(expr, assumptions):
return expr.shape[0] == 1 and expr.shape[1] == 1
@LowerTriangularPredicate.register(Transpose) # type: ignore
def _(expr, assumptions):
return ask(Q.upper_triangular(expr.arg), assumptions)
@LowerTriangularPredicate.register(Inverse) # type: ignore
def _(expr, assumptions):
return ask(Q.lower_triangular(expr.arg), assumptions)
@LowerTriangularPredicate.register(MatrixSlice) # type: ignore
def _(expr, assumptions):
if not expr.on_diag:
return None
else:
return ask(Q.lower_triangular(expr.parent), assumptions)
@LowerTriangularPredicate.register(Factorization) # type: ignore
def _(expr, assumptions):
return _Factorization(Q.lower_triangular, expr, assumptions)
# DiagonalPredicate
def _is_empty_or_1x1(expr):
return expr.shape in ((0, 0), (1, 1))
@DiagonalPredicate.register(MatMul) # type: ignore
def _(expr, assumptions):
if _is_empty_or_1x1(expr):
return True
factor, matrices = expr.as_coeff_matrices()
if all(ask(Q.diagonal(m), assumptions) for m in matrices):
return True
@DiagonalPredicate.register(MatPow) # type: ignore
def _(expr, assumptions):
# only for integer powers
base, exp = expr.args
int_exp = ask(Q.integer(exp), assumptions)
if not int_exp:
return None
non_negative = ask(~Q.negative(exp), assumptions)
if (non_negative or non_negative == False
and ask(Q.invertible(base), assumptions)):
return ask(Q.diagonal(base), assumptions)
return None
@DiagonalPredicate.register(MatAdd) # type: ignore
def _(expr, assumptions):
if all(ask(Q.diagonal(arg), assumptions) for arg in expr.args):
return True
@DiagonalPredicate.register(MatrixSymbol) # type: ignore
def _(expr, assumptions):
if _is_empty_or_1x1(expr):
return True
if Q.diagonal(expr) in conjuncts(assumptions):
return True
@DiagonalPredicate.register(OneMatrix) # type: ignore
def _(expr, assumptions):
return expr.shape[0] == 1 and expr.shape[1] == 1
@DiagonalPredicate.register_many(Inverse, Transpose) # type: ignore
def _(expr, assumptions):
return ask(Q.diagonal(expr.arg), assumptions)
@DiagonalPredicate.register(MatrixSlice) # type: ignore
def _(expr, assumptions):
if _is_empty_or_1x1(expr):
return True
if not expr.on_diag:
return None
else:
return ask(Q.diagonal(expr.parent), assumptions)
@DiagonalPredicate.register_many(DiagonalMatrix, DiagMatrix, Identity, ZeroMatrix) # type: ignore
def _(expr, assumptions):
return True
@DiagonalPredicate.register(Factorization) # type: ignore
def _(expr, assumptions):
return _Factorization(Q.diagonal, expr, assumptions)
# IntegerElementsPredicate
def BM_elements(predicate, expr, assumptions):
""" Block Matrix elements. """
return all(ask(predicate(b), assumptions) for b in expr.blocks)
def MS_elements(predicate, expr, assumptions):
""" Matrix Slice elements. """
return ask(predicate(expr.parent), assumptions)
def MatMul_elements(matrix_predicate, scalar_predicate, expr, assumptions):
d = sift(expr.args, lambda x: isinstance(x, MatrixExpr))
factors, matrices = d[False], d[True]
return fuzzy_and([
test_closed_group(Basic(*factors), assumptions, scalar_predicate),
test_closed_group(Basic(*matrices), assumptions, matrix_predicate)])
@IntegerElementsPredicate.register_many(Determinant, HadamardProduct, MatAdd, # type: ignore
Trace, Transpose)
def _(expr, assumptions):
return test_closed_group(expr, assumptions, Q.integer_elements)
@IntegerElementsPredicate.register(MatPow) # type: ignore
def _(expr, assumptions):
# only for integer powers
base, exp = expr.args
int_exp = ask(Q.integer(exp), assumptions)
if not int_exp:
return None
if exp.is_negative == False:
return ask(Q.integer_elements(base), assumptions)
return None
@IntegerElementsPredicate.register_many(Identity, OneMatrix, ZeroMatrix) # type: ignore
def _(expr, assumptions):
return True
@IntegerElementsPredicate.register(MatMul) # type: ignore
def _(expr, assumptions):
return MatMul_elements(Q.integer_elements, Q.integer, expr, assumptions)
@IntegerElementsPredicate.register(MatrixSlice) # type: ignore
def _(expr, assumptions):
return MS_elements(Q.integer_elements, expr, assumptions)
@IntegerElementsPredicate.register(BlockMatrix) # type: ignore
def _(expr, assumptions):
return BM_elements(Q.integer_elements, expr, assumptions)
# RealElementsPredicate
@RealElementsPredicate.register_many(Determinant, Factorization, HadamardProduct, # type: ignore
MatAdd, Trace, Transpose)
def _(expr, assumptions):
return test_closed_group(expr, assumptions, Q.real_elements)
@RealElementsPredicate.register(MatPow) # type: ignore
def _(expr, assumptions):
# only for integer powers
base, exp = expr.args
int_exp = ask(Q.integer(exp), assumptions)
if not int_exp:
return None
non_negative = ask(~Q.negative(exp), assumptions)
if (non_negative or non_negative == False
and ask(Q.invertible(base), assumptions)):
return ask(Q.real_elements(base), assumptions)
return None
@RealElementsPredicate.register(MatMul) # type: ignore
def _(expr, assumptions):
return MatMul_elements(Q.real_elements, Q.real, expr, assumptions)
@RealElementsPredicate.register(MatrixSlice) # type: ignore
def _(expr, assumptions):
return MS_elements(Q.real_elements, expr, assumptions)
@RealElementsPredicate.register(BlockMatrix) # type: ignore
def _(expr, assumptions):
return BM_elements(Q.real_elements, expr, assumptions)
# ComplexElementsPredicate
@ComplexElementsPredicate.register_many(Determinant, Factorization, HadamardProduct, # type: ignore
Inverse, MatAdd, Trace, Transpose)
def _(expr, assumptions):
return test_closed_group(expr, assumptions, Q.complex_elements)
@ComplexElementsPredicate.register(MatPow) # type: ignore
def _(expr, assumptions):
# only for integer powers
base, exp = expr.args
int_exp = ask(Q.integer(exp), assumptions)
if not int_exp:
return None
non_negative = ask(~Q.negative(exp), assumptions)
if (non_negative or non_negative == False
and ask(Q.invertible(base), assumptions)):
return ask(Q.complex_elements(base), assumptions)
return None
@ComplexElementsPredicate.register(MatMul) # type: ignore
def _(expr, assumptions):
return MatMul_elements(Q.complex_elements, Q.complex, expr, assumptions)
@ComplexElementsPredicate.register(MatrixSlice) # type: ignore
def _(expr, assumptions):
return MS_elements(Q.complex_elements, expr, assumptions)
@ComplexElementsPredicate.register(BlockMatrix) # type: ignore
def _(expr, assumptions):
return BM_elements(Q.complex_elements, expr, assumptions)
@ComplexElementsPredicate.register(DFT) # type: ignore
def _(expr, assumptions):
return True
|
21bcdbd20c2c78de1dd4626eb382d2d7b5421244ca1d529550780a613dca011f | """
Handlers related to order relations: positive, negative, etc.
"""
from sympy.assumptions import Q, ask
from sympy.core import Add, Basic, Expr, Mul, Pow
from sympy.core.logic import fuzzy_not, fuzzy_and, fuzzy_or
from sympy.core.numbers import E, ImaginaryUnit, NaN, I, pi
from sympy.functions import Abs, acos, acot, asin, atan, exp, factorial, log
from sympy.matrices import Determinant, Trace
from sympy.matrices.expressions.matexpr import MatrixElement
from sympy.multipledispatch import MDNotImplementedError
from ..predicates.order import (NegativePredicate, NonNegativePredicate,
NonZeroPredicate, ZeroPredicate, NonPositivePredicate, PositivePredicate,
ExtendedNegativePredicate, ExtendedNonNegativePredicate,
ExtendedNonPositivePredicate, ExtendedNonZeroPredicate,
ExtendedPositivePredicate,)
# NegativePredicate
def _NegativePredicate_number(expr, assumptions):
r, i = expr.as_real_imag()
# If the imaginary part can symbolically be shown to be zero then
# we just evaluate the real part; otherwise we evaluate the imaginary
# part to see if it actually evaluates to zero and if it does then
# we make the comparison between the real part and zero.
if not i:
r = r.evalf(2)
if r._prec != 1:
return r < 0
else:
i = i.evalf(2)
if i._prec != 1:
if i != 0:
return False
r = r.evalf(2)
if r._prec != 1:
return r < 0
@NegativePredicate.register(Basic) # type: ignore
def _(expr, assumptions):
if expr.is_number:
return _NegativePredicate_number(expr, assumptions)
@NegativePredicate.register(Expr) # type: ignore
def _(expr, assumptions):
ret = expr.is_negative
if ret is None:
raise MDNotImplementedError
return ret
@NegativePredicate.register(Add) # type: ignore
def _(expr, assumptions):
"""
Positive + Positive -> Positive,
Negative + Negative -> Negative
"""
if expr.is_number:
return _NegativePredicate_number(expr, assumptions)
r = ask(Q.real(expr), assumptions)
if r is not True:
return r
nonpos = 0
for arg in expr.args:
if ask(Q.negative(arg), assumptions) is not True:
if ask(Q.positive(arg), assumptions) is False:
nonpos += 1
else:
break
else:
if nonpos < len(expr.args):
return True
@NegativePredicate.register(Mul) # type: ignore
def _(expr, assumptions):
if expr.is_number:
return _NegativePredicate_number(expr, assumptions)
result = None
for arg in expr.args:
if result is None:
result = False
if ask(Q.negative(arg), assumptions):
result = not result
elif ask(Q.positive(arg), assumptions):
pass
else:
return
return result
@NegativePredicate.register(Pow) # type: ignore
def _(expr, assumptions):
"""
Real ** Even -> NonNegative
Real ** Odd -> same_as_base
NonNegative ** Positive -> NonNegative
"""
if expr.base == E:
# Exponential is always positive:
if ask(Q.real(expr.exp), assumptions):
return False
return
if expr.is_number:
return _NegativePredicate_number(expr, assumptions)
if ask(Q.real(expr.base), assumptions):
if ask(Q.positive(expr.base), assumptions):
if ask(Q.real(expr.exp), assumptions):
return False
if ask(Q.even(expr.exp), assumptions):
return False
if ask(Q.odd(expr.exp), assumptions):
return ask(Q.negative(expr.base), assumptions)
@NegativePredicate.register_many(Abs, ImaginaryUnit) # type: ignore
def _(expr, assumptions):
return False
@NegativePredicate.register(exp) # type: ignore
def _(expr, assumptions):
if ask(Q.real(expr.exp), assumptions):
return False
raise MDNotImplementedError
# NonNegativePredicate
@NonNegativePredicate.register(Basic) # type: ignore
def _(expr, assumptions):
if expr.is_number:
notnegative = fuzzy_not(_NegativePredicate_number(expr, assumptions))
if notnegative:
return ask(Q.real(expr), assumptions)
else:
return notnegative
@NonNegativePredicate.register(Expr) # type: ignore
def _(expr, assumptions):
ret = expr.is_nonnegative
if ret is None:
raise MDNotImplementedError
return ret
# NonZeroPredicate
@NonZeroPredicate.register(Expr) # type: ignore
def _(expr, assumptions):
ret = expr.is_nonzero
if ret is None:
raise MDNotImplementedError
return ret
@NonZeroPredicate.register(Basic) # type: ignore
def _(expr, assumptions):
if ask(Q.real(expr)) is False:
return False
if expr.is_number:
# if there are no symbols just evalf
i = expr.evalf(2)
def nonz(i):
if i._prec != 1:
return i != 0
return fuzzy_or(nonz(i) for i in i.as_real_imag())
@NonZeroPredicate.register(Add) # type: ignore
def _(expr, assumptions):
if all(ask(Q.positive(x), assumptions) for x in expr.args) \
or all(ask(Q.negative(x), assumptions) for x in expr.args):
return True
@NonZeroPredicate.register(Mul) # type: ignore
def _(expr, assumptions):
for arg in expr.args:
result = ask(Q.nonzero(arg), assumptions)
if result:
continue
return result
return True
@NonZeroPredicate.register(Pow) # type: ignore
def _(expr, assumptions):
return ask(Q.nonzero(expr.base), assumptions)
@NonZeroPredicate.register(Abs) # type: ignore
def _(expr, assumptions):
return ask(Q.nonzero(expr.args[0]), assumptions)
@NonZeroPredicate.register(NaN) # type: ignore
def _(expr, assumptions):
return None
# ZeroPredicate
@ZeroPredicate.register(Expr) # type: ignore
def _(expr, assumptions):
ret = expr.is_zero
if ret is None:
raise MDNotImplementedError
return ret
@ZeroPredicate.register(Basic) # type: ignore
def _(expr, assumptions):
return fuzzy_and([fuzzy_not(ask(Q.nonzero(expr), assumptions)),
ask(Q.real(expr), assumptions)])
@ZeroPredicate.register(Mul) # type: ignore
def _(expr, assumptions):
# TODO: This should be deducible from the nonzero handler
return fuzzy_or(ask(Q.zero(arg), assumptions) for arg in expr.args)
# NonPositivePredicate
@NonPositivePredicate.register(Expr) # type: ignore
def _(expr, assumptions):
ret = expr.is_nonpositive
if ret is None:
raise MDNotImplementedError
return ret
@NonPositivePredicate.register(Basic) # type: ignore
def _(expr, assumptions):
if expr.is_number:
notpositive = fuzzy_not(_PositivePredicate_number(expr, assumptions))
if notpositive:
return ask(Q.real(expr), assumptions)
else:
return notpositive
# PositivePredicate
def _PositivePredicate_number(expr, assumptions):
r, i = expr.as_real_imag()
# If the imaginary part can symbolically be shown to be zero then
# we just evaluate the real part; otherwise we evaluate the imaginary
# part to see if it actually evaluates to zero and if it does then
# we make the comparison between the real part and zero.
if not i:
r = r.evalf(2)
if r._prec != 1:
return r > 0
else:
i = i.evalf(2)
if i._prec != 1:
if i != 0:
return False
r = r.evalf(2)
if r._prec != 1:
return r > 0
@PositivePredicate.register(Expr) # type: ignore
def _(expr, assumptions):
ret = expr.is_positive
if ret is None:
raise MDNotImplementedError
return ret
@PositivePredicate.register(Basic) # type: ignore
def _(expr, assumptions):
if expr.is_number:
return _PositivePredicate_number(expr, assumptions)
@PositivePredicate.register(Mul) # type: ignore
def _(expr, assumptions):
if expr.is_number:
return _PositivePredicate_number(expr, assumptions)
result = True
for arg in expr.args:
if ask(Q.positive(arg), assumptions):
continue
elif ask(Q.negative(arg), assumptions):
result = result ^ True
else:
return
return result
@PositivePredicate.register(Add) # type: ignore
def _(expr, assumptions):
if expr.is_number:
return _PositivePredicate_number(expr, assumptions)
r = ask(Q.real(expr), assumptions)
if r is not True:
return r
nonneg = 0
for arg in expr.args:
if ask(Q.positive(arg), assumptions) is not True:
if ask(Q.negative(arg), assumptions) is False:
nonneg += 1
else:
break
else:
if nonneg < len(expr.args):
return True
@PositivePredicate.register(Pow) # type: ignore
def _(expr, assumptions):
if expr.base == E:
if ask(Q.real(expr.exp), assumptions):
return True
if ask(Q.imaginary(expr.exp), assumptions):
return ask(Q.even(expr.exp/(I*pi)), assumptions)
return
if expr.is_number:
return _PositivePredicate_number(expr, assumptions)
if ask(Q.positive(expr.base), assumptions):
if ask(Q.real(expr.exp), assumptions):
return True
if ask(Q.negative(expr.base), assumptions):
if ask(Q.even(expr.exp), assumptions):
return True
if ask(Q.odd(expr.exp), assumptions):
return False
@PositivePredicate.register(exp) # type: ignore
def _(expr, assumptions):
if ask(Q.real(expr.exp), assumptions):
return True
if ask(Q.imaginary(expr.exp), assumptions):
return ask(Q.even(expr.exp/(I*pi)), assumptions)
@PositivePredicate.register(log) # type: ignore
def _(expr, assumptions):
r = ask(Q.real(expr.args[0]), assumptions)
if r is not True:
return r
if ask(Q.positive(expr.args[0] - 1), assumptions):
return True
if ask(Q.negative(expr.args[0] - 1), assumptions):
return False
@PositivePredicate.register(factorial) # type: ignore
def _(expr, assumptions):
x = expr.args[0]
if ask(Q.integer(x) & Q.positive(x), assumptions):
return True
@PositivePredicate.register(ImaginaryUnit) # type: ignore
def _(expr, assumptions):
return False
@PositivePredicate.register(Abs) # type: ignore
def _(expr, assumptions):
return ask(Q.nonzero(expr), assumptions)
@PositivePredicate.register(Trace) # type: ignore
def _(expr, assumptions):
if ask(Q.positive_definite(expr.arg), assumptions):
return True
@PositivePredicate.register(Determinant) # type: ignore
def _(expr, assumptions):
if ask(Q.positive_definite(expr.arg), assumptions):
return True
@PositivePredicate.register(MatrixElement) # type: ignore
def _(expr, assumptions):
if (expr.i == expr.j
and ask(Q.positive_definite(expr.parent), assumptions)):
return True
@PositivePredicate.register(atan) # type: ignore
def _(expr, assumptions):
return ask(Q.positive(expr.args[0]), assumptions)
@PositivePredicate.register(asin) # type: ignore
def _(expr, assumptions):
x = expr.args[0]
if ask(Q.positive(x) & Q.nonpositive(x - 1), assumptions):
return True
if ask(Q.negative(x) & Q.nonnegative(x + 1), assumptions):
return False
@PositivePredicate.register(acos) # type: ignore
def _(expr, assumptions):
x = expr.args[0]
if ask(Q.nonpositive(x - 1) & Q.nonnegative(x + 1), assumptions):
return True
@PositivePredicate.register(acot) # type: ignore
def _(expr, assumptions):
return ask(Q.real(expr.args[0]), assumptions)
@PositivePredicate.register(NaN) # type: ignore
def _(expr, assumptions):
return None
# ExtendedNegativePredicate
@ExtendedNegativePredicate.register(object) # type: ignore
def _(expr, assumptions):
return ask(Q.negative(expr) | Q.negative_infinite(expr), assumptions)
# ExtendedPositivePredicate
@ExtendedPositivePredicate.register(object) # type: ignore
def _(expr, assumptions):
return ask(Q.positive(expr) | Q.positive_infinite(expr), assumptions)
# ExtendedNonZeroPredicate
@ExtendedNonZeroPredicate.register(object) # type: ignore
def _(expr, assumptions):
return ask(
Q.negative_infinite(expr) | Q.negative(expr) | Q.positive(expr) | Q.positive_infinite(expr),
assumptions)
# ExtendedNonPositivePredicate
@ExtendedNonPositivePredicate.register(object) # type: ignore
def _(expr, assumptions):
return ask(
Q.negative_infinite(expr) | Q.negative(expr) | Q.zero(expr),
assumptions)
# ExtendedNonNegativePredicate
@ExtendedNonNegativePredicate.register(object) # type: ignore
def _(expr, assumptions):
return ask(
Q.zero(expr) | Q.positive(expr) | Q.positive_infinite(expr),
assumptions)
|
6fa525c26ea11a628d2867758d3050b0a7af20778d04f4764fb11e7925726357 | """
Handlers for predicates related to set membership: integer, rational, etc.
"""
from sympy.assumptions import Q, ask
from sympy.core import Add, Basic, Expr, Mul, Pow, S
from sympy.core.numbers import (AlgebraicNumber, ComplexInfinity, Exp1, Float,
GoldenRatio, ImaginaryUnit, Infinity, Integer, NaN, NegativeInfinity,
Number, NumberSymbol, Pi, pi, Rational, TribonacciConstant, E)
from sympy.core.logic import fuzzy_bool
from sympy.functions import (Abs, acos, acot, asin, atan, cos, cot, exp, im,
log, re, sin, tan)
from sympy.core.numbers import I
from sympy.core.relational import Eq
from sympy.functions.elementary.complexes import conjugate
from sympy.matrices import Determinant, MatrixBase, Trace
from sympy.matrices.expressions.matexpr import MatrixElement
from sympy.multipledispatch import MDNotImplementedError
from .common import test_closed_group
from ..predicates.sets import (IntegerPredicate, RationalPredicate,
IrrationalPredicate, RealPredicate, ExtendedRealPredicate,
HermitianPredicate, ComplexPredicate, ImaginaryPredicate,
AntihermitianPredicate, AlgebraicPredicate)
# IntegerPredicate
def _IntegerPredicate_number(expr, assumptions):
# helper function
try:
i = int(expr.round())
if not (expr - i).equals(0):
raise TypeError
return True
except TypeError:
return False
@IntegerPredicate.register_many(int, Integer) # type:ignore
def _(expr, assumptions):
return True
@IntegerPredicate.register_many(Exp1, GoldenRatio, ImaginaryUnit, Infinity, # type: ignore
NegativeInfinity, Pi, Rational, TribonacciConstant)
def _(expr, assumptions):
return False
@IntegerPredicate.register(Expr) # type: ignore
def _(expr, assumptions):
ret = expr.is_integer
if ret is None:
raise MDNotImplementedError
return ret
@IntegerPredicate.register_many(Add, Pow) # type: ignore
def _(expr, assumptions):
"""
* Integer + Integer -> Integer
* Integer + !Integer -> !Integer
* !Integer + !Integer -> ?
"""
if expr.is_number:
return _IntegerPredicate_number(expr, assumptions)
return test_closed_group(expr, assumptions, Q.integer)
@IntegerPredicate.register(Mul) # type: ignore
def _(expr, assumptions):
"""
* Integer*Integer -> Integer
* Integer*Irrational -> !Integer
* Odd/Even -> !Integer
* Integer*Rational -> ?
"""
if expr.is_number:
return _IntegerPredicate_number(expr, assumptions)
_output = True
for arg in expr.args:
if not ask(Q.integer(arg), assumptions):
if arg.is_Rational:
if arg.q == 2:
return ask(Q.even(2*expr), assumptions)
if ~(arg.q & 1):
return None
elif ask(Q.irrational(arg), assumptions):
if _output:
_output = False
else:
return
else:
return
return _output
@IntegerPredicate.register(Abs) # type: ignore
def _(expr, assumptions):
return ask(Q.integer(expr.args[0]), assumptions)
@IntegerPredicate.register_many(Determinant, MatrixElement, Trace) # type: ignore
def _(expr, assumptions):
return ask(Q.integer_elements(expr.args[0]), assumptions)
# RationalPredicate
@RationalPredicate.register(Rational) # type: ignore
def _(expr, assumptions):
return True
@RationalPredicate.register(Float) # type: ignore
def _(expr, assumptions):
return None
@RationalPredicate.register_many(Exp1, GoldenRatio, ImaginaryUnit, Infinity, # type: ignore
NegativeInfinity, Pi, TribonacciConstant)
def _(expr, assumptions):
return False
@RationalPredicate.register(Expr) # type: ignore
def _(expr, assumptions):
ret = expr.is_rational
if ret is None:
raise MDNotImplementedError
return ret
@RationalPredicate.register_many(Add, Mul) # type: ignore
def _(expr, assumptions):
"""
* Rational + Rational -> Rational
* Rational + !Rational -> !Rational
* !Rational + !Rational -> ?
"""
if expr.is_number:
if expr.as_real_imag()[1]:
return False
return test_closed_group(expr, assumptions, Q.rational)
@RationalPredicate.register(Pow) # type: ignore
def _(expr, assumptions):
"""
* Rational ** Integer -> Rational
* Irrational ** Rational -> Irrational
* Rational ** Irrational -> ?
"""
if expr.base == E:
x = expr.exp
if ask(Q.rational(x), assumptions):
return ask(~Q.nonzero(x), assumptions)
return
if ask(Q.integer(expr.exp), assumptions):
return ask(Q.rational(expr.base), assumptions)
elif ask(Q.rational(expr.exp), assumptions):
if ask(Q.prime(expr.base), assumptions):
return False
@RationalPredicate.register_many(asin, atan, cos, sin, tan) # type: ignore
def _(expr, assumptions):
x = expr.args[0]
if ask(Q.rational(x), assumptions):
return ask(~Q.nonzero(x), assumptions)
@RationalPredicate.register(exp) # type: ignore
def _(expr, assumptions):
x = expr.exp
if ask(Q.rational(x), assumptions):
return ask(~Q.nonzero(x), assumptions)
@RationalPredicate.register_many(acot, cot) # type: ignore
def _(expr, assumptions):
x = expr.args[0]
if ask(Q.rational(x), assumptions):
return False
@RationalPredicate.register_many(acos, log) # type: ignore
def _(expr, assumptions):
x = expr.args[0]
if ask(Q.rational(x), assumptions):
return ask(~Q.nonzero(x - 1), assumptions)
# IrrationalPredicate
@IrrationalPredicate.register(Expr) # type: ignore
def _(expr, assumptions):
ret = expr.is_irrational
if ret is None:
raise MDNotImplementedError
return ret
@IrrationalPredicate.register(Basic) # type: ignore
def _(expr, assumptions):
_real = ask(Q.real(expr), assumptions)
if _real:
_rational = ask(Q.rational(expr), assumptions)
if _rational is None:
return None
return not _rational
else:
return _real
# RealPredicate
def _RealPredicate_number(expr, assumptions):
# let as_real_imag() work first since the expression may
# be simpler to evaluate
i = expr.as_real_imag()[1].evalf(2)
if i._prec != 1:
return not i
# allow None to be returned if we couldn't show for sure
# that i was 0
@RealPredicate.register_many(Abs, Exp1, Float, GoldenRatio, im, Pi, Rational, # type: ignore
re, TribonacciConstant)
def _(expr, assumptions):
return True
@RealPredicate.register_many(ImaginaryUnit, Infinity, NegativeInfinity) # type: ignore
def _(expr, assumptions):
return False
@RealPredicate.register(Expr) # type: ignore
def _(expr, assumptions):
ret = expr.is_real
if ret is None:
raise MDNotImplementedError
return ret
@RealPredicate.register(Add) # type: ignore
def _(expr, assumptions):
"""
* Real + Real -> Real
* Real + (Complex & !Real) -> !Real
"""
if expr.is_number:
return _RealPredicate_number(expr, assumptions)
return test_closed_group(expr, assumptions, Q.real)
@RealPredicate.register(Mul) # type: ignore
def _(expr, assumptions):
"""
* Real*Real -> Real
* Real*Imaginary -> !Real
* Imaginary*Imaginary -> Real
"""
if expr.is_number:
return _RealPredicate_number(expr, assumptions)
result = True
for arg in expr.args:
if ask(Q.real(arg), assumptions):
pass
elif ask(Q.imaginary(arg), assumptions):
result = result ^ True
else:
break
else:
return result
@RealPredicate.register(Pow) # type: ignore
def _(expr, assumptions):
"""
* Real**Integer -> Real
* Positive**Real -> Real
* Real**(Integer/Even) -> Real if base is nonnegative
* Real**(Integer/Odd) -> Real
* Imaginary**(Integer/Even) -> Real
* Imaginary**(Integer/Odd) -> not Real
* Imaginary**Real -> ? since Real could be 0 (giving real)
or 1 (giving imaginary)
* b**Imaginary -> Real if log(b) is imaginary and b != 0
and exponent != integer multiple of
I*pi/log(b)
* Real**Real -> ? e.g. sqrt(-1) is imaginary and
sqrt(2) is not
"""
if expr.is_number:
return _RealPredicate_number(expr, assumptions)
if expr.base == E:
return ask(
Q.integer(expr.exp/I/pi) | Q.real(expr.exp), assumptions
)
if expr.base.func == exp or (expr.base.is_Pow and expr.base.base == E):
if ask(Q.imaginary(expr.base.exp), assumptions):
if ask(Q.imaginary(expr.exp), assumptions):
return True
# If the i = (exp's arg)/(I*pi) is an integer or half-integer
# multiple of I*pi then 2*i will be an integer. In addition,
# exp(i*I*pi) = (-1)**i so the overall realness of the expr
# can be determined by replacing exp(i*I*pi) with (-1)**i.
i = expr.base.exp/I/pi
if ask(Q.integer(2*i), assumptions):
return ask(Q.real((S.NegativeOne**i)**expr.exp), assumptions)
return
if ask(Q.imaginary(expr.base), assumptions):
if ask(Q.integer(expr.exp), assumptions):
odd = ask(Q.odd(expr.exp), assumptions)
if odd is not None:
return not odd
return
if ask(Q.imaginary(expr.exp), assumptions):
imlog = ask(Q.imaginary(log(expr.base)), assumptions)
if imlog is not None:
# I**i -> real, log(I) is imag;
# (2*I)**i -> complex, log(2*I) is not imag
return imlog
if ask(Q.real(expr.base), assumptions):
if ask(Q.real(expr.exp), assumptions):
if expr.exp.is_Rational and \
ask(Q.even(expr.exp.q), assumptions):
return ask(Q.positive(expr.base), assumptions)
elif ask(Q.integer(expr.exp), assumptions):
return True
elif ask(Q.positive(expr.base), assumptions):
return True
elif ask(Q.negative(expr.base), assumptions):
return False
@RealPredicate.register_many(cos, sin) # type: ignore
def _(expr, assumptions):
if ask(Q.real(expr.args[0]), assumptions):
return True
@RealPredicate.register(exp) # type: ignore
def _(expr, assumptions):
return ask(
Q.integer(expr.exp/I/pi) | Q.real(expr.exp), assumptions
)
@RealPredicate.register(log) # type: ignore
def _(expr, assumptions):
return ask(Q.positive(expr.args[0]), assumptions)
@RealPredicate.register_many(Determinant, MatrixElement, Trace) # type: ignore
def _(expr, assumptions):
return ask(Q.real_elements(expr.args[0]), assumptions)
# ExtendedRealPredicate
@ExtendedRealPredicate.register(object) # type: ignore
def _(expr, assumptions):
return ask(Q.negative_infinite(expr)
| Q.negative(expr)
| Q.zero(expr)
| Q.positive(expr)
| Q.positive_infinite(expr),
assumptions)
@ExtendedRealPredicate.register_many(Infinity, NegativeInfinity) # type: ignore
def _(expr, assumptions):
return True
@ExtendedRealPredicate.register_many(Add, Mul, Pow) # type:ignore
def _(expr, assumptions):
return test_closed_group(expr, assumptions, Q.extended_real)
# HermitianPredicate
@HermitianPredicate.register(object) # type:ignore
def _(expr, assumptions):
if isinstance(expr, MatrixBase):
return None
return ask(Q.real(expr), assumptions)
@HermitianPredicate.register(Add) # type:ignore
def _(expr, assumptions):
"""
* Hermitian + Hermitian -> Hermitian
* Hermitian + !Hermitian -> !Hermitian
"""
if expr.is_number:
raise MDNotImplementedError
return test_closed_group(expr, assumptions, Q.hermitian)
@HermitianPredicate.register(Mul) # type:ignore
def _(expr, assumptions):
"""
As long as there is at most only one noncommutative term:
* Hermitian*Hermitian -> Hermitian
* Hermitian*Antihermitian -> !Hermitian
* Antihermitian*Antihermitian -> Hermitian
"""
if expr.is_number:
raise MDNotImplementedError
nccount = 0
result = True
for arg in expr.args:
if ask(Q.antihermitian(arg), assumptions):
result = result ^ True
elif not ask(Q.hermitian(arg), assumptions):
break
if ask(~Q.commutative(arg), assumptions):
nccount += 1
if nccount > 1:
break
else:
return result
@HermitianPredicate.register(Pow) # type:ignore
def _(expr, assumptions):
"""
* Hermitian**Integer -> Hermitian
"""
if expr.is_number:
raise MDNotImplementedError
if expr.base == E:
if ask(Q.hermitian(expr.exp), assumptions):
return True
raise MDNotImplementedError
if ask(Q.hermitian(expr.base), assumptions):
if ask(Q.integer(expr.exp), assumptions):
return True
raise MDNotImplementedError
@HermitianPredicate.register_many(cos, sin) # type:ignore
def _(expr, assumptions):
if ask(Q.hermitian(expr.args[0]), assumptions):
return True
raise MDNotImplementedError
@HermitianPredicate.register(exp) # type:ignore
def _(expr, assumptions):
if ask(Q.hermitian(expr.exp), assumptions):
return True
raise MDNotImplementedError
@HermitianPredicate.register(MatrixBase) # type:ignore
def _(mat, assumptions):
rows, cols = mat.shape
ret_val = True
for i in range(rows):
for j in range(i, cols):
cond = fuzzy_bool(Eq(mat[i, j], conjugate(mat[j, i])))
if cond is None:
ret_val = None
if cond == False:
return False
if ret_val is None:
raise MDNotImplementedError
return ret_val
# ComplexPredicate
@ComplexPredicate.register_many(Abs, cos, exp, im, ImaginaryUnit, log, Number, # type:ignore
NumberSymbol, re, sin)
def _(expr, assumptions):
return True
@ComplexPredicate.register_many(Infinity, NegativeInfinity) # type:ignore
def _(expr, assumptions):
return False
@ComplexPredicate.register(Expr) # type:ignore
def _(expr, assumptions):
ret = expr.is_complex
if ret is None:
raise MDNotImplementedError
return ret
@ComplexPredicate.register_many(Add, Mul) # type:ignore
def _(expr, assumptions):
return test_closed_group(expr, assumptions, Q.complex)
@ComplexPredicate.register(Pow) # type:ignore
def _(expr, assumptions):
if expr.base == E:
return True
return test_closed_group(expr, assumptions, Q.complex)
@ComplexPredicate.register_many(Determinant, MatrixElement, Trace) # type:ignore
def _(expr, assumptions):
return ask(Q.complex_elements(expr.args[0]), assumptions)
@ComplexPredicate.register(NaN) # type:ignore
def _(expr, assumptions):
return None
# ImaginaryPredicate
def _Imaginary_number(expr, assumptions):
# let as_real_imag() work first since the expression may
# be simpler to evaluate
r = expr.as_real_imag()[0].evalf(2)
if r._prec != 1:
return not r
# allow None to be returned if we couldn't show for sure
# that r was 0
@ImaginaryPredicate.register(ImaginaryUnit) # type:ignore
def _(expr, assumptions):
return True
@ImaginaryPredicate.register(Expr) # type:ignore
def _(expr, assumptions):
ret = expr.is_imaginary
if ret is None:
raise MDNotImplementedError
return ret
@ImaginaryPredicate.register(Add) # type:ignore
def _(expr, assumptions):
"""
* Imaginary + Imaginary -> Imaginary
* Imaginary + Complex -> ?
* Imaginary + Real -> !Imaginary
"""
if expr.is_number:
return _Imaginary_number(expr, assumptions)
reals = 0
for arg in expr.args:
if ask(Q.imaginary(arg), assumptions):
pass
elif ask(Q.real(arg), assumptions):
reals += 1
else:
break
else:
if reals == 0:
return True
if reals in (1, len(expr.args)):
# two reals could sum 0 thus giving an imaginary
return False
@ImaginaryPredicate.register(Mul) # type:ignore
def _(expr, assumptions):
"""
* Real*Imaginary -> Imaginary
* Imaginary*Imaginary -> Real
"""
if expr.is_number:
return _Imaginary_number(expr, assumptions)
result = False
reals = 0
for arg in expr.args:
if ask(Q.imaginary(arg), assumptions):
result = result ^ True
elif not ask(Q.real(arg), assumptions):
break
else:
if reals == len(expr.args):
return False
return result
@ImaginaryPredicate.register(Pow) # type:ignore
def _(expr, assumptions):
"""
* Imaginary**Odd -> Imaginary
* Imaginary**Even -> Real
* b**Imaginary -> !Imaginary if exponent is an integer
multiple of I*pi/log(b)
* Imaginary**Real -> ?
* Positive**Real -> Real
* Negative**Integer -> Real
* Negative**(Integer/2) -> Imaginary
* Negative**Real -> not Imaginary if exponent is not Rational
"""
if expr.is_number:
return _Imaginary_number(expr, assumptions)
if expr.base == E:
a = expr.exp/I/pi
return ask(Q.integer(2*a) & ~Q.integer(a), assumptions)
if expr.base.func == exp or (expr.base.is_Pow and expr.base.base == E):
if ask(Q.imaginary(expr.base.exp), assumptions):
if ask(Q.imaginary(expr.exp), assumptions):
return False
i = expr.base.exp/I/pi
if ask(Q.integer(2*i), assumptions):
return ask(Q.imaginary((S.NegativeOne**i)**expr.exp), assumptions)
if ask(Q.imaginary(expr.base), assumptions):
if ask(Q.integer(expr.exp), assumptions):
odd = ask(Q.odd(expr.exp), assumptions)
if odd is not None:
return odd
return
if ask(Q.imaginary(expr.exp), assumptions):
imlog = ask(Q.imaginary(log(expr.base)), assumptions)
if imlog is not None:
# I**i -> real; (2*I)**i -> complex ==> not imaginary
return False
if ask(Q.real(expr.base) & Q.real(expr.exp), assumptions):
if ask(Q.positive(expr.base), assumptions):
return False
else:
rat = ask(Q.rational(expr.exp), assumptions)
if not rat:
return rat
if ask(Q.integer(expr.exp), assumptions):
return False
else:
half = ask(Q.integer(2*expr.exp), assumptions)
if half:
return ask(Q.negative(expr.base), assumptions)
return half
@ImaginaryPredicate.register(log) # type:ignore
def _(expr, assumptions):
if ask(Q.real(expr.args[0]), assumptions):
if ask(Q.positive(expr.args[0]), assumptions):
return False
return
# XXX it should be enough to do
# return ask(Q.nonpositive(expr.args[0]), assumptions)
# but ask(Q.nonpositive(exp(x)), Q.imaginary(x)) -> None;
# it should return True since exp(x) will be either 0 or complex
if expr.args[0].func == exp or (expr.args[0].is_Pow and expr.args[0].base == E):
if expr.args[0].exp in [I, -I]:
return True
im = ask(Q.imaginary(expr.args[0]), assumptions)
if im is False:
return False
@ImaginaryPredicate.register(exp) # type:ignore
def _(expr, assumptions):
a = expr.exp/I/pi
return ask(Q.integer(2*a) & ~Q.integer(a), assumptions)
@ImaginaryPredicate.register_many(Number, NumberSymbol) # type:ignore
def _(expr, assumptions):
return not (expr.as_real_imag()[1] == 0)
@ImaginaryPredicate.register(NaN) # type:ignore
def _(expr, assumptions):
return None
# AntihermitianPredicate
@AntihermitianPredicate.register(object) # type:ignore
def _(expr, assumptions):
if isinstance(expr, MatrixBase):
return None
if ask(Q.zero(expr), assumptions):
return True
return ask(Q.imaginary(expr), assumptions)
@AntihermitianPredicate.register(Add) # type:ignore
def _(expr, assumptions):
"""
* Antihermitian + Antihermitian -> Antihermitian
* Antihermitian + !Antihermitian -> !Antihermitian
"""
if expr.is_number:
raise MDNotImplementedError
return test_closed_group(expr, assumptions, Q.antihermitian)
@AntihermitianPredicate.register(Mul) # type:ignore
def _(expr, assumptions):
"""
As long as there is at most only one noncommutative term:
* Hermitian*Hermitian -> !Antihermitian
* Hermitian*Antihermitian -> Antihermitian
* Antihermitian*Antihermitian -> !Antihermitian
"""
if expr.is_number:
raise MDNotImplementedError
nccount = 0
result = False
for arg in expr.args:
if ask(Q.antihermitian(arg), assumptions):
result = result ^ True
elif not ask(Q.hermitian(arg), assumptions):
break
if ask(~Q.commutative(arg), assumptions):
nccount += 1
if nccount > 1:
break
else:
return result
@AntihermitianPredicate.register(Pow) # type:ignore
def _(expr, assumptions):
"""
* Hermitian**Integer -> !Antihermitian
* Antihermitian**Even -> !Antihermitian
* Antihermitian**Odd -> Antihermitian
"""
if expr.is_number:
raise MDNotImplementedError
if ask(Q.hermitian(expr.base), assumptions):
if ask(Q.integer(expr.exp), assumptions):
return False
elif ask(Q.antihermitian(expr.base), assumptions):
if ask(Q.even(expr.exp), assumptions):
return False
elif ask(Q.odd(expr.exp), assumptions):
return True
raise MDNotImplementedError
@AntihermitianPredicate.register(MatrixBase) # type:ignore
def _(mat, assumptions):
rows, cols = mat.shape
ret_val = True
for i in range(rows):
for j in range(i, cols):
cond = fuzzy_bool(Eq(mat[i, j], -conjugate(mat[j, i])))
if cond is None:
ret_val = None
if cond == False:
return False
if ret_val is None:
raise MDNotImplementedError
return ret_val
# AlgebraicPredicate
@AlgebraicPredicate.register_many(AlgebraicNumber, Float, GoldenRatio, # type:ignore
ImaginaryUnit, TribonacciConstant)
def _(expr, assumptions):
return True
@AlgebraicPredicate.register_many(ComplexInfinity, Exp1, Infinity, # type:ignore
NegativeInfinity, Pi)
def _(expr, assumptions):
return False
@AlgebraicPredicate.register_many(Add, Mul) # type:ignore
def _(expr, assumptions):
return test_closed_group(expr, assumptions, Q.algebraic)
@AlgebraicPredicate.register(Pow) # type:ignore
def _(expr, assumptions):
if expr.base == E:
if ask(Q.algebraic(expr.exp), assumptions):
return ask(~Q.nonzero(expr.exp), assumptions)
return
return expr.exp.is_Rational and ask(Q.algebraic(expr.base), assumptions)
@AlgebraicPredicate.register(Rational) # type:ignore
def _(expr, assumptions):
return expr.q != 0
@AlgebraicPredicate.register_many(asin, atan, cos, sin, tan) # type:ignore
def _(expr, assumptions):
x = expr.args[0]
if ask(Q.algebraic(x), assumptions):
return ask(~Q.nonzero(x), assumptions)
@AlgebraicPredicate.register(exp) # type:ignore
def _(expr, assumptions):
x = expr.exp
if ask(Q.algebraic(x), assumptions):
return ask(~Q.nonzero(x), assumptions)
@AlgebraicPredicate.register_many(acot, cot) # type:ignore
def _(expr, assumptions):
x = expr.args[0]
if ask(Q.algebraic(x), assumptions):
return False
@AlgebraicPredicate.register_many(acos, log) # type:ignore
def _(expr, assumptions):
x = expr.args[0]
if ask(Q.algebraic(x), assumptions):
return ask(~Q.nonzero(x - 1), assumptions)
|
ed96b8913bc464ebef607a200f76189c8c77bbbf3fc396823d1cdded8a788d9e | from sympy.assumptions.ask import Q
from sympy.assumptions.refine import refine
from sympy.core.expr import Expr
from sympy.core.numbers import (I, Rational, nan, pi)
from sympy.core.singleton import S
from sympy.core.symbol import Symbol
from sympy.functions.elementary.complexes import (Abs, arg, im, re, sign)
from sympy.functions.elementary.exponential import exp
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.trigonometric import (atan, atan2)
from sympy.abc import w, x, y, z
from sympy.core.relational import Eq, Ne
from sympy.functions.elementary.piecewise import Piecewise
from sympy.matrices.expressions.matexpr import MatrixSymbol
def test_Abs():
assert refine(Abs(x), Q.positive(x)) == x
assert refine(1 + Abs(x), Q.positive(x)) == 1 + x
assert refine(Abs(x), Q.negative(x)) == -x
assert refine(1 + Abs(x), Q.negative(x)) == 1 - x
assert refine(Abs(x**2)) != x**2
assert refine(Abs(x**2), Q.real(x)) == x**2
def test_pow1():
assert refine((-1)**x, Q.even(x)) == 1
assert refine((-1)**x, Q.odd(x)) == -1
assert refine((-2)**x, Q.even(x)) == 2**x
# nested powers
assert refine(sqrt(x**2)) != Abs(x)
assert refine(sqrt(x**2), Q.complex(x)) != Abs(x)
assert refine(sqrt(x**2), Q.real(x)) == Abs(x)
assert refine(sqrt(x**2), Q.positive(x)) == x
assert refine((x**3)**Rational(1, 3)) != x
assert refine((x**3)**Rational(1, 3), Q.real(x)) != x
assert refine((x**3)**Rational(1, 3), Q.positive(x)) == x
assert refine(sqrt(1/x), Q.real(x)) != 1/sqrt(x)
assert refine(sqrt(1/x), Q.positive(x)) == 1/sqrt(x)
# powers of (-1)
assert refine((-1)**(x + y), Q.even(x)) == (-1)**y
assert refine((-1)**(x + y + z), Q.odd(x) & Q.odd(z)) == (-1)**y
assert refine((-1)**(x + y + 1), Q.odd(x)) == (-1)**y
assert refine((-1)**(x + y + 2), Q.odd(x)) == (-1)**(y + 1)
assert refine((-1)**(x + 3)) == (-1)**(x + 1)
# continuation
assert refine((-1)**((-1)**x/2 - S.Half), Q.integer(x)) == (-1)**x
assert refine((-1)**((-1)**x/2 + S.Half), Q.integer(x)) == (-1)**(x + 1)
assert refine((-1)**((-1)**x/2 + 5*S.Half), Q.integer(x)) == (-1)**(x + 1)
def test_pow2():
assert refine((-1)**((-1)**x/2 - 7*S.Half), Q.integer(x)) == (-1)**(x + 1)
assert refine((-1)**((-1)**x/2 - 9*S.Half), Q.integer(x)) == (-1)**x
# powers of Abs
assert refine(Abs(x)**2, Q.real(x)) == x**2
assert refine(Abs(x)**3, Q.real(x)) == Abs(x)**3
assert refine(Abs(x)**2) == Abs(x)**2
def test_exp():
x = Symbol('x', integer=True)
assert refine(exp(pi*I*2*x)) == 1
assert refine(exp(pi*I*2*(x + S.Half))) == -1
assert refine(exp(pi*I*2*(x + Rational(1, 4)))) == I
assert refine(exp(pi*I*2*(x + Rational(3, 4)))) == -I
def test_Piecewise():
assert refine(Piecewise((1, x < 0), (3, True)), (x < 0)) == 1
assert refine(Piecewise((1, x < 0), (3, True)), ~(x < 0)) == 3
assert refine(Piecewise((1, x < 0), (3, True)), (y < 0)) == \
Piecewise((1, x < 0), (3, True))
assert refine(Piecewise((1, x > 0), (3, True)), (x > 0)) == 1
assert refine(Piecewise((1, x > 0), (3, True)), ~(x > 0)) == 3
assert refine(Piecewise((1, x > 0), (3, True)), (y > 0)) == \
Piecewise((1, x > 0), (3, True))
assert refine(Piecewise((1, x <= 0), (3, True)), (x <= 0)) == 1
assert refine(Piecewise((1, x <= 0), (3, True)), ~(x <= 0)) == 3
assert refine(Piecewise((1, x <= 0), (3, True)), (y <= 0)) == \
Piecewise((1, x <= 0), (3, True))
assert refine(Piecewise((1, x >= 0), (3, True)), (x >= 0)) == 1
assert refine(Piecewise((1, x >= 0), (3, True)), ~(x >= 0)) == 3
assert refine(Piecewise((1, x >= 0), (3, True)), (y >= 0)) == \
Piecewise((1, x >= 0), (3, True))
assert refine(Piecewise((1, Eq(x, 0)), (3, True)), (Eq(x, 0)))\
== 1
assert refine(Piecewise((1, Eq(x, 0)), (3, True)), (Eq(0, x)))\
== 1
assert refine(Piecewise((1, Eq(x, 0)), (3, True)), ~(Eq(x, 0)))\
== 3
assert refine(Piecewise((1, Eq(x, 0)), (3, True)), ~(Eq(0, x)))\
== 3
assert refine(Piecewise((1, Eq(x, 0)), (3, True)), (Eq(y, 0)))\
== Piecewise((1, Eq(x, 0)), (3, True))
assert refine(Piecewise((1, Ne(x, 0)), (3, True)), (Ne(x, 0)))\
== 1
assert refine(Piecewise((1, Ne(x, 0)), (3, True)), ~(Ne(x, 0)))\
== 3
assert refine(Piecewise((1, Ne(x, 0)), (3, True)), (Ne(y, 0)))\
== Piecewise((1, Ne(x, 0)), (3, True))
def test_atan2():
assert refine(atan2(y, x), Q.real(y) & Q.positive(x)) == atan(y/x)
assert refine(atan2(y, x), Q.negative(y) & Q.positive(x)) == atan(y/x)
assert refine(atan2(y, x), Q.negative(y) & Q.negative(x)) == atan(y/x) - pi
assert refine(atan2(y, x), Q.positive(y) & Q.negative(x)) == atan(y/x) + pi
assert refine(atan2(y, x), Q.zero(y) & Q.negative(x)) == pi
assert refine(atan2(y, x), Q.positive(y) & Q.zero(x)) == pi/2
assert refine(atan2(y, x), Q.negative(y) & Q.zero(x)) == -pi/2
assert refine(atan2(y, x), Q.zero(y) & Q.zero(x)) is nan
def test_re():
assert refine(re(x), Q.real(x)) == x
assert refine(re(x), Q.imaginary(x)) is S.Zero
assert refine(re(x+y), Q.real(x) & Q.real(y)) == x + y
assert refine(re(x+y), Q.real(x) & Q.imaginary(y)) == x
assert refine(re(x*y), Q.real(x) & Q.real(y)) == x * y
assert refine(re(x*y), Q.real(x) & Q.imaginary(y)) == 0
assert refine(re(x*y*z), Q.real(x) & Q.real(y) & Q.real(z)) == x * y * z
def test_im():
assert refine(im(x), Q.imaginary(x)) == -I*x
assert refine(im(x), Q.real(x)) is S.Zero
assert refine(im(x+y), Q.imaginary(x) & Q.imaginary(y)) == -I*x - I*y
assert refine(im(x+y), Q.real(x) & Q.imaginary(y)) == -I*y
assert refine(im(x*y), Q.imaginary(x) & Q.real(y)) == -I*x*y
assert refine(im(x*y), Q.imaginary(x) & Q.imaginary(y)) == 0
assert refine(im(1/x), Q.imaginary(x)) == -I/x
assert refine(im(x*y*z), Q.imaginary(x) & Q.imaginary(y)
& Q.imaginary(z)) == -I*x*y*z
def test_complex():
assert refine(re(1/(x + I*y)), Q.real(x) & Q.real(y)) == \
x/(x**2 + y**2)
assert refine(im(1/(x + I*y)), Q.real(x) & Q.real(y)) == \
-y/(x**2 + y**2)
assert refine(re((w + I*x) * (y + I*z)), Q.real(w) & Q.real(x) & Q.real(y)
& Q.real(z)) == w*y - x*z
assert refine(im((w + I*x) * (y + I*z)), Q.real(w) & Q.real(x) & Q.real(y)
& Q.real(z)) == w*z + x*y
def test_sign():
x = Symbol('x', real = True)
assert refine(sign(x), Q.positive(x)) == 1
assert refine(sign(x), Q.negative(x)) == -1
assert refine(sign(x), Q.zero(x)) == 0
assert refine(sign(x), True) == sign(x)
assert refine(sign(Abs(x)), Q.nonzero(x)) == 1
x = Symbol('x', imaginary=True)
assert refine(sign(x), Q.positive(im(x))) == S.ImaginaryUnit
assert refine(sign(x), Q.negative(im(x))) == -S.ImaginaryUnit
assert refine(sign(x), True) == sign(x)
x = Symbol('x', complex=True)
assert refine(sign(x), Q.zero(x)) == 0
def test_arg():
x = Symbol('x', complex = True)
assert refine(arg(x), Q.positive(x)) == 0
assert refine(arg(x), Q.negative(x)) == pi
def test_func_args():
class MyClass(Expr):
# A class with nontrivial .func
def __init__(self, *args):
self.my_member = ""
@property
def func(self):
def my_func(*args):
obj = MyClass(*args)
obj.my_member = self.my_member
return obj
return my_func
x = MyClass()
x.my_member = "A very important value"
assert x.my_member == refine(x).my_member
def test_eval_refine():
class MockExpr(Expr):
def _eval_refine(self, assumptions):
return True
mock_obj = MockExpr()
assert refine(mock_obj)
def test_refine_issue_12724():
expr1 = refine(Abs(x * y), Q.positive(x))
expr2 = refine(Abs(x * y * z), Q.positive(x))
assert expr1 == x * Abs(y)
assert expr2 == x * Abs(y * z)
y1 = Symbol('y1', real = True)
expr3 = refine(Abs(x * y1**2 * z), Q.positive(x))
assert expr3 == x * y1**2 * Abs(z)
def test_matrixelement():
x = MatrixSymbol('x', 3, 3)
i = Symbol('i', positive = True)
j = Symbol('j', positive = True)
assert refine(x[0, 1], Q.symmetric(x)) == x[0, 1]
assert refine(x[1, 0], Q.symmetric(x)) == x[0, 1]
assert refine(x[i, j], Q.symmetric(x)) == x[j, i]
assert refine(x[j, i], Q.symmetric(x)) == x[j, i]
|
208aaa231ce42df00da53341284b02182a77066f339839d8776df0a2a2a1f441 | from sympy.assumptions.ask import Q
from sympy.assumptions.assume import assuming
from sympy.core.numbers import (I, pi)
from sympy.core.relational import (Eq, Gt)
from sympy.core.singleton import S
from sympy.core.symbol import symbols
from sympy.functions.elementary.complexes import Abs
from sympy.logic.boolalg import Implies
from sympy.matrices.expressions.matexpr import MatrixSymbol
from sympy.assumptions.cnf import CNF, Literal
from sympy.assumptions.satask import (satask, extract_predargs,
get_relevant_clsfacts)
from sympy.testing.pytest import raises, XFAIL
x, y, z = symbols('x y z')
def test_satask():
# No relevant facts
assert satask(Q.real(x), Q.real(x)) is True
assert satask(Q.real(x), ~Q.real(x)) is False
assert satask(Q.real(x)) is None
assert satask(Q.real(x), Q.positive(x)) is True
assert satask(Q.positive(x), Q.real(x)) is None
assert satask(Q.real(x), ~Q.positive(x)) is None
assert satask(Q.positive(x), ~Q.real(x)) is False
raises(ValueError, lambda: satask(Q.real(x), Q.real(x) & ~Q.real(x)))
with assuming(Q.positive(x)):
assert satask(Q.real(x)) is True
assert satask(~Q.positive(x)) is False
raises(ValueError, lambda: satask(Q.real(x), ~Q.positive(x)))
assert satask(Q.zero(x), Q.nonzero(x)) is False
assert satask(Q.positive(x), Q.zero(x)) is False
assert satask(Q.real(x), Q.zero(x)) is True
assert satask(Q.zero(x), Q.zero(x*y)) is None
assert satask(Q.zero(x*y), Q.zero(x))
def test_zero():
"""
Everything in this test doesn't work with the ask handlers, and most
things would be very difficult or impossible to make work under that
model.
"""
assert satask(Q.zero(x) | Q.zero(y), Q.zero(x*y)) is True
assert satask(Q.zero(x*y), Q.zero(x) | Q.zero(y)) is True
assert satask(Implies(Q.zero(x), Q.zero(x*y))) is True
# This one in particular requires computing the fixed-point of the
# relevant facts, because going from Q.nonzero(x*y) -> ~Q.zero(x*y) and
# Q.zero(x*y) -> Equivalent(Q.zero(x*y), Q.zero(x) | Q.zero(y)) takes two
# steps.
assert satask(Q.zero(x) | Q.zero(y), Q.nonzero(x*y)) is False
assert satask(Q.zero(x), Q.zero(x**2)) is True
def test_zero_positive():
assert satask(Q.zero(x + y), Q.positive(x) & Q.positive(y)) is False
assert satask(Q.positive(x) & Q.positive(y), Q.zero(x + y)) is False
assert satask(Q.nonzero(x + y), Q.positive(x) & Q.positive(y)) is True
assert satask(Q.positive(x) & Q.positive(y), Q.nonzero(x + y)) is None
# This one requires several levels of forward chaining
assert satask(Q.zero(x*(x + y)), Q.positive(x) & Q.positive(y)) is False
assert satask(Q.positive(pi*x*y + 1), Q.positive(x) & Q.positive(y)) is True
assert satask(Q.positive(pi*x*y - 5), Q.positive(x) & Q.positive(y)) is None
def test_zero_pow():
assert satask(Q.zero(x**y), Q.zero(x) & Q.positive(y)) is True
assert satask(Q.zero(x**y), Q.nonzero(x) & Q.zero(y)) is False
assert satask(Q.zero(x), Q.zero(x**y)) is True
assert satask(Q.zero(x**y), Q.zero(x)) is None
@XFAIL
# Requires correct Q.square calculation first
def test_invertible():
A = MatrixSymbol('A', 5, 5)
B = MatrixSymbol('B', 5, 5)
assert satask(Q.invertible(A*B), Q.invertible(A) & Q.invertible(B)) is True
assert satask(Q.invertible(A), Q.invertible(A*B)) is True
assert satask(Q.invertible(A) & Q.invertible(B), Q.invertible(A*B)) is True
def test_prime():
assert satask(Q.prime(5)) is True
assert satask(Q.prime(6)) is False
assert satask(Q.prime(-5)) is False
assert satask(Q.prime(x*y), Q.integer(x) & Q.integer(y)) is None
assert satask(Q.prime(x*y), Q.prime(x) & Q.prime(y)) is False
def test_old_assump():
assert satask(Q.positive(1)) is True
assert satask(Q.positive(-1)) is False
assert satask(Q.positive(0)) is False
assert satask(Q.positive(I)) is False
assert satask(Q.positive(pi)) is True
assert satask(Q.negative(1)) is False
assert satask(Q.negative(-1)) is True
assert satask(Q.negative(0)) is False
assert satask(Q.negative(I)) is False
assert satask(Q.negative(pi)) is False
assert satask(Q.zero(1)) is False
assert satask(Q.zero(-1)) is False
assert satask(Q.zero(0)) is True
assert satask(Q.zero(I)) is False
assert satask(Q.zero(pi)) is False
assert satask(Q.nonzero(1)) is True
assert satask(Q.nonzero(-1)) is True
assert satask(Q.nonzero(0)) is False
assert satask(Q.nonzero(I)) is False
assert satask(Q.nonzero(pi)) is True
assert satask(Q.nonpositive(1)) is False
assert satask(Q.nonpositive(-1)) is True
assert satask(Q.nonpositive(0)) is True
assert satask(Q.nonpositive(I)) is False
assert satask(Q.nonpositive(pi)) is False
assert satask(Q.nonnegative(1)) is True
assert satask(Q.nonnegative(-1)) is False
assert satask(Q.nonnegative(0)) is True
assert satask(Q.nonnegative(I)) is False
assert satask(Q.nonnegative(pi)) is True
def test_rational_irrational():
assert satask(Q.irrational(2)) is False
assert satask(Q.rational(2)) is True
assert satask(Q.irrational(pi)) is True
assert satask(Q.rational(pi)) is False
assert satask(Q.irrational(I)) is False
assert satask(Q.rational(I)) is False
assert satask(Q.irrational(x*y*z), Q.irrational(x) & Q.irrational(y) &
Q.rational(z)) is None
assert satask(Q.irrational(x*y*z), Q.irrational(x) & Q.rational(y) &
Q.rational(z)) is True
assert satask(Q.irrational(pi*x*y), Q.rational(x) & Q.rational(y)) is True
assert satask(Q.irrational(x + y + z), Q.irrational(x) & Q.irrational(y) &
Q.rational(z)) is None
assert satask(Q.irrational(x + y + z), Q.irrational(x) & Q.rational(y) &
Q.rational(z)) is True
assert satask(Q.irrational(pi + x + y), Q.rational(x) & Q.rational(y)) is True
assert satask(Q.irrational(x*y*z), Q.rational(x) & Q.rational(y) &
Q.rational(z)) is False
assert satask(Q.rational(x*y*z), Q.rational(x) & Q.rational(y) &
Q.rational(z)) is True
assert satask(Q.irrational(x + y + z), Q.rational(x) & Q.rational(y) &
Q.rational(z)) is False
assert satask(Q.rational(x + y + z), Q.rational(x) & Q.rational(y) &
Q.rational(z)) is True
def test_even_satask():
assert satask(Q.even(2)) is True
assert satask(Q.even(3)) is False
assert satask(Q.even(x*y), Q.even(x) & Q.odd(y)) is True
assert satask(Q.even(x*y), Q.even(x) & Q.integer(y)) is True
assert satask(Q.even(x*y), Q.even(x) & Q.even(y)) is True
assert satask(Q.even(x*y), Q.odd(x) & Q.odd(y)) is False
assert satask(Q.even(x*y), Q.even(x)) is None
assert satask(Q.even(x*y), Q.odd(x) & Q.integer(y)) is None
assert satask(Q.even(x*y), Q.odd(x) & Q.odd(y)) is False
assert satask(Q.even(abs(x)), Q.even(x)) is True
assert satask(Q.even(abs(x)), Q.odd(x)) is False
assert satask(Q.even(x), Q.even(abs(x))) is None # x could be complex
def test_odd_satask():
assert satask(Q.odd(2)) is False
assert satask(Q.odd(3)) is True
assert satask(Q.odd(x*y), Q.even(x) & Q.odd(y)) is False
assert satask(Q.odd(x*y), Q.even(x) & Q.integer(y)) is False
assert satask(Q.odd(x*y), Q.even(x) & Q.even(y)) is False
assert satask(Q.odd(x*y), Q.odd(x) & Q.odd(y)) is True
assert satask(Q.odd(x*y), Q.even(x)) is None
assert satask(Q.odd(x*y), Q.odd(x) & Q.integer(y)) is None
assert satask(Q.odd(x*y), Q.odd(x) & Q.odd(y)) is True
assert satask(Q.odd(abs(x)), Q.even(x)) is False
assert satask(Q.odd(abs(x)), Q.odd(x)) is True
assert satask(Q.odd(x), Q.odd(abs(x))) is None # x could be complex
def test_integer():
assert satask(Q.integer(1)) is True
assert satask(Q.integer(S.Half)) is False
assert satask(Q.integer(x + y), Q.integer(x) & Q.integer(y)) is True
assert satask(Q.integer(x + y), Q.integer(x)) is None
assert satask(Q.integer(x + y), Q.integer(x) & ~Q.integer(y)) is False
assert satask(Q.integer(x + y + z), Q.integer(x) & Q.integer(y) &
~Q.integer(z)) is False
assert satask(Q.integer(x + y + z), Q.integer(x) & ~Q.integer(y) &
~Q.integer(z)) is None
assert satask(Q.integer(x + y + z), Q.integer(x) & ~Q.integer(y)) is None
assert satask(Q.integer(x + y), Q.integer(x) & Q.irrational(y)) is False
assert satask(Q.integer(x*y), Q.integer(x) & Q.integer(y)) is True
assert satask(Q.integer(x*y), Q.integer(x)) is None
assert satask(Q.integer(x*y), Q.integer(x) & ~Q.integer(y)) is None
assert satask(Q.integer(x*y), Q.integer(x) & ~Q.rational(y)) is False
assert satask(Q.integer(x*y*z), Q.integer(x) & Q.integer(y) &
~Q.rational(z)) is False
assert satask(Q.integer(x*y*z), Q.integer(x) & ~Q.rational(y) &
~Q.rational(z)) is None
assert satask(Q.integer(x*y*z), Q.integer(x) & ~Q.rational(y)) is None
assert satask(Q.integer(x*y), Q.integer(x) & Q.irrational(y)) is False
def test_abs():
assert satask(Q.nonnegative(abs(x))) is True
assert satask(Q.positive(abs(x)), ~Q.zero(x)) is True
assert satask(Q.zero(x), ~Q.zero(abs(x))) is False
assert satask(Q.zero(x), Q.zero(abs(x))) is True
assert satask(Q.nonzero(x), ~Q.zero(abs(x))) is None # x could be complex
assert satask(Q.zero(abs(x)), Q.zero(x)) is True
def test_imaginary():
assert satask(Q.imaginary(2*I)) is True
assert satask(Q.imaginary(x*y), Q.imaginary(x)) is None
assert satask(Q.imaginary(x*y), Q.imaginary(x) & Q.real(y)) is True
assert satask(Q.imaginary(x), Q.real(x)) is False
assert satask(Q.imaginary(1)) is False
assert satask(Q.imaginary(x*y), Q.real(x) & Q.real(y)) is False
assert satask(Q.imaginary(x + y), Q.real(x) & Q.real(y)) is False
def test_real():
assert satask(Q.real(x*y), Q.real(x) & Q.real(y)) is True
assert satask(Q.real(x + y), Q.real(x) & Q.real(y)) is True
assert satask(Q.real(x*y*z), Q.real(x) & Q.real(y) & Q.real(z)) is True
assert satask(Q.real(x*y*z), Q.real(x) & Q.real(y)) is None
assert satask(Q.real(x*y*z), Q.real(x) & Q.real(y) & Q.imaginary(z)) is False
assert satask(Q.real(x + y + z), Q.real(x) & Q.real(y) & Q.real(z)) is True
assert satask(Q.real(x + y + z), Q.real(x) & Q.real(y)) is None
def test_pos_neg():
assert satask(~Q.positive(x), Q.negative(x)) is True
assert satask(~Q.negative(x), Q.positive(x)) is True
assert satask(Q.positive(x + y), Q.positive(x) & Q.positive(y)) is True
assert satask(Q.negative(x + y), Q.negative(x) & Q.negative(y)) is True
assert satask(Q.positive(x + y), Q.negative(x) & Q.negative(y)) is False
assert satask(Q.negative(x + y), Q.positive(x) & Q.positive(y)) is False
def test_pow_pos_neg():
assert satask(Q.nonnegative(x**2), Q.positive(x)) is True
assert satask(Q.nonpositive(x**2), Q.positive(x)) is False
assert satask(Q.positive(x**2), Q.positive(x)) is True
assert satask(Q.negative(x**2), Q.positive(x)) is False
assert satask(Q.real(x**2), Q.positive(x)) is True
assert satask(Q.nonnegative(x**2), Q.negative(x)) is True
assert satask(Q.nonpositive(x**2), Q.negative(x)) is False
assert satask(Q.positive(x**2), Q.negative(x)) is True
assert satask(Q.negative(x**2), Q.negative(x)) is False
assert satask(Q.real(x**2), Q.negative(x)) is True
assert satask(Q.nonnegative(x**2), Q.nonnegative(x)) is True
assert satask(Q.nonpositive(x**2), Q.nonnegative(x)) is None
assert satask(Q.positive(x**2), Q.nonnegative(x)) is None
assert satask(Q.negative(x**2), Q.nonnegative(x)) is False
assert satask(Q.real(x**2), Q.nonnegative(x)) is True
assert satask(Q.nonnegative(x**2), Q.nonpositive(x)) is True
assert satask(Q.nonpositive(x**2), Q.nonpositive(x)) is None
assert satask(Q.positive(x**2), Q.nonpositive(x)) is None
assert satask(Q.negative(x**2), Q.nonpositive(x)) is False
assert satask(Q.real(x**2), Q.nonpositive(x)) is True
assert satask(Q.nonnegative(x**3), Q.positive(x)) is True
assert satask(Q.nonpositive(x**3), Q.positive(x)) is False
assert satask(Q.positive(x**3), Q.positive(x)) is True
assert satask(Q.negative(x**3), Q.positive(x)) is False
assert satask(Q.real(x**3), Q.positive(x)) is True
assert satask(Q.nonnegative(x**3), Q.negative(x)) is False
assert satask(Q.nonpositive(x**3), Q.negative(x)) is True
assert satask(Q.positive(x**3), Q.negative(x)) is False
assert satask(Q.negative(x**3), Q.negative(x)) is True
assert satask(Q.real(x**3), Q.negative(x)) is True
assert satask(Q.nonnegative(x**3), Q.nonnegative(x)) is True
assert satask(Q.nonpositive(x**3), Q.nonnegative(x)) is None
assert satask(Q.positive(x**3), Q.nonnegative(x)) is None
assert satask(Q.negative(x**3), Q.nonnegative(x)) is False
assert satask(Q.real(x**3), Q.nonnegative(x)) is True
assert satask(Q.nonnegative(x**3), Q.nonpositive(x)) is None
assert satask(Q.nonpositive(x**3), Q.nonpositive(x)) is True
assert satask(Q.positive(x**3), Q.nonpositive(x)) is False
assert satask(Q.negative(x**3), Q.nonpositive(x)) is None
assert satask(Q.real(x**3), Q.nonpositive(x)) is True
# If x is zero, x**negative is not real.
assert satask(Q.nonnegative(x**-2), Q.nonpositive(x)) is None
assert satask(Q.nonpositive(x**-2), Q.nonpositive(x)) is None
assert satask(Q.positive(x**-2), Q.nonpositive(x)) is None
assert satask(Q.negative(x**-2), Q.nonpositive(x)) is None
assert satask(Q.real(x**-2), Q.nonpositive(x)) is None
# We could deduce things for negative powers if x is nonzero, but it
# isn't implemented yet.
def test_prime_composite():
assert satask(Q.prime(x), Q.composite(x)) is False
assert satask(Q.composite(x), Q.prime(x)) is False
assert satask(Q.composite(x), ~Q.prime(x)) is None
assert satask(Q.prime(x), ~Q.composite(x)) is None
# since 1 is neither prime nor composite the following should hold
assert satask(Q.prime(x), Q.integer(x) & Q.positive(x) & ~Q.composite(x)) is None
assert satask(Q.prime(2)) is True
assert satask(Q.prime(4)) is False
assert satask(Q.prime(1)) is False
assert satask(Q.composite(1)) is False
def test_extract_predargs():
props = CNF.from_prop(Q.zero(Abs(x*y)) & Q.zero(x*y))
assump = CNF.from_prop(Q.zero(x))
context = CNF.from_prop(Q.zero(y))
assert extract_predargs(props) == {Abs(x*y), x*y}
assert extract_predargs(props, assump) == {Abs(x*y), x*y, x}
assert extract_predargs(props, assump, context) == {Abs(x*y), x*y, x, y}
props = CNF.from_prop(Eq(x, y))
assump = CNF.from_prop(Gt(y, z))
assert extract_predargs(props, assump) == {x, y, z}
def test_get_relevant_clsfacts():
exprs = {Abs(x*y)}
exprs, facts = get_relevant_clsfacts(exprs)
assert exprs == {x*y}
assert facts.clauses == \
{frozenset({Literal(Q.odd(Abs(x*y)), False), Literal(Q.odd(x*y), True)}),
frozenset({Literal(Q.zero(Abs(x*y)), False), Literal(Q.zero(x*y), True)}),
frozenset({Literal(Q.even(Abs(x*y)), False), Literal(Q.even(x*y), True)}),
frozenset({Literal(Q.zero(Abs(x*y)), True), Literal(Q.zero(x*y), False)}),
frozenset({Literal(Q.even(Abs(x*y)), False),
Literal(Q.odd(Abs(x*y)), False),
Literal(Q.odd(x*y), True)}),
frozenset({Literal(Q.even(Abs(x*y)), False),
Literal(Q.even(x*y), True),
Literal(Q.odd(Abs(x*y)), False)}),
frozenset({Literal(Q.positive(Abs(x*y)), False),
Literal(Q.zero(Abs(x*y)), False)})}
|
9f34a87ee6b0735f2135ef4d8f474dfe54de0f06b629b3e3b782b6aef6f7c66c | from sympy.assumptions.ask import (Q, ask)
from sympy.core.symbol import Symbol
from sympy.matrices.expressions.diagonal import (DiagMatrix, DiagonalMatrix)
from sympy.matrices.dense import Matrix
from sympy.matrices.expressions import (MatrixSymbol, Identity, ZeroMatrix,
OneMatrix, Trace, MatrixSlice, Determinant, BlockMatrix, BlockDiagMatrix)
from sympy.matrices.expressions.factorizations import LofLU
from sympy.testing.pytest import XFAIL
X = MatrixSymbol('X', 2, 2)
Y = MatrixSymbol('Y', 2, 3)
Z = MatrixSymbol('Z', 2, 2)
A1x1 = MatrixSymbol('A1x1', 1, 1)
B1x1 = MatrixSymbol('B1x1', 1, 1)
C0x0 = MatrixSymbol('C0x0', 0, 0)
V1 = MatrixSymbol('V1', 2, 1)
V2 = MatrixSymbol('V2', 2, 1)
def test_square():
assert ask(Q.square(X))
assert not ask(Q.square(Y))
assert ask(Q.square(Y*Y.T))
def test_invertible():
assert ask(Q.invertible(X), Q.invertible(X))
assert ask(Q.invertible(Y)) is False
assert ask(Q.invertible(X*Y), Q.invertible(X)) is False
assert ask(Q.invertible(X*Z), Q.invertible(X)) is None
assert ask(Q.invertible(X*Z), Q.invertible(X) & Q.invertible(Z)) is True
assert ask(Q.invertible(X.T)) is None
assert ask(Q.invertible(X.T), Q.invertible(X)) is True
assert ask(Q.invertible(X.I)) is True
assert ask(Q.invertible(Identity(3))) is True
assert ask(Q.invertible(ZeroMatrix(3, 3))) is False
assert ask(Q.invertible(OneMatrix(1, 1))) is True
assert ask(Q.invertible(OneMatrix(3, 3))) is False
assert ask(Q.invertible(X), Q.fullrank(X) & Q.square(X))
def test_singular():
assert ask(Q.singular(X)) is None
assert ask(Q.singular(X), Q.invertible(X)) is False
assert ask(Q.singular(X), ~Q.invertible(X)) is True
@XFAIL
def test_invertible_fullrank():
assert ask(Q.invertible(X), Q.fullrank(X)) is True
def test_invertible_BlockMatrix():
assert ask(Q.invertible(BlockMatrix([Identity(3)]))) == True
assert ask(Q.invertible(BlockMatrix([ZeroMatrix(3, 3)]))) == False
X = Matrix([[1, 2, 3], [3, 5, 4]])
Y = Matrix([[4, 2, 7], [2, 3, 5]])
# non-invertible A block
assert ask(Q.invertible(BlockMatrix([
[Matrix.ones(3, 3), Y.T],
[X, Matrix.eye(2)],
]))) == True
# non-invertible B block
assert ask(Q.invertible(BlockMatrix([
[Y.T, Matrix.ones(3, 3)],
[Matrix.eye(2), X],
]))) == True
# non-invertible C block
assert ask(Q.invertible(BlockMatrix([
[X, Matrix.eye(2)],
[Matrix.ones(3, 3), Y.T],
]))) == True
# non-invertible D block
assert ask(Q.invertible(BlockMatrix([
[Matrix.eye(2), X],
[Y.T, Matrix.ones(3, 3)],
]))) == True
def test_invertible_BlockDiagMatrix():
assert ask(Q.invertible(BlockDiagMatrix(Identity(3), Identity(5)))) == True
assert ask(Q.invertible(BlockDiagMatrix(ZeroMatrix(3, 3), Identity(5)))) == False
assert ask(Q.invertible(BlockDiagMatrix(Identity(3), OneMatrix(5, 5)))) == False
def test_symmetric():
assert ask(Q.symmetric(X), Q.symmetric(X))
assert ask(Q.symmetric(X*Z), Q.symmetric(X)) is None
assert ask(Q.symmetric(X*Z), Q.symmetric(X) & Q.symmetric(Z)) is True
assert ask(Q.symmetric(X + Z), Q.symmetric(X) & Q.symmetric(Z)) is True
assert ask(Q.symmetric(Y)) is False
assert ask(Q.symmetric(Y*Y.T)) is True
assert ask(Q.symmetric(Y.T*X*Y)) is None
assert ask(Q.symmetric(Y.T*X*Y), Q.symmetric(X)) is True
assert ask(Q.symmetric(X**10), Q.symmetric(X)) is True
assert ask(Q.symmetric(A1x1)) is True
assert ask(Q.symmetric(A1x1 + B1x1)) is True
assert ask(Q.symmetric(A1x1 * B1x1)) is True
assert ask(Q.symmetric(V1.T*V1)) is True
assert ask(Q.symmetric(V1.T*(V1 + V2))) is True
assert ask(Q.symmetric(V1.T*(V1 + V2) + A1x1)) is True
assert ask(Q.symmetric(MatrixSlice(Y, (0, 1), (1, 2)))) is True
assert ask(Q.symmetric(Identity(3))) is True
assert ask(Q.symmetric(ZeroMatrix(3, 3))) is True
assert ask(Q.symmetric(OneMatrix(3, 3))) is True
def _test_orthogonal_unitary(predicate):
assert ask(predicate(X), predicate(X))
assert ask(predicate(X.T), predicate(X)) is True
assert ask(predicate(X.I), predicate(X)) is True
assert ask(predicate(X**2), predicate(X))
assert ask(predicate(Y)) is False
assert ask(predicate(X)) is None
assert ask(predicate(X), ~Q.invertible(X)) is False
assert ask(predicate(X*Z*X), predicate(X) & predicate(Z)) is True
assert ask(predicate(Identity(3))) is True
assert ask(predicate(ZeroMatrix(3, 3))) is False
assert ask(Q.invertible(X), predicate(X))
assert not ask(predicate(X + Z), predicate(X) & predicate(Z))
def test_orthogonal():
_test_orthogonal_unitary(Q.orthogonal)
def test_unitary():
_test_orthogonal_unitary(Q.unitary)
assert ask(Q.unitary(X), Q.orthogonal(X))
def test_fullrank():
assert ask(Q.fullrank(X), Q.fullrank(X))
assert ask(Q.fullrank(X**2), Q.fullrank(X))
assert ask(Q.fullrank(X.T), Q.fullrank(X)) is True
assert ask(Q.fullrank(X)) is None
assert ask(Q.fullrank(Y)) is None
assert ask(Q.fullrank(X*Z), Q.fullrank(X) & Q.fullrank(Z)) is True
assert ask(Q.fullrank(Identity(3))) is True
assert ask(Q.fullrank(ZeroMatrix(3, 3))) is False
assert ask(Q.fullrank(OneMatrix(1, 1))) is True
assert ask(Q.fullrank(OneMatrix(3, 3))) is False
assert ask(Q.invertible(X), ~Q.fullrank(X)) == False
def test_positive_definite():
assert ask(Q.positive_definite(X), Q.positive_definite(X))
assert ask(Q.positive_definite(X.T), Q.positive_definite(X)) is True
assert ask(Q.positive_definite(X.I), Q.positive_definite(X)) is True
assert ask(Q.positive_definite(Y)) is False
assert ask(Q.positive_definite(X)) is None
assert ask(Q.positive_definite(X**3), Q.positive_definite(X))
assert ask(Q.positive_definite(X*Z*X),
Q.positive_definite(X) & Q.positive_definite(Z)) is True
assert ask(Q.positive_definite(X), Q.orthogonal(X))
assert ask(Q.positive_definite(Y.T*X*Y),
Q.positive_definite(X) & Q.fullrank(Y)) is True
assert not ask(Q.positive_definite(Y.T*X*Y), Q.positive_definite(X))
assert ask(Q.positive_definite(Identity(3))) is True
assert ask(Q.positive_definite(ZeroMatrix(3, 3))) is False
assert ask(Q.positive_definite(OneMatrix(1, 1))) is True
assert ask(Q.positive_definite(OneMatrix(3, 3))) is False
assert ask(Q.positive_definite(X + Z), Q.positive_definite(X) &
Q.positive_definite(Z)) is True
assert not ask(Q.positive_definite(-X), Q.positive_definite(X))
assert ask(Q.positive(X[1, 1]), Q.positive_definite(X))
def test_triangular():
assert ask(Q.upper_triangular(X + Z.T + Identity(2)), Q.upper_triangular(X) &
Q.lower_triangular(Z)) is True
assert ask(Q.upper_triangular(X*Z.T), Q.upper_triangular(X) &
Q.lower_triangular(Z)) is True
assert ask(Q.lower_triangular(Identity(3))) is True
assert ask(Q.lower_triangular(ZeroMatrix(3, 3))) is True
assert ask(Q.upper_triangular(ZeroMatrix(3, 3))) is True
assert ask(Q.lower_triangular(OneMatrix(1, 1))) is True
assert ask(Q.upper_triangular(OneMatrix(1, 1))) is True
assert ask(Q.lower_triangular(OneMatrix(3, 3))) is False
assert ask(Q.upper_triangular(OneMatrix(3, 3))) is False
assert ask(Q.triangular(X), Q.unit_triangular(X))
assert ask(Q.upper_triangular(X**3), Q.upper_triangular(X))
assert ask(Q.lower_triangular(X**3), Q.lower_triangular(X))
def test_diagonal():
assert ask(Q.diagonal(X + Z.T + Identity(2)), Q.diagonal(X) &
Q.diagonal(Z)) is True
assert ask(Q.diagonal(ZeroMatrix(3, 3)))
assert ask(Q.diagonal(OneMatrix(1, 1))) is True
assert ask(Q.diagonal(OneMatrix(3, 3))) is False
assert ask(Q.lower_triangular(X) & Q.upper_triangular(X), Q.diagonal(X))
assert ask(Q.diagonal(X), Q.lower_triangular(X) & Q.upper_triangular(X))
assert ask(Q.symmetric(X), Q.diagonal(X))
assert ask(Q.triangular(X), Q.diagonal(X))
assert ask(Q.diagonal(C0x0))
assert ask(Q.diagonal(A1x1))
assert ask(Q.diagonal(A1x1 + B1x1))
assert ask(Q.diagonal(A1x1*B1x1))
assert ask(Q.diagonal(V1.T*V2))
assert ask(Q.diagonal(V1.T*(X + Z)*V1))
assert ask(Q.diagonal(MatrixSlice(Y, (0, 1), (1, 2)))) is True
assert ask(Q.diagonal(V1.T*(V1 + V2))) is True
assert ask(Q.diagonal(X**3), Q.diagonal(X))
assert ask(Q.diagonal(Identity(3)))
assert ask(Q.diagonal(DiagMatrix(V1)))
assert ask(Q.diagonal(DiagonalMatrix(X)))
def test_non_atoms():
assert ask(Q.real(Trace(X)), Q.positive(Trace(X)))
@XFAIL
def test_non_trivial_implies():
X = MatrixSymbol('X', 3, 3)
Y = MatrixSymbol('Y', 3, 3)
assert ask(Q.lower_triangular(X+Y), Q.lower_triangular(X) &
Q.lower_triangular(Y)) is True
assert ask(Q.triangular(X), Q.lower_triangular(X)) is True
assert ask(Q.triangular(X+Y), Q.lower_triangular(X) &
Q.lower_triangular(Y)) is True
def test_MatrixSlice():
X = MatrixSymbol('X', 4, 4)
B = MatrixSlice(X, (1, 3), (1, 3))
C = MatrixSlice(X, (0, 3), (1, 3))
assert ask(Q.symmetric(B), Q.symmetric(X))
assert ask(Q.invertible(B), Q.invertible(X))
assert ask(Q.diagonal(B), Q.diagonal(X))
assert ask(Q.orthogonal(B), Q.orthogonal(X))
assert ask(Q.upper_triangular(B), Q.upper_triangular(X))
assert not ask(Q.symmetric(C), Q.symmetric(X))
assert not ask(Q.invertible(C), Q.invertible(X))
assert not ask(Q.diagonal(C), Q.diagonal(X))
assert not ask(Q.orthogonal(C), Q.orthogonal(X))
assert not ask(Q.upper_triangular(C), Q.upper_triangular(X))
def test_det_trace_positive():
X = MatrixSymbol('X', 4, 4)
assert ask(Q.positive(Trace(X)), Q.positive_definite(X))
assert ask(Q.positive(Determinant(X)), Q.positive_definite(X))
def test_field_assumptions():
X = MatrixSymbol('X', 4, 4)
Y = MatrixSymbol('Y', 4, 4)
assert ask(Q.real_elements(X), Q.real_elements(X))
assert not ask(Q.integer_elements(X), Q.real_elements(X))
assert ask(Q.complex_elements(X), Q.real_elements(X))
assert ask(Q.complex_elements(X**2), Q.real_elements(X))
assert ask(Q.real_elements(X**2), Q.integer_elements(X))
assert ask(Q.real_elements(X+Y), Q.real_elements(X)) is None
assert ask(Q.real_elements(X+Y), Q.real_elements(X) & Q.real_elements(Y))
from sympy.matrices.expressions.hadamard import HadamardProduct
assert ask(Q.real_elements(HadamardProduct(X, Y)),
Q.real_elements(X) & Q.real_elements(Y))
assert ask(Q.complex_elements(X+Y), Q.real_elements(X) & Q.complex_elements(Y))
assert ask(Q.real_elements(X.T), Q.real_elements(X))
assert ask(Q.real_elements(X.I), Q.real_elements(X) & Q.invertible(X))
assert ask(Q.real_elements(Trace(X)), Q.real_elements(X))
assert ask(Q.integer_elements(Determinant(X)), Q.integer_elements(X))
assert not ask(Q.integer_elements(X.I), Q.integer_elements(X))
alpha = Symbol('alpha')
assert ask(Q.real_elements(alpha*X), Q.real_elements(X) & Q.real(alpha))
assert ask(Q.real_elements(LofLU(X)), Q.real_elements(X))
e = Symbol('e', integer=True, negative=True)
assert ask(Q.real_elements(X**e), Q.real_elements(X) & Q.invertible(X))
assert ask(Q.real_elements(X**e), Q.real_elements(X)) is None
def test_matrix_element_sets():
X = MatrixSymbol('X', 4, 4)
assert ask(Q.real(X[1, 2]), Q.real_elements(X))
assert ask(Q.integer(X[1, 2]), Q.integer_elements(X))
assert ask(Q.complex(X[1, 2]), Q.complex_elements(X))
assert ask(Q.integer_elements(Identity(3)))
assert ask(Q.integer_elements(ZeroMatrix(3, 3)))
assert ask(Q.integer_elements(OneMatrix(3, 3)))
from sympy.matrices.expressions.fourier import DFT
assert ask(Q.complex_elements(DFT(3)))
def test_matrix_element_sets_slices_blocks():
X = MatrixSymbol('X', 4, 4)
assert ask(Q.integer_elements(X[:, 3]), Q.integer_elements(X))
assert ask(Q.integer_elements(BlockMatrix([[X], [X]])),
Q.integer_elements(X))
def test_matrix_element_sets_determinant_trace():
assert ask(Q.integer(Determinant(X)), Q.integer_elements(X))
assert ask(Q.integer(Trace(X)), Q.integer_elements(X))
|
8cc09941bdc6ea9550e4c1da493595ff47942c768217c328c2ed762e5ef6ae0b | from sympy.assumptions.ask import Q
from sympy.core.basic import Basic
from sympy.core.expr import Expr
from sympy.core.mul import Mul
from sympy.core.symbol import symbols
from sympy.logic.boolalg import (And, Or)
from sympy.assumptions.sathandlers import (ClassFactRegistry, allargs,
anyarg, exactlyonearg,)
x, y, z = symbols('x y z')
def test_class_handler_registry():
my_handler_registry = ClassFactRegistry()
# The predicate doesn't matter here, so just pass
@my_handler_registry.register(Mul)
def fact1(expr):
pass
@my_handler_registry.multiregister(Expr)
def fact2(expr):
pass
assert my_handler_registry[Basic] == (frozenset(), frozenset())
assert my_handler_registry[Expr] == (frozenset(), frozenset({fact2}))
assert my_handler_registry[Mul] == (frozenset({fact1}), frozenset({fact2}))
def test_allargs():
assert allargs(x, Q.zero(x), x*y) == And(Q.zero(x), Q.zero(y))
assert allargs(x, Q.positive(x) | Q.negative(x), x*y) == And(Q.positive(x) | Q.negative(x), Q.positive(y) | Q.negative(y))
def test_anyarg():
assert anyarg(x, Q.zero(x), x*y) == Or(Q.zero(x), Q.zero(y))
assert anyarg(x, Q.positive(x) & Q.negative(x), x*y) == \
Or(Q.positive(x) & Q.negative(x), Q.positive(y) & Q.negative(y))
def test_exactlyonearg():
assert exactlyonearg(x, Q.zero(x), x*y) == \
Or(Q.zero(x) & ~Q.zero(y), Q.zero(y) & ~Q.zero(x))
assert exactlyonearg(x, Q.zero(x), x*y*z) == \
Or(Q.zero(x) & ~Q.zero(y) & ~Q.zero(z), Q.zero(y)
& ~Q.zero(x) & ~Q.zero(z), Q.zero(z) & ~Q.zero(x) & ~Q.zero(y))
assert exactlyonearg(x, Q.positive(x) | Q.negative(x), x*y) == \
Or((Q.positive(x) | Q.negative(x)) &
~(Q.positive(y) | Q.negative(y)), (Q.positive(y) | Q.negative(y)) &
~(Q.positive(x) | Q.negative(x)))
|
281ed502d6906d449dc21f7f069d12eb7450c27d5e9f61ad7391dfb39d08c258 | from sympy.assumptions.ask import Q
from sympy.core.symbol import Symbol
from sympy.assumptions.wrapper import (AssumptionsWrapper, is_infinite,
is_extended_real)
def test_AssumptionsWrapper():
x = Symbol('x', positive=True)
y = Symbol('y')
assert AssumptionsWrapper(x).is_positive
assert AssumptionsWrapper(y).is_positive is None
assert AssumptionsWrapper(y, Q.positive(y)).is_positive
def test_is_infinite():
x = Symbol('x', infinite=True)
y = Symbol('y', infinite=False)
z = Symbol('z')
assert is_infinite(x)
assert not is_infinite(y)
assert is_infinite(z) is None
assert is_infinite(z, Q.infinite(z))
def test_is_extended_real():
x = Symbol('x', extended_real=True)
y = Symbol('y', extended_real=False)
z = Symbol('z')
assert is_extended_real(x)
assert not is_extended_real(y)
assert is_extended_real(z) is None
assert is_extended_real(z, Q.extended_real(z))
|
76952670a7f58a8643ca0717255765cea2c76efe73808fddeca8387a7da7e55d | from sympy.abc import t, w, x, y, z, n, k, m, p, i
from sympy.assumptions import (ask, AssumptionsContext, Q, register_handler,
remove_handler)
from sympy.assumptions.assume import assuming, global_assumptions, Predicate
from sympy.assumptions.cnf import CNF, Literal
from sympy.assumptions.facts import (single_fact_lookup,
get_known_facts, generate_known_facts_dict, get_known_facts_keys)
from sympy.assumptions.handlers import AskHandler
from sympy.assumptions.ask_generated import (get_all_known_facts,
get_known_facts_dict)
from sympy.core.add import Add
from sympy.core.numbers import (I, Integer, Rational, oo, zoo, pi)
from sympy.core.singleton import S
from sympy.core.power import Pow
from sympy.core.symbol import symbols, Symbol
from sympy.functions.combinatorial.factorials import factorial
from sympy.functions.elementary.complexes import (Abs, im, re, sign)
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.trigonometric import (
acos, acot, asin, atan, cos, cot, sin, tan)
from sympy.logic.boolalg import Equivalent, Implies, Xor, And, to_cnf
from sympy.matrices import Matrix, SparseMatrix
from sympy.testing.pytest import XFAIL, slow, raises, warns_deprecated_sympy, _both_exp_pow
import math
def test_int_1():
z = 1
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is True
assert ask(Q.rational(z)) is True
assert ask(Q.real(z)) is True
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is False
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is True
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is False
assert ask(Q.odd(z)) is True
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is True
assert ask(Q.antihermitian(z)) is False
def test_int_11():
z = 11
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is True
assert ask(Q.rational(z)) is True
assert ask(Q.real(z)) is True
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is False
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is True
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is False
assert ask(Q.odd(z)) is True
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is True
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is True
assert ask(Q.antihermitian(z)) is False
def test_int_12():
z = 12
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is True
assert ask(Q.rational(z)) is True
assert ask(Q.real(z)) is True
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is False
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is True
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is True
assert ask(Q.odd(z)) is False
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is True
assert ask(Q.hermitian(z)) is True
assert ask(Q.antihermitian(z)) is False
def test_float_1():
z = 1.0
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is False
assert ask(Q.rational(z)) is None
assert ask(Q.real(z)) is True
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is None
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is True
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is False
assert ask(Q.odd(z)) is False
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is True
assert ask(Q.antihermitian(z)) is False
z = 7.2123
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is False
assert ask(Q.rational(z)) is None
assert ask(Q.real(z)) is True
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is None
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is True
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is False
assert ask(Q.odd(z)) is False
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is True
assert ask(Q.antihermitian(z)) is False
# test for issue #12168
assert ask(Q.rational(math.pi)) is None
def test_zero_0():
z = Integer(0)
assert ask(Q.nonzero(z)) is False
assert ask(Q.zero(z)) is True
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is True
assert ask(Q.rational(z)) is True
assert ask(Q.real(z)) is True
assert ask(Q.complex(z)) is True
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is False
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is True
assert ask(Q.odd(z)) is False
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is True
assert ask(Q.antihermitian(z)) is True
def test_negativeone():
z = Integer(-1)
assert ask(Q.nonzero(z)) is True
assert ask(Q.zero(z)) is False
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is True
assert ask(Q.rational(z)) is True
assert ask(Q.real(z)) is True
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is False
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is False
assert ask(Q.negative(z)) is True
assert ask(Q.even(z)) is False
assert ask(Q.odd(z)) is True
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is True
assert ask(Q.antihermitian(z)) is False
def test_infinity():
assert ask(Q.commutative(oo)) is True
assert ask(Q.integer(oo)) is False
assert ask(Q.rational(oo)) is False
assert ask(Q.algebraic(oo)) is False
assert ask(Q.real(oo)) is False
assert ask(Q.extended_real(oo)) is True
assert ask(Q.complex(oo)) is False
assert ask(Q.irrational(oo)) is False
assert ask(Q.imaginary(oo)) is False
assert ask(Q.positive(oo)) is False
assert ask(Q.extended_positive(oo)) is True
assert ask(Q.negative(oo)) is False
assert ask(Q.even(oo)) is False
assert ask(Q.odd(oo)) is False
assert ask(Q.finite(oo)) is False
assert ask(Q.infinite(oo)) is True
assert ask(Q.prime(oo)) is False
assert ask(Q.composite(oo)) is False
assert ask(Q.hermitian(oo)) is False
assert ask(Q.antihermitian(oo)) is False
assert ask(Q.positive_infinite(oo)) is True
assert ask(Q.negative_infinite(oo)) is False
def test_neg_infinity():
mm = S.NegativeInfinity
assert ask(Q.commutative(mm)) is True
assert ask(Q.integer(mm)) is False
assert ask(Q.rational(mm)) is False
assert ask(Q.algebraic(mm)) is False
assert ask(Q.real(mm)) is False
assert ask(Q.extended_real(mm)) is True
assert ask(Q.complex(mm)) is False
assert ask(Q.irrational(mm)) is False
assert ask(Q.imaginary(mm)) is False
assert ask(Q.positive(mm)) is False
assert ask(Q.negative(mm)) is False
assert ask(Q.extended_negative(mm)) is True
assert ask(Q.even(mm)) is False
assert ask(Q.odd(mm)) is False
assert ask(Q.finite(mm)) is False
assert ask(Q.infinite(oo)) is True
assert ask(Q.prime(mm)) is False
assert ask(Q.composite(mm)) is False
assert ask(Q.hermitian(mm)) is False
assert ask(Q.antihermitian(mm)) is False
assert ask(Q.positive_infinite(-oo)) is False
assert ask(Q.negative_infinite(-oo)) is True
def test_complex_infinity():
assert ask(Q.commutative(zoo)) is True
assert ask(Q.integer(zoo)) is False
assert ask(Q.rational(zoo)) is False
assert ask(Q.algebraic(zoo)) is False
assert ask(Q.real(zoo)) is False
assert ask(Q.extended_real(zoo)) is False
assert ask(Q.complex(zoo)) is False
assert ask(Q.irrational(zoo)) is False
assert ask(Q.imaginary(zoo)) is False
assert ask(Q.positive(zoo)) is False
assert ask(Q.negative(zoo)) is False
assert ask(Q.zero(zoo)) is False
assert ask(Q.nonzero(zoo)) is False
assert ask(Q.even(zoo)) is False
assert ask(Q.odd(zoo)) is False
assert ask(Q.finite(zoo)) is False
assert ask(Q.infinite(zoo)) is True
assert ask(Q.prime(zoo)) is False
assert ask(Q.composite(zoo)) is False
assert ask(Q.hermitian(zoo)) is False
assert ask(Q.antihermitian(zoo)) is False
assert ask(Q.positive_infinite(zoo)) is False
assert ask(Q.negative_infinite(zoo)) is False
def test_nan():
nan = S.NaN
assert ask(Q.commutative(nan)) is True
assert ask(Q.integer(nan)) is None
assert ask(Q.rational(nan)) is None
assert ask(Q.algebraic(nan)) is None
assert ask(Q.real(nan)) is None
assert ask(Q.extended_real(nan)) is None
assert ask(Q.complex(nan)) is None
assert ask(Q.irrational(nan)) is None
assert ask(Q.imaginary(nan)) is None
assert ask(Q.positive(nan)) is None
assert ask(Q.nonzero(nan)) is None
assert ask(Q.zero(nan)) is None
assert ask(Q.even(nan)) is None
assert ask(Q.odd(nan)) is None
assert ask(Q.finite(nan)) is None
assert ask(Q.infinite(nan)) is None
assert ask(Q.prime(nan)) is None
assert ask(Q.composite(nan)) is None
assert ask(Q.hermitian(nan)) is None
assert ask(Q.antihermitian(nan)) is None
def test_Rational_number():
r = Rational(3, 4)
assert ask(Q.commutative(r)) is True
assert ask(Q.integer(r)) is False
assert ask(Q.rational(r)) is True
assert ask(Q.real(r)) is True
assert ask(Q.complex(r)) is True
assert ask(Q.irrational(r)) is False
assert ask(Q.imaginary(r)) is False
assert ask(Q.positive(r)) is True
assert ask(Q.negative(r)) is False
assert ask(Q.even(r)) is False
assert ask(Q.odd(r)) is False
assert ask(Q.finite(r)) is True
assert ask(Q.prime(r)) is False
assert ask(Q.composite(r)) is False
assert ask(Q.hermitian(r)) is True
assert ask(Q.antihermitian(r)) is False
r = Rational(1, 4)
assert ask(Q.positive(r)) is True
assert ask(Q.negative(r)) is False
r = Rational(5, 4)
assert ask(Q.negative(r)) is False
assert ask(Q.positive(r)) is True
r = Rational(5, 3)
assert ask(Q.positive(r)) is True
assert ask(Q.negative(r)) is False
r = Rational(-3, 4)
assert ask(Q.positive(r)) is False
assert ask(Q.negative(r)) is True
r = Rational(-1, 4)
assert ask(Q.positive(r)) is False
assert ask(Q.negative(r)) is True
r = Rational(-5, 4)
assert ask(Q.negative(r)) is True
assert ask(Q.positive(r)) is False
r = Rational(-5, 3)
assert ask(Q.positive(r)) is False
assert ask(Q.negative(r)) is True
def test_sqrt_2():
z = sqrt(2)
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is False
assert ask(Q.rational(z)) is False
assert ask(Q.real(z)) is True
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is True
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is True
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is False
assert ask(Q.odd(z)) is False
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is True
assert ask(Q.antihermitian(z)) is False
def test_pi():
z = S.Pi
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is False
assert ask(Q.rational(z)) is False
assert ask(Q.algebraic(z)) is False
assert ask(Q.real(z)) is True
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is True
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is True
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is False
assert ask(Q.odd(z)) is False
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is True
assert ask(Q.antihermitian(z)) is False
z = S.Pi + 1
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is False
assert ask(Q.rational(z)) is False
assert ask(Q.algebraic(z)) is False
assert ask(Q.real(z)) is True
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is True
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is True
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is False
assert ask(Q.odd(z)) is False
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is True
assert ask(Q.antihermitian(z)) is False
z = 2*S.Pi
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is False
assert ask(Q.rational(z)) is False
assert ask(Q.algebraic(z)) is False
assert ask(Q.real(z)) is True
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is True
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is True
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is False
assert ask(Q.odd(z)) is False
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is True
assert ask(Q.antihermitian(z)) is False
z = S.Pi ** 2
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is False
assert ask(Q.rational(z)) is False
assert ask(Q.algebraic(z)) is False
assert ask(Q.real(z)) is True
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is True
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is True
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is False
assert ask(Q.odd(z)) is False
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is True
assert ask(Q.antihermitian(z)) is False
z = (1 + S.Pi) ** 2
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is False
assert ask(Q.rational(z)) is False
assert ask(Q.algebraic(z)) is False
assert ask(Q.real(z)) is True
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is True
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is True
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is False
assert ask(Q.odd(z)) is False
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is True
assert ask(Q.antihermitian(z)) is False
def test_E():
z = S.Exp1
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is False
assert ask(Q.rational(z)) is False
assert ask(Q.algebraic(z)) is False
assert ask(Q.real(z)) is True
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is True
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is True
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is False
assert ask(Q.odd(z)) is False
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is True
assert ask(Q.antihermitian(z)) is False
def test_GoldenRatio():
z = S.GoldenRatio
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is False
assert ask(Q.rational(z)) is False
assert ask(Q.algebraic(z)) is True
assert ask(Q.real(z)) is True
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is True
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is True
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is False
assert ask(Q.odd(z)) is False
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is True
assert ask(Q.antihermitian(z)) is False
def test_TribonacciConstant():
z = S.TribonacciConstant
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is False
assert ask(Q.rational(z)) is False
assert ask(Q.algebraic(z)) is True
assert ask(Q.real(z)) is True
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is True
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is True
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is False
assert ask(Q.odd(z)) is False
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is True
assert ask(Q.antihermitian(z)) is False
def test_I():
z = I
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is False
assert ask(Q.rational(z)) is False
assert ask(Q.algebraic(z)) is True
assert ask(Q.real(z)) is False
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is False
assert ask(Q.imaginary(z)) is True
assert ask(Q.positive(z)) is False
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is False
assert ask(Q.odd(z)) is False
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is False
assert ask(Q.antihermitian(z)) is True
z = 1 + I
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is False
assert ask(Q.rational(z)) is False
assert ask(Q.algebraic(z)) is True
assert ask(Q.real(z)) is False
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is False
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is False
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is False
assert ask(Q.odd(z)) is False
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is False
assert ask(Q.antihermitian(z)) is False
z = I*(1 + I)
assert ask(Q.commutative(z)) is True
assert ask(Q.integer(z)) is False
assert ask(Q.rational(z)) is False
assert ask(Q.algebraic(z)) is True
assert ask(Q.real(z)) is False
assert ask(Q.complex(z)) is True
assert ask(Q.irrational(z)) is False
assert ask(Q.imaginary(z)) is False
assert ask(Q.positive(z)) is False
assert ask(Q.negative(z)) is False
assert ask(Q.even(z)) is False
assert ask(Q.odd(z)) is False
assert ask(Q.finite(z)) is True
assert ask(Q.prime(z)) is False
assert ask(Q.composite(z)) is False
assert ask(Q.hermitian(z)) is False
assert ask(Q.antihermitian(z)) is False
z = I**(I)
assert ask(Q.imaginary(z)) is False
assert ask(Q.real(z)) is True
z = (-I)**(I)
assert ask(Q.imaginary(z)) is False
assert ask(Q.real(z)) is True
z = (3*I)**(I)
assert ask(Q.imaginary(z)) is False
assert ask(Q.real(z)) is False
z = (1)**(I)
assert ask(Q.imaginary(z)) is False
assert ask(Q.real(z)) is True
z = (-1)**(I)
assert ask(Q.imaginary(z)) is False
assert ask(Q.real(z)) is True
z = (1+I)**(I)
assert ask(Q.imaginary(z)) is False
assert ask(Q.real(z)) is False
z = (I)**(I+3)
assert ask(Q.imaginary(z)) is True
assert ask(Q.real(z)) is False
z = (I)**(I+2)
assert ask(Q.imaginary(z)) is False
assert ask(Q.real(z)) is True
z = (I)**(2)
assert ask(Q.imaginary(z)) is False
assert ask(Q.real(z)) is True
z = (I)**(3)
assert ask(Q.imaginary(z)) is True
assert ask(Q.real(z)) is False
z = (3)**(I)
assert ask(Q.imaginary(z)) is False
assert ask(Q.real(z)) is False
z = (I)**(0)
assert ask(Q.imaginary(z)) is False
assert ask(Q.real(z)) is True
def test_bounded():
x, y, z = symbols('x,y,z')
assert ask(Q.finite(x)) is None
assert ask(Q.finite(x), Q.finite(x)) is True
assert ask(Q.finite(x), Q.finite(y)) is None
assert ask(Q.finite(x), Q.complex(x)) is True
assert ask(Q.finite(x), Q.extended_real(x)) is None
assert ask(Q.finite(x + 1)) is None
assert ask(Q.finite(x + 1), Q.finite(x)) is True
a = x + y
x, y = a.args
# B + B
assert ask(Q.finite(a), Q.finite(x) & Q.finite(y)) is True
assert ask(Q.finite(a), Q.positive(x) & Q.finite(y)) is True
assert ask(Q.finite(a), Q.finite(x) & Q.positive(y)) is True
assert ask(Q.finite(a), Q.positive(x) & Q.positive(y)) is True
assert ask(Q.finite(a), Q.positive(x) & Q.finite(y)
& ~Q.positive(y)) is True
assert ask(Q.finite(a), Q.finite(x) & ~Q.positive(x)
& Q.positive(y)) is True
assert ask(Q.finite(a), Q.finite(x) & Q.finite(y) & ~Q.positive(x)
& ~Q.positive(y)) is True
# B + U
assert ask(Q.finite(a), Q.finite(x) & ~Q.finite(y)) is False
assert ask(Q.finite(a), Q.positive(x) & ~Q.finite(y)) is False
assert ask(Q.finite(a), Q.finite(x)
& Q.positive_infinite(y)) is False
assert ask(Q.finite(a), Q.positive(x)
& Q.positive_infinite(y)) is False
assert ask(Q.finite(a), Q.positive(x) & ~Q.finite(y)
& ~Q.positive(y)) is False
assert ask(Q.finite(a), Q.finite(x) & ~Q.positive(x)
& Q.positive_infinite(y)) is False
assert ask(Q.finite(a), Q.finite(x) & ~Q.positive(x) & ~Q.finite(y)
& ~Q.positive(y)) is False
# B + ?
assert ask(Q.finite(a), Q.finite(x)) is None
assert ask(Q.finite(a), Q.positive(x)) is None
assert ask(Q.finite(a), Q.finite(x)
& Q.extended_positive(y)) is None
assert ask(Q.finite(a), Q.positive(x)
& Q.extended_positive(y)) is None
assert ask(Q.finite(a), Q.positive(x) & ~Q.positive(y)) is None
assert ask(Q.finite(a), Q.finite(x) & ~Q.positive(x)
& Q.extended_positive(y)) is None
assert ask(Q.finite(a), Q.finite(x) & ~Q.positive(x)
& ~Q.positive(y)) is None
# U + U
assert ask(Q.finite(a), ~Q.finite(x) & ~Q.finite(y)) is None
assert ask(Q.finite(a), Q.positive_infinite(x)
& ~Q.finite(y)) is None
assert ask(Q.finite(a), ~Q.finite(x)
& Q.positive_infinite(y)) is None
assert ask(Q.finite(a), Q.positive_infinite(x)
& Q.positive_infinite(y)) is False
assert ask(Q.finite(a), Q.positive_infinite(x) & ~Q.finite(y)
& ~Q.extended_positive(y)) is None
assert ask(Q.finite(a), ~Q.finite(x) & ~Q.extended_positive(x)
& Q.positive_infinite(y)) is None
assert ask(Q.finite(a), ~Q.finite(x) & ~Q.finite(y)
& ~Q.extended_positive(x) & ~Q.extended_positive(y)) is False
# U + ?
assert ask(Q.finite(a), ~Q.finite(y)) is None
assert ask(Q.finite(a), Q.extended_positive(x)
& ~Q.finite(y)) is None
assert ask(Q.finite(a), Q.positive_infinite(y)) is None
assert ask(Q.finite(a), Q.extended_positive(x)
& Q.positive_infinite(y)) is False
assert ask(Q.finite(a), Q.extended_positive(x)
& ~Q.finite(y) & ~Q.extended_positive(y)) is None
assert ask(Q.finite(a), ~Q.extended_positive(x)
& Q.positive_infinite(y)) is None
assert ask(Q.finite(a), ~Q.extended_positive(x) & ~Q.finite(y)
& ~Q.extended_positive(y)) is False
# ? + ?
assert ask(Q.finite(a)) is None
assert ask(Q.finite(a), Q.extended_positive(x)) is None
assert ask(Q.finite(a), Q.extended_positive(y)) is None
assert ask(Q.finite(a), Q.extended_positive(x)
& Q.extended_positive(y)) is None
assert ask(Q.finite(a), Q.extended_positive(x)
& ~Q.extended_positive(y)) is None
assert ask(Q.finite(a), ~Q.extended_positive(x)
& Q.extended_positive(y)) is None
assert ask(Q.finite(a), ~Q.extended_positive(x)
& ~Q.extended_positive(y)) is None
x, y, z = symbols('x,y,z')
a = x + y + z
x, y, z = a.args
assert ask(Q.finite(a), Q.negative(x) & Q.negative(y)
& Q.negative(z)) is True
assert ask(Q.finite(a), Q.negative(x) & Q.negative(y)
& Q.finite(z)) is True
assert ask(Q.finite(a), Q.negative(x) & Q.negative(y)
& Q.positive(z)) is True
assert ask(Q.finite(a), Q.negative(x) & Q.negative(y)
& Q.negative_infinite(z)) is False
assert ask(Q.finite(a), Q.negative(x) & Q.negative(y)
& ~Q.finite(z)) is False
assert ask(Q.finite(a), Q.negative(x) & Q.negative(y)
& Q.positive_infinite(z)) is False
assert ask(Q.finite(a), Q.negative(x) & Q.negative(y)
& Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.negative(x) & Q.negative(y)) is None
assert ask(Q.finite(a), Q.negative(x) & Q.negative(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.negative(x) & Q.finite(y)
& Q.finite(z)) is True
assert ask(Q.finite(a), Q.negative(x) & Q.finite(y)
& Q.positive(z)) is True
assert ask(Q.finite(a), Q.negative(x) & Q.finite(y)
& Q.negative_infinite(z)) is False
assert ask(Q.finite(a), Q.negative(x) & Q.finite(y)
& ~Q.finite(z)) is False
assert ask(Q.finite(a), Q.negative(x) & Q.finite(y)
& Q.positive_infinite(z)) is False
assert ask(Q.finite(a), Q.negative(x) & Q.finite(y)
& Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.negative(x) & Q.finite(y)) is None
assert ask(Q.finite(a), Q.negative(x) & Q.finite(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.negative(x) & Q.positive(y)
& Q.positive(z)) is True
assert ask(Q.finite(a), Q.negative(x) & Q.positive(y)
& Q.negative_infinite(z)) is False
assert ask(Q.finite(a), Q.negative(x) & Q.positive(y)
& ~Q.finite(z)) is False
assert ask(Q.finite(a), Q.negative(x) & Q.positive(y)
& Q.positive_infinite(z)) is False
assert ask(Q.finite(a), Q.negative(x) & Q.positive(y)
& Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.negative(x) & Q.extended_positive(y)
& Q.finite(y)) is None
assert ask(Q.finite(a), Q.negative(x) & Q.positive(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.negative(x) & Q.negative_infinite(y)
& Q.negative_infinite(z)) is False
assert ask(Q.finite(a), Q.negative(x) & Q.negative_infinite(y)
& ~Q.finite(z)) is None
assert ask(Q.finite(a), Q.negative(x) & Q.negative_infinite(y)
& Q.positive_infinite(z)) is None
assert ask(Q.finite(a), Q.negative(x) & Q.negative_infinite(y)
& Q.extended_negative(z)) is False
assert ask(Q.finite(a), Q.negative(x)
& Q.negative_infinite(y)) is None
assert ask(Q.finite(a), Q.negative(x) & Q.negative_infinite(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.negative(x) & ~Q.finite(y)
& ~Q.finite(z)) is None
assert ask(Q.finite(a), Q.negative(x) & ~Q.finite(y)
& Q.positive_infinite(z)) is None
assert ask(Q.finite(a), Q.negative(x) & ~Q.finite(y)
& Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.negative(x) & ~Q.finite(y)) is None
assert ask(Q.finite(a), Q.negative(x) & ~Q.finite(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.negative(x) & Q.positive_infinite(y)
& Q.positive_infinite(z)) is False
assert ask(Q.finite(a), Q.negative(x) & Q.positive_infinite(y)
& Q.negative_infinite(z)) is None
assert ask(Q.finite(a), Q.negative(x) &
Q.positive_infinite(y)) is None
assert ask(Q.finite(a), Q.negative(x) & Q.positive_infinite(y)
& Q.extended_positive(z)) is False
assert ask(Q.finite(a), Q.negative(x) & Q.extended_negative(y)
& Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.negative(x)
& Q.extended_negative(y)) is None
assert ask(Q.finite(a), Q.negative(x) & Q.extended_negative(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.negative(x)) is None
assert ask(Q.finite(a), Q.negative(x)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.negative(x) & Q.extended_positive(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.finite(x) & Q.finite(y)
& Q.finite(z)) is True
assert ask(Q.finite(a), Q.finite(x) & Q.finite(y)
& Q.positive(z)) is True
assert ask(Q.finite(a), Q.finite(x) & Q.finite(y)
& Q.negative_infinite(z)) is False
assert ask(Q.finite(a), Q.finite(x) & Q.finite(y)
& ~Q.finite(z)) is False
assert ask(Q.finite(a), Q.finite(x) & Q.finite(y)
& Q.positive_infinite(z)) is False
assert ask(Q.finite(a), Q.finite(x) & Q.finite(y)
& Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.finite(x) & Q.finite(y)) is None
assert ask(Q.finite(a), Q.finite(x) & Q.finite(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.finite(x) & Q.positive(y)
& Q.positive(z)) is True
assert ask(Q.finite(a), Q.finite(x) & Q.positive(y)
& Q.negative_infinite(z)) is False
assert ask(Q.finite(a), Q.finite(x) & Q.positive(y)
& ~Q.finite(z)) is False
assert ask(Q.finite(a), Q.finite(x) & Q.positive(y)
& Q.positive_infinite(z)) is False
assert ask(Q.finite(a), Q.finite(x) & Q.positive(y)
& Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.finite(x) & Q.positive(y)) is None
assert ask(Q.finite(a), Q.finite(x) & Q.positive(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.finite(x) & Q.negative_infinite(y)
& Q.negative_infinite(z)) is False
assert ask(Q.finite(a), Q.finite(x) & Q.negative_infinite(y)
& ~Q.finite(z)) is None
assert ask(Q.finite(a), Q.finite(x) & Q.negative_infinite(y)
& Q.positive_infinite(z)) is None
assert ask(Q.finite(a), Q.finite(x) & Q.negative_infinite(y)
& Q.extended_negative(z)) is False
assert ask(Q.finite(a), Q.finite(x)
& Q.negative_infinite(y)) is None
assert ask(Q.finite(a), Q.finite(x) & Q.negative_infinite(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.finite(x) & ~Q.finite(y)
& ~Q.finite(z)) is None
assert ask(Q.finite(a), Q.finite(x) & ~Q.finite(y)
& Q.positive_infinite(z)) is None
assert ask(Q.finite(a), Q.finite(x) & ~Q.finite(y)
& Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.finite(x) & ~Q.finite(y)) is None
assert ask(Q.finite(a), Q.finite(x) & ~Q.finite(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.finite(x) & Q.positive_infinite(y)
& Q.positive_infinite(z)) is False
assert ask(Q.finite(a), Q.finite(x) & Q.positive_infinite(y)
& Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.finite(x)
& Q.positive_infinite(y)) is None
assert ask(Q.finite(a), Q.finite(x) & Q.positive_infinite(y)
& Q.extended_positive(z)) is False
assert ask(Q.finite(a), Q.finite(x) & Q.extended_negative(y)
& Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.finite(x)
& Q.extended_negative(y)) is None
assert ask(Q.finite(a), Q.finite(x) & Q.extended_negative(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.finite(x)) is None
assert ask(Q.finite(a), Q.finite(x)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.finite(x) & Q.extended_positive(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.positive(x) & Q.positive(y)
& Q.positive(z)) is True
assert ask(Q.finite(a), Q.positive(x) & Q.positive(y)
& Q.negative_infinite(z)) is False
assert ask(Q.finite(a), Q.positive(x) & Q.positive(y)
& ~Q.finite(z)) is False
assert ask(Q.finite(a), Q.positive(x) & Q.positive(y)
& Q.positive_infinite(z)) is False
assert ask(Q.finite(a), Q.positive(x) & Q.positive(y)
& Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.positive(x) & Q.positive(y)) is None
assert ask(Q.finite(a), Q.positive(x) & Q.positive(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.positive(x) & Q.negative_infinite(y)
& Q.negative_infinite(z)) is False
assert ask(Q.finite(a), Q.positive(x) & Q.negative_infinite(y)
& ~Q.finite(z)) is None
assert ask(Q.finite(a), Q.positive(x) & Q.negative_infinite(y)
& Q.positive_infinite(z)) is None
assert ask(Q.finite(a), Q.positive(x) & Q.negative_infinite(y)
& Q.extended_negative(z)) is False
assert ask(Q.finite(a), Q.positive(x)
& Q.negative_infinite(y)) is None
assert ask(Q.finite(a), Q.positive(x) & Q.negative_infinite(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.positive(x) & ~Q.finite(y)
& ~Q.finite(z)) is None
assert ask(Q.finite(a), Q.positive(x) & ~Q.finite(y)
& Q.positive_infinite(z)) is None
assert ask(Q.finite(a), Q.positive(x) & ~Q.finite(y)
& Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.positive(x) & ~Q.finite(y)) is None
assert ask(Q.finite(a), Q.positive(x) & ~Q.finite(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.positive(x) & Q.positive_infinite(y)
& Q.positive_infinite(z)) is False
assert ask(Q.finite(a), Q.positive(x) & Q.positive_infinite(y)
& Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.positive(x)
& Q.positive_infinite(y)) is None
assert ask(Q.finite(a), Q.positive(x) & Q.positive_infinite(y)
& Q.extended_positive(z)) is False
assert ask(Q.finite(a), Q.positive(x) & Q.extended_negative(y)
& Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.positive(x)
& Q.extended_negative(y)) is None
assert ask(Q.finite(a), Q.positive(x) & Q.extended_negative(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.positive(x)) is None
assert ask(Q.finite(a), Q.positive(x)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.positive(x) & Q.extended_positive(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)
& Q.negative_infinite(y) & Q.negative_infinite(z)) is False
assert ask(Q.finite(a), Q.negative_infinite(x)
& Q.negative_infinite(y) & ~Q.finite(z)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)
& Q.negative_infinite(y)& Q.positive_infinite(z)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)
& Q.negative_infinite(y) & Q.extended_negative(z)) is False
assert ask(Q.finite(a), Q.negative_infinite(x)
& Q.negative_infinite(y)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)
& Q.negative_infinite(y) & Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)
& ~Q.finite(y) & ~Q.finite(z)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)
& ~Q.finite(y) & Q.positive_infinite(z)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)
& ~Q.finite(y) & Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)
& ~Q.finite(y)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)
& ~Q.finite(y) & Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)
& Q.positive_infinite(y) & Q.positive_infinite(z)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)
& Q.positive_infinite(y) & Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)
& Q.positive_infinite(y)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)
& Q.positive_infinite(y) & Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)
& Q.extended_negative(y) & Q.extended_negative(z)) is False
assert ask(Q.finite(a), Q.negative_infinite(x)
& Q.extended_negative(y)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)
& Q.extended_negative(y) & Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.negative_infinite(x)
& Q.extended_positive(y) & Q.extended_positive(z)) is None
assert ask(Q.finite(a), ~Q.finite(x) & ~Q.finite(y)
& ~Q.finite(z)) is None
assert ask(Q.finite(a), ~Q.finite(x) & Q.positive_infinite(z)
& ~Q.finite(z)) is None
assert ask(Q.finite(a), ~Q.finite(x) & ~Q.finite(y)
& Q.extended_negative(z)) is None
assert ask(Q.finite(a), ~Q.finite(x) & ~Q.finite(y)) is None
assert ask(Q.finite(a), ~Q.finite(x) & ~Q.finite(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), ~Q.finite(x) & Q.positive_infinite(y)
& Q.positive_infinite(z)) is None
assert ask(Q.finite(a), ~Q.finite(x) & Q.positive_infinite(y)
& Q.extended_negative(z)) is None
assert ask(Q.finite(a), ~Q.finite(x)
& Q.positive_infinite(y)) is None
assert ask(Q.finite(a), ~Q.finite(x) & Q.positive_infinite(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), ~Q.finite(x) & Q.extended_negative(y)
& Q.extended_negative(z)) is None
assert ask(Q.finite(a), ~Q.finite(x)
& Q.extended_negative(y)) is None
assert ask(Q.finite(a), ~Q.finite(x) & Q.extended_negative(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), ~Q.finite(x)) is None
assert ask(Q.finite(a), ~Q.finite(x)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), ~Q.finite(x) & Q.extended_positive(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.positive_infinite(x)
& Q.positive_infinite(y) & Q.positive_infinite(z)) is False
assert ask(Q.finite(a), Q.positive_infinite(x)
& Q.positive_infinite(y) & Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.positive_infinite(x)
& Q.positive_infinite(y)) is None
assert ask(Q.finite(a), Q.positive_infinite(x)
& Q.positive_infinite(y) & Q.extended_positive(z)) is False
assert ask(Q.finite(a), Q.positive_infinite(x)
& Q.extended_negative(y) & Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.positive_infinite(x)
& Q.extended_negative(y)) is None
assert ask(Q.finite(a), Q.positive_infinite(x)
& Q.extended_negative(y) & Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.positive_infinite(x)) is None
assert ask(Q.finite(a), Q.positive_infinite(x)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.positive_infinite(x)
& Q.extended_positive(y) & Q.extended_positive(z)) is False
assert ask(Q.finite(a), Q.extended_negative(x)
& Q.extended_negative(y) & Q.extended_negative(z)) is None
assert ask(Q.finite(a), Q.extended_negative(x)
& Q.extended_negative(y)) is None
assert ask(Q.finite(a), Q.extended_negative(x)
& Q.extended_negative(y) & Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.extended_negative(x)) is None
assert ask(Q.finite(a), Q.extended_negative(x)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.extended_negative(x)
& Q.extended_positive(y) & Q.extended_positive(z)) is None
assert ask(Q.finite(a)) is None
assert ask(Q.finite(a), Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.extended_positive(y)
& Q.extended_positive(z)) is None
assert ask(Q.finite(a), Q.extended_positive(x)
& Q.extended_positive(y) & Q.extended_positive(z)) is None
assert ask(Q.finite(2*x)) is None
assert ask(Q.finite(2*x), Q.finite(x)) is True
x, y, z = symbols('x,y,z')
a = x*y
x, y = a.args
assert ask(Q.finite(a), Q.finite(x) & Q.finite(y)) is True
assert ask(Q.finite(a), Q.finite(x) & ~Q.finite(y)) is False
assert ask(Q.finite(a), Q.finite(x)) is None
assert ask(Q.finite(a), ~Q.finite(x) & Q.finite(y)) is False
assert ask(Q.finite(a), ~Q.finite(x) & ~Q.finite(y)) is False
assert ask(Q.finite(a), ~Q.finite(x)) is None
assert ask(Q.finite(a), Q.finite(y)) is None
assert ask(Q.finite(a), ~Q.finite(y)) is None
assert ask(Q.finite(a)) is None
a = x*y*z
x, y, z = a.args
assert ask(Q.finite(a), Q.finite(x) & Q.finite(y)
& Q.finite(z)) is True
assert ask(Q.finite(a), Q.finite(x) & Q.finite(y)
& ~Q.finite(z)) is False
assert ask(Q.finite(a), Q.finite(x) & Q.finite(y)) is None
assert ask(Q.finite(a), Q.finite(x) & ~Q.finite(y)
& Q.finite(z)) is False
assert ask(Q.finite(a), Q.finite(x) & ~Q.finite(y)
& ~Q.finite(z)) is False
assert ask(Q.finite(a), Q.finite(x) & ~Q.finite(y)) is None
assert ask(Q.finite(a), Q.finite(x) & Q.finite(z)) is None
assert ask(Q.finite(a), Q.finite(x) & ~Q.finite(z)) is None
assert ask(Q.finite(a), Q.finite(x)) is None
assert ask(Q.finite(a), ~Q.finite(x) & Q.finite(y)
& Q.finite(z)) is False
assert ask(Q.finite(a), ~Q.finite(x) & Q.finite(y)
& ~Q.finite(z)) is False
assert ask(Q.finite(a), ~Q.finite(x) & Q.finite(y)) is None
assert ask(Q.finite(a), ~Q.finite(x) & ~Q.finite(y)
& Q.finite(z)) is False
assert ask(Q.finite(a), ~Q.finite(x) & ~Q.finite(y)
& ~Q.finite(z)) is False
assert ask(Q.finite(a), ~Q.finite(x) & ~Q.finite(y)) is None
assert ask(Q.finite(a), ~Q.finite(x) & Q.finite(z)) is None
assert ask(Q.finite(a), ~Q.finite(x) & ~Q.finite(z)) is None
assert ask(Q.finite(a), ~Q.finite(x)) is None
assert ask(Q.finite(a), Q.finite(y) & Q.finite(z)) is None
assert ask(Q.finite(a), Q.finite(y) & ~Q.finite(z)) is None
assert ask(Q.finite(a), Q.finite(y)) is None
assert ask(Q.finite(a), ~Q.finite(y) & Q.finite(z)) is None
assert ask(Q.finite(a), ~Q.finite(y) & ~Q.finite(z)) is None
assert ask(Q.finite(a), ~Q.finite(y)) is None
assert ask(Q.finite(a), Q.finite(z)) is None
assert ask(Q.finite(a), ~Q.finite(z)) is None
assert ask(Q.finite(a), ~Q.finite(z) & Q.extended_nonzero(x)
& Q.extended_nonzero(y) & Q.extended_nonzero(z)) is None
assert ask(Q.finite(a), Q.extended_nonzero(x) & ~Q.finite(y)
& Q.extended_nonzero(y) & ~Q.finite(z)
& Q.extended_nonzero(z)) is False
x, y, z = symbols('x,y,z')
assert ask(Q.finite(x**2)) is None
assert ask(Q.finite(2**x)) is None
assert ask(Q.finite(2**x), Q.finite(x)) is True
assert ask(Q.finite(x**x)) is None
assert ask(Q.finite(S.Half ** x)) is None
assert ask(Q.finite(S.Half ** x), Q.extended_positive(x)) is True
assert ask(Q.finite(S.Half ** x), Q.extended_negative(x)) is None
assert ask(Q.finite(2**x), Q.extended_negative(x)) is True
assert ask(Q.finite(sqrt(x))) is None
assert ask(Q.finite(2**x), ~Q.finite(x)) is False
assert ask(Q.finite(x**2), ~Q.finite(x)) is False
# sign function
assert ask(Q.finite(sign(x))) is True
assert ask(Q.finite(sign(x)), ~Q.finite(x)) is True
# exponential functions
assert ask(Q.finite(log(x))) is None
assert ask(Q.finite(log(x)), Q.finite(x)) is None
assert ask(Q.finite(log(x)), ~Q.zero(x)) is True
assert ask(Q.finite(log(x)), Q.infinite(x)) is False
assert ask(Q.finite(log(x)), Q.zero(x)) is False
assert ask(Q.finite(exp(x))) is None
assert ask(Q.finite(exp(x)), Q.finite(x)) is True
assert ask(Q.finite(exp(2))) is True
# trigonometric functions
assert ask(Q.finite(sin(x))) is True
assert ask(Q.finite(sin(x)), ~Q.finite(x)) is True
assert ask(Q.finite(cos(x))) is True
assert ask(Q.finite(cos(x)), ~Q.finite(x)) is True
assert ask(Q.finite(2*sin(x))) is True
assert ask(Q.finite(sin(x)**2)) is True
assert ask(Q.finite(cos(x)**2)) is True
assert ask(Q.finite(cos(x) + sin(x))) is True
@XFAIL
def test_bounded_xfail():
"""We need to support relations in ask for this to work"""
assert ask(Q.finite(sin(x)**x)) is True
assert ask(Q.finite(cos(x)**x)) is True
def test_commutative():
"""By default objects are Q.commutative that is why it returns True
for both key=True and key=False"""
assert ask(Q.commutative(x)) is True
assert ask(Q.commutative(x), ~Q.commutative(x)) is False
assert ask(Q.commutative(x), Q.complex(x)) is True
assert ask(Q.commutative(x), Q.imaginary(x)) is True
assert ask(Q.commutative(x), Q.real(x)) is True
assert ask(Q.commutative(x), Q.positive(x)) is True
assert ask(Q.commutative(x), ~Q.commutative(y)) is True
assert ask(Q.commutative(2*x)) is True
assert ask(Q.commutative(2*x), ~Q.commutative(x)) is False
assert ask(Q.commutative(x + 1)) is True
assert ask(Q.commutative(x + 1), ~Q.commutative(x)) is False
assert ask(Q.commutative(x**2)) is True
assert ask(Q.commutative(x**2), ~Q.commutative(x)) is False
assert ask(Q.commutative(log(x))) is True
@_both_exp_pow
def test_complex():
assert ask(Q.complex(x)) is None
assert ask(Q.complex(x), Q.complex(x)) is True
assert ask(Q.complex(x), Q.complex(y)) is None
assert ask(Q.complex(x), ~Q.complex(x)) is False
assert ask(Q.complex(x), Q.real(x)) is True
assert ask(Q.complex(x), ~Q.real(x)) is None
assert ask(Q.complex(x), Q.rational(x)) is True
assert ask(Q.complex(x), Q.irrational(x)) is True
assert ask(Q.complex(x), Q.positive(x)) is True
assert ask(Q.complex(x), Q.imaginary(x)) is True
assert ask(Q.complex(x), Q.algebraic(x)) is True
# a+b
assert ask(Q.complex(x + 1), Q.complex(x)) is True
assert ask(Q.complex(x + 1), Q.real(x)) is True
assert ask(Q.complex(x + 1), Q.rational(x)) is True
assert ask(Q.complex(x + 1), Q.irrational(x)) is True
assert ask(Q.complex(x + 1), Q.imaginary(x)) is True
assert ask(Q.complex(x + 1), Q.integer(x)) is True
assert ask(Q.complex(x + 1), Q.even(x)) is True
assert ask(Q.complex(x + 1), Q.odd(x)) is True
assert ask(Q.complex(x + y), Q.complex(x) & Q.complex(y)) is True
assert ask(Q.complex(x + y), Q.real(x) & Q.imaginary(y)) is True
# a*x +b
assert ask(Q.complex(2*x + 1), Q.complex(x)) is True
assert ask(Q.complex(2*x + 1), Q.real(x)) is True
assert ask(Q.complex(2*x + 1), Q.positive(x)) is True
assert ask(Q.complex(2*x + 1), Q.rational(x)) is True
assert ask(Q.complex(2*x + 1), Q.irrational(x)) is True
assert ask(Q.complex(2*x + 1), Q.imaginary(x)) is True
assert ask(Q.complex(2*x + 1), Q.integer(x)) is True
assert ask(Q.complex(2*x + 1), Q.even(x)) is True
assert ask(Q.complex(2*x + 1), Q.odd(x)) is True
# x**2
assert ask(Q.complex(x**2), Q.complex(x)) is True
assert ask(Q.complex(x**2), Q.real(x)) is True
assert ask(Q.complex(x**2), Q.positive(x)) is True
assert ask(Q.complex(x**2), Q.rational(x)) is True
assert ask(Q.complex(x**2), Q.irrational(x)) is True
assert ask(Q.complex(x**2), Q.imaginary(x)) is True
assert ask(Q.complex(x**2), Q.integer(x)) is True
assert ask(Q.complex(x**2), Q.even(x)) is True
assert ask(Q.complex(x**2), Q.odd(x)) is True
# 2**x
assert ask(Q.complex(2**x), Q.complex(x)) is True
assert ask(Q.complex(2**x), Q.real(x)) is True
assert ask(Q.complex(2**x), Q.positive(x)) is True
assert ask(Q.complex(2**x), Q.rational(x)) is True
assert ask(Q.complex(2**x), Q.irrational(x)) is True
assert ask(Q.complex(2**x), Q.imaginary(x)) is True
assert ask(Q.complex(2**x), Q.integer(x)) is True
assert ask(Q.complex(2**x), Q.even(x)) is True
assert ask(Q.complex(2**x), Q.odd(x)) is True
assert ask(Q.complex(x**y), Q.complex(x) & Q.complex(y)) is True
# trigonometric expressions
assert ask(Q.complex(sin(x))) is True
assert ask(Q.complex(sin(2*x + 1))) is True
assert ask(Q.complex(cos(x))) is True
assert ask(Q.complex(cos(2*x + 1))) is True
# exponential
assert ask(Q.complex(exp(x))) is True
assert ask(Q.complex(exp(x))) is True
# Q.complexes
assert ask(Q.complex(Abs(x))) is True
assert ask(Q.complex(re(x))) is True
assert ask(Q.complex(im(x))) is True
def test_even_query():
assert ask(Q.even(x)) is None
assert ask(Q.even(x), Q.integer(x)) is None
assert ask(Q.even(x), ~Q.integer(x)) is False
assert ask(Q.even(x), Q.rational(x)) is None
assert ask(Q.even(x), Q.positive(x)) is None
assert ask(Q.even(2*x)) is None
assert ask(Q.even(2*x), Q.integer(x)) is True
assert ask(Q.even(2*x), Q.even(x)) is True
assert ask(Q.even(2*x), Q.irrational(x)) is False
assert ask(Q.even(2*x), Q.odd(x)) is True
assert ask(Q.even(2*x), ~Q.integer(x)) is None
assert ask(Q.even(3*x), Q.integer(x)) is None
assert ask(Q.even(3*x), Q.even(x)) is True
assert ask(Q.even(3*x), Q.odd(x)) is False
assert ask(Q.even(x + 1), Q.odd(x)) is True
assert ask(Q.even(x + 1), Q.even(x)) is False
assert ask(Q.even(x + 2), Q.odd(x)) is False
assert ask(Q.even(x + 2), Q.even(x)) is True
assert ask(Q.even(7 - x), Q.odd(x)) is True
assert ask(Q.even(7 + x), Q.odd(x)) is True
assert ask(Q.even(x + y), Q.odd(x) & Q.odd(y)) is True
assert ask(Q.even(x + y), Q.odd(x) & Q.even(y)) is False
assert ask(Q.even(x + y), Q.even(x) & Q.even(y)) is True
assert ask(Q.even(2*x + 1), Q.integer(x)) is False
assert ask(Q.even(2*x*y), Q.rational(x) & Q.rational(x)) is None
assert ask(Q.even(2*x*y), Q.irrational(x) & Q.irrational(x)) is None
assert ask(Q.even(x + y + z), Q.odd(x) & Q.odd(y) & Q.even(z)) is True
assert ask(Q.even(x + y + z + t),
Q.odd(x) & Q.odd(y) & Q.even(z) & Q.integer(t)) is None
assert ask(Q.even(Abs(x)), Q.even(x)) is True
assert ask(Q.even(Abs(x)), ~Q.even(x)) is None
assert ask(Q.even(re(x)), Q.even(x)) is True
assert ask(Q.even(re(x)), ~Q.even(x)) is None
assert ask(Q.even(im(x)), Q.even(x)) is True
assert ask(Q.even(im(x)), Q.real(x)) is True
assert ask(Q.even((-1)**n), Q.integer(n)) is False
assert ask(Q.even(k**2), Q.even(k)) is True
assert ask(Q.even(n**2), Q.odd(n)) is False
assert ask(Q.even(2**k), Q.even(k)) is None
assert ask(Q.even(x**2)) is None
assert ask(Q.even(k**m), Q.even(k) & Q.integer(m) & ~Q.negative(m)) is None
assert ask(Q.even(n**m), Q.odd(n) & Q.integer(m) & ~Q.negative(m)) is False
assert ask(Q.even(k**p), Q.even(k) & Q.integer(p) & Q.positive(p)) is True
assert ask(Q.even(n**p), Q.odd(n) & Q.integer(p) & Q.positive(p)) is False
assert ask(Q.even(m**k), Q.even(k) & Q.integer(m) & ~Q.negative(m)) is None
assert ask(Q.even(p**k), Q.even(k) & Q.integer(p) & Q.positive(p)) is None
assert ask(Q.even(m**n), Q.odd(n) & Q.integer(m) & ~Q.negative(m)) is None
assert ask(Q.even(p**n), Q.odd(n) & Q.integer(p) & Q.positive(p)) is None
assert ask(Q.even(k**x), Q.even(k)) is None
assert ask(Q.even(n**x), Q.odd(n)) is None
assert ask(Q.even(x*y), Q.integer(x) & Q.integer(y)) is None
assert ask(Q.even(x*x), Q.integer(x)) is None
assert ask(Q.even(x*(x + y)), Q.integer(x) & Q.odd(y)) is True
assert ask(Q.even(x*(x + y)), Q.integer(x) & Q.even(y)) is None
@XFAIL
def test_evenness_in_ternary_integer_product_with_odd():
# Tests that oddness inference is independent of term ordering.
# Term ordering at the point of testing depends on SymPy's symbol order, so
# we try to force a different order by modifying symbol names.
assert ask(Q.even(x*y*(y + z)), Q.integer(x) & Q.integer(y) & Q.odd(z)) is True
assert ask(Q.even(y*x*(x + z)), Q.integer(x) & Q.integer(y) & Q.odd(z)) is True
def test_evenness_in_ternary_integer_product_with_even():
assert ask(Q.even(x*y*(y + z)), Q.integer(x) & Q.integer(y) & Q.even(z)) is None
def test_extended_real():
assert ask(Q.extended_real(x), Q.positive_infinite(x)) is True
assert ask(Q.extended_real(x), Q.positive(x)) is True
assert ask(Q.extended_real(x), Q.zero(x)) is True
assert ask(Q.extended_real(x), Q.negative(x)) is True
assert ask(Q.extended_real(x), Q.negative_infinite(x)) is True
assert ask(Q.extended_real(-x), Q.positive(x)) is True
assert ask(Q.extended_real(-x), Q.negative(x)) is True
assert ask(Q.extended_real(x + S.Infinity), Q.real(x)) is True
assert ask(Q.extended_real(x), Q.infinite(x)) is None
@_both_exp_pow
def test_rational():
assert ask(Q.rational(x), Q.integer(x)) is True
assert ask(Q.rational(x), Q.irrational(x)) is False
assert ask(Q.rational(x), Q.real(x)) is None
assert ask(Q.rational(x), Q.positive(x)) is None
assert ask(Q.rational(x), Q.negative(x)) is None
assert ask(Q.rational(x), Q.nonzero(x)) is None
assert ask(Q.rational(x), ~Q.algebraic(x)) is False
assert ask(Q.rational(2*x), Q.rational(x)) is True
assert ask(Q.rational(2*x), Q.integer(x)) is True
assert ask(Q.rational(2*x), Q.even(x)) is True
assert ask(Q.rational(2*x), Q.odd(x)) is True
assert ask(Q.rational(2*x), Q.irrational(x)) is False
assert ask(Q.rational(x/2), Q.rational(x)) is True
assert ask(Q.rational(x/2), Q.integer(x)) is True
assert ask(Q.rational(x/2), Q.even(x)) is True
assert ask(Q.rational(x/2), Q.odd(x)) is True
assert ask(Q.rational(x/2), Q.irrational(x)) is False
assert ask(Q.rational(1/x), Q.rational(x)) is True
assert ask(Q.rational(1/x), Q.integer(x)) is True
assert ask(Q.rational(1/x), Q.even(x)) is True
assert ask(Q.rational(1/x), Q.odd(x)) is True
assert ask(Q.rational(1/x), Q.irrational(x)) is False
assert ask(Q.rational(2/x), Q.rational(x)) is True
assert ask(Q.rational(2/x), Q.integer(x)) is True
assert ask(Q.rational(2/x), Q.even(x)) is True
assert ask(Q.rational(2/x), Q.odd(x)) is True
assert ask(Q.rational(2/x), Q.irrational(x)) is False
assert ask(Q.rational(x), ~Q.algebraic(x)) is False
# with multiple symbols
assert ask(Q.rational(x*y), Q.irrational(x) & Q.irrational(y)) is None
assert ask(Q.rational(y/x), Q.rational(x) & Q.rational(y)) is True
assert ask(Q.rational(y/x), Q.integer(x) & Q.rational(y)) is True
assert ask(Q.rational(y/x), Q.even(x) & Q.rational(y)) is True
assert ask(Q.rational(y/x), Q.odd(x) & Q.rational(y)) is True
assert ask(Q.rational(y/x), Q.irrational(x) & Q.rational(y)) is False
for f in [exp, sin, tan, asin, atan, cos]:
assert ask(Q.rational(f(7))) is False
assert ask(Q.rational(f(7, evaluate=False))) is False
assert ask(Q.rational(f(0, evaluate=False))) is True
assert ask(Q.rational(f(x)), Q.rational(x)) is None
assert ask(Q.rational(f(x)), Q.rational(x) & Q.nonzero(x)) is False
for g in [log, acos]:
assert ask(Q.rational(g(7))) is False
assert ask(Q.rational(g(7, evaluate=False))) is False
assert ask(Q.rational(g(1, evaluate=False))) is True
assert ask(Q.rational(g(x)), Q.rational(x)) is None
assert ask(Q.rational(g(x)), Q.rational(x) & Q.nonzero(x - 1)) is False
for h in [cot, acot]:
assert ask(Q.rational(h(7))) is False
assert ask(Q.rational(h(7, evaluate=False))) is False
assert ask(Q.rational(h(x)), Q.rational(x)) is False
def test_hermitian():
assert ask(Q.hermitian(x)) is None
assert ask(Q.hermitian(x), Q.antihermitian(x)) is None
assert ask(Q.hermitian(x), Q.imaginary(x)) is False
assert ask(Q.hermitian(x), Q.prime(x)) is True
assert ask(Q.hermitian(x), Q.real(x)) is True
assert ask(Q.hermitian(x), Q.zero(x)) is True
assert ask(Q.hermitian(x + 1), Q.antihermitian(x)) is None
assert ask(Q.hermitian(x + 1), Q.complex(x)) is None
assert ask(Q.hermitian(x + 1), Q.hermitian(x)) is True
assert ask(Q.hermitian(x + 1), Q.imaginary(x)) is False
assert ask(Q.hermitian(x + 1), Q.real(x)) is True
assert ask(Q.hermitian(x + I), Q.antihermitian(x)) is None
assert ask(Q.hermitian(x + I), Q.complex(x)) is None
assert ask(Q.hermitian(x + I), Q.hermitian(x)) is False
assert ask(Q.hermitian(x + I), Q.imaginary(x)) is None
assert ask(Q.hermitian(x + I), Q.real(x)) is False
assert ask(
Q.hermitian(x + y), Q.antihermitian(x) & Q.antihermitian(y)) is None
assert ask(Q.hermitian(x + y), Q.antihermitian(x) & Q.complex(y)) is None
assert ask(
Q.hermitian(x + y), Q.antihermitian(x) & Q.hermitian(y)) is None
assert ask(Q.hermitian(x + y), Q.antihermitian(x) & Q.imaginary(y)) is None
assert ask(Q.hermitian(x + y), Q.antihermitian(x) & Q.real(y)) is None
assert ask(Q.hermitian(x + y), Q.hermitian(x) & Q.complex(y)) is None
assert ask(Q.hermitian(x + y), Q.hermitian(x) & Q.hermitian(y)) is True
assert ask(Q.hermitian(x + y), Q.hermitian(x) & Q.imaginary(y)) is False
assert ask(Q.hermitian(x + y), Q.hermitian(x) & Q.real(y)) is True
assert ask(Q.hermitian(x + y), Q.imaginary(x) & Q.complex(y)) is None
assert ask(Q.hermitian(x + y), Q.imaginary(x) & Q.imaginary(y)) is None
assert ask(Q.hermitian(x + y), Q.imaginary(x) & Q.real(y)) is False
assert ask(Q.hermitian(x + y), Q.real(x) & Q.complex(y)) is None
assert ask(Q.hermitian(x + y), Q.real(x) & Q.real(y)) is True
assert ask(Q.hermitian(I*x), Q.antihermitian(x)) is True
assert ask(Q.hermitian(I*x), Q.complex(x)) is None
assert ask(Q.hermitian(I*x), Q.hermitian(x)) is False
assert ask(Q.hermitian(I*x), Q.imaginary(x)) is True
assert ask(Q.hermitian(I*x), Q.real(x)) is False
assert ask(Q.hermitian(x*y), Q.hermitian(x) & Q.real(y)) is True
assert ask(
Q.hermitian(x + y + z), Q.real(x) & Q.real(y) & Q.real(z)) is True
assert ask(Q.hermitian(x + y + z),
Q.real(x) & Q.real(y) & Q.imaginary(z)) is False
assert ask(Q.hermitian(x + y + z),
Q.real(x) & Q.imaginary(y) & Q.imaginary(z)) is None
assert ask(Q.hermitian(x + y + z),
Q.imaginary(x) & Q.imaginary(y) & Q.imaginary(z)) is None
assert ask(Q.antihermitian(x)) is None
assert ask(Q.antihermitian(x), Q.real(x)) is False
assert ask(Q.antihermitian(x), Q.prime(x)) is False
assert ask(Q.antihermitian(x + 1), Q.antihermitian(x)) is False
assert ask(Q.antihermitian(x + 1), Q.complex(x)) is None
assert ask(Q.antihermitian(x + 1), Q.hermitian(x)) is None
assert ask(Q.antihermitian(x + 1), Q.imaginary(x)) is False
assert ask(Q.antihermitian(x + 1), Q.real(x)) is None
assert ask(Q.antihermitian(x + I), Q.antihermitian(x)) is True
assert ask(Q.antihermitian(x + I), Q.complex(x)) is None
assert ask(Q.antihermitian(x + I), Q.hermitian(x)) is None
assert ask(Q.antihermitian(x + I), Q.imaginary(x)) is True
assert ask(Q.antihermitian(x + I), Q.real(x)) is False
assert ask(Q.antihermitian(x), Q.zero(x)) is True
assert ask(
Q.antihermitian(x + y), Q.antihermitian(x) & Q.antihermitian(y)
) is True
assert ask(
Q.antihermitian(x + y), Q.antihermitian(x) & Q.complex(y)) is None
assert ask(
Q.antihermitian(x + y), Q.antihermitian(x) & Q.hermitian(y)) is None
assert ask(
Q.antihermitian(x + y), Q.antihermitian(x) & Q.imaginary(y)) is True
assert ask(Q.antihermitian(x + y), Q.antihermitian(x) & Q.real(y)
) is False
assert ask(Q.antihermitian(x + y), Q.hermitian(x) & Q.complex(y)) is None
assert ask(Q.antihermitian(x + y), Q.hermitian(x) & Q.hermitian(y)
) is None
assert ask(
Q.antihermitian(x + y), Q.hermitian(x) & Q.imaginary(y)) is None
assert ask(Q.antihermitian(x + y), Q.hermitian(x) & Q.real(y)) is None
assert ask(Q.antihermitian(x + y), Q.imaginary(x) & Q.complex(y)) is None
assert ask(Q.antihermitian(x + y), Q.imaginary(x) & Q.imaginary(y)) is True
assert ask(Q.antihermitian(x + y), Q.imaginary(x) & Q.real(y)) is False
assert ask(Q.antihermitian(x + y), Q.real(x) & Q.complex(y)) is None
assert ask(Q.antihermitian(x + y), Q.real(x) & Q.real(y)) is None
assert ask(Q.antihermitian(I*x), Q.real(x)) is True
assert ask(Q.antihermitian(I*x), Q.antihermitian(x)) is False
assert ask(Q.antihermitian(I*x), Q.complex(x)) is None
assert ask(Q.antihermitian(x*y), Q.antihermitian(x) & Q.real(y)) is True
assert ask(Q.antihermitian(x + y + z),
Q.real(x) & Q.real(y) & Q.real(z)) is None
assert ask(Q.antihermitian(x + y + z),
Q.real(x) & Q.real(y) & Q.imaginary(z)) is None
assert ask(Q.antihermitian(x + y + z),
Q.real(x) & Q.imaginary(y) & Q.imaginary(z)) is False
assert ask(Q.antihermitian(x + y + z),
Q.imaginary(x) & Q.imaginary(y) & Q.imaginary(z)) is True
@_both_exp_pow
def test_imaginary():
assert ask(Q.imaginary(x)) is None
assert ask(Q.imaginary(x), Q.real(x)) is False
assert ask(Q.imaginary(x), Q.prime(x)) is False
assert ask(Q.imaginary(x + 1), Q.real(x)) is False
assert ask(Q.imaginary(x + 1), Q.imaginary(x)) is False
assert ask(Q.imaginary(x + I), Q.real(x)) is False
assert ask(Q.imaginary(x + I), Q.imaginary(x)) is True
assert ask(Q.imaginary(x + y), Q.imaginary(x) & Q.imaginary(y)) is True
assert ask(Q.imaginary(x + y), Q.real(x) & Q.real(y)) is False
assert ask(Q.imaginary(x + y), Q.imaginary(x) & Q.real(y)) is False
assert ask(Q.imaginary(x + y), Q.complex(x) & Q.real(y)) is None
assert ask(
Q.imaginary(x + y + z), Q.real(x) & Q.real(y) & Q.real(z)) is False
assert ask(Q.imaginary(x + y + z),
Q.real(x) & Q.real(y) & Q.imaginary(z)) is None
assert ask(Q.imaginary(x + y + z),
Q.real(x) & Q.imaginary(y) & Q.imaginary(z)) is False
assert ask(Q.imaginary(I*x), Q.real(x)) is True
assert ask(Q.imaginary(I*x), Q.imaginary(x)) is False
assert ask(Q.imaginary(I*x), Q.complex(x)) is None
assert ask(Q.imaginary(x*y), Q.imaginary(x) & Q.real(y)) is True
assert ask(Q.imaginary(x*y), Q.real(x) & Q.real(y)) is False
assert ask(Q.imaginary(I**x), Q.negative(x)) is None
assert ask(Q.imaginary(I**x), Q.positive(x)) is None
assert ask(Q.imaginary(I**x), Q.even(x)) is False
assert ask(Q.imaginary(I**x), Q.odd(x)) is True
assert ask(Q.imaginary(I**x), Q.imaginary(x)) is False
assert ask(Q.imaginary((2*I)**x), Q.imaginary(x)) is False
assert ask(Q.imaginary(x**0), Q.imaginary(x)) is False
assert ask(Q.imaginary(x**y), Q.imaginary(x) & Q.imaginary(y)) is None
assert ask(Q.imaginary(x**y), Q.imaginary(x) & Q.real(y)) is None
assert ask(Q.imaginary(x**y), Q.real(x) & Q.imaginary(y)) is None
assert ask(Q.imaginary(x**y), Q.real(x) & Q.real(y)) is None
assert ask(Q.imaginary(x**y), Q.imaginary(x) & Q.integer(y)) is None
assert ask(Q.imaginary(x**y), Q.imaginary(y) & Q.integer(x)) is None
assert ask(Q.imaginary(x**y), Q.imaginary(x) & Q.odd(y)) is True
assert ask(Q.imaginary(x**y), Q.imaginary(x) & Q.rational(y)) is None
assert ask(Q.imaginary(x**y), Q.imaginary(x) & Q.even(y)) is False
assert ask(Q.imaginary(x**y), Q.real(x) & Q.integer(y)) is False
assert ask(Q.imaginary(x**y), Q.positive(x) & Q.real(y)) is False
assert ask(Q.imaginary(x**y), Q.negative(x) & Q.real(y)) is None
assert ask(Q.imaginary(x**y), Q.negative(x) & Q.real(y) & ~Q.rational(y)) is False
assert ask(Q.imaginary(x**y), Q.integer(x) & Q.imaginary(y)) is None
assert ask(Q.imaginary(x**y), Q.negative(x) & Q.rational(y) & Q.integer(2*y)) is True
assert ask(Q.imaginary(x**y), Q.negative(x) & Q.rational(y) & ~Q.integer(2*y)) is False
assert ask(Q.imaginary(x**y), Q.negative(x) & Q.rational(y)) is None
assert ask(Q.imaginary(x**y), Q.real(x) & Q.rational(y) & ~Q.integer(2*y)) is False
assert ask(Q.imaginary(x**y), Q.real(x) & Q.rational(y) & Q.integer(2*y)) is None
# logarithm
assert ask(Q.imaginary(log(I))) is True
assert ask(Q.imaginary(log(2*I))) is False
assert ask(Q.imaginary(log(I + 1))) is False
assert ask(Q.imaginary(log(x)), Q.complex(x)) is None
assert ask(Q.imaginary(log(x)), Q.imaginary(x)) is None
assert ask(Q.imaginary(log(x)), Q.positive(x)) is False
assert ask(Q.imaginary(log(exp(x))), Q.complex(x)) is None
assert ask(Q.imaginary(log(exp(x))), Q.imaginary(x)) is None # zoo/I/a+I*b
assert ask(Q.imaginary(log(exp(I)))) is True
# exponential
assert ask(Q.imaginary(exp(x)**x), Q.imaginary(x)) is False
eq = Pow(exp(pi*I*x, evaluate=False), x, evaluate=False)
assert ask(Q.imaginary(eq), Q.even(x)) is False
eq = Pow(exp(pi*I*x/2, evaluate=False), x, evaluate=False)
assert ask(Q.imaginary(eq), Q.odd(x)) is True
assert ask(Q.imaginary(exp(3*I*pi*x)**x), Q.integer(x)) is False
assert ask(Q.imaginary(exp(2*pi*I, evaluate=False))) is False
assert ask(Q.imaginary(exp(pi*I/2, evaluate=False))) is True
# issue 7886
assert ask(Q.imaginary(Pow(x, Rational(1, 4))), Q.real(x) & Q.negative(x)) is False
def test_integer():
assert ask(Q.integer(x)) is None
assert ask(Q.integer(x), Q.integer(x)) is True
assert ask(Q.integer(x), ~Q.integer(x)) is False
assert ask(Q.integer(x), ~Q.real(x)) is False
assert ask(Q.integer(x), ~Q.positive(x)) is None
assert ask(Q.integer(x), Q.even(x) | Q.odd(x)) is True
assert ask(Q.integer(2*x), Q.integer(x)) is True
assert ask(Q.integer(2*x), Q.even(x)) is True
assert ask(Q.integer(2*x), Q.prime(x)) is True
assert ask(Q.integer(2*x), Q.rational(x)) is None
assert ask(Q.integer(2*x), Q.real(x)) is None
assert ask(Q.integer(sqrt(2)*x), Q.integer(x)) is False
assert ask(Q.integer(sqrt(2)*x), Q.irrational(x)) is None
assert ask(Q.integer(x/2), Q.odd(x)) is False
assert ask(Q.integer(x/2), Q.even(x)) is True
assert ask(Q.integer(x/3), Q.odd(x)) is None
assert ask(Q.integer(x/3), Q.even(x)) is None
def test_negative():
assert ask(Q.negative(x), Q.negative(x)) is True
assert ask(Q.negative(x), Q.positive(x)) is False
assert ask(Q.negative(x), ~Q.real(x)) is False
assert ask(Q.negative(x), Q.prime(x)) is False
assert ask(Q.negative(x), ~Q.prime(x)) is None
assert ask(Q.negative(-x), Q.positive(x)) is True
assert ask(Q.negative(-x), ~Q.positive(x)) is None
assert ask(Q.negative(-x), Q.negative(x)) is False
assert ask(Q.negative(-x), Q.positive(x)) is True
assert ask(Q.negative(x - 1), Q.negative(x)) is True
assert ask(Q.negative(x + y)) is None
assert ask(Q.negative(x + y), Q.negative(x)) is None
assert ask(Q.negative(x + y), Q.negative(x) & Q.negative(y)) is True
assert ask(Q.negative(x + y), Q.negative(x) & Q.nonpositive(y)) is True
assert ask(Q.negative(2 + I)) is False
# although this could be False, it is representative of expressions
# that don't evaluate to a zero with precision
assert ask(Q.negative(cos(I)**2 + sin(I)**2 - 1)) is None
assert ask(Q.negative(-I + I*(cos(2)**2 + sin(2)**2))) is None
assert ask(Q.negative(x**2)) is None
assert ask(Q.negative(x**2), Q.real(x)) is False
assert ask(Q.negative(x**1.4), Q.real(x)) is None
assert ask(Q.negative(x**I), Q.positive(x)) is None
assert ask(Q.negative(x*y)) is None
assert ask(Q.negative(x*y), Q.positive(x) & Q.positive(y)) is False
assert ask(Q.negative(x*y), Q.positive(x) & Q.negative(y)) is True
assert ask(Q.negative(x*y), Q.complex(x) & Q.complex(y)) is None
assert ask(Q.negative(x**y)) is None
assert ask(Q.negative(x**y), Q.negative(x) & Q.even(y)) is False
assert ask(Q.negative(x**y), Q.negative(x) & Q.odd(y)) is True
assert ask(Q.negative(x**y), Q.positive(x) & Q.integer(y)) is False
assert ask(Q.negative(Abs(x))) is False
def test_nonzero():
assert ask(Q.nonzero(x)) is None
assert ask(Q.nonzero(x), Q.real(x)) is None
assert ask(Q.nonzero(x), Q.positive(x)) is True
assert ask(Q.nonzero(x), Q.negative(x)) is True
assert ask(Q.nonzero(x), Q.negative(x) | Q.positive(x)) is True
assert ask(Q.nonzero(x + y)) is None
assert ask(Q.nonzero(x + y), Q.positive(x) & Q.positive(y)) is True
assert ask(Q.nonzero(x + y), Q.positive(x) & Q.negative(y)) is None
assert ask(Q.nonzero(x + y), Q.negative(x) & Q.negative(y)) is True
assert ask(Q.nonzero(2*x)) is None
assert ask(Q.nonzero(2*x), Q.positive(x)) is True
assert ask(Q.nonzero(2*x), Q.negative(x)) is True
assert ask(Q.nonzero(x*y), Q.nonzero(x)) is None
assert ask(Q.nonzero(x*y), Q.nonzero(x) & Q.nonzero(y)) is True
assert ask(Q.nonzero(x**y), Q.nonzero(x)) is True
assert ask(Q.nonzero(Abs(x))) is None
assert ask(Q.nonzero(Abs(x)), Q.nonzero(x)) is True
assert ask(Q.nonzero(log(exp(2*I)))) is False
# although this could be False, it is representative of expressions
# that don't evaluate to a zero with precision
assert ask(Q.nonzero(cos(1)**2 + sin(1)**2 - 1)) is None
def test_zero():
assert ask(Q.zero(x)) is None
assert ask(Q.zero(x), Q.real(x)) is None
assert ask(Q.zero(x), Q.positive(x)) is False
assert ask(Q.zero(x), Q.negative(x)) is False
assert ask(Q.zero(x), Q.negative(x) | Q.positive(x)) is False
assert ask(Q.zero(x), Q.nonnegative(x) & Q.nonpositive(x)) is True
assert ask(Q.zero(x + y)) is None
assert ask(Q.zero(x + y), Q.positive(x) & Q.positive(y)) is False
assert ask(Q.zero(x + y), Q.positive(x) & Q.negative(y)) is None
assert ask(Q.zero(x + y), Q.negative(x) & Q.negative(y)) is False
assert ask(Q.zero(2*x)) is None
assert ask(Q.zero(2*x), Q.positive(x)) is False
assert ask(Q.zero(2*x), Q.negative(x)) is False
assert ask(Q.zero(x*y), Q.nonzero(x)) is None
assert ask(Q.zero(Abs(x))) is None
assert ask(Q.zero(Abs(x)), Q.zero(x)) is True
assert ask(Q.integer(x), Q.zero(x)) is True
assert ask(Q.even(x), Q.zero(x)) is True
assert ask(Q.odd(x), Q.zero(x)) is False
assert ask(Q.zero(x), Q.even(x)) is None
assert ask(Q.zero(x), Q.odd(x)) is False
assert ask(Q.zero(x) | Q.zero(y), Q.zero(x*y)) is True
def test_odd_query():
assert ask(Q.odd(x)) is None
assert ask(Q.odd(x), Q.odd(x)) is True
assert ask(Q.odd(x), Q.integer(x)) is None
assert ask(Q.odd(x), ~Q.integer(x)) is False
assert ask(Q.odd(x), Q.rational(x)) is None
assert ask(Q.odd(x), Q.positive(x)) is None
assert ask(Q.odd(-x), Q.odd(x)) is True
assert ask(Q.odd(2*x)) is None
assert ask(Q.odd(2*x), Q.integer(x)) is False
assert ask(Q.odd(2*x), Q.odd(x)) is False
assert ask(Q.odd(2*x), Q.irrational(x)) is False
assert ask(Q.odd(2*x), ~Q.integer(x)) is None
assert ask(Q.odd(3*x), Q.integer(x)) is None
assert ask(Q.odd(x/3), Q.odd(x)) is None
assert ask(Q.odd(x/3), Q.even(x)) is None
assert ask(Q.odd(x + 1), Q.even(x)) is True
assert ask(Q.odd(x + 2), Q.even(x)) is False
assert ask(Q.odd(x + 2), Q.odd(x)) is True
assert ask(Q.odd(3 - x), Q.odd(x)) is False
assert ask(Q.odd(3 - x), Q.even(x)) is True
assert ask(Q.odd(3 + x), Q.odd(x)) is False
assert ask(Q.odd(3 + x), Q.even(x)) is True
assert ask(Q.odd(x + y), Q.odd(x) & Q.odd(y)) is False
assert ask(Q.odd(x + y), Q.odd(x) & Q.even(y)) is True
assert ask(Q.odd(x - y), Q.even(x) & Q.odd(y)) is True
assert ask(Q.odd(x - y), Q.odd(x) & Q.odd(y)) is False
assert ask(Q.odd(x + y + z), Q.odd(x) & Q.odd(y) & Q.even(z)) is False
assert ask(Q.odd(x + y + z + t),
Q.odd(x) & Q.odd(y) & Q.even(z) & Q.integer(t)) is None
assert ask(Q.odd(2*x + 1), Q.integer(x)) is True
assert ask(Q.odd(2*x + y), Q.integer(x) & Q.odd(y)) is True
assert ask(Q.odd(2*x + y), Q.integer(x) & Q.even(y)) is False
assert ask(Q.odd(2*x + y), Q.integer(x) & Q.integer(y)) is None
assert ask(Q.odd(x*y), Q.odd(x) & Q.even(y)) is False
assert ask(Q.odd(x*y), Q.odd(x) & Q.odd(y)) is True
assert ask(Q.odd(2*x*y), Q.rational(x) & Q.rational(x)) is None
assert ask(Q.odd(2*x*y), Q.irrational(x) & Q.irrational(x)) is None
assert ask(Q.odd(Abs(x)), Q.odd(x)) is True
assert ask(Q.odd((-1)**n), Q.integer(n)) is True
assert ask(Q.odd(k**2), Q.even(k)) is False
assert ask(Q.odd(n**2), Q.odd(n)) is True
assert ask(Q.odd(3**k), Q.even(k)) is None
assert ask(Q.odd(k**m), Q.even(k) & Q.integer(m) & ~Q.negative(m)) is None
assert ask(Q.odd(n**m), Q.odd(n) & Q.integer(m) & ~Q.negative(m)) is True
assert ask(Q.odd(k**p), Q.even(k) & Q.integer(p) & Q.positive(p)) is False
assert ask(Q.odd(n**p), Q.odd(n) & Q.integer(p) & Q.positive(p)) is True
assert ask(Q.odd(m**k), Q.even(k) & Q.integer(m) & ~Q.negative(m)) is None
assert ask(Q.odd(p**k), Q.even(k) & Q.integer(p) & Q.positive(p)) is None
assert ask(Q.odd(m**n), Q.odd(n) & Q.integer(m) & ~Q.negative(m)) is None
assert ask(Q.odd(p**n), Q.odd(n) & Q.integer(p) & Q.positive(p)) is None
assert ask(Q.odd(k**x), Q.even(k)) is None
assert ask(Q.odd(n**x), Q.odd(n)) is None
assert ask(Q.odd(x*y), Q.integer(x) & Q.integer(y)) is None
assert ask(Q.odd(x*x), Q.integer(x)) is None
assert ask(Q.odd(x*(x + y)), Q.integer(x) & Q.odd(y)) is False
assert ask(Q.odd(x*(x + y)), Q.integer(x) & Q.even(y)) is None
@XFAIL
def test_oddness_in_ternary_integer_product_with_odd():
# Tests that oddness inference is independent of term ordering.
# Term ordering at the point of testing depends on SymPy's symbol order, so
# we try to force a different order by modifying symbol names.
assert ask(Q.odd(x*y*(y + z)), Q.integer(x) & Q.integer(y) & Q.odd(z)) is False
assert ask(Q.odd(y*x*(x + z)), Q.integer(x) & Q.integer(y) & Q.odd(z)) is False
def test_oddness_in_ternary_integer_product_with_even():
assert ask(Q.odd(x*y*(y + z)), Q.integer(x) & Q.integer(y) & Q.even(z)) is None
def test_prime():
assert ask(Q.prime(x), Q.prime(x)) is True
assert ask(Q.prime(x), ~Q.prime(x)) is False
assert ask(Q.prime(x), Q.integer(x)) is None
assert ask(Q.prime(x), ~Q.integer(x)) is False
assert ask(Q.prime(2*x), Q.integer(x)) is None
assert ask(Q.prime(x*y)) is None
assert ask(Q.prime(x*y), Q.prime(x)) is None
assert ask(Q.prime(x*y), Q.integer(x) & Q.integer(y)) is None
assert ask(Q.prime(4*x), Q.integer(x)) is False
assert ask(Q.prime(4*x)) is None
assert ask(Q.prime(x**2), Q.integer(x)) is False
assert ask(Q.prime(x**2), Q.prime(x)) is False
assert ask(Q.prime(x**y), Q.integer(x) & Q.integer(y)) is False
@_both_exp_pow
def test_positive():
assert ask(Q.positive(x), Q.positive(x)) is True
assert ask(Q.positive(x), Q.negative(x)) is False
assert ask(Q.positive(x), Q.nonzero(x)) is None
assert ask(Q.positive(-x), Q.positive(x)) is False
assert ask(Q.positive(-x), Q.negative(x)) is True
assert ask(Q.positive(x + y), Q.positive(x) & Q.positive(y)) is True
assert ask(Q.positive(x + y), Q.positive(x) & Q.nonnegative(y)) is True
assert ask(Q.positive(x + y), Q.positive(x) & Q.negative(y)) is None
assert ask(Q.positive(x + y), Q.positive(x) & Q.imaginary(y)) is False
assert ask(Q.positive(2*x), Q.positive(x)) is True
assumptions = Q.positive(x) & Q.negative(y) & Q.negative(z) & Q.positive(w)
assert ask(Q.positive(x*y*z)) is None
assert ask(Q.positive(x*y*z), assumptions) is True
assert ask(Q.positive(-x*y*z), assumptions) is False
assert ask(Q.positive(x**I), Q.positive(x)) is None
assert ask(Q.positive(x**2), Q.positive(x)) is True
assert ask(Q.positive(x**2), Q.negative(x)) is True
assert ask(Q.positive(x**3), Q.negative(x)) is False
assert ask(Q.positive(1/(1 + x**2)), Q.real(x)) is True
assert ask(Q.positive(2**I)) is False
assert ask(Q.positive(2 + I)) is False
# although this could be False, it is representative of expressions
# that don't evaluate to a zero with precision
assert ask(Q.positive(cos(I)**2 + sin(I)**2 - 1)) is None
assert ask(Q.positive(-I + I*(cos(2)**2 + sin(2)**2))) is None
#exponential
assert ask(Q.positive(exp(x)), Q.real(x)) is True
assert ask(~Q.negative(exp(x)), Q.real(x)) is True
assert ask(Q.positive(x + exp(x)), Q.real(x)) is None
assert ask(Q.positive(exp(x)), Q.imaginary(x)) is None
assert ask(Q.positive(exp(2*pi*I, evaluate=False)), Q.imaginary(x)) is True
assert ask(Q.negative(exp(pi*I, evaluate=False)), Q.imaginary(x)) is True
assert ask(Q.positive(exp(x*pi*I)), Q.even(x)) is True
assert ask(Q.positive(exp(x*pi*I)), Q.odd(x)) is False
assert ask(Q.positive(exp(x*pi*I)), Q.real(x)) is None
# logarithm
assert ask(Q.positive(log(x)), Q.imaginary(x)) is False
assert ask(Q.positive(log(x)), Q.negative(x)) is False
assert ask(Q.positive(log(x)), Q.positive(x)) is None
assert ask(Q.positive(log(x + 2)), Q.positive(x)) is True
# factorial
assert ask(Q.positive(factorial(x)), Q.integer(x) & Q.positive(x))
assert ask(Q.positive(factorial(x)), Q.integer(x)) is None
#absolute value
assert ask(Q.positive(Abs(x))) is None # Abs(0) = 0
assert ask(Q.positive(Abs(x)), Q.positive(x)) is True
def test_nonpositive():
assert ask(Q.nonpositive(-1))
assert ask(Q.nonpositive(0))
assert ask(Q.nonpositive(1)) is False
assert ask(~Q.positive(x), Q.nonpositive(x))
assert ask(Q.nonpositive(x), Q.positive(x)) is False
assert ask(Q.nonpositive(sqrt(-1))) is False
assert ask(Q.nonpositive(x), Q.imaginary(x)) is False
def test_nonnegative():
assert ask(Q.nonnegative(-1)) is False
assert ask(Q.nonnegative(0))
assert ask(Q.nonnegative(1))
assert ask(~Q.negative(x), Q.nonnegative(x))
assert ask(Q.nonnegative(x), Q.negative(x)) is False
assert ask(Q.nonnegative(sqrt(-1))) is False
assert ask(Q.nonnegative(x), Q.imaginary(x)) is False
def test_real_basic():
assert ask(Q.real(x)) is None
assert ask(Q.real(x), Q.real(x)) is True
assert ask(Q.real(x), Q.nonzero(x)) is True
assert ask(Q.real(x), Q.positive(x)) is True
assert ask(Q.real(x), Q.negative(x)) is True
assert ask(Q.real(x), Q.integer(x)) is True
assert ask(Q.real(x), Q.even(x)) is True
assert ask(Q.real(x), Q.prime(x)) is True
assert ask(Q.real(x/sqrt(2)), Q.real(x)) is True
assert ask(Q.real(x/sqrt(-2)), Q.real(x)) is False
assert ask(Q.real(x + 1), Q.real(x)) is True
assert ask(Q.real(x + I), Q.real(x)) is False
assert ask(Q.real(x + I), Q.complex(x)) is None
assert ask(Q.real(2*x), Q.real(x)) is True
assert ask(Q.real(I*x), Q.real(x)) is False
assert ask(Q.real(I*x), Q.imaginary(x)) is True
assert ask(Q.real(I*x), Q.complex(x)) is None
def test_real_pow():
assert ask(Q.real(x**2), Q.real(x)) is True
assert ask(Q.real(sqrt(x)), Q.negative(x)) is False
assert ask(Q.real(x**y), Q.real(x) & Q.integer(y)) is True
assert ask(Q.real(x**y), Q.real(x) & Q.real(y)) is None
assert ask(Q.real(x**y), Q.positive(x) & Q.real(y)) is True
assert ask(Q.real(x**y), Q.imaginary(x) & Q.imaginary(y)) is None # I**I or (2*I)**I
assert ask(Q.real(x**y), Q.imaginary(x) & Q.real(y)) is None # I**1 or I**0
assert ask(Q.real(x**y), Q.real(x) & Q.imaginary(y)) is None # could be exp(2*pi*I) or 2**I
assert ask(Q.real(x**0), Q.imaginary(x)) is True
assert ask(Q.real(x**y), Q.real(x) & Q.integer(y)) is True
assert ask(Q.real(x**y), Q.positive(x) & Q.real(y)) is True
assert ask(Q.real(x**y), Q.real(x) & Q.rational(y)) is None
assert ask(Q.real(x**y), Q.imaginary(x) & Q.integer(y)) is None
assert ask(Q.real(x**y), Q.imaginary(x) & Q.odd(y)) is False
assert ask(Q.real(x**y), Q.imaginary(x) & Q.even(y)) is True
assert ask(Q.real(x**(y/z)), Q.real(x) & Q.real(y/z) & Q.rational(y/z) & Q.even(z) & Q.positive(x)) is True
assert ask(Q.real(x**(y/z)), Q.real(x) & Q.rational(y/z) & Q.even(z) & Q.negative(x)) is False
assert ask(Q.real(x**(y/z)), Q.real(x) & Q.integer(y/z)) is True
assert ask(Q.real(x**(y/z)), Q.real(x) & Q.real(y/z) & Q.positive(x)) is True
assert ask(Q.real(x**(y/z)), Q.real(x) & Q.real(y/z) & Q.negative(x)) is False
assert ask(Q.real((-I)**i), Q.imaginary(i)) is True
assert ask(Q.real(I**i), Q.imaginary(i)) is True
assert ask(Q.real(i**i), Q.imaginary(i)) is None # i might be 2*I
assert ask(Q.real(x**i), Q.imaginary(i)) is None # x could be 0
assert ask(Q.real(x**(I*pi/log(x))), Q.real(x)) is True
@_both_exp_pow
def test_real_functions():
# trigonometric functions
assert ask(Q.real(sin(x))) is None
assert ask(Q.real(cos(x))) is None
assert ask(Q.real(sin(x)), Q.real(x)) is True
assert ask(Q.real(cos(x)), Q.real(x)) is True
# exponential function
assert ask(Q.real(exp(x))) is None
assert ask(Q.real(exp(x)), Q.real(x)) is True
assert ask(Q.real(x + exp(x)), Q.real(x)) is True
assert ask(Q.real(exp(2*pi*I, evaluate=False))) is True
assert ask(Q.real(exp(pi*I, evaluate=False))) is True
assert ask(Q.real(exp(pi*I/2, evaluate=False))) is False
# logarithm
assert ask(Q.real(log(I))) is False
assert ask(Q.real(log(2*I))) is False
assert ask(Q.real(log(I + 1))) is False
assert ask(Q.real(log(x)), Q.complex(x)) is None
assert ask(Q.real(log(x)), Q.imaginary(x)) is False
assert ask(Q.real(log(exp(x))), Q.imaginary(x)) is None # exp(2*pi*I) is 1, log(exp(pi*I)) is pi*I (disregarding periodicity)
assert ask(Q.real(log(exp(x))), Q.complex(x)) is None
eq = Pow(exp(2*pi*I*x, evaluate=False), x, evaluate=False)
assert ask(Q.real(eq), Q.integer(x)) is True
assert ask(Q.real(exp(x)**x), Q.imaginary(x)) is True
assert ask(Q.real(exp(x)**x), Q.complex(x)) is None
# Q.complexes
assert ask(Q.real(re(x))) is True
assert ask(Q.real(im(x))) is True
def test_matrix():
# hermitian
assert ask(Q.hermitian(Matrix([[2, 2 + I, 4], [2 - I, 3, I], [4, -I, 1]]))) == True
assert ask(Q.hermitian(Matrix([[2, 2 + I, 4], [2 + I, 3, I], [4, -I, 1]]))) == False
z = symbols('z', complex=True)
assert ask(Q.hermitian(Matrix([[2, 2 + I, z], [2 - I, 3, I], [4, -I, 1]]))) == None
assert ask(Q.hermitian(SparseMatrix(((25, 15, -5), (15, 18, 0), (-5, 0, 11))))) == True
assert ask(Q.hermitian(SparseMatrix(((25, 15, -5), (15, I, 0), (-5, 0, 11))))) == False
assert ask(Q.hermitian(SparseMatrix(((25, 15, -5), (15, z, 0), (-5, 0, 11))))) == None
# antihermitian
A = Matrix([[0, -2 - I, 0], [2 - I, 0, -I], [0, -I, 0]])
B = Matrix([[-I, 2 + I, 0], [-2 + I, 0, 2 + I], [0, -2 + I, -I]])
assert ask(Q.antihermitian(A)) is True
assert ask(Q.antihermitian(B)) is True
assert ask(Q.antihermitian(A**2)) is False
C = (B**3)
C.simplify()
assert ask(Q.antihermitian(C)) is True
_A = Matrix([[0, -2 - I, 0], [z, 0, -I], [0, -I, 0]])
assert ask(Q.antihermitian(_A)) is None
@_both_exp_pow
def test_algebraic():
assert ask(Q.algebraic(x)) is None
assert ask(Q.algebraic(I)) is True
assert ask(Q.algebraic(2*I)) is True
assert ask(Q.algebraic(I/3)) is True
assert ask(Q.algebraic(sqrt(7))) is True
assert ask(Q.algebraic(2*sqrt(7))) is True
assert ask(Q.algebraic(sqrt(7)/3)) is True
assert ask(Q.algebraic(I*sqrt(3))) is True
assert ask(Q.algebraic(sqrt(1 + I*sqrt(3)))) is True
assert ask(Q.algebraic(1 + I*sqrt(3)**Rational(17, 31))) is True
assert ask(Q.algebraic(1 + I*sqrt(3)**(17/pi))) is False
for f in [exp, sin, tan, asin, atan, cos]:
assert ask(Q.algebraic(f(7))) is False
assert ask(Q.algebraic(f(7, evaluate=False))) is False
assert ask(Q.algebraic(f(0, evaluate=False))) is True
assert ask(Q.algebraic(f(x)), Q.algebraic(x)) is None
assert ask(Q.algebraic(f(x)), Q.algebraic(x) & Q.nonzero(x)) is False
for g in [log, acos]:
assert ask(Q.algebraic(g(7))) is False
assert ask(Q.algebraic(g(7, evaluate=False))) is False
assert ask(Q.algebraic(g(1, evaluate=False))) is True
assert ask(Q.algebraic(g(x)), Q.algebraic(x)) is None
assert ask(Q.algebraic(g(x)), Q.algebraic(x) & Q.nonzero(x - 1)) is False
for h in [cot, acot]:
assert ask(Q.algebraic(h(7))) is False
assert ask(Q.algebraic(h(7, evaluate=False))) is False
assert ask(Q.algebraic(h(x)), Q.algebraic(x)) is False
assert ask(Q.algebraic(sqrt(sin(7)))) is False
assert ask(Q.algebraic(sqrt(y + I*sqrt(7)))) is None
assert ask(Q.algebraic(2.47)) is True
assert ask(Q.algebraic(x), Q.transcendental(x)) is False
assert ask(Q.transcendental(x), Q.algebraic(x)) is False
def test_global():
"""Test ask with global assumptions"""
assert ask(Q.integer(x)) is None
global_assumptions.add(Q.integer(x))
assert ask(Q.integer(x)) is True
global_assumptions.clear()
assert ask(Q.integer(x)) is None
def test_custom_context():
"""Test ask with custom assumptions context"""
assert ask(Q.integer(x)) is None
local_context = AssumptionsContext()
local_context.add(Q.integer(x))
assert ask(Q.integer(x), context=local_context) is True
assert ask(Q.integer(x)) is None
def test_functions_in_assumptions():
assert ask(Q.negative(x), Q.real(x) >> Q.positive(x)) is False
assert ask(Q.negative(x), Equivalent(Q.real(x), Q.positive(x))) is False
assert ask(Q.negative(x), Xor(Q.real(x), Q.negative(x))) is False
def test_composite_ask():
assert ask(Q.negative(x) & Q.integer(x),
assumptions=Q.real(x) >> Q.positive(x)) is False
def test_composite_proposition():
assert ask(True) is True
assert ask(False) is False
assert ask(~Q.negative(x), Q.positive(x)) is True
assert ask(~Q.real(x), Q.commutative(x)) is None
assert ask(Q.negative(x) & Q.integer(x), Q.positive(x)) is False
assert ask(Q.negative(x) & Q.integer(x)) is None
assert ask(Q.real(x) | Q.integer(x), Q.positive(x)) is True
assert ask(Q.real(x) | Q.integer(x)) is None
assert ask(Q.real(x) >> Q.positive(x), Q.negative(x)) is False
assert ask(Implies(
Q.real(x), Q.positive(x), evaluate=False), Q.negative(x)) is False
assert ask(Implies(Q.real(x), Q.positive(x), evaluate=False)) is None
assert ask(Equivalent(Q.integer(x), Q.even(x)), Q.even(x)) is True
assert ask(Equivalent(Q.integer(x), Q.even(x))) is None
assert ask(Equivalent(Q.positive(x), Q.integer(x)), Q.integer(x)) is None
assert ask(Q.real(x) | Q.integer(x), Q.real(x) | Q.integer(x)) is True
def test_tautology():
assert ask(Q.real(x) | ~Q.real(x)) is True
assert ask(Q.real(x) & ~Q.real(x)) is False
def test_composite_assumptions():
assert ask(Q.real(x), Q.real(x) & Q.real(y)) is True
assert ask(Q.positive(x), Q.positive(x) | Q.positive(y)) is None
assert ask(Q.positive(x), Q.real(x) >> Q.positive(y)) is None
assert ask(Q.real(x), ~(Q.real(x) >> Q.real(y))) is True
def test_key_extensibility():
"""test that you can add keys to the ask system at runtime"""
# make sure the key is not defined
raises(AttributeError, lambda: ask(Q.my_key(x)))
# Old handler system
class MyAskHandler(AskHandler):
@staticmethod
def Symbol(expr, assumptions):
return True
try:
with warns_deprecated_sympy():
register_handler('my_key', MyAskHandler)
with warns_deprecated_sympy():
assert ask(Q.my_key(x)) is True
with warns_deprecated_sympy():
assert ask(Q.my_key(x + 1)) is None
finally:
with warns_deprecated_sympy():
remove_handler('my_key', MyAskHandler)
del Q.my_key
raises(AttributeError, lambda: ask(Q.my_key(x)))
# New handler system
class MyPredicate(Predicate):
pass
try:
Q.my_key = MyPredicate()
@Q.my_key.register(Symbol)
def _(expr, assumptions):
return True
assert ask(Q.my_key(x)) is True
assert ask(Q.my_key(x+1)) is None
finally:
del Q.my_key
raises(AttributeError, lambda: ask(Q.my_key(x)))
def test_type_extensibility():
"""test that new types can be added to the ask system at runtime
"""
from sympy.core import Basic
class MyType(Basic):
pass
@Q.prime.register(MyType)
def _(expr, assumptions):
return True
assert ask(Q.prime(MyType())) is True
def test_single_fact_lookup():
known_facts = And(Implies(Q.integer, Q.rational),
Implies(Q.rational, Q.real),
Implies(Q.real, Q.complex))
known_facts_keys = {Q.integer, Q.rational, Q.real, Q.complex}
known_facts_cnf = to_cnf(known_facts)
mapping = single_fact_lookup(known_facts_keys, known_facts_cnf)
assert mapping[Q.rational] == {Q.real, Q.rational, Q.complex}
def test_generate_known_facts_dict():
known_facts = And(Implies(Q.integer(x), Q.rational(x)),
Implies(Q.rational(x), Q.real(x)),
Implies(Q.real(x), Q.complex(x)))
known_facts_keys = {Q.integer(x), Q.rational(x), Q.real(x), Q.complex(x)}
assert generate_known_facts_dict(known_facts_keys, known_facts) == \
{Q.complex: ({Q.complex}, set()),
Q.integer: ({Q.complex, Q.integer, Q.rational, Q.real}, set()),
Q.rational: ({Q.complex, Q.rational, Q.real}, set()),
Q.real: ({Q.complex, Q.real}, set())}
@slow
def test_known_facts_consistent():
""""Test that ask_generated.py is up-to-date"""
x = Symbol('x')
fact = get_known_facts(x)
# test cnf clauses of fact between unary predicates
cnf = CNF.to_CNF(fact)
clauses = set()
for cl in cnf.clauses:
clauses.add(frozenset(Literal(lit.arg.function, lit.is_Not) for lit in sorted(cl, key=str)))
assert get_all_known_facts() == clauses
# test dictionary of fact between unary predicates
keys = [pred(x) for pred in get_known_facts_keys()]
mapping = generate_known_facts_dict(keys, fact)
assert get_known_facts_dict() == mapping
def test_Add_queries():
assert ask(Q.prime(12345678901234567890 + (cos(1)**2 + sin(1)**2))) is True
assert ask(Q.even(Add(S(2), S(2), evaluate=0))) is True
assert ask(Q.prime(Add(S(2), S(2), evaluate=0))) is False
assert ask(Q.integer(Add(S(2), S(2), evaluate=0))) is True
def test_positive_assuming():
with assuming(Q.positive(x + 1)):
assert not ask(Q.positive(x))
def test_issue_5421():
raises(TypeError, lambda: ask(pi/log(x), Q.real))
def test_issue_3906():
raises(TypeError, lambda: ask(Q.positive))
def test_issue_5833():
assert ask(Q.positive(log(x)**2), Q.positive(x)) is None
assert ask(~Q.negative(log(x)**2), Q.positive(x)) is True
def test_issue_6732():
raises(ValueError, lambda: ask(Q.positive(x), Q.positive(x) & Q.negative(x)))
raises(ValueError, lambda: ask(Q.negative(x), Q.positive(x) & Q.negative(x)))
def test_issue_7246():
assert ask(Q.positive(atan(p)), Q.positive(p)) is True
assert ask(Q.positive(atan(p)), Q.negative(p)) is False
assert ask(Q.positive(atan(p)), Q.zero(p)) is False
assert ask(Q.positive(atan(x))) is None
assert ask(Q.positive(asin(p)), Q.positive(p)) is None
assert ask(Q.positive(asin(p)), Q.zero(p)) is None
assert ask(Q.positive(asin(Rational(1, 7)))) is True
assert ask(Q.positive(asin(x)), Q.positive(x) & Q.nonpositive(x - 1)) is True
assert ask(Q.positive(asin(x)), Q.negative(x) & Q.nonnegative(x + 1)) is False
assert ask(Q.positive(acos(p)), Q.positive(p)) is None
assert ask(Q.positive(acos(Rational(1, 7)))) is True
assert ask(Q.positive(acos(x)), Q.nonnegative(x + 1) & Q.nonpositive(x - 1)) is True
assert ask(Q.positive(acos(x)), Q.nonnegative(x - 1)) is None
assert ask(Q.positive(acot(x)), Q.positive(x)) is True
assert ask(Q.positive(acot(x)), Q.real(x)) is True
assert ask(Q.positive(acot(x)), Q.imaginary(x)) is False
assert ask(Q.positive(acot(x))) is None
@XFAIL
def test_issue_7246_failing():
#Move this test to test_issue_7246 once
#the new assumptions module is improved.
assert ask(Q.positive(acos(x)), Q.zero(x)) is True
def test_check_old_assumption():
x = symbols('x', real=True)
assert ask(Q.real(x)) is True
assert ask(Q.imaginary(x)) is False
assert ask(Q.complex(x)) is True
x = symbols('x', imaginary=True)
assert ask(Q.real(x)) is False
assert ask(Q.imaginary(x)) is True
assert ask(Q.complex(x)) is True
x = symbols('x', complex=True)
assert ask(Q.real(x)) is None
assert ask(Q.complex(x)) is True
x = symbols('x', positive=True, finite=True)
assert ask(Q.positive(x)) is True
assert ask(Q.negative(x)) is False
assert ask(Q.real(x)) is True
x = symbols('x', commutative=False)
assert ask(Q.commutative(x)) is False
x = symbols('x', negative=True)
assert ask(Q.positive(x)) is False
assert ask(Q.negative(x)) is True
x = symbols('x', nonnegative=True)
assert ask(Q.negative(x)) is False
assert ask(Q.positive(x)) is None
assert ask(Q.zero(x)) is None
x = symbols('x', finite=True)
assert ask(Q.finite(x)) is True
x = symbols('x', prime=True)
assert ask(Q.prime(x)) is True
assert ask(Q.composite(x)) is False
x = symbols('x', composite=True)
assert ask(Q.prime(x)) is False
assert ask(Q.composite(x)) is True
x = symbols('x', even=True)
assert ask(Q.even(x)) is True
assert ask(Q.odd(x)) is False
x = symbols('x', odd=True)
assert ask(Q.even(x)) is False
assert ask(Q.odd(x)) is True
x = symbols('x', nonzero=True)
assert ask(Q.nonzero(x)) is True
assert ask(Q.zero(x)) is False
x = symbols('x', zero=True)
assert ask(Q.zero(x)) is True
x = symbols('x', integer=True)
assert ask(Q.integer(x)) is True
x = symbols('x', rational=True)
assert ask(Q.rational(x)) is True
assert ask(Q.irrational(x)) is False
x = symbols('x', irrational=True)
assert ask(Q.irrational(x)) is True
assert ask(Q.rational(x)) is False
def test_issue_9636():
assert ask(Q.integer(1.0)) is False
assert ask(Q.prime(3.0)) is False
assert ask(Q.composite(4.0)) is False
assert ask(Q.even(2.0)) is False
assert ask(Q.odd(3.0)) is False
def test_autosimp_used_to_fail():
# See issue #9807
assert ask(Q.imaginary(0**I)) is None
assert ask(Q.imaginary(0**(-I))) is None
assert ask(Q.real(0**I)) is None
assert ask(Q.real(0**(-I))) is None
def test_custom_AskHandler():
from sympy.logic.boolalg import conjuncts
# Old handler system
class MersenneHandler(AskHandler):
@staticmethod
def Integer(expr, assumptions):
if ask(Q.integer(log(expr + 1, 2))):
return True
@staticmethod
def Symbol(expr, assumptions):
if expr in conjuncts(assumptions):
return True
try:
with warns_deprecated_sympy():
register_handler('mersenne', MersenneHandler)
n = Symbol('n', integer=True)
with warns_deprecated_sympy():
assert ask(Q.mersenne(7))
with warns_deprecated_sympy():
assert ask(Q.mersenne(n), Q.mersenne(n))
finally:
del Q.mersenne
# New handler system
class MersennePredicate(Predicate):
pass
try:
Q.mersenne = MersennePredicate()
@Q.mersenne.register(Integer)
def _(expr, assumptions):
if ask(Q.integer(log(expr + 1, 2))):
return True
@Q.mersenne.register(Symbol)
def _(expr, assumptions):
if expr in conjuncts(assumptions):
return True
assert ask(Q.mersenne(7))
assert ask(Q.mersenne(n), Q.mersenne(n))
finally:
del Q.mersenne
def test_polyadic_predicate():
class SexyPredicate(Predicate):
pass
try:
Q.sexyprime = SexyPredicate()
@Q.sexyprime.register(Integer, Integer)
def _(int1, int2, assumptions):
args = sorted([int1, int2])
if not all(ask(Q.prime(a), assumptions) for a in args):
return False
return args[1] - args[0] == 6
@Q.sexyprime.register(Integer, Integer, Integer)
def _(int1, int2, int3, assumptions):
args = sorted([int1, int2, int3])
if not all(ask(Q.prime(a), assumptions) for a in args):
return False
return args[2] - args[1] == 6 and args[1] - args[0] == 6
assert ask(Q.sexyprime(5, 11))
assert ask(Q.sexyprime(7, 13, 19))
finally:
del Q.sexyprime
def test_Predicate_handler_is_unique():
# Undefined predicate does not have a handler
assert Predicate('mypredicate').handler is None
# Handler of defined predicate is unique to the class
class MyPredicate(Predicate):
pass
mp1 = MyPredicate('mp1')
mp2 = MyPredicate('mp2')
assert mp1.handler is mp2.handler
def test_relational():
assert ask(Q.eq(x, 0), Q.zero(x))
assert not ask(Q.eq(x, 0), Q.nonzero(x))
assert not ask(Q.ne(x, 0), Q.zero(x))
assert ask(Q.ne(x, 0), Q.nonzero(x))
|
4e3a3217bc1de9faf85f377e644919531174eda336cd4957ff6e959118654867 | """
This module implements some special functions that commonly appear in
combinatorial contexts (e.g. in power series); in particular,
sequences of rational numbers such as Bernoulli and Fibonacci numbers.
Factorials, binomial coefficients and related functions are located in
the separate 'factorials' module.
"""
from typing import Callable, Dict as tDict, Tuple as tTuple
from sympy.core import S, Symbol, Add, Dummy
from sympy.core.cache import cacheit
from sympy.core.evalf import pure_complex
from sympy.core.expr import Expr
from sympy.core.function import Function, expand_mul
from sympy.core.logic import fuzzy_not
from sympy.core.mul import Mul, prod
from sympy.core.numbers import E, pi, oo, Rational, Integer
from sympy.core.relational import is_le, is_gt
from sympy.external.gmpy import SYMPY_INTS
from sympy.functions.combinatorial.factorials import (binomial,
factorial, subfactorial)
from sympy.functions.elementary.exponential import log
from sympy.functions.elementary.integers import floor
from sympy.functions.elementary.miscellaneous import sqrt, cbrt
from sympy.functions.elementary.trigonometric import sin, cos, cot
from sympy.ntheory import isprime
from sympy.ntheory.primetest import is_square
from sympy.utilities.enumerative import MultisetPartitionTraverser
from sympy.utilities.iterables import multiset, multiset_derangements, iterable
from sympy.utilities.memoization import recurrence_memo
from sympy.utilities.misc import as_int
from mpmath import bernfrac, workprec
from mpmath.libmp import ifib as _ifib
def _product(a, b):
p = 1
for k in range(a, b + 1):
p *= k
return p
# Dummy symbol used for computing polynomial sequences
_sym = Symbol('x')
#----------------------------------------------------------------------------#
# #
# Carmichael numbers #
# #
#----------------------------------------------------------------------------#
class carmichael(Function):
"""
Carmichael Numbers:
Certain cryptographic algorithms make use of big prime numbers.
However, checking whether a big number is prime is not so easy.
Randomized prime number checking tests exist that offer a high degree of confidence of
accurate determination at low cost, such as the Fermat test.
Let 'a' be a random number between 2 and n - 1, where n is the number whose primality we are testing.
Then, n is probably prime if it satisfies the modular arithmetic congruence relation :
a^(n-1) = 1(mod n).
(where mod refers to the modulo operation)
If a number passes the Fermat test several times, then it is prime with a
high probability.
Unfortunately, certain composite numbers (non-primes) still pass the Fermat test
with every number smaller than themselves.
These numbers are called Carmichael numbers.
A Carmichael number will pass a Fermat primality test to every base b relatively prime to the number,
even though it is not actually prime. This makes tests based on Fermat's Little Theorem less effective than
strong probable prime tests such as the Baillie-PSW primality test and the Miller-Rabin primality test.
mr functions given in sympy/sympy/ntheory/primetest.py will produce wrong results for each and every
carmichael number.
Examples
========
>>> from sympy import carmichael
>>> carmichael.find_first_n_carmichaels(5)
[561, 1105, 1729, 2465, 2821]
>>> carmichael.is_prime(2465)
False
>>> carmichael.is_prime(1729)
False
>>> carmichael.find_carmichael_numbers_in_range(0, 562)
[561]
>>> carmichael.find_carmichael_numbers_in_range(0,1000)
[561]
>>> carmichael.find_carmichael_numbers_in_range(0,2000)
[561, 1105, 1729]
References
==========
.. [1] https://en.wikipedia.org/wiki/Carmichael_number
.. [2] https://en.wikipedia.org/wiki/Fermat_primality_test
.. [3] https://www.jstor.org/stable/23248683?seq=1#metadata_info_tab_contents
"""
@staticmethod
def is_perfect_square(n):
return is_square(n)
@staticmethod
def divides(p, n):
return n % p == 0
@staticmethod
def is_prime(n):
return isprime(n)
@staticmethod
def is_carmichael(n):
if n >= 0:
if (n == 1) or (carmichael.is_prime(n)) or (n % 2 == 0):
return False
divisors = list([1, n])
# get divisors
for i in range(3, n // 2 + 1, 2):
if n % i == 0:
divisors.append(i)
for i in divisors:
if carmichael.is_perfect_square(i) and i != 1:
return False
if carmichael.is_prime(i):
if not carmichael.divides(i - 1, n - 1):
return False
return True
else:
raise ValueError('The provided number must be greater than or equal to 0')
@staticmethod
def find_carmichael_numbers_in_range(x, y):
if 0 <= x <= y:
if x % 2 == 0:
return list([i for i in range(x + 1, y, 2) if carmichael.is_carmichael(i)])
else:
return list([i for i in range(x, y, 2) if carmichael.is_carmichael(i)])
else:
raise ValueError('The provided range is not valid. x and y must be non-negative integers and x <= y')
@staticmethod
def find_first_n_carmichaels(n):
i = 1
carmichaels = list()
while len(carmichaels) < n:
if carmichael.is_carmichael(i):
carmichaels.append(i)
i += 2
return carmichaels
#----------------------------------------------------------------------------#
# #
# Fibonacci numbers #
# #
#----------------------------------------------------------------------------#
class fibonacci(Function):
r"""
Fibonacci numbers / Fibonacci polynomials
The Fibonacci numbers are the integer sequence defined by the
initial terms `F_0 = 0`, `F_1 = 1` and the two-term recurrence
relation `F_n = F_{n-1} + F_{n-2}`. This definition
extended to arbitrary real and complex arguments using
the formula
.. math :: F_z = \frac{\phi^z - \cos(\pi z) \phi^{-z}}{\sqrt 5}
The Fibonacci polynomials are defined by `F_1(x) = 1`,
`F_2(x) = x`, and `F_n(x) = x*F_{n-1}(x) + F_{n-2}(x)` for `n > 2`.
For all positive integers `n`, `F_n(1) = F_n`.
* ``fibonacci(n)`` gives the `n^{th}` Fibonacci number, `F_n`
* ``fibonacci(n, x)`` gives the `n^{th}` Fibonacci polynomial in `x`, `F_n(x)`
Examples
========
>>> from sympy import fibonacci, Symbol
>>> [fibonacci(x) for x in range(11)]
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55]
>>> fibonacci(5, Symbol('t'))
t**4 + 3*t**2 + 1
See Also
========
bell, bernoulli, catalan, euler, harmonic, lucas, genocchi, partition, tribonacci
References
==========
.. [1] https://en.wikipedia.org/wiki/Fibonacci_number
.. [2] http://mathworld.wolfram.com/FibonacciNumber.html
"""
@staticmethod
def _fib(n):
return _ifib(n)
@staticmethod
@recurrence_memo([None, S.One, _sym])
def _fibpoly(n, prev):
return (prev[-2] + _sym*prev[-1]).expand()
@classmethod
def eval(cls, n, sym=None):
if n is S.Infinity:
return S.Infinity
if n.is_Integer:
if sym is None:
n = int(n)
if n < 0:
return S.NegativeOne**(n + 1) * fibonacci(-n)
else:
return Integer(cls._fib(n))
else:
if n < 1:
raise ValueError("Fibonacci polynomials are defined "
"only for positive integer indices.")
return cls._fibpoly(n).subs(_sym, sym)
def _eval_rewrite_as_sqrt(self, n, **kwargs):
return 2**(-n)*sqrt(5)*((1 + sqrt(5))**n - (-sqrt(5) + 1)**n) / 5
def _eval_rewrite_as_GoldenRatio(self,n, **kwargs):
return (S.GoldenRatio**n - 1/(-S.GoldenRatio)**n)/(2*S.GoldenRatio-1)
#----------------------------------------------------------------------------#
# #
# Lucas numbers #
# #
#----------------------------------------------------------------------------#
class lucas(Function):
"""
Lucas numbers
Lucas numbers satisfy a recurrence relation similar to that of
the Fibonacci sequence, in which each term is the sum of the
preceding two. They are generated by choosing the initial
values `L_0 = 2` and `L_1 = 1`.
* ``lucas(n)`` gives the `n^{th}` Lucas number
Examples
========
>>> from sympy import lucas
>>> [lucas(x) for x in range(11)]
[2, 1, 3, 4, 7, 11, 18, 29, 47, 76, 123]
See Also
========
bell, bernoulli, catalan, euler, fibonacci, harmonic, genocchi, partition, tribonacci
References
==========
.. [1] https://en.wikipedia.org/wiki/Lucas_number
.. [2] http://mathworld.wolfram.com/LucasNumber.html
"""
@classmethod
def eval(cls, n):
if n is S.Infinity:
return S.Infinity
if n.is_Integer:
return fibonacci(n + 1) + fibonacci(n - 1)
def _eval_rewrite_as_sqrt(self, n, **kwargs):
return 2**(-n)*((1 + sqrt(5))**n + (-sqrt(5) + 1)**n)
#----------------------------------------------------------------------------#
# #
# Tribonacci numbers #
# #
#----------------------------------------------------------------------------#
class tribonacci(Function):
r"""
Tribonacci numbers / Tribonacci polynomials
The Tribonacci numbers are the integer sequence defined by the
initial terms `T_0 = 0`, `T_1 = 1`, `T_2 = 1` and the three-term
recurrence relation `T_n = T_{n-1} + T_{n-2} + T_{n-3}`.
The Tribonacci polynomials are defined by `T_0(x) = 0`, `T_1(x) = 1`,
`T_2(x) = x^2`, and `T_n(x) = x^2 T_{n-1}(x) + x T_{n-2}(x) + T_{n-3}(x)`
for `n > 2`. For all positive integers `n`, `T_n(1) = T_n`.
* ``tribonacci(n)`` gives the `n^{th}` Tribonacci number, `T_n`
* ``tribonacci(n, x)`` gives the `n^{th}` Tribonacci polynomial in `x`, `T_n(x)`
Examples
========
>>> from sympy import tribonacci, Symbol
>>> [tribonacci(x) for x in range(11)]
[0, 1, 1, 2, 4, 7, 13, 24, 44, 81, 149]
>>> tribonacci(5, Symbol('t'))
t**8 + 3*t**5 + 3*t**2
See Also
========
bell, bernoulli, catalan, euler, fibonacci, harmonic, lucas, genocchi, partition
References
==========
.. [1] https://en.wikipedia.org/wiki/Generalizations_of_Fibonacci_numbers#Tribonacci_numbers
.. [2] http://mathworld.wolfram.com/TribonacciNumber.html
.. [3] https://oeis.org/A000073
"""
@staticmethod
@recurrence_memo([S.Zero, S.One, S.One])
def _trib(n, prev):
return (prev[-3] + prev[-2] + prev[-1])
@staticmethod
@recurrence_memo([S.Zero, S.One, _sym**2])
def _tribpoly(n, prev):
return (prev[-3] + _sym*prev[-2] + _sym**2*prev[-1]).expand()
@classmethod
def eval(cls, n, sym=None):
if n is S.Infinity:
return S.Infinity
if n.is_Integer:
n = int(n)
if n < 0:
raise ValueError("Tribonacci polynomials are defined "
"only for non-negative integer indices.")
if sym is None:
return Integer(cls._trib(n))
else:
return cls._tribpoly(n).subs(_sym, sym)
def _eval_rewrite_as_sqrt(self, n, **kwargs):
w = (-1 + S.ImaginaryUnit * sqrt(3)) / 2
a = (1 + cbrt(19 + 3*sqrt(33)) + cbrt(19 - 3*sqrt(33))) / 3
b = (1 + w*cbrt(19 + 3*sqrt(33)) + w**2*cbrt(19 - 3*sqrt(33))) / 3
c = (1 + w**2*cbrt(19 + 3*sqrt(33)) + w*cbrt(19 - 3*sqrt(33))) / 3
Tn = (a**(n + 1)/((a - b)*(a - c))
+ b**(n + 1)/((b - a)*(b - c))
+ c**(n + 1)/((c - a)*(c - b)))
return Tn
def _eval_rewrite_as_TribonacciConstant(self, n, **kwargs):
b = cbrt(586 + 102*sqrt(33))
Tn = 3 * b * S.TribonacciConstant**n / (b**2 - 2*b + 4)
return floor(Tn + S.Half)
#----------------------------------------------------------------------------#
# #
# Bernoulli numbers #
# #
#----------------------------------------------------------------------------#
class bernoulli(Function):
r"""
Bernoulli numbers / Bernoulli polynomials
The Bernoulli numbers are a sequence of rational numbers
defined by `B_0 = 1` and the recursive relation (`n > 0`):
.. math :: 0 = \sum_{k=0}^n \binom{n+1}{k} B_k
They are also commonly defined by their exponential generating
function, which is `\frac{x}{e^x - 1}`. For odd indices > 1, the
Bernoulli numbers are zero.
The Bernoulli polynomials satisfy the analogous formula:
.. math :: B_n(x) = \sum_{k=0}^n \binom{n}{k} B_k x^{n-k}
Bernoulli numbers and Bernoulli polynomials are related as
`B_n(0) = B_n`.
We compute Bernoulli numbers using Ramanujan's formula:
.. math :: B_n = \frac{A(n) - S(n)}{\binom{n+3}{n}}
where:
.. math :: A(n) = \begin{cases} \frac{n+3}{3} &
n \equiv 0\ \text{or}\ 2 \pmod{6} \\
-\frac{n+3}{6} & n \equiv 4 \pmod{6} \end{cases}
and:
.. math :: S(n) = \sum_{k=1}^{[n/6]} \binom{n+3}{n-6k} B_{n-6k}
This formula is similar to the sum given in the definition, but
cuts 2/3 of the terms. For Bernoulli polynomials, we use the
formula in the definition.
* ``bernoulli(n)`` gives the nth Bernoulli number, `B_n`
* ``bernoulli(n, x)`` gives the nth Bernoulli polynomial in `x`, `B_n(x)`
Examples
========
>>> from sympy import bernoulli
>>> [bernoulli(n) for n in range(11)]
[1, -1/2, 1/6, 0, -1/30, 0, 1/42, 0, -1/30, 0, 5/66]
>>> bernoulli(1000001)
0
See Also
========
bell, catalan, euler, fibonacci, harmonic, lucas, genocchi, partition, tribonacci
References
==========
.. [1] https://en.wikipedia.org/wiki/Bernoulli_number
.. [2] https://en.wikipedia.org/wiki/Bernoulli_polynomial
.. [3] http://mathworld.wolfram.com/BernoulliNumber.html
.. [4] http://mathworld.wolfram.com/BernoulliPolynomial.html
"""
args: tTuple[Integer]
# Calculates B_n for positive even n
@staticmethod
def _calc_bernoulli(n):
s = 0
a = int(binomial(n + 3, n - 6))
for j in range(1, n//6 + 1):
s += a * bernoulli(n - 6*j)
# Avoid computing each binomial coefficient from scratch
a *= _product(n - 6 - 6*j + 1, n - 6*j)
a //= _product(6*j + 4, 6*j + 9)
if n % 6 == 4:
s = -Rational(n + 3, 6) - s
else:
s = Rational(n + 3, 3) - s
return s / binomial(n + 3, n)
# We implement a specialized memoization scheme to handle each
# case modulo 6 separately
_cache = {0: S.One, 2: Rational(1, 6), 4: Rational(-1, 30)}
_highest = {0: 0, 2: 2, 4: 4}
@classmethod
def eval(cls, n, sym=None):
if n.is_Number:
if n.is_Integer and n.is_nonnegative:
if n.is_zero:
return S.One
elif n is S.One:
if sym is None:
return Rational(-1, 2)
else:
return sym - S.Half
# Bernoulli numbers
elif sym is None:
if n.is_odd:
return S.Zero
n = int(n)
# Use mpmath for enormous Bernoulli numbers
if n > 500:
p, q = bernfrac(n)
return Rational(int(p), int(q))
case = n % 6
highest_cached = cls._highest[case]
if n <= highest_cached:
return cls._cache[n]
# To avoid excessive recursion when, say, bernoulli(1000) is
# requested, calculate and cache the entire sequence ... B_988,
# B_994, B_1000 in increasing order
for i in range(highest_cached + 6, n + 6, 6):
b = cls._calc_bernoulli(i)
cls._cache[i] = b
cls._highest[case] = i
return b
# Bernoulli polynomials
else:
n, result = int(n), []
for k in range(n + 1):
result.append(binomial(n, k)*cls(k)*sym**(n - k))
return Add(*result)
else:
raise ValueError("Bernoulli numbers are defined only"
" for nonnegative integer indices.")
if sym is None:
if n.is_odd and (n - 1).is_positive:
return S.Zero
#----------------------------------------------------------------------------#
# #
# Bell numbers #
# #
#----------------------------------------------------------------------------#
class bell(Function):
r"""
Bell numbers / Bell polynomials
The Bell numbers satisfy `B_0 = 1` and
.. math:: B_n = \sum_{k=0}^{n-1} \binom{n-1}{k} B_k.
They are also given by:
.. math:: B_n = \frac{1}{e} \sum_{k=0}^{\infty} \frac{k^n}{k!}.
The Bell polynomials are given by `B_0(x) = 1` and
.. math:: B_n(x) = x \sum_{k=1}^{n-1} \binom{n-1}{k-1} B_{k-1}(x).
The second kind of Bell polynomials (are sometimes called "partial" Bell
polynomials or incomplete Bell polynomials) are defined as
.. math:: B_{n,k}(x_1, x_2,\dotsc x_{n-k+1}) =
\sum_{j_1+j_2+j_2+\dotsb=k \atop j_1+2j_2+3j_2+\dotsb=n}
\frac{n!}{j_1!j_2!\dotsb j_{n-k+1}!}
\left(\frac{x_1}{1!} \right)^{j_1}
\left(\frac{x_2}{2!} \right)^{j_2} \dotsb
\left(\frac{x_{n-k+1}}{(n-k+1)!} \right) ^{j_{n-k+1}}.
* ``bell(n)`` gives the `n^{th}` Bell number, `B_n`.
* ``bell(n, x)`` gives the `n^{th}` Bell polynomial, `B_n(x)`.
* ``bell(n, k, (x1, x2, ...))`` gives Bell polynomials of the second kind,
`B_{n,k}(x_1, x_2, \dotsc, x_{n-k+1})`.
Notes
=====
Not to be confused with Bernoulli numbers and Bernoulli polynomials,
which use the same notation.
Examples
========
>>> from sympy import bell, Symbol, symbols
>>> [bell(n) for n in range(11)]
[1, 1, 2, 5, 15, 52, 203, 877, 4140, 21147, 115975]
>>> bell(30)
846749014511809332450147
>>> bell(4, Symbol('t'))
t**4 + 6*t**3 + 7*t**2 + t
>>> bell(6, 2, symbols('x:6')[1:])
6*x1*x5 + 15*x2*x4 + 10*x3**2
See Also
========
bernoulli, catalan, euler, fibonacci, harmonic, lucas, genocchi, partition, tribonacci
References
==========
.. [1] https://en.wikipedia.org/wiki/Bell_number
.. [2] http://mathworld.wolfram.com/BellNumber.html
.. [3] http://mathworld.wolfram.com/BellPolynomial.html
"""
@staticmethod
@recurrence_memo([1, 1])
def _bell(n, prev):
s = 1
a = 1
for k in range(1, n):
a = a * (n - k) // k
s += a * prev[k]
return s
@staticmethod
@recurrence_memo([S.One, _sym])
def _bell_poly(n, prev):
s = 1
a = 1
for k in range(2, n + 1):
a = a * (n - k + 1) // (k - 1)
s += a * prev[k - 1]
return expand_mul(_sym * s)
@staticmethod
def _bell_incomplete_poly(n, k, symbols):
r"""
The second kind of Bell polynomials (incomplete Bell polynomials).
Calculated by recurrence formula:
.. math:: B_{n,k}(x_1, x_2, \dotsc, x_{n-k+1}) =
\sum_{m=1}^{n-k+1}
\x_m \binom{n-1}{m-1} B_{n-m,k-1}(x_1, x_2, \dotsc, x_{n-m-k})
where
`B_{0,0} = 1;`
`B_{n,0} = 0; for n \ge 1`
`B_{0,k} = 0; for k \ge 1`
"""
if (n == 0) and (k == 0):
return S.One
elif (n == 0) or (k == 0):
return S.Zero
s = S.Zero
a = S.One
for m in range(1, n - k + 2):
s += a * bell._bell_incomplete_poly(
n - m, k - 1, symbols) * symbols[m - 1]
a = a * (n - m) / m
return expand_mul(s)
@classmethod
def eval(cls, n, k_sym=None, symbols=None):
if n is S.Infinity:
if k_sym is None:
return S.Infinity
else:
raise ValueError("Bell polynomial is not defined")
if n.is_negative or n.is_integer is False:
raise ValueError("a non-negative integer expected")
if n.is_Integer and n.is_nonnegative:
if k_sym is None:
return Integer(cls._bell(int(n)))
elif symbols is None:
return cls._bell_poly(int(n)).subs(_sym, k_sym)
else:
r = cls._bell_incomplete_poly(int(n), int(k_sym), symbols)
return r
def _eval_rewrite_as_Sum(self, n, k_sym=None, symbols=None, **kwargs):
from sympy.concrete.summations import Sum
if (k_sym is not None) or (symbols is not None):
return self
# Dobinski's formula
if not n.is_nonnegative:
return self
k = Dummy('k', integer=True, nonnegative=True)
return 1 / E * Sum(k**n / factorial(k), (k, 0, S.Infinity))
#----------------------------------------------------------------------------#
# #
# Harmonic numbers #
# #
#----------------------------------------------------------------------------#
class harmonic(Function):
r"""
Harmonic numbers
The nth harmonic number is given by `\operatorname{H}_{n} =
1 + \frac{1}{2} + \frac{1}{3} + \ldots + \frac{1}{n}`.
More generally:
.. math:: \operatorname{H}_{n,m} = \sum_{k=1}^{n} \frac{1}{k^m}
As `n \rightarrow \infty`, `\operatorname{H}_{n,m} \rightarrow \zeta(m)`,
the Riemann zeta function.
* ``harmonic(n)`` gives the nth harmonic number, `\operatorname{H}_n`
* ``harmonic(n, m)`` gives the nth generalized harmonic number
of order `m`, `\operatorname{H}_{n,m}`, where
``harmonic(n) == harmonic(n, 1)``
Examples
========
>>> from sympy import harmonic, oo
>>> [harmonic(n) for n in range(6)]
[0, 1, 3/2, 11/6, 25/12, 137/60]
>>> [harmonic(n, 2) for n in range(6)]
[0, 1, 5/4, 49/36, 205/144, 5269/3600]
>>> harmonic(oo, 2)
pi**2/6
>>> from sympy import Symbol, Sum
>>> n = Symbol("n")
>>> harmonic(n).rewrite(Sum)
Sum(1/_k, (_k, 1, n))
We can evaluate harmonic numbers for all integral and positive
rational arguments:
>>> from sympy import S, expand_func, simplify
>>> harmonic(8)
761/280
>>> harmonic(11)
83711/27720
>>> H = harmonic(1/S(3))
>>> H
harmonic(1/3)
>>> He = expand_func(H)
>>> He
-log(6) - sqrt(3)*pi/6 + 2*Sum(log(sin(_k*pi/3))*cos(2*_k*pi/3), (_k, 1, 1))
+ 3*Sum(1/(3*_k + 1), (_k, 0, 0))
>>> He.doit()
-log(6) - sqrt(3)*pi/6 - log(sqrt(3)/2) + 3
>>> H = harmonic(25/S(7))
>>> He = simplify(expand_func(H).doit())
>>> He
log(sin(2*pi/7)**(2*cos(16*pi/7))/(14*sin(pi/7)**(2*cos(pi/7))*cos(pi/14)**(2*sin(pi/14)))) + pi*tan(pi/14)/2 + 30247/9900
>>> He.n(40)
1.983697455232980674869851942390639915940
>>> harmonic(25/S(7)).n(40)
1.983697455232980674869851942390639915940
We can rewrite harmonic numbers in terms of polygamma functions:
>>> from sympy import digamma, polygamma
>>> m = Symbol("m")
>>> harmonic(n).rewrite(digamma)
polygamma(0, n + 1) + EulerGamma
>>> harmonic(n).rewrite(polygamma)
polygamma(0, n + 1) + EulerGamma
>>> harmonic(n,3).rewrite(polygamma)
polygamma(2, n + 1)/2 - polygamma(2, 1)/2
>>> harmonic(n,m).rewrite(polygamma)
(-1)**m*(polygamma(m - 1, 1) - polygamma(m - 1, n + 1))/factorial(m - 1)
Integer offsets in the argument can be pulled out:
>>> from sympy import expand_func
>>> expand_func(harmonic(n+4))
harmonic(n) + 1/(n + 4) + 1/(n + 3) + 1/(n + 2) + 1/(n + 1)
>>> expand_func(harmonic(n-4))
harmonic(n) - 1/(n - 1) - 1/(n - 2) - 1/(n - 3) - 1/n
Some limits can be computed as well:
>>> from sympy import limit, oo
>>> limit(harmonic(n), n, oo)
oo
>>> limit(harmonic(n, 2), n, oo)
pi**2/6
>>> limit(harmonic(n, 3), n, oo)
-polygamma(2, 1)/2
However we cannot compute the general relation yet:
>>> limit(harmonic(n, m), n, oo)
harmonic(oo, m)
which equals ``zeta(m)`` for ``m > 1``.
See Also
========
bell, bernoulli, catalan, euler, fibonacci, lucas, genocchi, partition, tribonacci
References
==========
.. [1] https://en.wikipedia.org/wiki/Harmonic_number
.. [2] http://functions.wolfram.com/GammaBetaErf/HarmonicNumber/
.. [3] http://functions.wolfram.com/GammaBetaErf/HarmonicNumber2/
"""
# Generate one memoized Harmonic number-generating function for each
# order and store it in a dictionary
_functions = {} # type: tDict[Integer, Callable[[int], Rational]]
@classmethod
def eval(cls, n, m=None):
from sympy.functions.special.zeta_functions import zeta
if m is S.One:
return cls(n)
if m is None:
m = S.One
if m.is_zero:
return n
if n is S.Infinity:
if m.is_negative:
return S.NaN
elif is_le(m, S.One):
return S.Infinity
elif is_gt(m, S.One):
return zeta(m)
else:
return
if n == 0:
return S.Zero
if n.is_Integer and n.is_nonnegative and m.is_Integer:
if not m in cls._functions:
@recurrence_memo([0])
def f(n, prev):
return prev[-1] + S.One / n**m
cls._functions[m] = f
return cls._functions[m](int(n))
def _eval_rewrite_as_polygamma(self, n, m=1, **kwargs):
from sympy.functions.special.gamma_functions import polygamma
return S.NegativeOne**m/factorial(m - 1) * (polygamma(m - 1, 1) - polygamma(m - 1, n + 1))
def _eval_rewrite_as_digamma(self, n, m=1, **kwargs):
from sympy.functions.special.gamma_functions import polygamma
return self.rewrite(polygamma)
def _eval_rewrite_as_trigamma(self, n, m=1, **kwargs):
from sympy.functions.special.gamma_functions import polygamma
return self.rewrite(polygamma)
def _eval_rewrite_as_Sum(self, n, m=None, **kwargs):
from sympy.concrete.summations import Sum
k = Dummy("k", integer=True)
if m is None:
m = S.One
return Sum(k**(-m), (k, 1, n))
def _eval_expand_func(self, **hints):
from sympy.concrete.summations import Sum
n = self.args[0]
m = self.args[1] if len(self.args) == 2 else 1
if m == S.One:
if n.is_Add:
off = n.args[0]
nnew = n - off
if off.is_Integer and off.is_positive:
result = [S.One/(nnew + i) for i in range(off, 0, -1)] + [harmonic(nnew)]
return Add(*result)
elif off.is_Integer and off.is_negative:
result = [-S.One/(nnew + i) for i in range(0, off, -1)] + [harmonic(nnew)]
return Add(*result)
if n.is_Rational:
# Expansions for harmonic numbers at general rational arguments (u + p/q)
# Split n as u + p/q with p < q
p, q = n.as_numer_denom()
u = p // q
p = p - u * q
if u.is_nonnegative and p.is_positive and q.is_positive and p < q:
k = Dummy("k")
t1 = q * Sum(1 / (q * k + p), (k, 0, u))
t2 = 2 * Sum(cos((2 * pi * p * k) / S(q)) *
log(sin((pi * k) / S(q))),
(k, 1, floor((q - 1) / S(2))))
t3 = (pi / 2) * cot((pi * p) / q) + log(2 * q)
return t1 + t2 - t3
return self
def _eval_rewrite_as_tractable(self, n, m=1, limitvar=None, **kwargs):
from sympy.functions.special.gamma_functions import polygamma
return self.rewrite(polygamma).rewrite("tractable", deep=True)
def _eval_evalf(self, prec):
from sympy.functions.special.gamma_functions import polygamma
if all(i.is_number for i in self.args):
return self.rewrite(polygamma)._eval_evalf(prec)
#----------------------------------------------------------------------------#
# #
# Euler numbers #
# #
#----------------------------------------------------------------------------#
class euler(Function):
r"""
Euler numbers / Euler polynomials
The Euler numbers are given by:
.. math:: E_{2n} = I \sum_{k=1}^{2n+1} \sum_{j=0}^k \binom{k}{j}
\frac{(-1)^j (k-2j)^{2n+1}}{2^k I^k k}
.. math:: E_{2n+1} = 0
Euler numbers and Euler polynomials are related by
.. math:: E_n = 2^n E_n\left(\frac{1}{2}\right).
We compute symbolic Euler polynomials using [5]_
.. math:: E_n(x) = \sum_{k=0}^n \binom{n}{k} \frac{E_k}{2^k}
\left(x - \frac{1}{2}\right)^{n-k}.
However, numerical evaluation of the Euler polynomial is computed
more efficiently (and more accurately) using the mpmath library.
* ``euler(n)`` gives the `n^{th}` Euler number, `E_n`.
* ``euler(n, x)`` gives the `n^{th}` Euler polynomial, `E_n(x)`.
Examples
========
>>> from sympy import euler, Symbol, S
>>> [euler(n) for n in range(10)]
[1, 0, -1, 0, 5, 0, -61, 0, 1385, 0]
>>> n = Symbol("n")
>>> euler(n + 2*n)
euler(3*n)
>>> x = Symbol("x")
>>> euler(n, x)
euler(n, x)
>>> euler(0, x)
1
>>> euler(1, x)
x - 1/2
>>> euler(2, x)
x**2 - x
>>> euler(3, x)
x**3 - 3*x**2/2 + 1/4
>>> euler(4, x)
x**4 - 2*x**3 + x
>>> euler(12, S.Half)
2702765/4096
>>> euler(12)
2702765
See Also
========
bell, bernoulli, catalan, fibonacci, harmonic, lucas, genocchi, partition, tribonacci
References
==========
.. [1] https://en.wikipedia.org/wiki/Euler_numbers
.. [2] http://mathworld.wolfram.com/EulerNumber.html
.. [3] https://en.wikipedia.org/wiki/Alternating_permutation
.. [4] http://mathworld.wolfram.com/AlternatingPermutation.html
.. [5] http://dlmf.nist.gov/24.2#ii
"""
@classmethod
def eval(cls, m, sym=None):
if m.is_Number:
if m.is_Integer and m.is_nonnegative:
# Euler numbers
if sym is None:
if m.is_odd:
return S.Zero
from mpmath import mp
m = m._to_mpmath(mp.prec)
res = mp.eulernum(m, exact=True)
return Integer(res)
# Euler polynomial
else:
reim = pure_complex(sym, or_real=True)
# Evaluate polynomial numerically using mpmath
if reim and all(a.is_Float or a.is_Integer for a in reim) \
and any(a.is_Float for a in reim):
from mpmath import mp
m = int(m)
# XXX ComplexFloat (#12192) would be nice here, above
prec = min([a._prec for a in reim if a.is_Float])
with workprec(prec):
res = mp.eulerpoly(m, sym)
return Expr._from_mpmath(res, prec)
# Construct polynomial symbolically from definition
m, result = int(m), []
for k in range(m + 1):
result.append(binomial(m, k)*cls(k)/(2**k)*(sym - S.Half)**(m - k))
return Add(*result).expand()
else:
raise ValueError("Euler numbers are defined only"
" for nonnegative integer indices.")
if sym is None:
if m.is_odd and m.is_positive:
return S.Zero
def _eval_rewrite_as_Sum(self, n, x=None, **kwargs):
from sympy.concrete.summations import Sum
if x is None and n.is_even:
k = Dummy("k", integer=True)
j = Dummy("j", integer=True)
n = n / 2
Em = (S.ImaginaryUnit * Sum(Sum(binomial(k, j) * (S.NegativeOne**j *
(k - 2*j)**(2*n + 1)) /
(2**k*S.ImaginaryUnit**k * k), (j, 0, k)), (k, 1, 2*n + 1)))
return Em
if x:
k = Dummy("k", integer=True)
return Sum(binomial(n, k)*euler(k)/2**k*(x - S.Half)**(n - k), (k, 0, n))
def _eval_evalf(self, prec):
m, x = (self.args[0], None) if len(self.args) == 1 else self.args
if x is None and m.is_Integer and m.is_nonnegative:
from mpmath import mp
m = m._to_mpmath(prec)
with workprec(prec):
res = mp.eulernum(m)
return Expr._from_mpmath(res, prec)
if x and x.is_number and m.is_Integer and m.is_nonnegative:
from mpmath import mp
m = int(m)
x = x._to_mpmath(prec)
with workprec(prec):
res = mp.eulerpoly(m, x)
return Expr._from_mpmath(res, prec)
#----------------------------------------------------------------------------#
# #
# Catalan numbers #
# #
#----------------------------------------------------------------------------#
class catalan(Function):
r"""
Catalan numbers
The `n^{th}` catalan number is given by:
.. math :: C_n = \frac{1}{n+1} \binom{2n}{n}
* ``catalan(n)`` gives the `n^{th}` Catalan number, `C_n`
Examples
========
>>> from sympy import (Symbol, binomial, gamma, hyper,
... catalan, diff, combsimp, Rational, I)
>>> [catalan(i) for i in range(1,10)]
[1, 2, 5, 14, 42, 132, 429, 1430, 4862]
>>> n = Symbol("n", integer=True)
>>> catalan(n)
catalan(n)
Catalan numbers can be transformed into several other, identical
expressions involving other mathematical functions
>>> catalan(n).rewrite(binomial)
binomial(2*n, n)/(n + 1)
>>> catalan(n).rewrite(gamma)
4**n*gamma(n + 1/2)/(sqrt(pi)*gamma(n + 2))
>>> catalan(n).rewrite(hyper)
hyper((1 - n, -n), (2,), 1)
For some non-integer values of n we can get closed form
expressions by rewriting in terms of gamma functions:
>>> catalan(Rational(1, 2)).rewrite(gamma)
8/(3*pi)
We can differentiate the Catalan numbers C(n) interpreted as a
continuous real function in n:
>>> diff(catalan(n), n)
(polygamma(0, n + 1/2) - polygamma(0, n + 2) + log(4))*catalan(n)
As a more advanced example consider the following ratio
between consecutive numbers:
>>> combsimp((catalan(n + 1)/catalan(n)).rewrite(binomial))
2*(2*n + 1)/(n + 2)
The Catalan numbers can be generalized to complex numbers:
>>> catalan(I).rewrite(gamma)
4**I*gamma(1/2 + I)/(sqrt(pi)*gamma(2 + I))
and evaluated with arbitrary precision:
>>> catalan(I).evalf(20)
0.39764993382373624267 - 0.020884341620842555705*I
See Also
========
bell, bernoulli, euler, fibonacci, harmonic, lucas, genocchi, partition, tribonacci
sympy.functions.combinatorial.factorials.binomial
References
==========
.. [1] https://en.wikipedia.org/wiki/Catalan_number
.. [2] http://mathworld.wolfram.com/CatalanNumber.html
.. [3] http://functions.wolfram.com/GammaBetaErf/CatalanNumber/
.. [4] http://geometer.org/mathcircles/catalan.pdf
"""
@classmethod
def eval(cls, n):
from sympy.functions.special.gamma_functions import gamma
if (n.is_Integer and n.is_nonnegative) or \
(n.is_noninteger and n.is_negative):
return 4**n*gamma(n + S.Half)/(gamma(S.Half)*gamma(n + 2))
if (n.is_integer and n.is_negative):
if (n + 1).is_negative:
return S.Zero
if (n + 1).is_zero:
return Rational(-1, 2)
def fdiff(self, argindex=1):
from sympy.functions.special.gamma_functions import polygamma
n = self.args[0]
return catalan(n)*(polygamma(0, n + S.Half) - polygamma(0, n + 2) + log(4))
def _eval_rewrite_as_binomial(self, n, **kwargs):
return binomial(2*n, n)/(n + 1)
def _eval_rewrite_as_factorial(self, n, **kwargs):
return factorial(2*n) / (factorial(n+1) * factorial(n))
def _eval_rewrite_as_gamma(self, n, piecewise=True, **kwargs):
from sympy.functions.special.gamma_functions import gamma
# The gamma function allows to generalize Catalan numbers to complex n
return 4**n*gamma(n + S.Half)/(gamma(S.Half)*gamma(n + 2))
def _eval_rewrite_as_hyper(self, n, **kwargs):
from sympy.functions.special.hyper import hyper
return hyper([1 - n, -n], [2], 1)
def _eval_rewrite_as_Product(self, n, **kwargs):
from sympy.concrete.products import Product
if not (n.is_integer and n.is_nonnegative):
return self
k = Dummy('k', integer=True, positive=True)
return Product((n + k) / k, (k, 2, n))
def _eval_is_integer(self):
if self.args[0].is_integer and self.args[0].is_nonnegative:
return True
def _eval_is_positive(self):
if self.args[0].is_nonnegative:
return True
def _eval_is_composite(self):
if self.args[0].is_integer and (self.args[0] - 3).is_positive:
return True
def _eval_evalf(self, prec):
from sympy.functions.special.gamma_functions import gamma
if self.args[0].is_number:
return self.rewrite(gamma)._eval_evalf(prec)
#----------------------------------------------------------------------------#
# #
# Genocchi numbers #
# #
#----------------------------------------------------------------------------#
class genocchi(Function):
r"""
Genocchi numbers
The Genocchi numbers are a sequence of integers `G_n` that satisfy the
relation:
.. math:: \frac{2t}{e^t + 1} = \sum_{n=1}^\infty \frac{G_n t^n}{n!}
Examples
========
>>> from sympy import genocchi, Symbol
>>> [genocchi(n) for n in range(1, 9)]
[1, -1, 0, 1, 0, -3, 0, 17]
>>> n = Symbol('n', integer=True, positive=True)
>>> genocchi(2*n + 1)
0
See Also
========
bell, bernoulli, catalan, euler, fibonacci, harmonic, lucas, partition, tribonacci
References
==========
.. [1] https://en.wikipedia.org/wiki/Genocchi_number
.. [2] http://mathworld.wolfram.com/GenocchiNumber.html
"""
@classmethod
def eval(cls, n):
if n.is_Number:
if (not n.is_Integer) or n.is_nonpositive:
raise ValueError("Genocchi numbers are defined only for " +
"positive integers")
return 2 * (1 - S(2) ** n) * bernoulli(n)
if n.is_odd and (n - 1).is_positive:
return S.Zero
if (n - 1).is_zero:
return S.One
def _eval_rewrite_as_bernoulli(self, n, **kwargs):
if n.is_integer and n.is_nonnegative:
return (1 - S(2) ** n) * bernoulli(n) * 2
def _eval_is_integer(self):
if self.args[0].is_integer and self.args[0].is_positive:
return True
def _eval_is_negative(self):
n = self.args[0]
if n.is_integer and n.is_positive:
if n.is_odd:
return False
return (n / 2).is_odd
def _eval_is_positive(self):
n = self.args[0]
if n.is_integer and n.is_positive:
if n.is_odd:
return fuzzy_not((n - 1).is_positive)
return (n / 2).is_even
def _eval_is_even(self):
n = self.args[0]
if n.is_integer and n.is_positive:
if n.is_even:
return False
return (n - 1).is_positive
def _eval_is_odd(self):
n = self.args[0]
if n.is_integer and n.is_positive:
if n.is_even:
return True
return fuzzy_not((n - 1).is_positive)
def _eval_is_prime(self):
n = self.args[0]
# only G_6 = -3 and G_8 = 17 are prime,
# but SymPy does not consider negatives as prime
# so only n=8 is tested
return (n - 8).is_zero
#----------------------------------------------------------------------------#
# #
# Partition numbers #
# #
#----------------------------------------------------------------------------#
_npartition = [1, 1]
class partition(Function):
r"""
Partition numbers
The Partition numbers are a sequence of integers `p_n` that represent the
number of distinct ways of representing `n` as a sum of natural numbers
(with order irrelevant). The generating function for `p_n` is given by:
.. math:: \sum_{n=0}^\infty p_n x^n = \prod_{k=1}^\infty (1 - x^k)^{-1}
Examples
========
>>> from sympy import partition, Symbol
>>> [partition(n) for n in range(9)]
[1, 1, 2, 3, 5, 7, 11, 15, 22]
>>> n = Symbol('n', integer=True, negative=True)
>>> partition(n)
0
See Also
========
bell, bernoulli, catalan, euler, fibonacci, harmonic, lucas, genocchi, tribonacci
References
==========
.. [1] https://en.wikipedia.org/wiki/Partition_(number_theory%29
.. [2] https://en.wikipedia.org/wiki/Pentagonal_number_theorem
"""
@staticmethod
def _partition(n):
L = len(_npartition)
if n < L:
return _npartition[n]
# lengthen cache
for _n in range(L, n + 1):
v, p, i = 0, 0, 0
while 1:
s = 0
p += 3*i + 1 # p = pentagonal number: 1, 5, 12, ...
if _n >= p:
s += _npartition[_n - p]
i += 1
gp = p + i # gp = generalized pentagonal: 2, 7, 15, ...
if _n >= gp:
s += _npartition[_n - gp]
if s == 0:
break
else:
v += s if i%2 == 1 else -s
_npartition.append(v)
return v
@classmethod
def eval(cls, n):
is_int = n.is_integer
if is_int == False:
raise ValueError("Partition numbers are defined only for "
"integers")
elif is_int:
if n.is_negative:
return S.Zero
if n.is_zero or (n - 1).is_zero:
return S.One
if n.is_Integer:
return Integer(cls._partition(n))
def _eval_is_integer(self):
if self.args[0].is_integer:
return True
def _eval_is_negative(self):
if self.args[0].is_integer:
return False
def _eval_is_positive(self):
n = self.args[0]
if n.is_nonnegative and n.is_integer:
return True
#######################################################################
###
### Functions for enumerating partitions, permutations and combinations
###
#######################################################################
class _MultisetHistogram(tuple):
pass
_N = -1
_ITEMS = -2
_M = slice(None, _ITEMS)
def _multiset_histogram(n):
"""Return tuple used in permutation and combination counting. Input
is a dictionary giving items with counts as values or a sequence of
items (which need not be sorted).
The data is stored in a class deriving from tuple so it is easily
recognized and so it can be converted easily to a list.
"""
if isinstance(n, dict): # item: count
if not all(isinstance(v, int) and v >= 0 for v in n.values()):
raise ValueError
tot = sum(n.values())
items = sum(1 for k in n if n[k] > 0)
return _MultisetHistogram([n[k] for k in n if n[k] > 0] + [items, tot])
else:
n = list(n)
s = set(n)
lens = len(s)
lenn = len(n)
if lens == lenn:
n = [1]*lenn + [lenn, lenn]
return _MultisetHistogram(n)
m = dict(zip(s, range(lens)))
d = dict(zip(range(lens), (0,)*lens))
for i in n:
d[m[i]] += 1
return _multiset_histogram(d)
def nP(n, k=None, replacement=False):
"""Return the number of permutations of ``n`` items taken ``k`` at a time.
Possible values for ``n``:
integer - set of length ``n``
sequence - converted to a multiset internally
multiset - {element: multiplicity}
If ``k`` is None then the total of all permutations of length 0
through the number of items represented by ``n`` will be returned.
If ``replacement`` is True then a given item can appear more than once
in the ``k`` items. (For example, for 'ab' permutations of 2 would
include 'aa', 'ab', 'ba' and 'bb'.) The multiplicity of elements in
``n`` is ignored when ``replacement`` is True but the total number
of elements is considered since no element can appear more times than
the number of elements in ``n``.
Examples
========
>>> from sympy.functions.combinatorial.numbers import nP
>>> from sympy.utilities.iterables import multiset_permutations, multiset
>>> nP(3, 2)
6
>>> nP('abc', 2) == nP(multiset('abc'), 2) == 6
True
>>> nP('aab', 2)
3
>>> nP([1, 2, 2], 2)
3
>>> [nP(3, i) for i in range(4)]
[1, 3, 6, 6]
>>> nP(3) == sum(_)
True
When ``replacement`` is True, each item can have multiplicity
equal to the length represented by ``n``:
>>> nP('aabc', replacement=True)
121
>>> [len(list(multiset_permutations('aaaabbbbcccc', i))) for i in range(5)]
[1, 3, 9, 27, 81]
>>> sum(_)
121
See Also
========
sympy.utilities.iterables.multiset_permutations
References
==========
.. [1] https://en.wikipedia.org/wiki/Permutation
"""
try:
n = as_int(n)
except ValueError:
return Integer(_nP(_multiset_histogram(n), k, replacement))
return Integer(_nP(n, k, replacement))
@cacheit
def _nP(n, k=None, replacement=False):
if k == 0:
return 1
if isinstance(n, SYMPY_INTS): # n different items
# assert n >= 0
if k is None:
return sum(_nP(n, i, replacement) for i in range(n + 1))
elif replacement:
return n**k
elif k > n:
return 0
elif k == n:
return factorial(k)
elif k == 1:
return n
else:
# assert k >= 0
return _product(n - k + 1, n)
elif isinstance(n, _MultisetHistogram):
if k is None:
return sum(_nP(n, i, replacement) for i in range(n[_N] + 1))
elif replacement:
return n[_ITEMS]**k
elif k == n[_N]:
return factorial(k)/prod([factorial(i) for i in n[_M] if i > 1])
elif k > n[_N]:
return 0
elif k == 1:
return n[_ITEMS]
else:
# assert k >= 0
tot = 0
n = list(n)
for i in range(len(n[_M])):
if not n[i]:
continue
n[_N] -= 1
if n[i] == 1:
n[i] = 0
n[_ITEMS] -= 1
tot += _nP(_MultisetHistogram(n), k - 1)
n[_ITEMS] += 1
n[i] = 1
else:
n[i] -= 1
tot += _nP(_MultisetHistogram(n), k - 1)
n[i] += 1
n[_N] += 1
return tot
@cacheit
def _AOP_product(n):
"""for n = (m1, m2, .., mk) return the coefficients of the polynomial,
prod(sum(x**i for i in range(nj + 1)) for nj in n); i.e. the coefficients
of the product of AOPs (all-one polynomials) or order given in n. The
resulting coefficient corresponding to x**r is the number of r-length
combinations of sum(n) elements with multiplicities given in n.
The coefficients are given as a default dictionary (so if a query is made
for a key that is not present, 0 will be returned).
Examples
========
>>> from sympy.functions.combinatorial.numbers import _AOP_product
>>> from sympy.abc import x
>>> n = (2, 2, 3) # e.g. aabbccc
>>> prod = ((x**2 + x + 1)*(x**2 + x + 1)*(x**3 + x**2 + x + 1)).expand()
>>> c = _AOP_product(n); dict(c)
{0: 1, 1: 3, 2: 6, 3: 8, 4: 8, 5: 6, 6: 3, 7: 1}
>>> [c[i] for i in range(8)] == [prod.coeff(x, i) for i in range(8)]
True
The generating poly used here is the same as that listed in
http://tinyurl.com/cep849r, but in a refactored form.
"""
from collections import defaultdict
n = list(n)
ord = sum(n)
need = (ord + 2)//2
rv = [1]*(n.pop() + 1)
rv.extend((0,) * (need - len(rv)))
rv = rv[:need]
while n:
ni = n.pop()
N = ni + 1
was = rv[:]
for i in range(1, min(N, len(rv))):
rv[i] += rv[i - 1]
for i in range(N, need):
rv[i] += rv[i - 1] - was[i - N]
rev = list(reversed(rv))
if ord % 2:
rv = rv + rev
else:
rv[-1:] = rev
d = defaultdict(int)
for i in range(len(rv)):
d[i] = rv[i]
return d
def nC(n, k=None, replacement=False):
"""Return the number of combinations of ``n`` items taken ``k`` at a time.
Possible values for ``n``:
integer - set of length ``n``
sequence - converted to a multiset internally
multiset - {element: multiplicity}
If ``k`` is None then the total of all combinations of length 0
through the number of items represented in ``n`` will be returned.
If ``replacement`` is True then a given item can appear more than once
in the ``k`` items. (For example, for 'ab' sets of 2 would include 'aa',
'ab', and 'bb'.) The multiplicity of elements in ``n`` is ignored when
``replacement`` is True but the total number of elements is considered
since no element can appear more times than the number of elements in
``n``.
Examples
========
>>> from sympy.functions.combinatorial.numbers import nC
>>> from sympy.utilities.iterables import multiset_combinations
>>> nC(3, 2)
3
>>> nC('abc', 2)
3
>>> nC('aab', 2)
2
When ``replacement`` is True, each item can have multiplicity
equal to the length represented by ``n``:
>>> nC('aabc', replacement=True)
35
>>> [len(list(multiset_combinations('aaaabbbbcccc', i))) for i in range(5)]
[1, 3, 6, 10, 15]
>>> sum(_)
35
If there are ``k`` items with multiplicities ``m_1, m_2, ..., m_k``
then the total of all combinations of length 0 through ``k`` is the
product, ``(m_1 + 1)*(m_2 + 1)*...*(m_k + 1)``. When the multiplicity
of each item is 1 (i.e., k unique items) then there are 2**k
combinations. For example, if there are 4 unique items, the total number
of combinations is 16:
>>> sum(nC(4, i) for i in range(5))
16
See Also
========
sympy.utilities.iterables.multiset_combinations
References
==========
.. [1] https://en.wikipedia.org/wiki/Combination
.. [2] http://tinyurl.com/cep849r
"""
if isinstance(n, SYMPY_INTS):
if k is None:
if not replacement:
return 2**n
return sum(nC(n, i, replacement) for i in range(n + 1))
if k < 0:
raise ValueError("k cannot be negative")
if replacement:
return binomial(n + k - 1, k)
return binomial(n, k)
if isinstance(n, _MultisetHistogram):
N = n[_N]
if k is None:
if not replacement:
return prod(m + 1 for m in n[_M])
return sum(nC(n, i, replacement) for i in range(N + 1))
elif replacement:
return nC(n[_ITEMS], k, replacement)
# assert k >= 0
elif k in (1, N - 1):
return n[_ITEMS]
elif k in (0, N):
return 1
return _AOP_product(tuple(n[_M]))[k]
else:
return nC(_multiset_histogram(n), k, replacement)
def _eval_stirling1(n, k):
if n == k == 0:
return S.One
if 0 in (n, k):
return S.Zero
# some special values
if n == k:
return S.One
elif k == n - 1:
return binomial(n, 2)
elif k == n - 2:
return (3*n - 1)*binomial(n, 3)/4
elif k == n - 3:
return binomial(n, 2)*binomial(n, 4)
return _stirling1(n, k)
@cacheit
def _stirling1(n, k):
row = [0, 1]+[0]*(k-1) # for n = 1
for i in range(2, n+1):
for j in range(min(k,i), 0, -1):
row[j] = (i-1) * row[j] + row[j-1]
return Integer(row[k])
def _eval_stirling2(n, k):
if n == k == 0:
return S.One
if 0 in (n, k):
return S.Zero
# some special values
if n == k:
return S.One
elif k == n - 1:
return binomial(n, 2)
elif k == 1:
return S.One
elif k == 2:
return Integer(2**(n - 1) - 1)
return _stirling2(n, k)
@cacheit
def _stirling2(n, k):
row = [0, 1]+[0]*(k-1) # for n = 1
for i in range(2, n+1):
for j in range(min(k,i), 0, -1):
row[j] = j * row[j] + row[j-1]
return Integer(row[k])
def stirling(n, k, d=None, kind=2, signed=False):
r"""Return Stirling number $S(n, k)$ of the first or second (default) kind.
The sum of all Stirling numbers of the second kind for $k = 1$
through $n$ is ``bell(n)``. The recurrence relationship for these numbers
is:
.. math :: {0 \brace 0} = 1; {n \brace 0} = {0 \brace k} = 0;
.. math :: {{n+1} \brace k} = j {n \brace k} + {n \brace {k-1}}
where $j$ is:
$n$ for Stirling numbers of the first kind,
$-n$ for signed Stirling numbers of the first kind,
$k$ for Stirling numbers of the second kind.
The first kind of Stirling number counts the number of permutations of
``n`` distinct items that have ``k`` cycles; the second kind counts the
ways in which ``n`` distinct items can be partitioned into ``k`` parts.
If ``d`` is given, the "reduced Stirling number of the second kind" is
returned: $S^{d}(n, k) = S(n - d + 1, k - d + 1)$ with $n \ge k \ge d$.
(This counts the ways to partition $n$ consecutive integers into $k$
groups with no pairwise difference less than $d$. See example below.)
To obtain the signed Stirling numbers of the first kind, use keyword
``signed=True``. Using this keyword automatically sets ``kind`` to 1.
Examples
========
>>> from sympy.functions.combinatorial.numbers import stirling, bell
>>> from sympy.combinatorics import Permutation
>>> from sympy.utilities.iterables import multiset_partitions, permutations
First kind (unsigned by default):
>>> [stirling(6, i, kind=1) for i in range(7)]
[0, 120, 274, 225, 85, 15, 1]
>>> perms = list(permutations(range(4)))
>>> [sum(Permutation(p).cycles == i for p in perms) for i in range(5)]
[0, 6, 11, 6, 1]
>>> [stirling(4, i, kind=1) for i in range(5)]
[0, 6, 11, 6, 1]
First kind (signed):
>>> [stirling(4, i, signed=True) for i in range(5)]
[0, -6, 11, -6, 1]
Second kind:
>>> [stirling(10, i) for i in range(12)]
[0, 1, 511, 9330, 34105, 42525, 22827, 5880, 750, 45, 1, 0]
>>> sum(_) == bell(10)
True
>>> len(list(multiset_partitions(range(4), 2))) == stirling(4, 2)
True
Reduced second kind:
>>> from sympy import subsets, oo
>>> def delta(p):
... if len(p) == 1:
... return oo
... return min(abs(i[0] - i[1]) for i in subsets(p, 2))
>>> parts = multiset_partitions(range(5), 3)
>>> d = 2
>>> sum(1 for p in parts if all(delta(i) >= d for i in p))
7
>>> stirling(5, 3, 2)
7
See Also
========
sympy.utilities.iterables.multiset_partitions
References
==========
.. [1] https://en.wikipedia.org/wiki/Stirling_numbers_of_the_first_kind
.. [2] https://en.wikipedia.org/wiki/Stirling_numbers_of_the_second_kind
"""
# TODO: make this a class like bell()
n = as_int(n)
k = as_int(k)
if n < 0:
raise ValueError('n must be nonnegative')
if k > n:
return S.Zero
if d:
# assert k >= d
# kind is ignored -- only kind=2 is supported
return _eval_stirling2(n - d + 1, k - d + 1)
elif signed:
# kind is ignored -- only kind=1 is supported
return S.NegativeOne**(n - k)*_eval_stirling1(n, k)
if kind == 1:
return _eval_stirling1(n, k)
elif kind == 2:
return _eval_stirling2(n, k)
else:
raise ValueError('kind must be 1 or 2, not %s' % k)
@cacheit
def _nT(n, k):
"""Return the partitions of ``n`` items into ``k`` parts. This
is used by ``nT`` for the case when ``n`` is an integer."""
# really quick exits
if k > n or k < 0:
return 0
if k in (1, n):
return 1
if k == 0:
return 0
# exits that could be done below but this is quicker
if k == 2:
return n//2
d = n - k
if d <= 3:
return d
# quick exit
if 3*k >= n: # or, equivalently, 2*k >= d
# all the information needed in this case
# will be in the cache needed to calculate
# partition(d), so...
# update cache
tot = partition._partition(d)
# and correct for values not needed
if d - k > 0:
tot -= sum(_npartition[:d - k])
return tot
# regular exit
# nT(n, k) = Sum(nT(n - k, m), (m, 1, k));
# calculate needed nT(i, j) values
p = [1]*d
for i in range(2, k + 1):
for m in range(i + 1, d):
p[m] += p[m - i]
d -= 1
# if p[0] were appended to the end of p then the last
# k values of p are the nT(n, j) values for 0 < j < k in reverse
# order p[-1] = nT(n, 1), p[-2] = nT(n, 2), etc.... Instead of
# putting the 1 from p[0] there, however, it is simply added to
# the sum below which is valid for 1 < k <= n//2
return (1 + sum(p[1 - k:]))
def nT(n, k=None):
"""Return the number of ``k``-sized partitions of ``n`` items.
Possible values for ``n``:
integer - ``n`` identical items
sequence - converted to a multiset internally
multiset - {element: multiplicity}
Note: the convention for ``nT`` is different than that of ``nC`` and
``nP`` in that
here an integer indicates ``n`` *identical* items instead of a set of
length ``n``; this is in keeping with the ``partitions`` function which
treats its integer-``n`` input like a list of ``n`` 1s. One can use
``range(n)`` for ``n`` to indicate ``n`` distinct items.
If ``k`` is None then the total number of ways to partition the elements
represented in ``n`` will be returned.
Examples
========
>>> from sympy.functions.combinatorial.numbers import nT
Partitions of the given multiset:
>>> [nT('aabbc', i) for i in range(1, 7)]
[1, 8, 11, 5, 1, 0]
>>> nT('aabbc') == sum(_)
True
>>> [nT("mississippi", i) for i in range(1, 12)]
[1, 74, 609, 1521, 1768, 1224, 579, 197, 50, 9, 1]
Partitions when all items are identical:
>>> [nT(5, i) for i in range(1, 6)]
[1, 2, 2, 1, 1]
>>> nT('1'*5) == sum(_)
True
When all items are different:
>>> [nT(range(5), i) for i in range(1, 6)]
[1, 15, 25, 10, 1]
>>> nT(range(5)) == sum(_)
True
Partitions of an integer expressed as a sum of positive integers:
>>> from sympy import partition
>>> partition(4)
5
>>> nT(4, 1) + nT(4, 2) + nT(4, 3) + nT(4, 4)
5
>>> nT('1'*4)
5
See Also
========
sympy.utilities.iterables.partitions
sympy.utilities.iterables.multiset_partitions
sympy.functions.combinatorial.numbers.partition
References
==========
.. [1] http://undergraduate.csse.uwa.edu.au/units/CITS7209/partition.pdf
"""
if isinstance(n, SYMPY_INTS):
# n identical items
if k is None:
return partition(n)
if isinstance(k, SYMPY_INTS):
n = as_int(n)
k = as_int(k)
return Integer(_nT(n, k))
if not isinstance(n, _MultisetHistogram):
try:
# if n contains hashable items there is some
# quick handling that can be done
u = len(set(n))
if u <= 1:
return nT(len(n), k)
elif u == len(n):
n = range(u)
raise TypeError
except TypeError:
n = _multiset_histogram(n)
N = n[_N]
if k is None and N == 1:
return 1
if k in (1, N):
return 1
if k == 2 or N == 2 and k is None:
m, r = divmod(N, 2)
rv = sum(nC(n, i) for i in range(1, m + 1))
if not r:
rv -= nC(n, m)//2
if k is None:
rv += 1 # for k == 1
return rv
if N == n[_ITEMS]:
# all distinct
if k is None:
return bell(N)
return stirling(N, k)
m = MultisetPartitionTraverser()
if k is None:
return m.count_partitions(n[_M])
# MultisetPartitionTraverser does not have a range-limited count
# method, so need to enumerate and count
tot = 0
for discard in m.enum_range(n[_M], k-1, k):
tot += 1
return tot
#-----------------------------------------------------------------------------#
# #
# Motzkin numbers #
# #
#-----------------------------------------------------------------------------#
class motzkin(Function):
"""
The nth Motzkin number is the number
of ways of drawing non-intersecting chords
between n points on a circle (not necessarily touching
every point by a chord). The Motzkin numbers are named
after Theodore Motzkin and have diverse applications
in geometry, combinatorics and number theory.
Motzkin numbers are the integer sequence defined by the
initial terms `M_0 = 1`, `M_1 = 1` and the two-term recurrence relation
`M_n = \frac{2*n + 1}{n + 2} * M_{n-1} + \frac{3n - 3}{n + 2} * M_{n-2}`.
Examples
========
>>> from sympy import motzkin
>>> motzkin.is_motzkin(5)
False
>>> motzkin.find_motzkin_numbers_in_range(2,300)
[2, 4, 9, 21, 51, 127]
>>> motzkin.find_motzkin_numbers_in_range(2,900)
[2, 4, 9, 21, 51, 127, 323, 835]
>>> motzkin.find_first_n_motzkins(10)
[1, 1, 2, 4, 9, 21, 51, 127, 323, 835]
References
==========
.. [1] https://en.wikipedia.org/wiki/Motzkin_number
.. [2] https://mathworld.wolfram.com/MotzkinNumber.html
"""
@staticmethod
def is_motzkin(n):
try:
n = as_int(n)
except ValueError:
return False
if n > 0:
if n in (1, 2):
return True
tn1 = 1
tn = 2
i = 3
while tn < n:
a = ((2*i + 1)*tn + (3*i - 3)*tn1)/(i + 2)
i += 1
tn1 = tn
tn = a
if tn == n:
return True
else:
return False
else:
return False
@staticmethod
def find_motzkin_numbers_in_range(x, y):
if 0 <= x <= y:
motzkins = list()
if x <= 1 <= y:
motzkins.append(1)
tn1 = 1
tn = 2
i = 3
while tn <= y:
if tn >= x:
motzkins.append(tn)
a = ((2*i + 1)*tn + (3*i - 3)*tn1)/(i + 2)
i += 1
tn1 = tn
tn = int(a)
return motzkins
else:
raise ValueError('The provided range is not valid. This condition should satisfy x <= y')
@staticmethod
def find_first_n_motzkins(n):
try:
n = as_int(n)
except ValueError:
raise ValueError('The provided number must be a positive integer')
if n < 0:
raise ValueError('The provided number must be a positive integer')
motzkins = [1]
if n >= 1:
motzkins.append(1)
tn1 = 1
tn = 2
i = 3
while i <= n:
motzkins.append(tn)
a = ((2*i + 1)*tn + (3*i - 3)*tn1)/(i + 2)
i += 1
tn1 = tn
tn = int(a)
return motzkins
@staticmethod
@recurrence_memo([S.One, S.One])
def _motzkin(n, prev):
return ((2*n + 1)*prev[-1] + (3*n - 3)*prev[-2]) // (n + 2)
@classmethod
def eval(cls, n):
try:
n = as_int(n)
except ValueError:
raise ValueError('The provided number must be a positive integer')
if n < 0:
raise ValueError('The provided number must be a positive integer')
return Integer(cls._motzkin(n - 1))
def nD(i=None, brute=None, *, n=None, m=None):
"""return the number of derangements for: ``n`` unique items, ``i``
items (as a sequence or multiset), or multiplicities, ``m`` given
as a sequence or multiset.
Examples
========
>>> from sympy.utilities.iterables import generate_derangements as enum
>>> from sympy.functions.combinatorial.numbers import nD
A derangement ``d`` of sequence ``s`` has all ``d[i] != s[i]``:
>>> set([''.join(i) for i in enum('abc')])
{'bca', 'cab'}
>>> nD('abc')
2
Input as iterable or dictionary (multiset form) is accepted:
>>> assert nD([1, 2, 2, 3, 3, 3]) == nD({1: 1, 2: 2, 3: 3})
By default, a brute-force enumeration and count of multiset permutations
is only done if there are fewer than 9 elements. There may be cases when
there is high multiplicty with few unique elements that will benefit
from a brute-force enumeration, too. For this reason, the `brute`
keyword (default None) is provided. When False, the brute-force
enumeration will never be used. When True, it will always be used.
>>> nD('1111222233', brute=True)
44
For convenience, one may specify ``n`` distinct items using the
``n`` keyword:
>>> assert nD(n=3) == nD('abc') == 2
Since the number of derangments depends on the multiplicity of the
elements and not the elements themselves, it may be more convenient
to give a list or multiset of multiplicities using keyword ``m``:
>>> assert nD('abc') == nD(m=(1,1,1)) == nD(m={1:3}) == 2
"""
from sympy.integrals.integrals import integrate
from sympy.functions.elementary.exponential import exp
from sympy.functions.special.polynomials import laguerre
from sympy.abc import x
def ok(x):
if not isinstance(x, SYMPY_INTS):
raise TypeError('expecting integer values')
if x < 0:
raise ValueError('value must not be negative')
return True
if (i, n, m).count(None) != 2:
raise ValueError('enter only 1 of i, n, or m')
if i is not None:
if isinstance(i, SYMPY_INTS):
raise TypeError('items must be a list or dictionary')
if not i:
return S.Zero
if type(i) is not dict:
s = list(i)
ms = multiset(s)
elif type(i) is dict:
all(ok(_) for _ in i.values())
ms = {k: v for k, v in i.items() if v}
s = None
if not ms:
return S.Zero
N = sum(ms.values())
counts = multiset(ms.values())
nkey = len(ms)
elif n is not None:
ok(n)
if not n:
return S.Zero
return subfactorial(n)
elif m is not None:
if isinstance(m, dict):
all(ok(i) and ok(j) for i, j in m.items())
counts = {k: v for k, v in m.items() if k*v}
elif iterable(m) or isinstance(m, str):
m = list(m)
all(ok(i) for i in m)
counts = multiset([i for i in m if i])
else:
raise TypeError('expecting iterable')
if not counts:
return S.Zero
N = sum(k*v for k, v in counts.items())
nkey = sum(counts.values())
s = None
big = int(max(counts))
if big == 1: # no repetition
return subfactorial(nkey)
nval = len(counts)
if big*2 > N:
return S.Zero
if big*2 == N:
if nkey == 2 and nval == 1:
return S.One # aaabbb
if nkey - 1 == big: # one element repeated
return factorial(big) # e.g. abc part of abcddd
if N < 9 and brute is None or brute:
# for all possibilities, this was found to be faster
if s is None:
s = []
i = 0
for m, v in counts.items():
for j in range(v):
s.extend([i]*m)
i += 1
return Integer(sum(1 for i in multiset_derangements(s)))
return Integer(abs(integrate(exp(-x)*Mul(*[
laguerre(i, x)**m for i, m in counts.items()]), (x, 0, oo))))
|
78d9a32a83feca81b85e07c704da166766337507d819895c4242c38a0b9638ab | from typing import List
from functools import reduce
from sympy.core import S, sympify, Dummy, Mod
from sympy.core.cache import cacheit
from sympy.core.function import Function, ArgumentIndexError, PoleError
from sympy.core.logic import fuzzy_and
from sympy.core.numbers import Integer, pi, I
from sympy.core.relational import Eq
from sympy.external.gmpy import HAS_GMPY, gmpy
from sympy.ntheory import sieve
from sympy.polys.polytools import Poly
from math import sqrt as _sqrt
class CombinatorialFunction(Function):
"""Base class for combinatorial functions. """
def _eval_simplify(self, **kwargs):
from sympy.simplify.combsimp import combsimp
# combinatorial function with non-integer arguments is
# automatically passed to gammasimp
expr = combsimp(self)
measure = kwargs['measure']
if measure(expr) <= kwargs['ratio']*measure(self):
return expr
return self
###############################################################################
######################## FACTORIAL and MULTI-FACTORIAL ########################
###############################################################################
class factorial(CombinatorialFunction):
r"""Implementation of factorial function over nonnegative integers.
By convention (consistent with the gamma function and the binomial
coefficients), factorial of a negative integer is complex infinity.
The factorial is very important in combinatorics where it gives
the number of ways in which `n` objects can be permuted. It also
arises in calculus, probability, number theory, etc.
There is strict relation of factorial with gamma function. In
fact `n! = gamma(n+1)` for nonnegative integers. Rewrite of this
kind is very useful in case of combinatorial simplification.
Computation of the factorial is done using two algorithms. For
small arguments a precomputed look up table is used. However for bigger
input algorithm Prime-Swing is used. It is the fastest algorithm
known and computes `n!` via prime factorization of special class
of numbers, called here the 'Swing Numbers'.
Examples
========
>>> from sympy import Symbol, factorial, S
>>> n = Symbol('n', integer=True)
>>> factorial(0)
1
>>> factorial(7)
5040
>>> factorial(-2)
zoo
>>> factorial(n)
factorial(n)
>>> factorial(2*n)
factorial(2*n)
>>> factorial(S(1)/2)
factorial(1/2)
See Also
========
factorial2, RisingFactorial, FallingFactorial
"""
def fdiff(self, argindex=1):
from sympy.functions.special.gamma_functions import (gamma, polygamma)
if argindex == 1:
return gamma(self.args[0] + 1)*polygamma(0, self.args[0] + 1)
else:
raise ArgumentIndexError(self, argindex)
_small_swing = [
1, 1, 1, 3, 3, 15, 5, 35, 35, 315, 63, 693, 231, 3003, 429, 6435, 6435, 109395,
12155, 230945, 46189, 969969, 88179, 2028117, 676039, 16900975, 1300075,
35102025, 5014575, 145422675, 9694845, 300540195, 300540195
]
_small_factorials = [] # type: List[int]
@classmethod
def _swing(cls, n):
if n < 33:
return cls._small_swing[n]
else:
N, primes = int(_sqrt(n)), []
for prime in sieve.primerange(3, N + 1):
p, q = 1, n
while True:
q //= prime
if q > 0:
if q & 1 == 1:
p *= prime
else:
break
if p > 1:
primes.append(p)
for prime in sieve.primerange(N + 1, n//3 + 1):
if (n // prime) & 1 == 1:
primes.append(prime)
L_product = R_product = 1
for prime in sieve.primerange(n//2 + 1, n + 1):
L_product *= prime
for prime in primes:
R_product *= prime
return L_product*R_product
@classmethod
def _recursive(cls, n):
if n < 2:
return 1
else:
return (cls._recursive(n//2)**2)*cls._swing(n)
@classmethod
def eval(cls, n):
n = sympify(n)
if n.is_Number:
if n.is_zero:
return S.One
elif n is S.Infinity:
return S.Infinity
elif n.is_Integer:
if n.is_negative:
return S.ComplexInfinity
else:
n = n.p
if n < 20:
if not cls._small_factorials:
result = 1
for i in range(1, 20):
result *= i
cls._small_factorials.append(result)
result = cls._small_factorials[n-1]
# GMPY factorial is faster, use it when available
elif HAS_GMPY:
result = gmpy.fac(n)
else:
bits = bin(n).count('1')
result = cls._recursive(n)*2**(n - bits)
return Integer(result)
def _facmod(self, n, q):
res, N = 1, int(_sqrt(n))
# Exponent of prime p in n! is e_p(n) = [n/p] + [n/p**2] + ...
# for p > sqrt(n), e_p(n) < sqrt(n), the primes with [n/p] = m,
# occur consecutively and are grouped together in pw[m] for
# simultaneous exponentiation at a later stage
pw = [1]*N
m = 2 # to initialize the if condition below
for prime in sieve.primerange(2, n + 1):
if m > 1:
m, y = 0, n // prime
while y:
m += y
y //= prime
if m < N:
pw[m] = pw[m]*prime % q
else:
res = res*pow(prime, m, q) % q
for ex, bs in enumerate(pw):
if ex == 0 or bs == 1:
continue
if bs == 0:
return 0
res = res*pow(bs, ex, q) % q
return res
def _eval_Mod(self, q):
n = self.args[0]
if n.is_integer and n.is_nonnegative and q.is_integer:
aq = abs(q)
d = aq - n
if d.is_nonpositive:
return S.Zero
else:
isprime = aq.is_prime
if d == 1:
# Apply Wilson's theorem (if a natural number n > 1
# is a prime number, then (n-1)! = -1 mod n) and
# its inverse (if n > 4 is a composite number, then
# (n-1)! = 0 mod n)
if isprime:
return -1 % q
elif isprime is False and (aq - 6).is_nonnegative:
return S.Zero
elif n.is_Integer and q.is_Integer:
n, d, aq = map(int, (n, d, aq))
if isprime and (d - 1 < n):
fc = self._facmod(d - 1, aq)
fc = pow(fc, aq - 2, aq)
if d%2:
fc = -fc
else:
fc = self._facmod(n, aq)
return fc % q
def _eval_rewrite_as_gamma(self, n, piecewise=True, **kwargs):
from sympy.functions.special.gamma_functions import gamma
return gamma(n + 1)
def _eval_rewrite_as_Product(self, n, **kwargs):
from sympy.concrete.products import Product
if n.is_nonnegative and n.is_integer:
i = Dummy('i', integer=True)
return Product(i, (i, 1, n))
def _eval_is_integer(self):
if self.args[0].is_integer and self.args[0].is_nonnegative:
return True
def _eval_is_positive(self):
if self.args[0].is_integer and self.args[0].is_nonnegative:
return True
def _eval_is_even(self):
x = self.args[0]
if x.is_integer and x.is_nonnegative:
return (x - 2).is_nonnegative
def _eval_is_composite(self):
x = self.args[0]
if x.is_integer and x.is_nonnegative:
return (x - 3).is_nonnegative
def _eval_is_real(self):
x = self.args[0]
if x.is_nonnegative or x.is_noninteger:
return True
def _eval_as_leading_term(self, x, logx=None, cdir=0):
arg = self.args[0].as_leading_term(x)
arg0 = arg.subs(x, 0)
if arg0.is_zero:
return S.One
elif not arg0.is_infinite:
return self.func(arg)
raise PoleError("Cannot expand %s around 0" % (self))
class MultiFactorial(CombinatorialFunction):
pass
class subfactorial(CombinatorialFunction):
r"""The subfactorial counts the derangements of n items and is
defined for non-negative integers as:
.. math:: !n = \begin{cases} 1 & n = 0 \\ 0 & n = 1 \\
(n-1)(!(n-1) + !(n-2)) & n > 1 \end{cases}
It can also be written as ``int(round(n!/exp(1)))`` but the
recursive definition with caching is implemented for this function.
An interesting analytic expression is the following [2]_
.. math:: !x = \Gamma(x + 1, -1)/e
which is valid for non-negative integers `x`. The above formula
is not very useful incase of non-integers. :math:`\Gamma(x + 1, -1)` is
single-valued only for integral arguments `x`, elsewhere on the positive
real axis it has an infinite number of branches none of which are real.
References
==========
.. [1] https://en.wikipedia.org/wiki/Subfactorial
.. [2] http://mathworld.wolfram.com/Subfactorial.html
Examples
========
>>> from sympy import subfactorial
>>> from sympy.abc import n
>>> subfactorial(n + 1)
subfactorial(n + 1)
>>> subfactorial(5)
44
See Also
========
sympy.functions.combinatorial.factorials.factorial,
sympy.utilities.iterables.generate_derangements,
sympy.functions.special.gamma_functions.uppergamma
"""
@classmethod
@cacheit
def _eval(self, n):
if not n:
return S.One
elif n == 1:
return S.Zero
else:
z1, z2 = 1, 0
for i in range(2, n + 1):
z1, z2 = z2, (i - 1)*(z2 + z1)
return z2
@classmethod
def eval(cls, arg):
if arg.is_Number:
if arg.is_Integer and arg.is_nonnegative:
return cls._eval(arg)
elif arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.Infinity
def _eval_is_even(self):
if self.args[0].is_odd and self.args[0].is_nonnegative:
return True
def _eval_is_integer(self):
if self.args[0].is_integer and self.args[0].is_nonnegative:
return True
def _eval_rewrite_as_factorial(self, arg, **kwargs):
from sympy.concrete.summations import summation
i = Dummy('i')
f = S.NegativeOne**i / factorial(i)
return factorial(arg) * summation(f, (i, 0, arg))
def _eval_rewrite_as_gamma(self, arg, piecewise=True, **kwargs):
from sympy.functions.elementary.exponential import exp
from sympy.functions.special.gamma_functions import (gamma, lowergamma)
return (S.NegativeOne**(arg + 1)*exp(-I*pi*arg)*lowergamma(arg + 1, -1)
+ gamma(arg + 1))*exp(-1)
def _eval_rewrite_as_uppergamma(self, arg, **kwargs):
from sympy.functions.special.gamma_functions import uppergamma
return uppergamma(arg + 1, -1)/S.Exp1
def _eval_is_nonnegative(self):
if self.args[0].is_integer and self.args[0].is_nonnegative:
return True
def _eval_is_odd(self):
if self.args[0].is_even and self.args[0].is_nonnegative:
return True
class factorial2(CombinatorialFunction):
r"""The double factorial `n!!`, not to be confused with `(n!)!`
The double factorial is defined for nonnegative integers and for odd
negative integers as:
.. math:: n!! = \begin{cases} 1 & n = 0 \\
n(n-2)(n-4) \cdots 1 & n\ \text{positive odd} \\
n(n-2)(n-4) \cdots 2 & n\ \text{positive even} \\
(n+2)!!/(n+2) & n\ \text{negative odd} \end{cases}
References
==========
.. [1] https://en.wikipedia.org/wiki/Double_factorial
Examples
========
>>> from sympy import factorial2, var
>>> n = var('n')
>>> n
n
>>> factorial2(n + 1)
factorial2(n + 1)
>>> factorial2(5)
15
>>> factorial2(-1)
1
>>> factorial2(-5)
1/3
See Also
========
factorial, RisingFactorial, FallingFactorial
"""
@classmethod
def eval(cls, arg):
# TODO: extend this to complex numbers?
if arg.is_Number:
if not arg.is_Integer:
raise ValueError("argument must be nonnegative integer "
"or negative odd integer")
# This implementation is faster than the recursive one
# It also avoids "maximum recursion depth exceeded" runtime error
if arg.is_nonnegative:
if arg.is_even:
k = arg / 2
return 2**k * factorial(k)
return factorial(arg) / factorial2(arg - 1)
if arg.is_odd:
return arg*(S.NegativeOne)**((1 - arg)/2) / factorial2(-arg)
raise ValueError("argument must be nonnegative integer "
"or negative odd integer")
def _eval_is_even(self):
# Double factorial is even for every positive even input
n = self.args[0]
if n.is_integer:
if n.is_odd:
return False
if n.is_even:
if n.is_positive:
return True
if n.is_zero:
return False
def _eval_is_integer(self):
# Double factorial is an integer for every nonnegative input, and for
# -1 and -3
n = self.args[0]
if n.is_integer:
if (n + 1).is_nonnegative:
return True
if n.is_odd:
return (n + 3).is_nonnegative
def _eval_is_odd(self):
# Double factorial is odd for every odd input not smaller than -3, and
# for 0
n = self.args[0]
if n.is_odd:
return (n + 3).is_nonnegative
if n.is_even:
if n.is_positive:
return False
if n.is_zero:
return True
def _eval_is_positive(self):
# Double factorial is positive for every nonnegative input, and for
# every odd negative input which is of the form -1-4k for an
# nonnegative integer k
n = self.args[0]
if n.is_integer:
if (n + 1).is_nonnegative:
return True
if n.is_odd:
return ((n + 1) / 2).is_even
def _eval_rewrite_as_gamma(self, n, piecewise=True, **kwargs):
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.piecewise import Piecewise
from sympy.functions.special.gamma_functions import gamma
return 2**(n/2)*gamma(n/2 + 1) * Piecewise((1, Eq(Mod(n, 2), 0)),
(sqrt(2/pi), Eq(Mod(n, 2), 1)))
###############################################################################
######################## RISING and FALLING FACTORIALS ########################
###############################################################################
class RisingFactorial(CombinatorialFunction):
r"""
Rising factorial (also called Pochhammer symbol) is a double valued
function arising in concrete mathematics, hypergeometric functions
and series expansions. It is defined by:
.. math:: rf(x,k) = x \cdot (x+1) \cdots (x+k-1)
where `x` can be arbitrary expression and `k` is an integer. For
more information check "Concrete mathematics" by Graham, pp. 66
or visit http://mathworld.wolfram.com/RisingFactorial.html page.
When `x` is a Poly instance of degree >= 1 with a single variable,
`rf(x,k) = x(y) \cdot x(y+1) \cdots x(y+k-1)`, where `y` is the
variable of `x`. This is as described in Peter Paule, "Greatest
Factorial Factorization and Symbolic Summation", Journal of
Symbolic Computation, vol. 20, pp. 235-268, 1995.
Examples
========
>>> from sympy import rf, Poly
>>> from sympy.abc import x
>>> rf(x, 0)
1
>>> rf(1, 5)
120
>>> rf(x, 5) == x*(1 + x)*(2 + x)*(3 + x)*(4 + x)
True
>>> rf(Poly(x**3, x), 2)
Poly(x**6 + 3*x**5 + 3*x**4 + x**3, x, domain='ZZ')
Rewriting is complicated unless the relationship between
the arguments is known, but rising factorial can
be rewritten in terms of gamma, factorial and binomial
and falling factorial.
>>> from sympy import Symbol, factorial, ff, binomial, gamma
>>> n = Symbol('n', integer=True, positive=True)
>>> R = rf(n, n + 2)
>>> for i in (rf, ff, factorial, binomial, gamma):
... R.rewrite(i)
...
RisingFactorial(n, n + 2)
FallingFactorial(2*n + 1, n + 2)
factorial(2*n + 1)/factorial(n - 1)
binomial(2*n + 1, n + 2)*factorial(n + 2)
gamma(2*n + 2)/gamma(n)
See Also
========
factorial, factorial2, FallingFactorial
References
==========
.. [1] https://en.wikipedia.org/wiki/Pochhammer_symbol
"""
@classmethod
def eval(cls, x, k):
x = sympify(x)
k = sympify(k)
if x is S.NaN or k is S.NaN:
return S.NaN
elif x is S.One:
return factorial(k)
elif k.is_Integer:
if k.is_zero:
return S.One
else:
if k.is_positive:
if x is S.Infinity:
return S.Infinity
elif x is S.NegativeInfinity:
if k.is_odd:
return S.NegativeInfinity
else:
return S.Infinity
else:
if isinstance(x, Poly):
gens = x.gens
if len(gens)!= 1:
raise ValueError("rf only defined for "
"polynomials on one generator")
else:
return reduce(lambda r, i:
r*(x.shift(i)),
range(0, int(k)), 1)
else:
return reduce(lambda r, i: r*(x + i),
range(0, int(k)), 1)
else:
if x is S.Infinity:
return S.Infinity
elif x is S.NegativeInfinity:
return S.Infinity
else:
if isinstance(x, Poly):
gens = x.gens
if len(gens)!= 1:
raise ValueError("rf only defined for "
"polynomials on one generator")
else:
return 1/reduce(lambda r, i:
r*(x.shift(-i)),
range(1, abs(int(k)) + 1), 1)
else:
return 1/reduce(lambda r, i:
r*(x - i),
range(1, abs(int(k)) + 1), 1)
if k.is_integer == False:
if x.is_integer and x.is_negative:
return S.Zero
def _eval_rewrite_as_gamma(self, x, k, piecewise=True, **kwargs):
from sympy.functions.elementary.piecewise import Piecewise
from sympy.functions.special.gamma_functions import gamma
if not piecewise:
if (x <= 0) == True:
return S.NegativeOne**k*gamma(1 - x) / gamma(-k - x + 1)
return gamma(x + k) / gamma(x)
return Piecewise(
(gamma(x + k) / gamma(x), x > 0),
(S.NegativeOne**k*gamma(1 - x) / gamma(-k - x + 1), True))
def _eval_rewrite_as_FallingFactorial(self, x, k, **kwargs):
return FallingFactorial(x + k - 1, k)
def _eval_rewrite_as_factorial(self, x, k, **kwargs):
from sympy.functions.elementary.piecewise import Piecewise
if x.is_integer and k.is_integer:
return Piecewise(
(factorial(k + x - 1)/factorial(x - 1), x > 0),
(S.NegativeOne**k*factorial(-x)/factorial(-k - x), True))
def _eval_rewrite_as_binomial(self, x, k, **kwargs):
if k.is_integer:
return factorial(k) * binomial(x + k - 1, k)
def _eval_rewrite_as_tractable(self, x, k, limitvar=None, **kwargs):
from sympy.functions.special.gamma_functions import gamma
if limitvar:
k_lim = k.subs(limitvar, S.Infinity)
if k_lim is S.Infinity:
return (gamma(x + k).rewrite('tractable', deep=True) / gamma(x))
elif k_lim is S.NegativeInfinity:
return (S.NegativeOne**k*gamma(1 - x) / gamma(-k - x + 1).rewrite('tractable', deep=True))
return self.rewrite(gamma).rewrite('tractable', deep=True)
def _eval_is_integer(self):
return fuzzy_and((self.args[0].is_integer, self.args[1].is_integer,
self.args[1].is_nonnegative))
class FallingFactorial(CombinatorialFunction):
r"""
Falling factorial (related to rising factorial) is a double valued
function arising in concrete mathematics, hypergeometric functions
and series expansions. It is defined by
.. math:: ff(x,k) = x \cdot (x-1) \cdots (x-k+1)
where `x` can be arbitrary expression and `k` is an integer. For
more information check "Concrete mathematics" by Graham, pp. 66
or visit http://mathworld.wolfram.com/FallingFactorial.html page.
When `x` is a Poly instance of degree >= 1 with single variable,
`ff(x,k) = x(y) \cdot x(y-1) \cdots x(y-k+1)`, where `y` is the
variable of `x`. This is as described in Peter Paule, "Greatest
Factorial Factorization and Symbolic Summation", Journal of
Symbolic Computation, vol. 20, pp. 235-268, 1995.
>>> from sympy import ff, Poly, Symbol
>>> from sympy.abc import x
>>> n = Symbol('n', integer=True)
>>> ff(x, 0)
1
>>> ff(5, 5)
120
>>> ff(x, 5) == x*(x - 1)*(x - 2)*(x - 3)*(x - 4)
True
>>> ff(Poly(x**2, x), 2)
Poly(x**4 - 2*x**3 + x**2, x, domain='ZZ')
>>> ff(n, n)
factorial(n)
Rewriting is complicated unless the relationship between
the arguments is known, but falling factorial can
be rewritten in terms of gamma, factorial and binomial
and rising factorial.
>>> from sympy import factorial, rf, gamma, binomial, Symbol
>>> n = Symbol('n', integer=True, positive=True)
>>> F = ff(n, n - 2)
>>> for i in (rf, ff, factorial, binomial, gamma):
... F.rewrite(i)
...
RisingFactorial(3, n - 2)
FallingFactorial(n, n - 2)
factorial(n)/2
binomial(n, n - 2)*factorial(n - 2)
gamma(n + 1)/2
See Also
========
factorial, factorial2, RisingFactorial
References
==========
.. [1] http://mathworld.wolfram.com/FallingFactorial.html
"""
@classmethod
def eval(cls, x, k):
x = sympify(x)
k = sympify(k)
if x is S.NaN or k is S.NaN:
return S.NaN
elif k.is_integer and x == k:
return factorial(x)
elif k.is_Integer:
if k.is_zero:
return S.One
else:
if k.is_positive:
if x is S.Infinity:
return S.Infinity
elif x is S.NegativeInfinity:
if k.is_odd:
return S.NegativeInfinity
else:
return S.Infinity
else:
if isinstance(x, Poly):
gens = x.gens
if len(gens)!= 1:
raise ValueError("ff only defined for "
"polynomials on one generator")
else:
return reduce(lambda r, i:
r*(x.shift(-i)),
range(0, int(k)), 1)
else:
return reduce(lambda r, i: r*(x - i),
range(0, int(k)), 1)
else:
if x is S.Infinity:
return S.Infinity
elif x is S.NegativeInfinity:
return S.Infinity
else:
if isinstance(x, Poly):
gens = x.gens
if len(gens)!= 1:
raise ValueError("rf only defined for "
"polynomials on one generator")
else:
return 1/reduce(lambda r, i:
r*(x.shift(i)),
range(1, abs(int(k)) + 1), 1)
else:
return 1/reduce(lambda r, i: r*(x + i),
range(1, abs(int(k)) + 1), 1)
def _eval_rewrite_as_gamma(self, x, k, piecewise=True, **kwargs):
from sympy.functions.elementary.piecewise import Piecewise
from sympy.functions.special.gamma_functions import gamma
if not piecewise:
if (x < 0) == True:
return S.NegativeOne**k*gamma(k - x) / gamma(-x)
return gamma(x + 1) / gamma(x - k + 1)
return Piecewise(
(gamma(x + 1) / gamma(x - k + 1), x >= 0),
(S.NegativeOne**k*gamma(k - x) / gamma(-x), True))
def _eval_rewrite_as_RisingFactorial(self, x, k, **kwargs):
return rf(x - k + 1, k)
def _eval_rewrite_as_binomial(self, x, k, **kwargs):
if k.is_integer:
return factorial(k) * binomial(x, k)
def _eval_rewrite_as_factorial(self, x, k, **kwargs):
from sympy.functions.elementary.piecewise import Piecewise
if x.is_integer and k.is_integer:
return Piecewise(
(factorial(x)/factorial(-k + x), x >= 0),
(S.NegativeOne**k*factorial(k - x - 1)/factorial(-x - 1), True))
def _eval_rewrite_as_tractable(self, x, k, limitvar=None, **kwargs):
from sympy.functions.special.gamma_functions import gamma
if limitvar:
k_lim = k.subs(limitvar, S.Infinity)
if k_lim is S.Infinity:
return (S.NegativeOne**k*gamma(k - x).rewrite('tractable', deep=True) / gamma(-x))
elif k_lim is S.NegativeInfinity:
return (gamma(x + 1) / gamma(x - k + 1).rewrite('tractable', deep=True))
return self.rewrite(gamma).rewrite('tractable', deep=True)
def _eval_is_integer(self):
return fuzzy_and((self.args[0].is_integer, self.args[1].is_integer,
self.args[1].is_nonnegative))
rf = RisingFactorial
ff = FallingFactorial
###############################################################################
########################### BINOMIAL COEFFICIENTS #############################
###############################################################################
class binomial(CombinatorialFunction):
r"""Implementation of the binomial coefficient. It can be defined
in two ways depending on its desired interpretation:
.. math:: \binom{n}{k} = \frac{n!}{k!(n-k)!}\ \text{or}\
\binom{n}{k} = \frac{ff(n, k)}{k!}
First, in a strict combinatorial sense it defines the
number of ways we can choose `k` elements from a set of
`n` elements. In this case both arguments are nonnegative
integers and binomial is computed using an efficient
algorithm based on prime factorization.
The other definition is generalization for arbitrary `n`,
however `k` must also be nonnegative. This case is very
useful when evaluating summations.
For the sake of convenience for negative integer `k` this function
will return zero no matter what valued is the other argument.
To expand the binomial when `n` is a symbol, use either
``expand_func()`` or ``expand(func=True)``. The former will keep
the polynomial in factored form while the latter will expand the
polynomial itself. See examples for details.
Examples
========
>>> from sympy import Symbol, Rational, binomial, expand_func
>>> n = Symbol('n', integer=True, positive=True)
>>> binomial(15, 8)
6435
>>> binomial(n, -1)
0
Rows of Pascal's triangle can be generated with the binomial function:
>>> for N in range(8):
... print([binomial(N, i) for i in range(N + 1)])
...
[1]
[1, 1]
[1, 2, 1]
[1, 3, 3, 1]
[1, 4, 6, 4, 1]
[1, 5, 10, 10, 5, 1]
[1, 6, 15, 20, 15, 6, 1]
[1, 7, 21, 35, 35, 21, 7, 1]
As can a given diagonal, e.g. the 4th diagonal:
>>> N = -4
>>> [binomial(N, i) for i in range(1 - N)]
[1, -4, 10, -20, 35]
>>> binomial(Rational(5, 4), 3)
-5/128
>>> binomial(Rational(-5, 4), 3)
-195/128
>>> binomial(n, 3)
binomial(n, 3)
>>> binomial(n, 3).expand(func=True)
n**3/6 - n**2/2 + n/3
>>> expand_func(binomial(n, 3))
n*(n - 2)*(n - 1)/6
References
==========
.. [1] https://www.johndcook.com/blog/binomial_coefficients/
"""
def fdiff(self, argindex=1):
from sympy.functions.special.gamma_functions import polygamma
if argindex == 1:
# http://functions.wolfram.com/GammaBetaErf/Binomial/20/01/01/
n, k = self.args
return binomial(n, k)*(polygamma(0, n + 1) - \
polygamma(0, n - k + 1))
elif argindex == 2:
# http://functions.wolfram.com/GammaBetaErf/Binomial/20/01/02/
n, k = self.args
return binomial(n, k)*(polygamma(0, n - k + 1) - \
polygamma(0, k + 1))
else:
raise ArgumentIndexError(self, argindex)
@classmethod
def _eval(self, n, k):
# n.is_Number and k.is_Integer and k != 1 and n != k
if k.is_Integer:
if n.is_Integer and n >= 0:
n, k = int(n), int(k)
if k > n:
return S.Zero
elif k > n // 2:
k = n - k
if HAS_GMPY:
return Integer(gmpy.bincoef(n, k))
d, result = n - k, 1
for i in range(1, k + 1):
d += 1
result = result * d // i
return Integer(result)
else:
d, result = n - k, 1
for i in range(1, k + 1):
d += 1
result *= d
result /= i
return result
@classmethod
def eval(cls, n, k):
n, k = map(sympify, (n, k))
d = n - k
n_nonneg, n_isint = n.is_nonnegative, n.is_integer
if k.is_zero or ((n_nonneg or n_isint is False)
and d.is_zero):
return S.One
if (k - 1).is_zero or ((n_nonneg or n_isint is False)
and (d - 1).is_zero):
return n
if k.is_integer:
if k.is_negative or (n_nonneg and n_isint and d.is_negative):
return S.Zero
elif n.is_number:
res = cls._eval(n, k)
return res.expand(basic=True) if res else res
elif n_nonneg is False and n_isint:
# a special case when binomial evaluates to complex infinity
return S.ComplexInfinity
elif k.is_number:
from sympy.functions.special.gamma_functions import gamma
return gamma(n + 1)/(gamma(k + 1)*gamma(n - k + 1))
def _eval_Mod(self, q):
n, k = self.args
if any(x.is_integer is False for x in (n, k, q)):
raise ValueError("Integers expected for binomial Mod")
if all(x.is_Integer for x in (n, k, q)):
n, k = map(int, (n, k))
aq, res = abs(q), 1
# handle negative integers k or n
if k < 0:
return S.Zero
if n < 0:
n = -n + k - 1
res = -1 if k%2 else 1
# non negative integers k and n
if k > n:
return S.Zero
isprime = aq.is_prime
aq = int(aq)
if isprime:
if aq < n:
# use Lucas Theorem
N, K = n, k
while N or K:
res = res*binomial(N % aq, K % aq) % aq
N, K = N // aq, K // aq
else:
# use Factorial Modulo
d = n - k
if k > d:
k, d = d, k
kf = 1
for i in range(2, k + 1):
kf = kf*i % aq
df = kf
for i in range(k + 1, d + 1):
df = df*i % aq
res *= df
for i in range(d + 1, n + 1):
res = res*i % aq
res *= pow(kf*df % aq, aq - 2, aq)
res %= aq
else:
# Binomial Factorization is performed by calculating the
# exponents of primes <= n in `n! /(k! (n - k)!)`,
# for non-negative integers n and k. As the exponent of
# prime in n! is e_p(n) = [n/p] + [n/p**2] + ...
# the exponent of prime in binomial(n, k) would be
# e_p(n) - e_p(k) - e_p(n - k)
M = int(_sqrt(n))
for prime in sieve.primerange(2, n + 1):
if prime > n - k:
res = res*prime % aq
elif prime > n // 2:
continue
elif prime > M:
if n % prime < k % prime:
res = res*prime % aq
else:
N, K = n, k
exp = a = 0
while N > 0:
a = int((N % prime) < (K % prime + a))
N, K = N // prime, K // prime
exp += a
if exp > 0:
res *= pow(prime, exp, aq)
res %= aq
return S(res % q)
def _eval_expand_func(self, **hints):
"""
Function to expand binomial(n, k) when m is positive integer
Also,
n is self.args[0] and k is self.args[1] while using binomial(n, k)
"""
n = self.args[0]
if n.is_Number:
return binomial(*self.args)
k = self.args[1]
if (n-k).is_Integer:
k = n - k
if k.is_Integer:
if k.is_zero:
return S.One
elif k.is_negative:
return S.Zero
else:
n, result = self.args[0], 1
for i in range(1, k + 1):
result *= n - k + i
result /= i
return result
else:
return binomial(*self.args)
def _eval_rewrite_as_factorial(self, n, k, **kwargs):
return factorial(n)/(factorial(k)*factorial(n - k))
def _eval_rewrite_as_gamma(self, n, k, piecewise=True, **kwargs):
from sympy.functions.special.gamma_functions import gamma
return gamma(n + 1)/(gamma(k + 1)*gamma(n - k + 1))
def _eval_rewrite_as_tractable(self, n, k, limitvar=None, **kwargs):
return self._eval_rewrite_as_gamma(n, k).rewrite('tractable')
def _eval_rewrite_as_FallingFactorial(self, n, k, **kwargs):
if k.is_integer:
return ff(n, k) / factorial(k)
def _eval_is_integer(self):
n, k = self.args
if n.is_integer and k.is_integer:
return True
elif k.is_integer is False:
return False
def _eval_is_nonnegative(self):
n, k = self.args
if n.is_integer and k.is_integer:
if n.is_nonnegative or k.is_negative or k.is_even:
return True
elif k.is_even is False:
return False
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.functions.special.gamma_functions import gamma
return self.rewrite(gamma)._eval_as_leading_term(x, logx=logx, cdir=cdir)
|
f5ef6fd705008447bca804fa42b8d27e42043ab421dfca59126e102939925565 | from typing import Tuple as tTuple
from sympy.core.add import Add
from sympy.core.basic import sympify, cacheit
from sympy.core.expr import Expr
from sympy.core.function import Function, ArgumentIndexError, PoleError, expand_mul
from sympy.core.logic import fuzzy_not, fuzzy_or, FuzzyBool, fuzzy_and
from sympy.core.numbers import igcdex, Rational, pi, Integer
from sympy.core.relational import Ne
from sympy.core.singleton import S
from sympy.core.symbol import Symbol, Dummy
from sympy.functions.combinatorial.factorials import factorial, RisingFactorial
from sympy.functions.elementary.exponential import log, exp
from sympy.functions.elementary.integers import floor
from sympy.functions.elementary.hyperbolic import (acoth, asinh, atanh, cosh,
coth, HyperbolicFunction, sinh, tanh)
from sympy.functions.elementary.miscellaneous import sqrt, Min, Max
from sympy.functions.elementary.piecewise import Piecewise
from sympy.sets.sets import FiniteSet
from sympy.utilities.iterables import numbered_symbols
###############################################################################
########################## TRIGONOMETRIC FUNCTIONS ############################
###############################################################################
class TrigonometricFunction(Function):
"""Base class for trigonometric functions. """
unbranched = True
_singularities = (S.ComplexInfinity,)
def _eval_is_rational(self):
s = self.func(*self.args)
if s.func == self.func:
if s.args[0].is_rational and fuzzy_not(s.args[0].is_zero):
return False
else:
return s.is_rational
def _eval_is_algebraic(self):
s = self.func(*self.args)
if s.func == self.func:
if fuzzy_not(self.args[0].is_zero) and self.args[0].is_algebraic:
return False
pi_coeff = _pi_coeff(self.args[0])
if pi_coeff is not None and pi_coeff.is_rational:
return True
else:
return s.is_algebraic
def _eval_expand_complex(self, deep=True, **hints):
re_part, im_part = self.as_real_imag(deep=deep, **hints)
return re_part + im_part*S.ImaginaryUnit
def _as_real_imag(self, deep=True, **hints):
if self.args[0].is_extended_real:
if deep:
hints['complex'] = False
return (self.args[0].expand(deep, **hints), S.Zero)
else:
return (self.args[0], S.Zero)
if deep:
re, im = self.args[0].expand(deep, **hints).as_real_imag()
else:
re, im = self.args[0].as_real_imag()
return (re, im)
def _period(self, general_period, symbol=None):
f = expand_mul(self.args[0])
if symbol is None:
symbol = tuple(f.free_symbols)[0]
if not f.has(symbol):
return S.Zero
if f == symbol:
return general_period
if symbol in f.free_symbols:
if f.is_Mul:
g, h = f.as_independent(symbol)
if h == symbol:
return general_period/abs(g)
if f.is_Add:
a, h = f.as_independent(symbol)
g, h = h.as_independent(symbol, as_Add=False)
if h == symbol:
return general_period/abs(g)
raise NotImplementedError("Use the periodicity function instead.")
def _peeloff_pi(arg):
"""
Split ARG into two parts, a "rest" and a multiple of pi.
This assumes ARG to be an Add.
The multiple of pi returned in the second position is always a Rational.
Examples
========
>>> from sympy.functions.elementary.trigonometric import _peeloff_pi as peel
>>> from sympy import pi
>>> from sympy.abc import x, y
>>> peel(x + pi/2)
(x, 1/2)
>>> peel(x + 2*pi/3 + pi*y)
(x + pi*y + pi/6, 1/2)
"""
pi_coeff = S.Zero
rest_terms = []
for a in Add.make_args(arg):
K = a.coeff(S.Pi)
if K and K.is_rational:
pi_coeff += K
else:
rest_terms.append(a)
if pi_coeff is S.Zero:
return arg, S.Zero
m1 = (pi_coeff % S.Half)
m2 = pi_coeff - m1
if m2.is_integer or ((2*m2).is_integer and m2.is_even is False):
return Add(*(rest_terms + [m1*pi])), m2
return arg, S.Zero
def _pi_coeff(arg, cycles=1):
"""
When arg is a Number times pi (e.g. 3*pi/2) then return the Number
normalized to be in the range [0, 2], else None.
When an even multiple of pi is encountered, if it is multiplying
something with known parity then the multiple is returned as 0 otherwise
as 2.
Examples
========
>>> from sympy.functions.elementary.trigonometric import _pi_coeff as coeff
>>> from sympy import pi, Dummy
>>> from sympy.abc import x
>>> coeff(3*x*pi)
3*x
>>> coeff(11*pi/7)
11/7
>>> coeff(-11*pi/7)
3/7
>>> coeff(4*pi)
0
>>> coeff(5*pi)
1
>>> coeff(5.0*pi)
1
>>> coeff(5.5*pi)
3/2
>>> coeff(2 + pi)
>>> coeff(2*Dummy(integer=True)*pi)
2
>>> coeff(2*Dummy(even=True)*pi)
0
"""
arg = sympify(arg)
if arg is S.Pi:
return S.One
elif not arg:
return S.Zero
elif arg.is_Mul:
cx = arg.coeff(S.Pi)
if cx:
c, x = cx.as_coeff_Mul() # pi is not included as coeff
if c.is_Float:
# recast exact binary fractions to Rationals
f = abs(c) % 1
if f != 0:
p = -int(round(log(f, 2).evalf()))
m = 2**p
cm = c*m
i = int(cm)
if i == cm:
c = Rational(i, m)
cx = c*x
else:
c = Rational(int(c))
cx = c*x
if x.is_integer:
c2 = c % 2
if c2 == 1:
return x
elif not c2:
if x.is_even is not None: # known parity
return S.Zero
return Integer(2)
else:
return c2*x
return cx
elif arg.is_zero:
return S.Zero
class sin(TrigonometricFunction):
"""
The sine function.
Returns the sine of x (measured in radians).
Explanation
===========
This function will evaluate automatically in the
case x/pi is some rational number [4]_. For example,
if x is a multiple of pi, pi/2, pi/3, pi/4 and pi/6.
Examples
========
>>> from sympy import sin, pi
>>> from sympy.abc import x
>>> sin(x**2).diff(x)
2*x*cos(x**2)
>>> sin(1).diff(x)
0
>>> sin(pi)
0
>>> sin(pi/2)
1
>>> sin(pi/6)
1/2
>>> sin(pi/12)
-sqrt(2)/4 + sqrt(6)/4
See Also
========
csc, cos, sec, tan, cot
asin, acsc, acos, asec, atan, acot, atan2
References
==========
.. [1] https://en.wikipedia.org/wiki/Trigonometric_functions
.. [2] http://dlmf.nist.gov/4.14
.. [3] http://functions.wolfram.com/ElementaryFunctions/Sin
.. [4] http://mathworld.wolfram.com/TrigonometryAngles.html
"""
def period(self, symbol=None):
return self._period(2*pi, symbol)
def fdiff(self, argindex=1):
if argindex == 1:
return cos(self.args[0])
else:
raise ArgumentIndexError(self, argindex)
@classmethod
def eval(cls, arg):
from sympy.calculus import AccumBounds
from sympy.sets.setexpr import SetExpr
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg.is_zero:
return S.Zero
elif arg in (S.Infinity, S.NegativeInfinity):
return AccumBounds(-1, 1)
if arg is S.ComplexInfinity:
return S.NaN
if isinstance(arg, AccumBounds):
min, max = arg.min, arg.max
d = floor(min/(2*S.Pi))
if min is not S.NegativeInfinity:
min = min - d*2*S.Pi
if max is not S.Infinity:
max = max - d*2*S.Pi
if AccumBounds(min, max).intersection(FiniteSet(S.Pi/2, S.Pi*Rational(5, 2))) \
is not S.EmptySet and \
AccumBounds(min, max).intersection(FiniteSet(S.Pi*Rational(3, 2),
S.Pi*Rational(7, 2))) is not S.EmptySet:
return AccumBounds(-1, 1)
elif AccumBounds(min, max).intersection(FiniteSet(S.Pi/2, S.Pi*Rational(5, 2))) \
is not S.EmptySet:
return AccumBounds(Min(sin(min), sin(max)), 1)
elif AccumBounds(min, max).intersection(FiniteSet(S.Pi*Rational(3, 2), S.Pi*Rational(8, 2))) \
is not S.EmptySet:
return AccumBounds(-1, Max(sin(min), sin(max)))
else:
return AccumBounds(Min(sin(min), sin(max)),
Max(sin(min), sin(max)))
elif isinstance(arg, SetExpr):
return arg._eval_func(cls)
if arg.could_extract_minus_sign():
return -cls(-arg)
i_coeff = arg.as_coefficient(S.ImaginaryUnit)
if i_coeff is not None:
return S.ImaginaryUnit*sinh(i_coeff)
pi_coeff = _pi_coeff(arg)
if pi_coeff is not None:
if pi_coeff.is_integer:
return S.Zero
if (2*pi_coeff).is_integer:
# is_even-case handled above as then pi_coeff.is_integer,
# so check if known to be not even
if pi_coeff.is_even is False:
return S.NegativeOne**(pi_coeff - S.Half)
if not pi_coeff.is_Rational:
narg = pi_coeff*S.Pi
if narg != arg:
return cls(narg)
return None
# https://github.com/sympy/sympy/issues/6048
# transform a sine to a cosine, to avoid redundant code
if pi_coeff.is_Rational:
x = pi_coeff % 2
if x > 1:
return -cls((x % 1)*S.Pi)
if 2*x > 1:
return cls((1 - x)*S.Pi)
narg = ((pi_coeff + Rational(3, 2)) % 2)*S.Pi
result = cos(narg)
if not isinstance(result, cos):
return result
if pi_coeff*S.Pi != arg:
return cls(pi_coeff*S.Pi)
return None
if arg.is_Add:
x, m = _peeloff_pi(arg)
if m:
m = m*S.Pi
return sin(m)*cos(x) + cos(m)*sin(x)
if arg.is_zero:
return S.Zero
if isinstance(arg, asin):
return arg.args[0]
if isinstance(arg, atan):
x = arg.args[0]
return x/sqrt(1 + x**2)
if isinstance(arg, atan2):
y, x = arg.args
return y/sqrt(x**2 + y**2)
if isinstance(arg, acos):
x = arg.args[0]
return sqrt(1 - x**2)
if isinstance(arg, acot):
x = arg.args[0]
return 1/(sqrt(1 + 1/x**2)*x)
if isinstance(arg, acsc):
x = arg.args[0]
return 1/x
if isinstance(arg, asec):
x = arg.args[0]
return sqrt(1 - 1/x**2)
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
if n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
if len(previous_terms) > 2:
p = previous_terms[-2]
return -p*x**2/(n*(n - 1))
else:
return S.NegativeOne**(n//2)*x**n/factorial(n)
def _eval_nseries(self, x, n, logx, cdir=0):
arg = self.args[0]
if logx is not None:
arg = arg.subs(log(x), logx)
if arg.subs(x, 0).has(S.NaN, S.ComplexInfinity):
raise PoleError("Cannot expand %s around 0" % (self))
return Function._eval_nseries(self, x, n=n, logx=logx, cdir=cdir)
def _eval_rewrite_as_exp(self, arg, **kwargs):
I = S.ImaginaryUnit
if isinstance(arg, (TrigonometricFunction, HyperbolicFunction)):
arg = arg.func(arg.args[0]).rewrite(exp)
return (exp(arg*I) - exp(-arg*I))/(2*I)
def _eval_rewrite_as_Pow(self, arg, **kwargs):
if isinstance(arg, log):
I = S.ImaginaryUnit
x = arg.args[0]
return I*x**-I/2 - I*x**I /2
def _eval_rewrite_as_cos(self, arg, **kwargs):
return cos(arg - S.Pi/2, evaluate=False)
def _eval_rewrite_as_tan(self, arg, **kwargs):
tan_half = tan(S.Half*arg)
return 2*tan_half/(1 + tan_half**2)
def _eval_rewrite_as_sincos(self, arg, **kwargs):
return sin(arg)*cos(arg)/cos(arg)
def _eval_rewrite_as_cot(self, arg, **kwargs):
cot_half = cot(S.Half*arg)
return 2*cot_half/(1 + cot_half**2)
def _eval_rewrite_as_pow(self, arg, **kwargs):
return self.rewrite(cos).rewrite(pow)
def _eval_rewrite_as_sqrt(self, arg, **kwargs):
return self.rewrite(cos).rewrite(sqrt)
def _eval_rewrite_as_csc(self, arg, **kwargs):
return 1/csc(arg)
def _eval_rewrite_as_sec(self, arg, **kwargs):
return 1/sec(arg - S.Pi/2, evaluate=False)
def _eval_rewrite_as_sinc(self, arg, **kwargs):
return arg*sinc(arg)
def _eval_conjugate(self):
return self.func(self.args[0].conjugate())
def as_real_imag(self, deep=True, **hints):
re, im = self._as_real_imag(deep=deep, **hints)
return (sin(re)*cosh(im), cos(re)*sinh(im))
def _eval_expand_trig(self, **hints):
from sympy.functions.special.polynomials import chebyshevt, chebyshevu
arg = self.args[0]
x = None
if arg.is_Add: # TODO, implement more if deep stuff here
# TODO: Do this more efficiently for more than two terms
x, y = arg.as_two_terms()
sx = sin(x, evaluate=False)._eval_expand_trig()
sy = sin(y, evaluate=False)._eval_expand_trig()
cx = cos(x, evaluate=False)._eval_expand_trig()
cy = cos(y, evaluate=False)._eval_expand_trig()
return sx*cy + sy*cx
elif arg.is_Mul:
n, x = arg.as_coeff_Mul(rational=True)
if n.is_Integer: # n will be positive because of .eval
# canonicalization
# See http://mathworld.wolfram.com/Multiple-AngleFormulas.html
if n.is_odd:
return S.NegativeOne**((n - 1)/2)*chebyshevt(n, sin(x))
else:
return expand_mul(S.NegativeOne**(n/2 - 1)*cos(x)*
chebyshevu(n - 1, sin(x)), deep=False)
pi_coeff = _pi_coeff(arg)
if pi_coeff is not None:
if pi_coeff.is_Rational:
return self.rewrite(sqrt)
return sin(arg)
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.functions.elementary.complexes import re
from sympy.calculus.util import AccumBounds
arg = self.args[0]
x0 = arg.subs(x, 0).cancel()
n = x0/S.Pi
if n.is_integer:
lt = (arg - n*S.Pi).as_leading_term(x)
return (S.NegativeOne**n)*lt
if x0 is S.ComplexInfinity:
x0 = arg.limit(x, 0, dir='-' if re(cdir).is_negative else '+')
if x0 in [S.Infinity, S.NegativeInfinity]:
return AccumBounds(-1, 1)
return self.func(x0) if x0.is_finite else self
def _eval_is_extended_real(self):
if self.args[0].is_extended_real:
return True
def _eval_is_finite(self):
arg = self.args[0]
if arg.is_extended_real:
return True
def _eval_is_zero(self):
rest, pi_mult = _peeloff_pi(self.args[0])
if rest.is_zero:
return pi_mult.is_integer
def _eval_is_complex(self):
if self.args[0].is_extended_real \
or self.args[0].is_complex:
return True
class cos(TrigonometricFunction):
"""
The cosine function.
Returns the cosine of x (measured in radians).
Explanation
===========
See :func:`sin` for notes about automatic evaluation.
Examples
========
>>> from sympy import cos, pi
>>> from sympy.abc import x
>>> cos(x**2).diff(x)
-2*x*sin(x**2)
>>> cos(1).diff(x)
0
>>> cos(pi)
-1
>>> cos(pi/2)
0
>>> cos(2*pi/3)
-1/2
>>> cos(pi/12)
sqrt(2)/4 + sqrt(6)/4
See Also
========
sin, csc, sec, tan, cot
asin, acsc, acos, asec, atan, acot, atan2
References
==========
.. [1] https://en.wikipedia.org/wiki/Trigonometric_functions
.. [2] http://dlmf.nist.gov/4.14
.. [3] http://functions.wolfram.com/ElementaryFunctions/Cos
"""
def period(self, symbol=None):
return self._period(2*pi, symbol)
def fdiff(self, argindex=1):
if argindex == 1:
return -sin(self.args[0])
else:
raise ArgumentIndexError(self, argindex)
@classmethod
def eval(cls, arg):
from sympy.functions.special.polynomials import chebyshevt
from sympy.calculus.util import AccumBounds
from sympy.sets.setexpr import SetExpr
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg.is_zero:
return S.One
elif arg in (S.Infinity, S.NegativeInfinity):
# In this case it is better to return AccumBounds(-1, 1)
# rather than returning S.NaN, since AccumBounds(-1, 1)
# preserves the information that sin(oo) is between
# -1 and 1, where S.NaN does not do that.
return AccumBounds(-1, 1)
if arg is S.ComplexInfinity:
return S.NaN
if isinstance(arg, AccumBounds):
return sin(arg + S.Pi/2)
elif isinstance(arg, SetExpr):
return arg._eval_func(cls)
if arg.is_extended_real and arg.is_finite is False:
return AccumBounds(-1, 1)
if arg.could_extract_minus_sign():
return cls(-arg)
i_coeff = arg.as_coefficient(S.ImaginaryUnit)
if i_coeff is not None:
return cosh(i_coeff)
pi_coeff = _pi_coeff(arg)
if pi_coeff is not None:
if pi_coeff.is_integer:
return (S.NegativeOne)**pi_coeff
if (2*pi_coeff).is_integer:
# is_even-case handled above as then pi_coeff.is_integer,
# so check if known to be not even
if pi_coeff.is_even is False:
return S.Zero
if not pi_coeff.is_Rational:
narg = pi_coeff*S.Pi
if narg != arg:
return cls(narg)
return None
# cosine formula #####################
# https://github.com/sympy/sympy/issues/6048
# explicit calculations are performed for
# cos(k pi/n) for n = 8,10,12,15,20,24,30,40,60,120
# Some other exact values like cos(k pi/240) can be
# calculated using a partial-fraction decomposition
# by calling cos( X ).rewrite(sqrt)
cst_table_some = {
3: S.Half,
5: (sqrt(5) + 1)/4,
}
if pi_coeff.is_Rational:
q = pi_coeff.q
p = pi_coeff.p % (2*q)
if p > q:
narg = (pi_coeff - 1)*S.Pi
return -cls(narg)
if 2*p > q:
narg = (1 - pi_coeff)*S.Pi
return -cls(narg)
# If nested sqrt's are worse than un-evaluation
# you can require q to be in (1, 2, 3, 4, 6, 12)
# q <= 12, q=15, q=20, q=24, q=30, q=40, q=60, q=120 return
# expressions with 2 or fewer sqrt nestings.
table2 = {
12: (3, 4),
20: (4, 5),
30: (5, 6),
15: (6, 10),
24: (6, 8),
40: (8, 10),
60: (20, 30),
120: (40, 60)
}
if q in table2:
a, b = p*S.Pi/table2[q][0], p*S.Pi/table2[q][1]
nvala, nvalb = cls(a), cls(b)
if None in (nvala, nvalb):
return None
return nvala*nvalb + cls(S.Pi/2 - a)*cls(S.Pi/2 - b)
if q > 12:
return None
if q in cst_table_some:
cts = cst_table_some[pi_coeff.q]
return chebyshevt(pi_coeff.p, cts).expand()
if 0 == q % 2:
narg = (pi_coeff*2)*S.Pi
nval = cls(narg)
if None == nval:
return None
x = (2*pi_coeff + 1)/2
sign_cos = (-1)**((-1 if x < 0 else 1)*int(abs(x)))
return sign_cos*sqrt( (1 + nval)/2 )
return None
if arg.is_Add:
x, m = _peeloff_pi(arg)
if m:
m = m*S.Pi
return cos(m)*cos(x) - sin(m)*sin(x)
if arg.is_zero:
return S.One
if isinstance(arg, acos):
return arg.args[0]
if isinstance(arg, atan):
x = arg.args[0]
return 1/sqrt(1 + x**2)
if isinstance(arg, atan2):
y, x = arg.args
return x/sqrt(x**2 + y**2)
if isinstance(arg, asin):
x = arg.args[0]
return sqrt(1 - x ** 2)
if isinstance(arg, acot):
x = arg.args[0]
return 1/sqrt(1 + 1/x**2)
if isinstance(arg, acsc):
x = arg.args[0]
return sqrt(1 - 1/x**2)
if isinstance(arg, asec):
x = arg.args[0]
return 1/x
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
if n < 0 or n % 2 == 1:
return S.Zero
else:
x = sympify(x)
if len(previous_terms) > 2:
p = previous_terms[-2]
return -p*x**2/(n*(n - 1))
else:
return S.NegativeOne**(n//2)*x**n/factorial(n)
def _eval_nseries(self, x, n, logx, cdir=0):
arg = self.args[0]
if logx is not None:
arg = arg.subs(log(x), logx)
if arg.subs(x, 0).has(S.NaN, S.ComplexInfinity):
raise PoleError("Cannot expand %s around 0" % (self))
return Function._eval_nseries(self, x, n=n, logx=logx, cdir=cdir)
def _eval_rewrite_as_exp(self, arg, **kwargs):
I = S.ImaginaryUnit
if isinstance(arg, (TrigonometricFunction, HyperbolicFunction)):
arg = arg.func(arg.args[0]).rewrite(exp)
return (exp(arg*I) + exp(-arg*I))/2
def _eval_rewrite_as_Pow(self, arg, **kwargs):
if isinstance(arg, log):
I = S.ImaginaryUnit
x = arg.args[0]
return x**I/2 + x**-I/2
def _eval_rewrite_as_sin(self, arg, **kwargs):
return sin(arg + S.Pi/2, evaluate=False)
def _eval_rewrite_as_tan(self, arg, **kwargs):
tan_half = tan(S.Half*arg)**2
return (1 - tan_half)/(1 + tan_half)
def _eval_rewrite_as_sincos(self, arg, **kwargs):
return sin(arg)*cos(arg)/sin(arg)
def _eval_rewrite_as_cot(self, arg, **kwargs):
cot_half = cot(S.Half*arg)**2
return (cot_half - 1)/(cot_half + 1)
def _eval_rewrite_as_pow(self, arg, **kwargs):
return self._eval_rewrite_as_sqrt(arg)
def _eval_rewrite_as_sqrt(self, arg, **kwargs):
from sympy.functions.special.polynomials import chebyshevt
def migcdex(x):
# recursive calcuation of gcd and linear combination
# for a sequence of integers.
# Given (x1, x2, x3)
# Returns (y1, y1, y3, g)
# such that g is the gcd and x1*y1+x2*y2+x3*y3 - g = 0
# Note, that this is only one such linear combination.
if len(x) == 1:
return (1, x[0])
if len(x) == 2:
return igcdex(x[0], x[-1])
g = migcdex(x[1:])
u, v, h = igcdex(x[0], g[-1])
return tuple([u] + [v*i for i in g[0:-1] ] + [h])
def ipartfrac(r, factors=None):
from sympy.ntheory import factorint
if isinstance(r, int):
return r
if not isinstance(r, Rational):
raise TypeError("r is not rational")
n = r.q
if 2 > r.q*r.q:
return r.q
if None == factors:
a = [n//x**y for x, y in factorint(r.q).items()]
else:
a = [n//x for x in factors]
if len(a) == 1:
return [ r ]
h = migcdex(a)
ans = [ r.p*Rational(i*j, r.q) for i, j in zip(h[:-1], a) ]
assert r == sum(ans)
return ans
pi_coeff = _pi_coeff(arg)
if pi_coeff is None:
return None
if pi_coeff.is_integer:
# it was unevaluated
return self.func(pi_coeff*S.Pi)
if not pi_coeff.is_Rational:
return None
def _cospi257():
""" Express cos(pi/257) explicitly as a function of radicals
Based upon the equations in
http://math.stackexchange.com/questions/516142/how-does-cos2-pi-257-look-like-in-real-radicals
See also http://www.susqu.edu/brakke/constructions/257-gon.m.txt
"""
def f1(a, b):
return (a + sqrt(a**2 + b))/2, (a - sqrt(a**2 + b))/2
def f2(a, b):
return (a - sqrt(a**2 + b))/2
t1, t2 = f1(-1, 256)
z1, z3 = f1(t1, 64)
z2, z4 = f1(t2, 64)
y1, y5 = f1(z1, 4*(5 + t1 + 2*z1))
y6, y2 = f1(z2, 4*(5 + t2 + 2*z2))
y3, y7 = f1(z3, 4*(5 + t1 + 2*z3))
y8, y4 = f1(z4, 4*(5 + t2 + 2*z4))
x1, x9 = f1(y1, -4*(t1 + y1 + y3 + 2*y6))
x2, x10 = f1(y2, -4*(t2 + y2 + y4 + 2*y7))
x3, x11 = f1(y3, -4*(t1 + y3 + y5 + 2*y8))
x4, x12 = f1(y4, -4*(t2 + y4 + y6 + 2*y1))
x5, x13 = f1(y5, -4*(t1 + y5 + y7 + 2*y2))
x6, x14 = f1(y6, -4*(t2 + y6 + y8 + 2*y3))
x15, x7 = f1(y7, -4*(t1 + y7 + y1 + 2*y4))
x8, x16 = f1(y8, -4*(t2 + y8 + y2 + 2*y5))
v1 = f2(x1, -4*(x1 + x2 + x3 + x6))
v2 = f2(x2, -4*(x2 + x3 + x4 + x7))
v3 = f2(x8, -4*(x8 + x9 + x10 + x13))
v4 = f2(x9, -4*(x9 + x10 + x11 + x14))
v5 = f2(x10, -4*(x10 + x11 + x12 + x15))
v6 = f2(x16, -4*(x16 + x1 + x2 + x5))
u1 = -f2(-v1, -4*(v2 + v3))
u2 = -f2(-v4, -4*(v5 + v6))
w1 = -2*f2(-u1, -4*u2)
return sqrt(sqrt(2)*sqrt(w1 + 4)/8 + S.Half)
cst_table_some = {
3: S.Half,
5: (sqrt(5) + 1)/4,
17: sqrt((15 + sqrt(17))/32 + sqrt(2)*(sqrt(17 - sqrt(17)) +
sqrt(sqrt(2)*(-8*sqrt(17 + sqrt(17)) - (1 - sqrt(17))
*sqrt(17 - sqrt(17))) + 6*sqrt(17) + 34))/32),
257: _cospi257()
# 65537 is the only other known Fermat prime and the very
# large expression is intentionally omitted from SymPy; see
# http://www.susqu.edu/brakke/constructions/65537-gon.m.txt
}
def _fermatCoords(n):
# if n can be factored in terms of Fermat primes with
# multiplicity of each being 1, return those primes, else
# False
primes = []
for p_i in cst_table_some:
quotient, remainder = divmod(n, p_i)
if remainder == 0:
n = quotient
primes.append(p_i)
if n == 1:
return tuple(primes)
return False
if pi_coeff.q in cst_table_some:
rv = chebyshevt(pi_coeff.p, cst_table_some[pi_coeff.q])
if pi_coeff.q < 257:
rv = rv.expand()
return rv
if not pi_coeff.q % 2: # recursively remove factors of 2
pico2 = pi_coeff*2
nval = cos(pico2*S.Pi).rewrite(sqrt)
x = (pico2 + 1)/2
sign_cos = -1 if int(x) % 2 else 1
return sign_cos*sqrt( (1 + nval)/2 )
FC = _fermatCoords(pi_coeff.q)
if FC:
decomp = ipartfrac(pi_coeff, FC)
X = [(x[1], x[0]*S.Pi) for x in zip(decomp, numbered_symbols('z'))]
pcls = cos(sum([x[0] for x in X]))._eval_expand_trig().subs(X)
return pcls.rewrite(sqrt)
else:
decomp = ipartfrac(pi_coeff)
X = [(x[1], x[0]*S.Pi) for x in zip(decomp, numbered_symbols('z'))]
pcls = cos(sum([x[0] for x in X]))._eval_expand_trig().subs(X)
return pcls
def _eval_rewrite_as_sec(self, arg, **kwargs):
return 1/sec(arg)
def _eval_rewrite_as_csc(self, arg, **kwargs):
return 1/sec(arg).rewrite(csc)
def _eval_conjugate(self):
return self.func(self.args[0].conjugate())
def as_real_imag(self, deep=True, **hints):
re, im = self._as_real_imag(deep=deep, **hints)
return (cos(re)*cosh(im), -sin(re)*sinh(im))
def _eval_expand_trig(self, **hints):
from sympy.functions.special.polynomials import chebyshevt
arg = self.args[0]
x = None
if arg.is_Add: # TODO: Do this more efficiently for more than two terms
x, y = arg.as_two_terms()
sx = sin(x, evaluate=False)._eval_expand_trig()
sy = sin(y, evaluate=False)._eval_expand_trig()
cx = cos(x, evaluate=False)._eval_expand_trig()
cy = cos(y, evaluate=False)._eval_expand_trig()
return cx*cy - sx*sy
elif arg.is_Mul:
coeff, terms = arg.as_coeff_Mul(rational=True)
if coeff.is_Integer:
return chebyshevt(coeff, cos(terms))
pi_coeff = _pi_coeff(arg)
if pi_coeff is not None:
if pi_coeff.is_Rational:
return self.rewrite(sqrt)
return cos(arg)
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.functions.elementary.complexes import re
from sympy.calculus.util import AccumBounds
arg = self.args[0]
x0 = arg.subs(x, 0).cancel()
n = (x0 + S.Pi/2)/S.Pi
if n.is_integer:
lt = (arg - n*S.Pi + S.Pi/2).as_leading_term(x)
return (S.NegativeOne**n)*lt
if x0 is S.ComplexInfinity:
x0 = arg.limit(x, 0, dir='-' if re(cdir).is_negative else '+')
if x0 in [S.Infinity, S.NegativeInfinity]:
return AccumBounds(-1, 1)
return self.func(x0) if x0.is_finite else self
def _eval_is_extended_real(self):
if self.args[0].is_extended_real:
return True
def _eval_is_finite(self):
arg = self.args[0]
if arg.is_extended_real:
return True
def _eval_is_complex(self):
if self.args[0].is_extended_real \
or self.args[0].is_complex:
return True
def _eval_is_zero(self):
rest, pi_mult = _peeloff_pi(self.args[0])
if pi_mult:
return fuzzy_and([(pi_mult - S.Half).is_integer, rest.is_zero])
else:
return rest.is_zero
class tan(TrigonometricFunction):
"""
The tangent function.
Returns the tangent of x (measured in radians).
Explanation
===========
See :func:`sin` for notes about automatic evaluation.
Examples
========
>>> from sympy import tan, pi
>>> from sympy.abc import x
>>> tan(x**2).diff(x)
2*x*(tan(x**2)**2 + 1)
>>> tan(1).diff(x)
0
>>> tan(pi/8).expand()
-1 + sqrt(2)
See Also
========
sin, csc, cos, sec, cot
asin, acsc, acos, asec, atan, acot, atan2
References
==========
.. [1] https://en.wikipedia.org/wiki/Trigonometric_functions
.. [2] http://dlmf.nist.gov/4.14
.. [3] http://functions.wolfram.com/ElementaryFunctions/Tan
"""
def period(self, symbol=None):
return self._period(pi, symbol)
def fdiff(self, argindex=1):
if argindex == 1:
return S.One + self**2
else:
raise ArgumentIndexError(self, argindex)
def inverse(self, argindex=1):
"""
Returns the inverse of this function.
"""
return atan
@classmethod
def eval(cls, arg):
from sympy.calculus.util import AccumBounds
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg.is_zero:
return S.Zero
elif arg in (S.Infinity, S.NegativeInfinity):
return AccumBounds(S.NegativeInfinity, S.Infinity)
if arg is S.ComplexInfinity:
return S.NaN
if isinstance(arg, AccumBounds):
min, max = arg.min, arg.max
d = floor(min/S.Pi)
if min is not S.NegativeInfinity:
min = min - d*S.Pi
if max is not S.Infinity:
max = max - d*S.Pi
if AccumBounds(min, max).intersection(FiniteSet(S.Pi/2, S.Pi*Rational(3, 2))):
return AccumBounds(S.NegativeInfinity, S.Infinity)
else:
return AccumBounds(tan(min), tan(max))
if arg.could_extract_minus_sign():
return -cls(-arg)
i_coeff = arg.as_coefficient(S.ImaginaryUnit)
if i_coeff is not None:
return S.ImaginaryUnit*tanh(i_coeff)
pi_coeff = _pi_coeff(arg, 2)
if pi_coeff is not None:
if pi_coeff.is_integer:
return S.Zero
if not pi_coeff.is_Rational:
narg = pi_coeff*S.Pi
if narg != arg:
return cls(narg)
return None
if pi_coeff.is_Rational:
q = pi_coeff.q
p = pi_coeff.p % q
# ensure simplified results are returned for n*pi/5, n*pi/10
table10 = {
1: sqrt(1 - 2*sqrt(5)/5),
2: sqrt(5 - 2*sqrt(5)),
3: sqrt(1 + 2*sqrt(5)/5),
4: sqrt(5 + 2*sqrt(5))
}
if q in (5, 10):
n = 10*p/q
if n > 5:
n = 10 - n
return -table10[n]
else:
return table10[n]
if not pi_coeff.q % 2:
narg = pi_coeff*S.Pi*2
cresult, sresult = cos(narg), cos(narg - S.Pi/2)
if not isinstance(cresult, cos) \
and not isinstance(sresult, cos):
if sresult == 0:
return S.ComplexInfinity
return 1/sresult - cresult/sresult
table2 = {
12: (3, 4),
20: (4, 5),
30: (5, 6),
15: (6, 10),
24: (6, 8),
40: (8, 10),
60: (20, 30),
120: (40, 60)
}
if q in table2:
nvala, nvalb = cls(p*S.Pi/table2[q][0]), cls(p*S.Pi/table2[q][1])
if None in (nvala, nvalb):
return None
return (nvala - nvalb)/(1 + nvala*nvalb)
narg = ((pi_coeff + S.Half) % 1 - S.Half)*S.Pi
# see cos() to specify which expressions should be
# expanded automatically in terms of radicals
cresult, sresult = cos(narg), cos(narg - S.Pi/2)
if not isinstance(cresult, cos) \
and not isinstance(sresult, cos):
if cresult == 0:
return S.ComplexInfinity
return (sresult/cresult)
if narg != arg:
return cls(narg)
if arg.is_Add:
x, m = _peeloff_pi(arg)
if m:
tanm = tan(m*S.Pi)
if tanm is S.ComplexInfinity:
return -cot(x)
else: # tanm == 0
return tan(x)
if arg.is_zero:
return S.Zero
if isinstance(arg, atan):
return arg.args[0]
if isinstance(arg, atan2):
y, x = arg.args
return y/x
if isinstance(arg, asin):
x = arg.args[0]
return x/sqrt(1 - x**2)
if isinstance(arg, acos):
x = arg.args[0]
return sqrt(1 - x**2)/x
if isinstance(arg, acot):
x = arg.args[0]
return 1/x
if isinstance(arg, acsc):
x = arg.args[0]
return 1/(sqrt(1 - 1/x**2)*x)
if isinstance(arg, asec):
x = arg.args[0]
return sqrt(1 - 1/x**2)*x
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
from sympy.functions.combinatorial.numbers import bernoulli
if n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
a, b = ((n - 1)//2), 2**(n + 1)
B = bernoulli(n + 1)
F = factorial(n + 1)
return S.NegativeOne**a*b*(b - 1)*B/F*x**n
def _eval_nseries(self, x, n, logx, cdir=0):
i = self.args[0].limit(x, 0)*2/S.Pi
if i and i.is_Integer:
return self.rewrite(cos)._eval_nseries(x, n=n, logx=logx)
return Function._eval_nseries(self, x, n=n, logx=logx)
def _eval_rewrite_as_Pow(self, arg, **kwargs):
if isinstance(arg, log):
I = S.ImaginaryUnit
x = arg.args[0]
return I*(x**-I - x**I)/(x**-I + x**I)
def _eval_conjugate(self):
return self.func(self.args[0].conjugate())
def as_real_imag(self, deep=True, **hints):
re, im = self._as_real_imag(deep=deep, **hints)
if im:
denom = cos(2*re) + cosh(2*im)
return (sin(2*re)/denom, sinh(2*im)/denom)
else:
return (self.func(re), S.Zero)
def _eval_expand_trig(self, **hints):
from sympy.functions.elementary.complexes import (im, re)
arg = self.args[0]
x = None
if arg.is_Add:
from sympy.polys.specialpolys import symmetric_poly
n = len(arg.args)
TX = []
for x in arg.args:
tx = tan(x, evaluate=False)._eval_expand_trig()
TX.append(tx)
Yg = numbered_symbols('Y')
Y = [ next(Yg) for i in range(n) ]
p = [0, 0]
for i in range(n + 1):
p[1 - i % 2] += symmetric_poly(i, Y)*(-1)**((i % 4)//2)
return (p[0]/p[1]).subs(list(zip(Y, TX)))
elif arg.is_Mul:
coeff, terms = arg.as_coeff_Mul(rational=True)
if coeff.is_Integer and coeff > 1:
I = S.ImaginaryUnit
z = Symbol('dummy', real=True)
P = ((1 + I*z)**coeff).expand()
return (im(P)/re(P)).subs([(z, tan(terms))])
return tan(arg)
def _eval_rewrite_as_exp(self, arg, **kwargs):
I = S.ImaginaryUnit
if isinstance(arg, (TrigonometricFunction, HyperbolicFunction)):
arg = arg.func(arg.args[0]).rewrite(exp)
neg_exp, pos_exp = exp(-arg*I), exp(arg*I)
return I*(neg_exp - pos_exp)/(neg_exp + pos_exp)
def _eval_rewrite_as_sin(self, x, **kwargs):
return 2*sin(x)**2/sin(2*x)
def _eval_rewrite_as_cos(self, x, **kwargs):
return cos(x - S.Pi/2, evaluate=False)/cos(x)
def _eval_rewrite_as_sincos(self, arg, **kwargs):
return sin(arg)/cos(arg)
def _eval_rewrite_as_cot(self, arg, **kwargs):
return 1/cot(arg)
def _eval_rewrite_as_sec(self, arg, **kwargs):
sin_in_sec_form = sin(arg).rewrite(sec)
cos_in_sec_form = cos(arg).rewrite(sec)
return sin_in_sec_form/cos_in_sec_form
def _eval_rewrite_as_csc(self, arg, **kwargs):
sin_in_csc_form = sin(arg).rewrite(csc)
cos_in_csc_form = cos(arg).rewrite(csc)
return sin_in_csc_form/cos_in_csc_form
def _eval_rewrite_as_pow(self, arg, **kwargs):
y = self.rewrite(cos).rewrite(pow)
if y.has(cos):
return None
return y
def _eval_rewrite_as_sqrt(self, arg, **kwargs):
y = self.rewrite(cos).rewrite(sqrt)
if y.has(cos):
return None
return y
def _eval_as_leading_term(self, x, logx=None, cdir=0):
arg = self.args[0]
x0 = arg.subs(x, 0).cancel()
n = 2*x0/S.Pi
if n.is_integer:
lt = (arg - n*S.Pi/2).as_leading_term(x)
return lt if n.is_even else -1/lt
return self.func(x0) if x0.is_finite else self
def _eval_is_extended_real(self):
# FIXME: currently tan(pi/2) return zoo
return self.args[0].is_extended_real
def _eval_is_real(self):
arg = self.args[0]
if arg.is_real and (arg/pi - S.Half).is_integer is False:
return True
def _eval_is_finite(self):
arg = self.args[0]
if arg.is_real and (arg/pi - S.Half).is_integer is False:
return True
if arg.is_imaginary:
return True
def _eval_is_zero(self):
rest, pi_mult = _peeloff_pi(self.args[0])
if rest.is_zero:
return pi_mult.is_integer
def _eval_is_complex(self):
arg = self.args[0]
if arg.is_real and (arg/pi - S.Half).is_integer is False:
return True
class cot(TrigonometricFunction):
"""
The cotangent function.
Returns the cotangent of x (measured in radians).
Explanation
===========
See :func:`sin` for notes about automatic evaluation.
Examples
========
>>> from sympy import cot, pi
>>> from sympy.abc import x
>>> cot(x**2).diff(x)
2*x*(-cot(x**2)**2 - 1)
>>> cot(1).diff(x)
0
>>> cot(pi/12)
sqrt(3) + 2
See Also
========
sin, csc, cos, sec, tan
asin, acsc, acos, asec, atan, acot, atan2
References
==========
.. [1] https://en.wikipedia.org/wiki/Trigonometric_functions
.. [2] http://dlmf.nist.gov/4.14
.. [3] http://functions.wolfram.com/ElementaryFunctions/Cot
"""
def period(self, symbol=None):
return self._period(pi, symbol)
def fdiff(self, argindex=1):
if argindex == 1:
return S.NegativeOne - self**2
else:
raise ArgumentIndexError(self, argindex)
def inverse(self, argindex=1):
"""
Returns the inverse of this function.
"""
return acot
@classmethod
def eval(cls, arg):
from sympy.calculus.util import AccumBounds
if arg.is_Number:
if arg is S.NaN:
return S.NaN
if arg.is_zero:
return S.ComplexInfinity
if arg is S.ComplexInfinity:
return S.NaN
if isinstance(arg, AccumBounds):
return -tan(arg + S.Pi/2)
if arg.could_extract_minus_sign():
return -cls(-arg)
i_coeff = arg.as_coefficient(S.ImaginaryUnit)
if i_coeff is not None:
return -S.ImaginaryUnit*coth(i_coeff)
pi_coeff = _pi_coeff(arg, 2)
if pi_coeff is not None:
if pi_coeff.is_integer:
return S.ComplexInfinity
if not pi_coeff.is_Rational:
narg = pi_coeff*S.Pi
if narg != arg:
return cls(narg)
return None
if pi_coeff.is_Rational:
if pi_coeff.q in (5, 10):
return tan(S.Pi/2 - arg)
if pi_coeff.q > 2 and not pi_coeff.q % 2:
narg = pi_coeff*S.Pi*2
cresult, sresult = cos(narg), cos(narg - S.Pi/2)
if not isinstance(cresult, cos) \
and not isinstance(sresult, cos):
return 1/sresult + cresult/sresult
table2 = {
12: (3, 4),
20: (4, 5),
30: (5, 6),
15: (6, 10),
24: (6, 8),
40: (8, 10),
60: (20, 30),
120: (40, 60)
}
q = pi_coeff.q
p = pi_coeff.p % q
if q in table2:
nvala, nvalb = cls(p*S.Pi/table2[q][0]), cls(p*S.Pi/table2[q][1])
if None in (nvala, nvalb):
return None
return (1 + nvala*nvalb)/(nvalb - nvala)
narg = (((pi_coeff + S.Half) % 1) - S.Half)*S.Pi
# see cos() to specify which expressions should be
# expanded automatically in terms of radicals
cresult, sresult = cos(narg), cos(narg - S.Pi/2)
if not isinstance(cresult, cos) \
and not isinstance(sresult, cos):
if sresult == 0:
return S.ComplexInfinity
return cresult/sresult
if narg != arg:
return cls(narg)
if arg.is_Add:
x, m = _peeloff_pi(arg)
if m:
cotm = cot(m*S.Pi)
if cotm is S.ComplexInfinity:
return cot(x)
else: # cotm == 0
return -tan(x)
if arg.is_zero:
return S.ComplexInfinity
if isinstance(arg, acot):
return arg.args[0]
if isinstance(arg, atan):
x = arg.args[0]
return 1/x
if isinstance(arg, atan2):
y, x = arg.args
return x/y
if isinstance(arg, asin):
x = arg.args[0]
return sqrt(1 - x**2)/x
if isinstance(arg, acos):
x = arg.args[0]
return x/sqrt(1 - x**2)
if isinstance(arg, acsc):
x = arg.args[0]
return sqrt(1 - 1/x**2)*x
if isinstance(arg, asec):
x = arg.args[0]
return 1/(sqrt(1 - 1/x**2)*x)
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
from sympy.functions.combinatorial.numbers import bernoulli
if n == 0:
return 1/sympify(x)
elif n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
B = bernoulli(n + 1)
F = factorial(n + 1)
return S.NegativeOne**((n + 1)//2)*2**(n + 1)*B/F*x**n
def _eval_nseries(self, x, n, logx, cdir=0):
i = self.args[0].limit(x, 0)/S.Pi
if i and i.is_Integer:
return self.rewrite(cos)._eval_nseries(x, n=n, logx=logx)
return self.rewrite(tan)._eval_nseries(x, n=n, logx=logx)
def _eval_conjugate(self):
return self.func(self.args[0].conjugate())
def as_real_imag(self, deep=True, **hints):
re, im = self._as_real_imag(deep=deep, **hints)
if im:
denom = cos(2*re) - cosh(2*im)
return (-sin(2*re)/denom, sinh(2*im)/denom)
else:
return (self.func(re), S.Zero)
def _eval_rewrite_as_exp(self, arg, **kwargs):
I = S.ImaginaryUnit
if isinstance(arg, (TrigonometricFunction, HyperbolicFunction)):
arg = arg.func(arg.args[0]).rewrite(exp)
neg_exp, pos_exp = exp(-arg*I), exp(arg*I)
return I*(pos_exp + neg_exp)/(pos_exp - neg_exp)
def _eval_rewrite_as_Pow(self, arg, **kwargs):
if isinstance(arg, log):
I = S.ImaginaryUnit
x = arg.args[0]
return -I*(x**-I + x**I)/(x**-I - x**I)
def _eval_rewrite_as_sin(self, x, **kwargs):
return sin(2*x)/(2*(sin(x)**2))
def _eval_rewrite_as_cos(self, x, **kwargs):
return cos(x)/cos(x - S.Pi/2, evaluate=False)
def _eval_rewrite_as_sincos(self, arg, **kwargs):
return cos(arg)/sin(arg)
def _eval_rewrite_as_tan(self, arg, **kwargs):
return 1/tan(arg)
def _eval_rewrite_as_sec(self, arg, **kwargs):
cos_in_sec_form = cos(arg).rewrite(sec)
sin_in_sec_form = sin(arg).rewrite(sec)
return cos_in_sec_form/sin_in_sec_form
def _eval_rewrite_as_csc(self, arg, **kwargs):
cos_in_csc_form = cos(arg).rewrite(csc)
sin_in_csc_form = sin(arg).rewrite(csc)
return cos_in_csc_form/sin_in_csc_form
def _eval_rewrite_as_pow(self, arg, **kwargs):
y = self.rewrite(cos).rewrite(pow)
if y.has(cos):
return None
return y
def _eval_rewrite_as_sqrt(self, arg, **kwargs):
y = self.rewrite(cos).rewrite(sqrt)
if y.has(cos):
return None
return y
def _eval_as_leading_term(self, x, logx=None, cdir=0):
arg = self.args[0]
x0 = arg.subs(x, 0).cancel()
n = 2*x0/S.Pi
if n.is_integer:
lt = (arg - n*S.Pi/2).as_leading_term(x)
return 1/lt if n.is_even else -lt
return self.func(x0) if x0.is_finite else self
def _eval_is_extended_real(self):
return self.args[0].is_extended_real
def _eval_expand_trig(self, **hints):
from sympy.functions.elementary.complexes import (im, re)
arg = self.args[0]
x = None
if arg.is_Add:
from sympy.polys.specialpolys import symmetric_poly
n = len(arg.args)
CX = []
for x in arg.args:
cx = cot(x, evaluate=False)._eval_expand_trig()
CX.append(cx)
Yg = numbered_symbols('Y')
Y = [ next(Yg) for i in range(n) ]
p = [0, 0]
for i in range(n, -1, -1):
p[(n - i) % 2] += symmetric_poly(i, Y)*(-1)**(((n - i) % 4)//2)
return (p[0]/p[1]).subs(list(zip(Y, CX)))
elif arg.is_Mul:
coeff, terms = arg.as_coeff_Mul(rational=True)
if coeff.is_Integer and coeff > 1:
I = S.ImaginaryUnit
z = Symbol('dummy', real=True)
P = ((z + I)**coeff).expand()
return (re(P)/im(P)).subs([(z, cot(terms))])
return cot(arg) # XXX sec and csc return 1/cos and 1/sin
def _eval_is_finite(self):
arg = self.args[0]
if arg.is_real and (arg/pi).is_integer is False:
return True
if arg.is_imaginary:
return True
def _eval_is_real(self):
arg = self.args[0]
if arg.is_real and (arg/pi).is_integer is False:
return True
def _eval_is_complex(self):
arg = self.args[0]
if arg.is_real and (arg/pi).is_integer is False:
return True
def _eval_is_zero(self):
rest, pimult = _peeloff_pi(self.args[0])
if pimult and rest.is_zero:
return (pimult - S.Half).is_integer
def _eval_subs(self, old, new):
arg = self.args[0]
argnew = arg.subs(old, new)
if arg != argnew and (argnew/S.Pi).is_integer:
return S.ComplexInfinity
return cot(argnew)
class ReciprocalTrigonometricFunction(TrigonometricFunction):
"""Base class for reciprocal functions of trigonometric functions. """
_reciprocal_of = None # mandatory, to be defined in subclass
_singularities = (S.ComplexInfinity,)
# _is_even and _is_odd are used for correct evaluation of csc(-x), sec(-x)
# TODO refactor into TrigonometricFunction common parts of
# trigonometric functions eval() like even/odd, func(x+2*k*pi), etc.
# optional, to be defined in subclasses:
_is_even = None # type: FuzzyBool
_is_odd = None # type: FuzzyBool
@classmethod
def eval(cls, arg):
if arg.could_extract_minus_sign():
if cls._is_even:
return cls(-arg)
if cls._is_odd:
return -cls(-arg)
pi_coeff = _pi_coeff(arg)
if (pi_coeff is not None
and not (2*pi_coeff).is_integer
and pi_coeff.is_Rational):
q = pi_coeff.q
p = pi_coeff.p % (2*q)
if p > q:
narg = (pi_coeff - 1)*S.Pi
return -cls(narg)
if 2*p > q:
narg = (1 - pi_coeff)*S.Pi
if cls._is_odd:
return cls(narg)
elif cls._is_even:
return -cls(narg)
if hasattr(arg, 'inverse') and arg.inverse() == cls:
return arg.args[0]
t = cls._reciprocal_of.eval(arg)
if t is None:
return t
elif any(isinstance(i, cos) for i in (t, -t)):
return (1/t).rewrite(sec)
elif any(isinstance(i, sin) for i in (t, -t)):
return (1/t).rewrite(csc)
else:
return 1/t
def _call_reciprocal(self, method_name, *args, **kwargs):
# Calls method_name on _reciprocal_of
o = self._reciprocal_of(self.args[0])
return getattr(o, method_name)(*args, **kwargs)
def _calculate_reciprocal(self, method_name, *args, **kwargs):
# If calling method_name on _reciprocal_of returns a value != None
# then return the reciprocal of that value
t = self._call_reciprocal(method_name, *args, **kwargs)
return 1/t if t is not None else t
def _rewrite_reciprocal(self, method_name, arg):
# Special handling for rewrite functions. If reciprocal rewrite returns
# unmodified expression, then return None
t = self._call_reciprocal(method_name, arg)
if t is not None and t != self._reciprocal_of(arg):
return 1/t
def _period(self, symbol):
f = expand_mul(self.args[0])
return self._reciprocal_of(f).period(symbol)
def fdiff(self, argindex=1):
return -self._calculate_reciprocal("fdiff", argindex)/self**2
def _eval_rewrite_as_exp(self, arg, **kwargs):
return self._rewrite_reciprocal("_eval_rewrite_as_exp", arg)
def _eval_rewrite_as_Pow(self, arg, **kwargs):
return self._rewrite_reciprocal("_eval_rewrite_as_Pow", arg)
def _eval_rewrite_as_sin(self, arg, **kwargs):
return self._rewrite_reciprocal("_eval_rewrite_as_sin", arg)
def _eval_rewrite_as_cos(self, arg, **kwargs):
return self._rewrite_reciprocal("_eval_rewrite_as_cos", arg)
def _eval_rewrite_as_tan(self, arg, **kwargs):
return self._rewrite_reciprocal("_eval_rewrite_as_tan", arg)
def _eval_rewrite_as_pow(self, arg, **kwargs):
return self._rewrite_reciprocal("_eval_rewrite_as_pow", arg)
def _eval_rewrite_as_sqrt(self, arg, **kwargs):
return self._rewrite_reciprocal("_eval_rewrite_as_sqrt", arg)
def _eval_conjugate(self):
return self.func(self.args[0].conjugate())
def as_real_imag(self, deep=True, **hints):
return (1/self._reciprocal_of(self.args[0])).as_real_imag(deep,
**hints)
def _eval_expand_trig(self, **hints):
return self._calculate_reciprocal("_eval_expand_trig", **hints)
def _eval_is_extended_real(self):
return self._reciprocal_of(self.args[0])._eval_is_extended_real()
def _eval_as_leading_term(self, x, logx=None, cdir=0):
return (1/self._reciprocal_of(self.args[0]))._eval_as_leading_term(x)
def _eval_is_finite(self):
return (1/self._reciprocal_of(self.args[0])).is_finite
def _eval_nseries(self, x, n, logx, cdir=0):
return (1/self._reciprocal_of(self.args[0]))._eval_nseries(x, n, logx)
class sec(ReciprocalTrigonometricFunction):
"""
The secant function.
Returns the secant of x (measured in radians).
Explanation
===========
See :func:`sin` for notes about automatic evaluation.
Examples
========
>>> from sympy import sec
>>> from sympy.abc import x
>>> sec(x**2).diff(x)
2*x*tan(x**2)*sec(x**2)
>>> sec(1).diff(x)
0
See Also
========
sin, csc, cos, tan, cot
asin, acsc, acos, asec, atan, acot, atan2
References
==========
.. [1] https://en.wikipedia.org/wiki/Trigonometric_functions
.. [2] http://dlmf.nist.gov/4.14
.. [3] http://functions.wolfram.com/ElementaryFunctions/Sec
"""
_reciprocal_of = cos
_is_even = True
def period(self, symbol=None):
return self._period(symbol)
def _eval_rewrite_as_cot(self, arg, **kwargs):
cot_half_sq = cot(arg/2)**2
return (cot_half_sq + 1)/(cot_half_sq - 1)
def _eval_rewrite_as_cos(self, arg, **kwargs):
return (1/cos(arg))
def _eval_rewrite_as_sincos(self, arg, **kwargs):
return sin(arg)/(cos(arg)*sin(arg))
def _eval_rewrite_as_sin(self, arg, **kwargs):
return (1/cos(arg).rewrite(sin))
def _eval_rewrite_as_tan(self, arg, **kwargs):
return (1/cos(arg).rewrite(tan))
def _eval_rewrite_as_csc(self, arg, **kwargs):
return csc(pi/2 - arg, evaluate=False)
def fdiff(self, argindex=1):
if argindex == 1:
return tan(self.args[0])*sec(self.args[0])
else:
raise ArgumentIndexError(self, argindex)
def _eval_is_complex(self):
arg = self.args[0]
if arg.is_complex and (arg/pi - S.Half).is_integer is False:
return True
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
# Reference Formula:
# http://functions.wolfram.com/ElementaryFunctions/Sec/06/01/02/01/
from sympy.functions.combinatorial.numbers import euler
if n < 0 or n % 2 == 1:
return S.Zero
else:
x = sympify(x)
k = n//2
return S.NegativeOne**k*euler(2*k)/factorial(2*k)*x**(2*k)
def _eval_as_leading_term(self, x, logx=None, cdir=0):
arg = self.args[0]
x0 = arg.subs(x, 0).cancel()
n = (x0 + S.Pi/2)/S.Pi
if n.is_integer:
lt = (arg - n*S.Pi + S.Pi/2).as_leading_term(x)
return (S.NegativeOne**n)/lt
return self.func(x0)
class csc(ReciprocalTrigonometricFunction):
"""
The cosecant function.
Returns the cosecant of x (measured in radians).
Explanation
===========
See :func:`sin` for notes about automatic evaluation.
Examples
========
>>> from sympy import csc
>>> from sympy.abc import x
>>> csc(x**2).diff(x)
-2*x*cot(x**2)*csc(x**2)
>>> csc(1).diff(x)
0
See Also
========
sin, cos, sec, tan, cot
asin, acsc, acos, asec, atan, acot, atan2
References
==========
.. [1] https://en.wikipedia.org/wiki/Trigonometric_functions
.. [2] http://dlmf.nist.gov/4.14
.. [3] http://functions.wolfram.com/ElementaryFunctions/Csc
"""
_reciprocal_of = sin
_is_odd = True
def period(self, symbol=None):
return self._period(symbol)
def _eval_rewrite_as_sin(self, arg, **kwargs):
return (1/sin(arg))
def _eval_rewrite_as_sincos(self, arg, **kwargs):
return cos(arg)/(sin(arg)*cos(arg))
def _eval_rewrite_as_cot(self, arg, **kwargs):
cot_half = cot(arg/2)
return (1 + cot_half**2)/(2*cot_half)
def _eval_rewrite_as_cos(self, arg, **kwargs):
return 1/sin(arg).rewrite(cos)
def _eval_rewrite_as_sec(self, arg, **kwargs):
return sec(pi/2 - arg, evaluate=False)
def _eval_rewrite_as_tan(self, arg, **kwargs):
return (1/sin(arg).rewrite(tan))
def fdiff(self, argindex=1):
if argindex == 1:
return -cot(self.args[0])*csc(self.args[0])
else:
raise ArgumentIndexError(self, argindex)
def _eval_is_complex(self):
arg = self.args[0]
if arg.is_real and (arg/pi).is_integer is False:
return True
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
from sympy.functions.combinatorial.numbers import bernoulli
if n == 0:
return 1/sympify(x)
elif n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
k = n//2 + 1
return (S.NegativeOne**(k - 1)*2*(2**(2*k - 1) - 1)*
bernoulli(2*k)*x**(2*k - 1)/factorial(2*k))
class sinc(Function):
r"""
Represents an unnormalized sinc function:
.. math::
\operatorname{sinc}(x) =
\begin{cases}
\frac{\sin x}{x} & \qquad x \neq 0 \\
1 & \qquad x = 0
\end{cases}
Examples
========
>>> from sympy import sinc, oo, jn
>>> from sympy.abc import x
>>> sinc(x)
sinc(x)
* Automated Evaluation
>>> sinc(0)
1
>>> sinc(oo)
0
* Differentiation
>>> sinc(x).diff()
cos(x)/x - sin(x)/x**2
* Series Expansion
>>> sinc(x).series()
1 - x**2/6 + x**4/120 + O(x**6)
* As zero'th order spherical Bessel Function
>>> sinc(x).rewrite(jn)
jn(0, x)
See also
========
sin
References
==========
.. [1] https://en.wikipedia.org/wiki/Sinc_function
"""
_singularities = (S.ComplexInfinity,)
def fdiff(self, argindex=1):
x = self.args[0]
if argindex == 1:
# We would like to return the Piecewise here, but Piecewise.diff
# currently can't handle removable singularities, meaning things
# like sinc(x).diff(x, 2) give the wrong answer at x = 0. See
# https://github.com/sympy/sympy/issues/11402.
#
# return Piecewise(((x*cos(x) - sin(x))/x**2, Ne(x, S.Zero)), (S.Zero, S.true))
return cos(x)/x - sin(x)/x**2
else:
raise ArgumentIndexError(self, argindex)
@classmethod
def eval(cls, arg):
if arg.is_zero:
return S.One
if arg.is_Number:
if arg in [S.Infinity, S.NegativeInfinity]:
return S.Zero
elif arg is S.NaN:
return S.NaN
if arg is S.ComplexInfinity:
return S.NaN
if arg.could_extract_minus_sign():
return cls(-arg)
pi_coeff = _pi_coeff(arg)
if pi_coeff is not None:
if pi_coeff.is_integer:
if fuzzy_not(arg.is_zero):
return S.Zero
elif (2*pi_coeff).is_integer:
return S.NegativeOne**(pi_coeff - S.Half)/arg
def _eval_nseries(self, x, n, logx, cdir=0):
x = self.args[0]
return (sin(x)/x)._eval_nseries(x, n, logx)
def _eval_rewrite_as_jn(self, arg, **kwargs):
from sympy.functions.special.bessel import jn
return jn(0, arg)
def _eval_rewrite_as_sin(self, arg, **kwargs):
return Piecewise((sin(arg)/arg, Ne(arg, S.Zero)), (S.One, S.true))
def _eval_is_zero(self):
if self.args[0].is_infinite:
return True
rest, pi_mult = _peeloff_pi(self.args[0])
if rest.is_zero:
return fuzzy_and([pi_mult.is_integer, pi_mult.is_nonzero])
if rest.is_Number and pi_mult.is_integer:
return False
def _eval_is_real(self):
if self.args[0].is_extended_real or self.args[0].is_imaginary:
return True
_eval_is_finite = _eval_is_real
###############################################################################
########################### TRIGONOMETRIC INVERSES ############################
###############################################################################
class InverseTrigonometricFunction(Function):
"""Base class for inverse trigonometric functions."""
_singularities = (S.One, S.NegativeOne, S.Zero, S.ComplexInfinity) # type: tTuple[Expr, ...]
@staticmethod
def _asin_table():
# Only keys with could_extract_minus_sign() == False
# are actually needed.
return {
sqrt(3)/2: S.Pi/3,
sqrt(2)/2: S.Pi/4,
1/sqrt(2): S.Pi/4,
sqrt((5 - sqrt(5))/8): S.Pi/5,
sqrt(2)*sqrt(5 - sqrt(5))/4: S.Pi/5,
sqrt((5 + sqrt(5))/8): S.Pi*Rational(2, 5),
sqrt(2)*sqrt(5 + sqrt(5))/4: S.Pi*Rational(2, 5),
S.Half: S.Pi/6,
sqrt(2 - sqrt(2))/2: S.Pi/8,
sqrt(S.Half - sqrt(2)/4): S.Pi/8,
sqrt(2 + sqrt(2))/2: S.Pi*Rational(3, 8),
sqrt(S.Half + sqrt(2)/4): S.Pi*Rational(3, 8),
(sqrt(5) - 1)/4: S.Pi/10,
(1 - sqrt(5))/4: -S.Pi/10,
(sqrt(5) + 1)/4: S.Pi*Rational(3, 10),
sqrt(6)/4 - sqrt(2)/4: S.Pi/12,
-sqrt(6)/4 + sqrt(2)/4: -S.Pi/12,
(sqrt(3) - 1)/sqrt(8): S.Pi/12,
(1 - sqrt(3))/sqrt(8): -S.Pi/12,
sqrt(6)/4 + sqrt(2)/4: S.Pi*Rational(5, 12),
(1 + sqrt(3))/sqrt(8): S.Pi*Rational(5, 12)
}
@staticmethod
def _atan_table():
# Only keys with could_extract_minus_sign() == False
# are actually needed.
return {
sqrt(3)/3: S.Pi/6,
1/sqrt(3): S.Pi/6,
sqrt(3): S.Pi/3,
sqrt(2) - 1: S.Pi/8,
1 - sqrt(2): -S.Pi/8,
1 + sqrt(2): S.Pi*Rational(3, 8),
sqrt(5 - 2*sqrt(5)): S.Pi/5,
sqrt(5 + 2*sqrt(5)): S.Pi*Rational(2, 5),
sqrt(1 - 2*sqrt(5)/5): S.Pi/10,
sqrt(1 + 2*sqrt(5)/5): S.Pi*Rational(3, 10),
2 - sqrt(3): S.Pi/12,
-2 + sqrt(3): -S.Pi/12,
2 + sqrt(3): S.Pi*Rational(5, 12)
}
@staticmethod
def _acsc_table():
# Keys for which could_extract_minus_sign()
# will obviously return True are omitted.
return {
2*sqrt(3)/3: S.Pi/3,
sqrt(2): S.Pi/4,
sqrt(2 + 2*sqrt(5)/5): S.Pi/5,
1/sqrt(Rational(5, 8) - sqrt(5)/8): S.Pi/5,
sqrt(2 - 2*sqrt(5)/5): S.Pi*Rational(2, 5),
1/sqrt(Rational(5, 8) + sqrt(5)/8): S.Pi*Rational(2, 5),
2: S.Pi/6,
sqrt(4 + 2*sqrt(2)): S.Pi/8,
2/sqrt(2 - sqrt(2)): S.Pi/8,
sqrt(4 - 2*sqrt(2)): S.Pi*Rational(3, 8),
2/sqrt(2 + sqrt(2)): S.Pi*Rational(3, 8),
1 + sqrt(5): S.Pi/10,
sqrt(5) - 1: S.Pi*Rational(3, 10),
-(sqrt(5) - 1): S.Pi*Rational(-3, 10),
sqrt(6) + sqrt(2): S.Pi/12,
sqrt(6) - sqrt(2): S.Pi*Rational(5, 12),
-(sqrt(6) - sqrt(2)): S.Pi*Rational(-5, 12)
}
class asin(InverseTrigonometricFunction):
"""
The inverse sine function.
Returns the arcsine of x in radians.
Explanation
===========
``asin(x)`` will evaluate automatically in the cases ``oo``, ``-oo``,
``0``, ``1``, ``-1`` and for some instances when the result is a rational
multiple of pi (see the eval class method).
A purely imaginary argument will lead to an asinh expression.
Examples
========
>>> from sympy import asin, oo
>>> asin(1)
pi/2
>>> asin(-1)
-pi/2
>>> asin(-oo)
oo*I
>>> asin(oo)
-oo*I
See Also
========
sin, csc, cos, sec, tan, cot
acsc, acos, asec, atan, acot, atan2
References
==========
.. [1] https://en.wikipedia.org/wiki/Inverse_trigonometric_functions
.. [2] http://dlmf.nist.gov/4.23
.. [3] http://functions.wolfram.com/ElementaryFunctions/ArcSin
"""
def fdiff(self, argindex=1):
if argindex == 1:
return 1/sqrt(1 - self.args[0]**2)
else:
raise ArgumentIndexError(self, argindex)
def _eval_is_rational(self):
s = self.func(*self.args)
if s.func == self.func:
if s.args[0].is_rational:
return False
else:
return s.is_rational
def _eval_is_positive(self):
return self._eval_is_extended_real() and self.args[0].is_positive
def _eval_is_negative(self):
return self._eval_is_extended_real() and self.args[0].is_negative
@classmethod
def eval(cls, arg):
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.NegativeInfinity*S.ImaginaryUnit
elif arg is S.NegativeInfinity:
return S.Infinity*S.ImaginaryUnit
elif arg.is_zero:
return S.Zero
elif arg is S.One:
return S.Pi/2
elif arg is S.NegativeOne:
return -S.Pi/2
if arg is S.ComplexInfinity:
return S.ComplexInfinity
if arg.could_extract_minus_sign():
return -cls(-arg)
if arg.is_number:
asin_table = cls._asin_table()
if arg in asin_table:
return asin_table[arg]
i_coeff = arg.as_coefficient(S.ImaginaryUnit)
if i_coeff is not None:
return S.ImaginaryUnit*asinh(i_coeff)
if arg.is_zero:
return S.Zero
if isinstance(arg, sin):
ang = arg.args[0]
if ang.is_comparable:
ang %= 2*pi # restrict to [0,2*pi)
if ang > pi: # restrict to (-pi,pi]
ang = pi - ang
# restrict to [-pi/2,pi/2]
if ang > pi/2:
ang = pi - ang
if ang < -pi/2:
ang = -pi - ang
return ang
if isinstance(arg, cos): # acos(x) + asin(x) = pi/2
ang = arg.args[0]
if ang.is_comparable:
return pi/2 - acos(arg)
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
if n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
if len(previous_terms) >= 2 and n > 2:
p = previous_terms[-2]
return p*(n - 2)**2/(n*(n - 1))*x**2
else:
k = (n - 1) // 2
R = RisingFactorial(S.Half, k)
F = factorial(k)
return R/F*x**n/n
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.functions.elementary.complexes import im
arg = self.args[0]
x0 = arg.subs(x, 0).cancel()
if x0.is_zero:
return arg.as_leading_term(x)
if x0 is S.ComplexInfinity:
return S.ImaginaryUnit*log(arg.as_leading_term(x))
if cdir != 0:
cdir = arg.dir(x, cdir)
if im(cdir) < 0 and x0.is_real and x0 < S.NegativeOne:
return -S.Pi - self.func(x0)
elif im(cdir) > 0 and x0.is_real and x0 > S.One:
return S.Pi - self.func(x0)
return self.func(x0)
def _eval_nseries(self, x, n, logx, cdir=0): # asin
from sympy.functions.elementary.complexes import im
from sympy.series.order import O
arg0 = self.args[0].subs(x, 0)
if arg0 is S.One:
t = Dummy('t', positive=True)
ser = asin(S.One - t**2).rewrite(log).nseries(t, 0, 2*n)
arg1 = S.One - self.args[0]
f = arg1.as_leading_term(x)
g = (arg1 - f)/ f
if not g.is_meromorphic(x, 0): # cannot be expanded
return O(1) if n == 0 else S.Pi/2 + O(sqrt(x))
res1 = sqrt(S.One + g)._eval_nseries(x, n=n, logx=logx)
res = (res1.removeO()*sqrt(f)).expand()
return ser.removeO().subs(t, res).expand().powsimp() + O(x**n, x)
if arg0 is S.NegativeOne:
t = Dummy('t', positive=True)
ser = asin(S.NegativeOne + t**2).rewrite(log).nseries(t, 0, 2*n)
arg1 = S.One + self.args[0]
f = arg1.as_leading_term(x)
g = (arg1 - f)/ f
if not g.is_meromorphic(x, 0): # cannot be expanded
return O(1) if n == 0 else -S.Pi/2 + O(sqrt(x))
res1 = sqrt(S.One + g)._eval_nseries(x, n=n, logx=logx)
res = (res1.removeO()*sqrt(f)).expand()
return ser.removeO().subs(t, res).expand().powsimp() + O(x**n, x)
res = Function._eval_nseries(self, x, n=n, logx=logx)
if arg0 is S.ComplexInfinity:
return res
if cdir != 0:
cdir = self.args[0].dir(x, cdir)
if im(cdir) < 0 and arg0.is_real and arg0 < S.NegativeOne:
return -S.Pi - res
elif im(cdir) > 0 and arg0.is_real and arg0 > S.One:
return S.Pi - res
return res
def _eval_rewrite_as_acos(self, x, **kwargs):
return S.Pi/2 - acos(x)
def _eval_rewrite_as_atan(self, x, **kwargs):
return 2*atan(x/(1 + sqrt(1 - x**2)))
def _eval_rewrite_as_log(self, x, **kwargs):
return -S.ImaginaryUnit*log(S.ImaginaryUnit*x + sqrt(1 - x**2))
def _eval_rewrite_as_acot(self, arg, **kwargs):
return 2*acot((1 + sqrt(1 - arg**2))/arg)
def _eval_rewrite_as_asec(self, arg, **kwargs):
return S.Pi/2 - asec(1/arg)
def _eval_rewrite_as_acsc(self, arg, **kwargs):
return acsc(1/arg)
def _eval_is_extended_real(self):
x = self.args[0]
return x.is_extended_real and (1 - abs(x)).is_nonnegative
def inverse(self, argindex=1):
"""
Returns the inverse of this function.
"""
return sin
class acos(InverseTrigonometricFunction):
"""
The inverse cosine function.
Returns the arc cosine of x (measured in radians).
Examples
========
``acos(x)`` will evaluate automatically in the cases
``oo``, ``-oo``, ``0``, ``1``, ``-1`` and for some instances when
the result is a rational multiple of pi (see the eval class method).
``acos(zoo)`` evaluates to ``zoo``
(see note in :class:`sympy.functions.elementary.trigonometric.asec`)
A purely imaginary argument will be rewritten to asinh.
Examples
========
>>> from sympy import acos, oo
>>> acos(1)
0
>>> acos(0)
pi/2
>>> acos(oo)
oo*I
See Also
========
sin, csc, cos, sec, tan, cot
asin, acsc, asec, atan, acot, atan2
References
==========
.. [1] https://en.wikipedia.org/wiki/Inverse_trigonometric_functions
.. [2] http://dlmf.nist.gov/4.23
.. [3] http://functions.wolfram.com/ElementaryFunctions/ArcCos
"""
def fdiff(self, argindex=1):
if argindex == 1:
return -1/sqrt(1 - self.args[0]**2)
else:
raise ArgumentIndexError(self, argindex)
def _eval_is_rational(self):
s = self.func(*self.args)
if s.func == self.func:
if s.args[0].is_rational:
return False
else:
return s.is_rational
@classmethod
def eval(cls, arg):
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.Infinity*S.ImaginaryUnit
elif arg is S.NegativeInfinity:
return S.NegativeInfinity*S.ImaginaryUnit
elif arg.is_zero:
return S.Pi/2
elif arg is S.One:
return S.Zero
elif arg is S.NegativeOne:
return S.Pi
if arg is S.ComplexInfinity:
return S.ComplexInfinity
if arg.is_number:
asin_table = cls._asin_table()
if arg in asin_table:
return pi/2 - asin_table[arg]
elif -arg in asin_table:
return pi/2 + asin_table[-arg]
i_coeff = arg.as_coefficient(S.ImaginaryUnit)
if i_coeff is not None:
return pi/2 - asin(arg)
if isinstance(arg, cos):
ang = arg.args[0]
if ang.is_comparable:
ang %= 2*pi # restrict to [0,2*pi)
if ang > pi: # restrict to [0,pi]
ang = 2*pi - ang
return ang
if isinstance(arg, sin): # acos(x) + asin(x) = pi/2
ang = arg.args[0]
if ang.is_comparable:
return pi/2 - asin(arg)
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
if n == 0:
return S.Pi/2
elif n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
if len(previous_terms) >= 2 and n > 2:
p = previous_terms[-2]
return p*(n - 2)**2/(n*(n - 1))*x**2
else:
k = (n - 1) // 2
R = RisingFactorial(S.Half, k)
F = factorial(k)
return -R/F*x**n/n
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.functions.elementary.complexes import im
arg = self.args[0]
x0 = arg.subs(x, 0).cancel()
if x0 == 1:
return sqrt(2)*sqrt((S.One - arg).as_leading_term(x))
if x0 is S.ComplexInfinity:
return S.ImaginaryUnit*log(arg.as_leading_term(x))
if cdir != 0:
cdir = arg.dir(x, cdir)
if im(cdir) < 0 and x0.is_real and x0 < S.NegativeOne:
return 2*S.Pi - self.func(x0)
elif im(cdir) > 0 and x0.is_real and x0 > S.One:
return -self.func(x0)
return self.func(x0)
def _eval_is_extended_real(self):
x = self.args[0]
return x.is_extended_real and (1 - abs(x)).is_nonnegative
def _eval_is_nonnegative(self):
return self._eval_is_extended_real()
def _eval_nseries(self, x, n, logx, cdir=0): # acos
from sympy.functions.elementary.complexes import im
from sympy.series.order import O
arg0 = self.args[0].subs(x, 0)
if arg0 is S.One:
t = Dummy('t', positive=True)
ser = acos(S.One - t**2).rewrite(log).nseries(t, 0, 2*n)
arg1 = S.One - self.args[0]
f = arg1.as_leading_term(x)
g = (arg1 - f)/ f
if not g.is_meromorphic(x, 0): # cannot be expanded
return O(1) if n == 0 else O(sqrt(x))
res1 = sqrt(S.One + g)._eval_nseries(x, n=n, logx=logx)
res = (res1.removeO()*sqrt(f)).expand()
return ser.removeO().subs(t, res).expand().powsimp() + O(x**n, x)
if arg0 is S.NegativeOne:
t = Dummy('t', positive=True)
ser = acos(S.NegativeOne + t**2).rewrite(log).nseries(t, 0, 2*n)
arg1 = S.One + self.args[0]
f = arg1.as_leading_term(x)
g = (arg1 - f)/ f
if not g.is_meromorphic(x, 0): # cannot be expanded
return O(1) if n == 0 else S.Pi + O(sqrt(x))
res1 = sqrt(S.One + g)._eval_nseries(x, n=n, logx=logx)
res = (res1.removeO()*sqrt(f)).expand()
return ser.removeO().subs(t, res).expand().powsimp() + O(x**n, x)
res = Function._eval_nseries(self, x, n=n, logx=logx)
if arg0 is S.ComplexInfinity:
return res
if cdir != 0:
cdir = self.args[0].dir(x, cdir)
if im(cdir) < 0 and arg0.is_real and arg0 < S.NegativeOne:
return 2*S.Pi - res
elif im(cdir) > 0 and arg0.is_real and arg0 > S.One:
return -res
return res
def _eval_rewrite_as_log(self, x, **kwargs):
return S.Pi/2 + S.ImaginaryUnit*\
log(S.ImaginaryUnit*x + sqrt(1 - x**2))
def _eval_rewrite_as_asin(self, x, **kwargs):
return S.Pi/2 - asin(x)
def _eval_rewrite_as_atan(self, x, **kwargs):
return atan(sqrt(1 - x**2)/x) + (S.Pi/2)*(1 - x*sqrt(1/x**2))
def inverse(self, argindex=1):
"""
Returns the inverse of this function.
"""
return cos
def _eval_rewrite_as_acot(self, arg, **kwargs):
return S.Pi/2 - 2*acot((1 + sqrt(1 - arg**2))/arg)
def _eval_rewrite_as_asec(self, arg, **kwargs):
return asec(1/arg)
def _eval_rewrite_as_acsc(self, arg, **kwargs):
return S.Pi/2 - acsc(1/arg)
def _eval_conjugate(self):
z = self.args[0]
r = self.func(self.args[0].conjugate())
if z.is_extended_real is False:
return r
elif z.is_extended_real and (z + 1).is_nonnegative and (z - 1).is_nonpositive:
return r
class atan(InverseTrigonometricFunction):
"""
The inverse tangent function.
Returns the arc tangent of x (measured in radians).
Explanation
===========
``atan(x)`` will evaluate automatically in the cases
``oo``, ``-oo``, ``0``, ``1``, ``-1`` and for some instances when the
result is a rational multiple of pi (see the eval class method).
Examples
========
>>> from sympy import atan, oo
>>> atan(0)
0
>>> atan(1)
pi/4
>>> atan(oo)
pi/2
See Also
========
sin, csc, cos, sec, tan, cot
asin, acsc, acos, asec, acot, atan2
References
==========
.. [1] https://en.wikipedia.org/wiki/Inverse_trigonometric_functions
.. [2] http://dlmf.nist.gov/4.23
.. [3] http://functions.wolfram.com/ElementaryFunctions/ArcTan
"""
args: tTuple[Expr]
_singularities = (S.ImaginaryUnit, -S.ImaginaryUnit)
def fdiff(self, argindex=1):
if argindex == 1:
return 1/(1 + self.args[0]**2)
else:
raise ArgumentIndexError(self, argindex)
def _eval_is_rational(self):
s = self.func(*self.args)
if s.func == self.func:
if s.args[0].is_rational:
return False
else:
return s.is_rational
def _eval_is_positive(self):
return self.args[0].is_extended_positive
def _eval_is_nonnegative(self):
return self.args[0].is_extended_nonnegative
def _eval_is_zero(self):
return self.args[0].is_zero
def _eval_is_real(self):
return self.args[0].is_extended_real
@classmethod
def eval(cls, arg):
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.Pi/2
elif arg is S.NegativeInfinity:
return -S.Pi/2
elif arg.is_zero:
return S.Zero
elif arg is S.One:
return S.Pi/4
elif arg is S.NegativeOne:
return -S.Pi/4
if arg is S.ComplexInfinity:
from sympy.calculus.util import AccumBounds
return AccumBounds(-S.Pi/2, S.Pi/2)
if arg.could_extract_minus_sign():
return -cls(-arg)
if arg.is_number:
atan_table = cls._atan_table()
if arg in atan_table:
return atan_table[arg]
i_coeff = arg.as_coefficient(S.ImaginaryUnit)
if i_coeff is not None:
return S.ImaginaryUnit*atanh(i_coeff)
if arg.is_zero:
return S.Zero
if isinstance(arg, tan):
ang = arg.args[0]
if ang.is_comparable:
ang %= pi # restrict to [0,pi)
if ang > pi/2: # restrict to [-pi/2,pi/2]
ang -= pi
return ang
if isinstance(arg, cot): # atan(x) + acot(x) = pi/2
ang = arg.args[0]
if ang.is_comparable:
ang = pi/2 - acot(arg)
if ang > pi/2: # restrict to [-pi/2,pi/2]
ang -= pi
return ang
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
if n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
return S.NegativeOne**((n - 1)//2)*x**n/n
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.functions.elementary.complexes import (im, re)
arg = self.args[0]
x0 = arg.subs(x, 0).cancel()
if x0.is_zero:
return arg.as_leading_term(x)
if x0 is S.ComplexInfinity:
return acot(1/arg)._eval_as_leading_term(x, cdir=cdir)
if cdir != 0:
cdir = arg.dir(x, cdir)
if re(cdir) < 0 and re(x0).is_zero and im(x0) > S.One:
return self.func(x0) - S.Pi
elif re(cdir) > 0 and re(x0).is_zero and im(x0) < S.NegativeOne:
return self.func(x0) + S.Pi
return self.func(x0)
def _eval_nseries(self, x, n, logx, cdir=0): # atan
from sympy.functions.elementary.complexes import (im, re)
arg0 = self.args[0].subs(x, 0)
res = Function._eval_nseries(self, x, n=n, logx=logx)
if cdir != 0:
cdir = self.args[0].dir(x, cdir)
if arg0 is S.ComplexInfinity:
if re(cdir) > 0:
return res - S.Pi
return res
if re(cdir) < 0 and re(arg0).is_zero and im(arg0) > S.One:
return res - S.Pi
elif re(cdir) > 0 and re(arg0).is_zero and im(arg0) < S.NegativeOne:
return res + S.Pi
return res
def _eval_rewrite_as_log(self, x, **kwargs):
return S.ImaginaryUnit/2*(log(S.One - S.ImaginaryUnit*x)
- log(S.One + S.ImaginaryUnit*x))
def _eval_aseries(self, n, args0, x, logx):
if args0[0] is S.Infinity:
return (S.Pi/2 - atan(1/self.args[0]))._eval_nseries(x, n, logx)
elif args0[0] is S.NegativeInfinity:
return (-S.Pi/2 - atan(1/self.args[0]))._eval_nseries(x, n, logx)
else:
return super()._eval_aseries(n, args0, x, logx)
def inverse(self, argindex=1):
"""
Returns the inverse of this function.
"""
return tan
def _eval_rewrite_as_asin(self, arg, **kwargs):
return sqrt(arg**2)/arg*(S.Pi/2 - asin(1/sqrt(1 + arg**2)))
def _eval_rewrite_as_acos(self, arg, **kwargs):
return sqrt(arg**2)/arg*acos(1/sqrt(1 + arg**2))
def _eval_rewrite_as_acot(self, arg, **kwargs):
return acot(1/arg)
def _eval_rewrite_as_asec(self, arg, **kwargs):
return sqrt(arg**2)/arg*asec(sqrt(1 + arg**2))
def _eval_rewrite_as_acsc(self, arg, **kwargs):
return sqrt(arg**2)/arg*(S.Pi/2 - acsc(sqrt(1 + arg**2)))
class acot(InverseTrigonometricFunction):
r"""
The inverse cotangent function.
Returns the arc cotangent of x (measured in radians).
Explanation
===========
``acot(x)`` will evaluate automatically in the cases ``oo``, ``-oo``,
``zoo``, ``0``, ``1``, ``-1`` and for some instances when the result is a
rational multiple of pi (see the eval class method).
A purely imaginary argument will lead to an ``acoth`` expression.
``acot(x)`` has a branch cut along `(-i, i)`, hence it is discontinuous
at 0. Its range for real ``x`` is `(-\frac{\pi}{2}, \frac{\pi}{2}]`.
Examples
========
>>> from sympy import acot, sqrt
>>> acot(0)
pi/2
>>> acot(1)
pi/4
>>> acot(sqrt(3) - 2)
-5*pi/12
See Also
========
sin, csc, cos, sec, tan, cot
asin, acsc, acos, asec, atan, atan2
References
==========
.. [1] http://dlmf.nist.gov/4.23
.. [2] http://functions.wolfram.com/ElementaryFunctions/ArcCot
"""
_singularities = (S.ImaginaryUnit, -S.ImaginaryUnit)
def fdiff(self, argindex=1):
if argindex == 1:
return -1/(1 + self.args[0]**2)
else:
raise ArgumentIndexError(self, argindex)
def _eval_is_rational(self):
s = self.func(*self.args)
if s.func == self.func:
if s.args[0].is_rational:
return False
else:
return s.is_rational
def _eval_is_positive(self):
return self.args[0].is_nonnegative
def _eval_is_negative(self):
return self.args[0].is_negative
def _eval_is_extended_real(self):
return self.args[0].is_extended_real
@classmethod
def eval(cls, arg):
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.Zero
elif arg is S.NegativeInfinity:
return S.Zero
elif arg.is_zero:
return S.Pi/ 2
elif arg is S.One:
return S.Pi/4
elif arg is S.NegativeOne:
return -S.Pi/4
if arg is S.ComplexInfinity:
return S.Zero
if arg.could_extract_minus_sign():
return -cls(-arg)
if arg.is_number:
atan_table = cls._atan_table()
if arg in atan_table:
ang = pi/2 - atan_table[arg]
if ang > pi/2: # restrict to (-pi/2,pi/2]
ang -= pi
return ang
i_coeff = arg.as_coefficient(S.ImaginaryUnit)
if i_coeff is not None:
return -S.ImaginaryUnit*acoth(i_coeff)
if arg.is_zero:
return S.Pi*S.Half
if isinstance(arg, cot):
ang = arg.args[0]
if ang.is_comparable:
ang %= pi # restrict to [0,pi)
if ang > pi/2: # restrict to (-pi/2,pi/2]
ang -= pi;
return ang
if isinstance(arg, tan): # atan(x) + acot(x) = pi/2
ang = arg.args[0]
if ang.is_comparable:
ang = pi/2 - atan(arg)
if ang > pi/2: # restrict to (-pi/2,pi/2]
ang -= pi
return ang
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
if n == 0:
return S.Pi/2 # FIX THIS
elif n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
return S.NegativeOne**((n + 1)//2)*x**n/n
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.functions.elementary.complexes import (im, re)
arg = self.args[0]
x0 = arg.subs(x, 0).cancel()
if x0 is S.ComplexInfinity:
return (1/arg).as_leading_term(x)
if cdir != 0:
cdir = arg.dir(x, cdir)
if x0.is_zero:
if re(cdir) < 0:
return self.func(x0) - S.Pi
return self.func(x0)
if re(cdir) > 0 and re(x0).is_zero and im(x0) > S.Zero and im(x0) < S.One:
return self.func(x0) + S.Pi
if re(cdir) < 0 and re(x0).is_zero and im(x0) < S.Zero and im(x0) > S.NegativeOne:
return self.func(x0) - S.Pi
return self.func(x0)
def _eval_nseries(self, x, n, logx, cdir=0): # acot
from sympy.functions.elementary.complexes import (im, re)
arg0 = self.args[0].subs(x, 0)
res = Function._eval_nseries(self, x, n=n, logx=logx)
if arg0 is S.ComplexInfinity:
return res
if cdir != 0:
cdir = self.args[0].dir(x, cdir)
if arg0.is_zero:
if re(cdir) < 0:
return res - S.Pi
return res
if re(cdir) > 0 and re(arg0).is_zero and im(arg0) > S.Zero and im(arg0) < S.One:
return res + S.Pi
if re(cdir) < 0 and re(arg0).is_zero and im(arg0) < S.Zero and im(arg0) > S.NegativeOne:
return res - S.Pi
return res
def _eval_aseries(self, n, args0, x, logx):
if args0[0] is S.Infinity:
return (S.Pi/2 - acot(1/self.args[0]))._eval_nseries(x, n, logx)
elif args0[0] is S.NegativeInfinity:
return (S.Pi*Rational(3, 2) - acot(1/self.args[0]))._eval_nseries(x, n, logx)
else:
return super(atan, self)._eval_aseries(n, args0, x, logx)
def _eval_rewrite_as_log(self, x, **kwargs):
return S.ImaginaryUnit/2*(log(1 - S.ImaginaryUnit/x)
- log(1 + S.ImaginaryUnit/x))
def inverse(self, argindex=1):
"""
Returns the inverse of this function.
"""
return cot
def _eval_rewrite_as_asin(self, arg, **kwargs):
return (arg*sqrt(1/arg**2)*
(S.Pi/2 - asin(sqrt(-arg**2)/sqrt(-arg**2 - 1))))
def _eval_rewrite_as_acos(self, arg, **kwargs):
return arg*sqrt(1/arg**2)*acos(sqrt(-arg**2)/sqrt(-arg**2 - 1))
def _eval_rewrite_as_atan(self, arg, **kwargs):
return atan(1/arg)
def _eval_rewrite_as_asec(self, arg, **kwargs):
return arg*sqrt(1/arg**2)*asec(sqrt((1 + arg**2)/arg**2))
def _eval_rewrite_as_acsc(self, arg, **kwargs):
return arg*sqrt(1/arg**2)*(S.Pi/2 - acsc(sqrt((1 + arg**2)/arg**2)))
class asec(InverseTrigonometricFunction):
r"""
The inverse secant function.
Returns the arc secant of x (measured in radians).
Explanation
===========
``asec(x)`` will evaluate automatically in the cases ``oo``, ``-oo``,
``0``, ``1``, ``-1`` and for some instances when the result is a rational
multiple of pi (see the eval class method).
``asec(x)`` has branch cut in the interval [-1, 1]. For complex arguments,
it can be defined [4]_ as
.. math::
\operatorname{sec^{-1}}(z) = -i\frac{\log\left(\sqrt{1 - z^2} + 1\right)}{z}
At ``x = 0``, for positive branch cut, the limit evaluates to ``zoo``. For
negative branch cut, the limit
.. math::
\lim_{z \to 0}-i\frac{\log\left(-\sqrt{1 - z^2} + 1\right)}{z}
simplifies to :math:`-i\log\left(z/2 + O\left(z^3\right)\right)` which
ultimately evaluates to ``zoo``.
As ``acos(x)`` = ``asec(1/x)``, a similar argument can be given for
``acos(x)``.
Examples
========
>>> from sympy import asec, oo
>>> asec(1)
0
>>> asec(-1)
pi
>>> asec(0)
zoo
>>> asec(-oo)
pi/2
See Also
========
sin, csc, cos, sec, tan, cot
asin, acsc, acos, atan, acot, atan2
References
==========
.. [1] https://en.wikipedia.org/wiki/Inverse_trigonometric_functions
.. [2] http://dlmf.nist.gov/4.23
.. [3] http://functions.wolfram.com/ElementaryFunctions/ArcSec
.. [4] http://reference.wolfram.com/language/ref/ArcSec.html
"""
@classmethod
def eval(cls, arg):
if arg.is_zero:
return S.ComplexInfinity
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.One:
return S.Zero
elif arg is S.NegativeOne:
return S.Pi
if arg in [S.Infinity, S.NegativeInfinity, S.ComplexInfinity]:
return S.Pi/2
if arg.is_number:
acsc_table = cls._acsc_table()
if arg in acsc_table:
return pi/2 - acsc_table[arg]
elif -arg in acsc_table:
return pi/2 + acsc_table[-arg]
if isinstance(arg, sec):
ang = arg.args[0]
if ang.is_comparable:
ang %= 2*pi # restrict to [0,2*pi)
if ang > pi: # restrict to [0,pi]
ang = 2*pi - ang
return ang
if isinstance(arg, csc): # asec(x) + acsc(x) = pi/2
ang = arg.args[0]
if ang.is_comparable:
return pi/2 - acsc(arg)
def fdiff(self, argindex=1):
if argindex == 1:
return 1/(self.args[0]**2*sqrt(1 - 1/self.args[0]**2))
else:
raise ArgumentIndexError(self, argindex)
def inverse(self, argindex=1):
"""
Returns the inverse of this function.
"""
return sec
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.functions.elementary.complexes import im
arg = self.args[0]
x0 = arg.subs(x, 0).cancel()
if x0 == 1:
return sqrt(2)*sqrt((arg - S.One).as_leading_term(x))
if x0.is_zero:
return S.ImaginaryUnit*log(arg.as_leading_term(x))
if cdir != 0:
cdir = arg.dir(x, cdir)
if im(cdir) < 0 and x0.is_real and x0 > S.Zero and x0 < S.One:
return -self.func(x0)
elif im(cdir) > 0 and x0.is_real and x0 < S.Zero and x0 > S.NegativeOne:
return 2*S.Pi - self.func(x0)
return self.func(x0)
def _eval_nseries(self, x, n, logx, cdir=0): # asec
from sympy.functions.elementary.complexes import im
from sympy.series.order import O
arg0 = self.args[0].subs(x, 0)
if arg0 is S.One:
t = Dummy('t', positive=True)
ser = asec(S.One + t**2).rewrite(log).nseries(t, 0, 2*n)
arg1 = S.NegativeOne + self.args[0]
f = arg1.as_leading_term(x)
g = (arg1 - f)/ f
res1 = sqrt(S.One + g)._eval_nseries(x, n=n, logx=logx)
res = (res1.removeO()*sqrt(f)).expand()
return ser.removeO().subs(t, res).expand().powsimp() + O(x**n, x)
if arg0 is S.NegativeOne:
t = Dummy('t', positive=True)
ser = asec(S.NegativeOne - t**2).rewrite(log).nseries(t, 0, 2*n)
arg1 = S.NegativeOne - self.args[0]
f = arg1.as_leading_term(x)
g = (arg1 - f)/ f
res1 = sqrt(S.One + g)._eval_nseries(x, n=n, logx=logx)
res = (res1.removeO()*sqrt(f)).expand()
return ser.removeO().subs(t, res).expand().powsimp() + O(x**n, x)
res = Function._eval_nseries(self, x, n=n, logx=logx)
if arg0 is S.ComplexInfinity:
return res
if cdir != 0:
cdir = self.args[0].dir(x, cdir)
if im(cdir) < 0 and arg0.is_real and arg0 > S.Zero and arg0 < S.One:
return -res
elif im(cdir) > 0 and arg0.is_real and arg0 < S.Zero and arg0 > S.NegativeOne:
return 2*S.Pi - res
return res
def _eval_is_extended_real(self):
x = self.args[0]
if x.is_extended_real is False:
return False
return fuzzy_or(((x - 1).is_nonnegative, (-x - 1).is_nonnegative))
def _eval_rewrite_as_log(self, arg, **kwargs):
return S.Pi/2 + S.ImaginaryUnit*log(S.ImaginaryUnit/arg + sqrt(1 - 1/arg**2))
def _eval_rewrite_as_asin(self, arg, **kwargs):
return S.Pi/2 - asin(1/arg)
def _eval_rewrite_as_acos(self, arg, **kwargs):
return acos(1/arg)
def _eval_rewrite_as_atan(self, arg, **kwargs):
return sqrt(arg**2)/arg*(-S.Pi/2 + 2*atan(arg + sqrt(arg**2 - 1)))
def _eval_rewrite_as_acot(self, arg, **kwargs):
return sqrt(arg**2)/arg*(-S.Pi/2 + 2*acot(arg - sqrt(arg**2 - 1)))
def _eval_rewrite_as_acsc(self, arg, **kwargs):
return S.Pi/2 - acsc(arg)
class acsc(InverseTrigonometricFunction):
"""
The inverse cosecant function.
Returns the arc cosecant of x (measured in radians).
Explanation
===========
``acsc(x)`` will evaluate automatically in the cases ``oo``, ``-oo``,
``0``, ``1``, ``-1`` and for some instances when the result is a rational
multiple of pi (see the eval class method).
Examples
========
>>> from sympy import acsc, oo
>>> acsc(1)
pi/2
>>> acsc(-1)
-pi/2
>>> acsc(oo)
0
>>> acsc(-oo) == acsc(oo)
True
>>> acsc(0)
zoo
See Also
========
sin, csc, cos, sec, tan, cot
asin, acos, asec, atan, acot, atan2
References
==========
.. [1] https://en.wikipedia.org/wiki/Inverse_trigonometric_functions
.. [2] http://dlmf.nist.gov/4.23
.. [3] http://functions.wolfram.com/ElementaryFunctions/ArcCsc
"""
@classmethod
def eval(cls, arg):
if arg.is_zero:
return S.ComplexInfinity
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.One:
return S.Pi/2
elif arg is S.NegativeOne:
return -S.Pi/2
if arg in [S.Infinity, S.NegativeInfinity, S.ComplexInfinity]:
return S.Zero
if arg.could_extract_minus_sign():
return -cls(-arg)
if arg.is_number:
acsc_table = cls._acsc_table()
if arg in acsc_table:
return acsc_table[arg]
if isinstance(arg, csc):
ang = arg.args[0]
if ang.is_comparable:
ang %= 2*pi # restrict to [0,2*pi)
if ang > pi: # restrict to (-pi,pi]
ang = pi - ang
# restrict to [-pi/2,pi/2]
if ang > pi/2:
ang = pi - ang
if ang < -pi/2:
ang = -pi - ang
return ang
if isinstance(arg, sec): # asec(x) + acsc(x) = pi/2
ang = arg.args[0]
if ang.is_comparable:
return pi/2 - asec(arg)
def fdiff(self, argindex=1):
if argindex == 1:
return -1/(self.args[0]**2*sqrt(1 - 1/self.args[0]**2))
else:
raise ArgumentIndexError(self, argindex)
def inverse(self, argindex=1):
"""
Returns the inverse of this function.
"""
return csc
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.functions.elementary.complexes import im
arg = self.args[0]
x0 = arg.subs(x, 0).cancel()
if x0.is_zero:
return S.ImaginaryUnit*log(arg.as_leading_term(x))
if x0 is S.ComplexInfinity:
return arg.as_leading_term(x)
if cdir != 0:
cdir = arg.dir(x, cdir)
if im(cdir) < 0 and x0.is_real and x0 > S.Zero and x0 < S.One:
return S.Pi - self.func(x0)
elif im(cdir) > 0 and x0.is_real and x0 < S.Zero and x0 > S.NegativeOne:
return -S.Pi - self.func(x0)
return self.func(x0)
def _eval_nseries(self, x, n, logx, cdir=0): # acsc
from sympy.functions.elementary.complexes import im
from sympy.series.order import O
arg0 = self.args[0].subs(x, 0)
if arg0 is S.One:
t = Dummy('t', positive=True)
ser = acsc(S.One + t**2).rewrite(log).nseries(t, 0, 2*n)
arg1 = S.NegativeOne + self.args[0]
f = arg1.as_leading_term(x)
g = (arg1 - f)/ f
res1 = sqrt(S.One + g)._eval_nseries(x, n=n, logx=logx)
res = (res1.removeO()*sqrt(f)).expand()
return ser.removeO().subs(t, res).expand().powsimp() + O(x**n, x)
if arg0 is S.NegativeOne:
t = Dummy('t', positive=True)
ser = acsc(S.NegativeOne - t**2).rewrite(log).nseries(t, 0, 2*n)
arg1 = S.NegativeOne - self.args[0]
f = arg1.as_leading_term(x)
g = (arg1 - f)/ f
res1 = sqrt(S.One + g)._eval_nseries(x, n=n, logx=logx)
res = (res1.removeO()*sqrt(f)).expand()
return ser.removeO().subs(t, res).expand().powsimp() + O(x**n, x)
res = Function._eval_nseries(self, x, n=n, logx=logx)
if arg0 is S.ComplexInfinity:
return res
if cdir != 0:
cdir = self.args[0].dir(x, cdir)
if im(cdir) < 0 and arg0.is_real and arg0 > S.Zero and arg0 < S.One:
return S.Pi - res
elif im(cdir) > 0 and arg0.is_real and arg0 < S.Zero and arg0 > S.NegativeOne:
return -S.Pi - res
return res
def _eval_rewrite_as_log(self, arg, **kwargs):
return -S.ImaginaryUnit*log(S.ImaginaryUnit/arg + sqrt(1 - 1/arg**2))
def _eval_rewrite_as_asin(self, arg, **kwargs):
return asin(1/arg)
def _eval_rewrite_as_acos(self, arg, **kwargs):
return S.Pi/2 - acos(1/arg)
def _eval_rewrite_as_atan(self, arg, **kwargs):
return sqrt(arg**2)/arg*(S.Pi/2 - atan(sqrt(arg**2 - 1)))
def _eval_rewrite_as_acot(self, arg, **kwargs):
return sqrt(arg**2)/arg*(S.Pi/2 - acot(1/sqrt(arg**2 - 1)))
def _eval_rewrite_as_asec(self, arg, **kwargs):
return S.Pi/2 - asec(arg)
class atan2(InverseTrigonometricFunction):
r"""
The function ``atan2(y, x)`` computes `\operatorname{atan}(y/x)` taking
two arguments `y` and `x`. Signs of both `y` and `x` are considered to
determine the appropriate quadrant of `\operatorname{atan}(y/x)`.
The range is `(-\pi, \pi]`. The complete definition reads as follows:
.. math::
\operatorname{atan2}(y, x) =
\begin{cases}
\arctan\left(\frac y x\right) & \qquad x > 0 \\
\arctan\left(\frac y x\right) + \pi& \qquad y \ge 0, x < 0 \\
\arctan\left(\frac y x\right) - \pi& \qquad y < 0, x < 0 \\
+\frac{\pi}{2} & \qquad y > 0, x = 0 \\
-\frac{\pi}{2} & \qquad y < 0, x = 0 \\
\text{undefined} & \qquad y = 0, x = 0
\end{cases}
Attention: Note the role reversal of both arguments. The `y`-coordinate
is the first argument and the `x`-coordinate the second.
If either `x` or `y` is complex:
.. math::
\operatorname{atan2}(y, x) =
-i\log\left(\frac{x + iy}{\sqrt{x**2 + y**2}}\right)
Examples
========
Going counter-clock wise around the origin we find the
following angles:
>>> from sympy import atan2
>>> atan2(0, 1)
0
>>> atan2(1, 1)
pi/4
>>> atan2(1, 0)
pi/2
>>> atan2(1, -1)
3*pi/4
>>> atan2(0, -1)
pi
>>> atan2(-1, -1)
-3*pi/4
>>> atan2(-1, 0)
-pi/2
>>> atan2(-1, 1)
-pi/4
which are all correct. Compare this to the results of the ordinary
`\operatorname{atan}` function for the point `(x, y) = (-1, 1)`
>>> from sympy import atan, S
>>> atan(S(1)/-1)
-pi/4
>>> atan2(1, -1)
3*pi/4
where only the `\operatorname{atan2}` function reurns what we expect.
We can differentiate the function with respect to both arguments:
>>> from sympy import diff
>>> from sympy.abc import x, y
>>> diff(atan2(y, x), x)
-y/(x**2 + y**2)
>>> diff(atan2(y, x), y)
x/(x**2 + y**2)
We can express the `\operatorname{atan2}` function in terms of
complex logarithms:
>>> from sympy import log
>>> atan2(y, x).rewrite(log)
-I*log((x + I*y)/sqrt(x**2 + y**2))
and in terms of `\operatorname(atan)`:
>>> from sympy import atan
>>> atan2(y, x).rewrite(atan)
Piecewise((2*atan(y/(x + sqrt(x**2 + y**2))), Ne(y, 0)), (pi, re(x) < 0), (0, Ne(x, 0)), (nan, True))
but note that this form is undefined on the negative real axis.
See Also
========
sin, csc, cos, sec, tan, cot
asin, acsc, acos, asec, atan, acot
References
==========
.. [1] https://en.wikipedia.org/wiki/Inverse_trigonometric_functions
.. [2] https://en.wikipedia.org/wiki/Atan2
.. [3] http://functions.wolfram.com/ElementaryFunctions/ArcTan2
"""
@classmethod
def eval(cls, y, x):
from sympy.functions.elementary.complexes import (im, re)
from sympy.functions.special.delta_functions import Heaviside
if x is S.NegativeInfinity:
if y.is_zero:
# Special case y = 0 because we define Heaviside(0) = 1/2
return S.Pi
return 2*S.Pi*(Heaviside(re(y))) - S.Pi
elif x is S.Infinity:
return S.Zero
elif x.is_imaginary and y.is_imaginary and x.is_number and y.is_number:
x = im(x)
y = im(y)
if x.is_extended_real and y.is_extended_real:
if x.is_positive:
return atan(y/x)
elif x.is_negative:
if y.is_negative:
return atan(y/x) - S.Pi
elif y.is_nonnegative:
return atan(y/x) + S.Pi
elif x.is_zero:
if y.is_positive:
return S.Pi/2
elif y.is_negative:
return -S.Pi/2
elif y.is_zero:
return S.NaN
if y.is_zero:
if x.is_extended_nonzero:
return S.Pi*(S.One - Heaviside(x))
if x.is_number:
return Piecewise((S.Pi, re(x) < 0),
(0, Ne(x, 0)),
(S.NaN, True))
if x.is_number and y.is_number:
return -S.ImaginaryUnit*log(
(x + S.ImaginaryUnit*y)/sqrt(x**2 + y**2))
def _eval_rewrite_as_log(self, y, x, **kwargs):
return -S.ImaginaryUnit*log((x + S.ImaginaryUnit*y)/sqrt(x**2 + y**2))
def _eval_rewrite_as_atan(self, y, x, **kwargs):
from sympy.functions.elementary.complexes import re
return Piecewise((2*atan(y/(x + sqrt(x**2 + y**2))), Ne(y, 0)),
(pi, re(x) < 0),
(0, Ne(x, 0)),
(S.NaN, True))
def _eval_rewrite_as_arg(self, y, x, **kwargs):
from sympy.functions.elementary.complexes import arg
if x.is_extended_real and y.is_extended_real:
return arg(x + y*S.ImaginaryUnit)
n = x + S.ImaginaryUnit*y
d = x**2 + y**2
return arg(n/sqrt(d)) - S.ImaginaryUnit*log(abs(n)/sqrt(abs(d)))
def _eval_is_extended_real(self):
return self.args[0].is_extended_real and self.args[1].is_extended_real
def _eval_conjugate(self):
return self.func(self.args[0].conjugate(), self.args[1].conjugate())
def fdiff(self, argindex):
y, x = self.args
if argindex == 1:
# Diff wrt y
return x/(x**2 + y**2)
elif argindex == 2:
# Diff wrt x
return -y/(x**2 + y**2)
else:
raise ArgumentIndexError(self, argindex)
def _eval_evalf(self, prec):
y, x = self.args
if x.is_extended_real and y.is_extended_real:
return super()._eval_evalf(prec)
|
677596a478dfd406ce1c80b6e50e39cf93c267d00d66fd151eeb7c917145c108 | from sympy.core import Function, S, sympify, NumberKind
from sympy.utilities.iterables import sift
from sympy.core.add import Add
from sympy.core.containers import Tuple
from sympy.core.operations import LatticeOp, ShortCircuit
from sympy.core.function import (Application, Lambda,
ArgumentIndexError)
from sympy.core.expr import Expr
from sympy.core.exprtools import factor_terms
from sympy.core.mod import Mod
from sympy.core.mul import Mul
from sympy.core.numbers import Rational
from sympy.core.power import Pow
from sympy.core.relational import Eq, Relational
from sympy.core.singleton import Singleton
from sympy.core.sorting import ordered
from sympy.core.symbol import Dummy
from sympy.core.rules import Transform
from sympy.core.logic import fuzzy_and, fuzzy_or, _torf
from sympy.core.traversal import walk
from sympy.core.numbers import Integer
from sympy.logic.boolalg import And, Or
def _minmax_as_Piecewise(op, *args):
# helper for Min/Max rewrite as Piecewise
from sympy.functions.elementary.piecewise import Piecewise
ec = []
for i, a in enumerate(args):
c = []
for j in range(i + 1, len(args)):
c.append(Relational(a, args[j], op))
ec.append((a, And(*c)))
return Piecewise(*ec)
class IdentityFunction(Lambda, metaclass=Singleton):
"""
The identity function
Examples
========
>>> from sympy import Id, Symbol
>>> x = Symbol('x')
>>> Id(x)
x
"""
_symbol = Dummy('x')
@property
def signature(self):
return Tuple(self._symbol)
@property
def expr(self):
return self._symbol
Id = S.IdentityFunction
###############################################################################
############################# ROOT and SQUARE ROOT FUNCTION ###################
###############################################################################
def sqrt(arg, evaluate=None):
"""Returns the principal square root.
Parameters
==========
evaluate : bool, optional
The parameter determines if the expression should be evaluated.
If ``None``, its value is taken from
``global_parameters.evaluate``.
Examples
========
>>> from sympy import sqrt, Symbol, S
>>> x = Symbol('x')
>>> sqrt(x)
sqrt(x)
>>> sqrt(x)**2
x
Note that sqrt(x**2) does not simplify to x.
>>> sqrt(x**2)
sqrt(x**2)
This is because the two are not equal to each other in general.
For example, consider x == -1:
>>> from sympy import Eq
>>> Eq(sqrt(x**2), x).subs(x, -1)
False
This is because sqrt computes the principal square root, so the square may
put the argument in a different branch. This identity does hold if x is
positive:
>>> y = Symbol('y', positive=True)
>>> sqrt(y**2)
y
You can force this simplification by using the powdenest() function with
the force option set to True:
>>> from sympy import powdenest
>>> sqrt(x**2)
sqrt(x**2)
>>> powdenest(sqrt(x**2), force=True)
x
To get both branches of the square root you can use the rootof function:
>>> from sympy import rootof
>>> [rootof(x**2-3,i) for i in (0,1)]
[-sqrt(3), sqrt(3)]
Although ``sqrt`` is printed, there is no ``sqrt`` function so looking for
``sqrt`` in an expression will fail:
>>> from sympy.utilities.misc import func_name
>>> func_name(sqrt(x))
'Pow'
>>> sqrt(x).has(sqrt)
Traceback (most recent call last):
...
sympy.core.sympify.SympifyError: SympifyError: <function sqrt at 0x10e8900d0>
To find ``sqrt`` look for ``Pow`` with an exponent of ``1/2``:
>>> (x + 1/sqrt(x)).find(lambda i: i.is_Pow and abs(i.exp) is S.Half)
{1/sqrt(x)}
See Also
========
sympy.polys.rootoftools.rootof, root, real_root
References
==========
.. [1] https://en.wikipedia.org/wiki/Square_root
.. [2] https://en.wikipedia.org/wiki/Principal_value
"""
# arg = sympify(arg) is handled by Pow
return Pow(arg, S.Half, evaluate=evaluate)
def cbrt(arg, evaluate=None):
"""Returns the principal cube root.
Parameters
==========
evaluate : bool, optional
The parameter determines if the expression should be evaluated.
If ``None``, its value is taken from
``global_parameters.evaluate``.
Examples
========
>>> from sympy import cbrt, Symbol
>>> x = Symbol('x')
>>> cbrt(x)
x**(1/3)
>>> cbrt(x)**3
x
Note that cbrt(x**3) does not simplify to x.
>>> cbrt(x**3)
(x**3)**(1/3)
This is because the two are not equal to each other in general.
For example, consider `x == -1`:
>>> from sympy import Eq
>>> Eq(cbrt(x**3), x).subs(x, -1)
False
This is because cbrt computes the principal cube root, this
identity does hold if `x` is positive:
>>> y = Symbol('y', positive=True)
>>> cbrt(y**3)
y
See Also
========
sympy.polys.rootoftools.rootof, root, real_root
References
==========
.. [1] https://en.wikipedia.org/wiki/Cube_root
.. [2] https://en.wikipedia.org/wiki/Principal_value
"""
return Pow(arg, Rational(1, 3), evaluate=evaluate)
def root(arg, n, k=0, evaluate=None):
r"""Returns the *k*-th *n*-th root of ``arg``.
Parameters
==========
k : int, optional
Should be an integer in $\{0, 1, ..., n-1\}$.
Defaults to the principal root if $0$.
evaluate : bool, optional
The parameter determines if the expression should be evaluated.
If ``None``, its value is taken from
``global_parameters.evaluate``.
Examples
========
>>> from sympy import root, Rational
>>> from sympy.abc import x, n
>>> root(x, 2)
sqrt(x)
>>> root(x, 3)
x**(1/3)
>>> root(x, n)
x**(1/n)
>>> root(x, -Rational(2, 3))
x**(-3/2)
To get the k-th n-th root, specify k:
>>> root(-2, 3, 2)
-(-1)**(2/3)*2**(1/3)
To get all n n-th roots you can use the rootof function.
The following examples show the roots of unity for n
equal 2, 3 and 4:
>>> from sympy import rootof
>>> [rootof(x**2 - 1, i) for i in range(2)]
[-1, 1]
>>> [rootof(x**3 - 1,i) for i in range(3)]
[1, -1/2 - sqrt(3)*I/2, -1/2 + sqrt(3)*I/2]
>>> [rootof(x**4 - 1,i) for i in range(4)]
[-1, 1, -I, I]
SymPy, like other symbolic algebra systems, returns the
complex root of negative numbers. This is the principal
root and differs from the text-book result that one might
be expecting. For example, the cube root of -8 does not
come back as -2:
>>> root(-8, 3)
2*(-1)**(1/3)
The real_root function can be used to either make the principal
result real (or simply to return the real root directly):
>>> from sympy import real_root
>>> real_root(_)
-2
>>> real_root(-32, 5)
-2
Alternatively, the n//2-th n-th root of a negative number can be
computed with root:
>>> root(-32, 5, 5//2)
-2
See Also
========
sympy.polys.rootoftools.rootof
sympy.core.power.integer_nthroot
sqrt, real_root
References
==========
.. [1] https://en.wikipedia.org/wiki/Square_root
.. [2] https://en.wikipedia.org/wiki/Real_root
.. [3] https://en.wikipedia.org/wiki/Root_of_unity
.. [4] https://en.wikipedia.org/wiki/Principal_value
.. [5] http://mathworld.wolfram.com/CubeRoot.html
"""
n = sympify(n)
if k:
return Mul(Pow(arg, S.One/n, evaluate=evaluate), S.NegativeOne**(2*k/n), evaluate=evaluate)
return Pow(arg, 1/n, evaluate=evaluate)
def real_root(arg, n=None, evaluate=None):
"""Return the real *n*'th-root of *arg* if possible.
Parameters
==========
n : int or None, optional
If *n* is ``None``, then all instances of
``(-n)**(1/odd)`` will be changed to ``-n**(1/odd)``.
This will only create a real root of a principal root.
The presence of other factors may cause the result to not be
real.
evaluate : bool, optional
The parameter determines if the expression should be evaluated.
If ``None``, its value is taken from
``global_parameters.evaluate``.
Examples
========
>>> from sympy import root, real_root
>>> real_root(-8, 3)
-2
>>> root(-8, 3)
2*(-1)**(1/3)
>>> real_root(_)
-2
If one creates a non-principal root and applies real_root, the
result will not be real (so use with caution):
>>> root(-8, 3, 2)
-2*(-1)**(2/3)
>>> real_root(_)
-2*(-1)**(2/3)
See Also
========
sympy.polys.rootoftools.rootof
sympy.core.power.integer_nthroot
root, sqrt
"""
from sympy.functions.elementary.complexes import Abs, im, sign
from sympy.functions.elementary.piecewise import Piecewise
if n is not None:
return Piecewise(
(root(arg, n, evaluate=evaluate), Or(Eq(n, S.One), Eq(n, S.NegativeOne))),
(Mul(sign(arg), root(Abs(arg), n, evaluate=evaluate), evaluate=evaluate),
And(Eq(im(arg), S.Zero), Eq(Mod(n, 2), S.One))),
(root(arg, n, evaluate=evaluate), True))
rv = sympify(arg)
n1pow = Transform(lambda x: -(-x.base)**x.exp,
lambda x:
x.is_Pow and
x.base.is_negative and
x.exp.is_Rational and
x.exp.p == 1 and x.exp.q % 2)
return rv.xreplace(n1pow)
###############################################################################
############################# MINIMUM and MAXIMUM #############################
###############################################################################
class MinMaxBase(Expr, LatticeOp):
def __new__(cls, *args, **assumptions):
evaluate = assumptions.pop('evaluate', True)
args = (sympify(arg) for arg in args)
# first standard filter, for cls.zero and cls.identity
# also reshape Max(a, Max(b, c)) to Max(a, b, c)
if evaluate:
try:
args = frozenset(cls._new_args_filter(args))
except ShortCircuit:
return cls.zero
else:
args = frozenset(args)
if evaluate:
# remove redundant args that are easily identified
args = cls._collapse_arguments(args, **assumptions)
# find local zeros
args = cls._find_localzeros(args, **assumptions)
if not args:
return cls.identity
if len(args) == 1:
return list(args).pop()
# base creation
_args = frozenset(args)
obj = Expr.__new__(cls, *ordered(_args), **assumptions)
obj._argset = _args
return obj
@classmethod
def _collapse_arguments(cls, args, **assumptions):
"""Remove redundant args.
Examples
========
>>> from sympy import Min, Max
>>> from sympy.abc import a, b, c, d, e
Any arg in parent that appears in any
parent-like function in any of the flat args
of parent can be removed from that sub-arg:
>>> Min(a, Max(b, Min(a, c, d)))
Min(a, Max(b, Min(c, d)))
If the arg of parent appears in an opposite-than parent
function in any of the flat args of parent that function
can be replaced with the arg:
>>> Min(a, Max(b, Min(c, d, Max(a, e))))
Min(a, Max(b, Min(a, c, d)))
"""
if not args:
return args
args = list(ordered(args))
if cls == Min:
other = Max
else:
other = Min
# find global comparable max of Max and min of Min if a new
# value is being introduced in these args at position 0 of
# the ordered args
if args[0].is_number:
sifted = mins, maxs = [], []
for i in args:
for v in walk(i, Min, Max):
if v.args[0].is_comparable:
sifted[isinstance(v, Max)].append(v)
small = Min.identity
for i in mins:
v = i.args[0]
if v.is_number and (v < small) == True:
small = v
big = Max.identity
for i in maxs:
v = i.args[0]
if v.is_number and (v > big) == True:
big = v
# at the point when this function is called from __new__,
# there may be more than one numeric arg present since
# local zeros have not been handled yet, so look through
# more than the first arg
if cls == Min:
for i in range(len(args)):
if not args[i].is_number:
break
if (args[i] < small) == True:
small = args[i]
elif cls == Max:
for i in range(len(args)):
if not args[i].is_number:
break
if (args[i] > big) == True:
big = args[i]
T = None
if cls == Min:
if small != Min.identity:
other = Max
T = small
elif big != Max.identity:
other = Min
T = big
if T is not None:
# remove numerical redundancy
for i in range(len(args)):
a = args[i]
if isinstance(a, other):
a0 = a.args[0]
if ((a0 > T) if other == Max else (a0 < T)) == True:
args[i] = cls.identity
# remove redundant symbolic args
def do(ai, a):
if not isinstance(ai, (Min, Max)):
return ai
cond = a in ai.args
if not cond:
return ai.func(*[do(i, a) for i in ai.args],
evaluate=False)
if isinstance(ai, cls):
return ai.func(*[do(i, a) for i in ai.args if i != a],
evaluate=False)
return a
for i, a in enumerate(args):
args[i + 1:] = [do(ai, a) for ai in args[i + 1:]]
# factor out common elements as for
# Min(Max(x, y), Max(x, z)) -> Max(x, Min(y, z))
# and vice versa when swapping Min/Max -- do this only for the
# easy case where all functions contain something in common;
# trying to find some optimal subset of args to modify takes
# too long
def factor_minmax(args):
is_other = lambda arg: isinstance(arg, other)
other_args, remaining_args = sift(args, is_other, binary=True)
if not other_args:
return args
# Min(Max(x, y, z), Max(x, y, u, v)) -> {x,y}, ({z}, {u,v})
arg_sets = [set(arg.args) for arg in other_args]
common = set.intersection(*arg_sets)
if not common:
return args
new_other_args = list(common)
arg_sets_diff = [arg_set - common for arg_set in arg_sets]
# If any set is empty after removing common then all can be
# discarded e.g. Min(Max(a, b, c), Max(a, b)) -> Max(a, b)
if all(arg_sets_diff):
other_args_diff = [other(*s, evaluate=False) for s in arg_sets_diff]
new_other_args.append(cls(*other_args_diff, evaluate=False))
other_args_factored = other(*new_other_args, evaluate=False)
return remaining_args + [other_args_factored]
if len(args) > 1:
args = factor_minmax(args)
return args
@classmethod
def _new_args_filter(cls, arg_sequence):
"""
Generator filtering args.
first standard filter, for cls.zero and cls.identity.
Also reshape Max(a, Max(b, c)) to Max(a, b, c),
and check arguments for comparability
"""
for arg in arg_sequence:
# pre-filter, checking comparability of arguments
if not isinstance(arg, Expr) or arg.is_extended_real is False or (
arg.is_number and
not arg.is_comparable):
raise ValueError("The argument '%s' is not comparable." % arg)
if arg == cls.zero:
raise ShortCircuit(arg)
elif arg == cls.identity:
continue
elif arg.func == cls:
yield from arg.args
else:
yield arg
@classmethod
def _find_localzeros(cls, values, **options):
"""
Sequentially allocate values to localzeros.
When a value is identified as being more extreme than another member it
replaces that member; if this is never true, then the value is simply
appended to the localzeros.
"""
localzeros = set()
for v in values:
is_newzero = True
localzeros_ = list(localzeros)
for z in localzeros_:
if id(v) == id(z):
is_newzero = False
else:
con = cls._is_connected(v, z)
if con:
is_newzero = False
if con is True or con == cls:
localzeros.remove(z)
localzeros.update([v])
if is_newzero:
localzeros.update([v])
return localzeros
@classmethod
def _is_connected(cls, x, y):
"""
Check if x and y are connected somehow.
"""
for i in range(2):
if x == y:
return True
t, f = Max, Min
for op in "><":
for j in range(2):
try:
if op == ">":
v = x >= y
else:
v = x <= y
except TypeError:
return False # non-real arg
if not v.is_Relational:
return t if v else f
t, f = f, t
x, y = y, x
x, y = y, x # run next pass with reversed order relative to start
# simplification can be expensive, so be conservative
# in what is attempted
x = factor_terms(x - y)
y = S.Zero
return False
def _eval_derivative(self, s):
# f(x).diff(s) -> x.diff(s) * f.fdiff(1)(s)
i = 0
l = []
for a in self.args:
i += 1
da = a.diff(s)
if da.is_zero:
continue
try:
df = self.fdiff(i)
except ArgumentIndexError:
df = Function.fdiff(self, i)
l.append(df * da)
return Add(*l)
def _eval_rewrite_as_Abs(self, *args, **kwargs):
from sympy.functions.elementary.complexes import Abs
s = (args[0] + self.func(*args[1:]))/2
d = abs(args[0] - self.func(*args[1:]))/2
return (s + d if isinstance(self, Max) else s - d).rewrite(Abs)
def evalf(self, n=15, **options):
return self.func(*[a.evalf(n, **options) for a in self.args])
def n(self, *args, **kwargs):
return self.evalf(*args, **kwargs)
_eval_is_algebraic = lambda s: _torf(i.is_algebraic for i in s.args)
_eval_is_antihermitian = lambda s: _torf(i.is_antihermitian for i in s.args)
_eval_is_commutative = lambda s: _torf(i.is_commutative for i in s.args)
_eval_is_complex = lambda s: _torf(i.is_complex for i in s.args)
_eval_is_composite = lambda s: _torf(i.is_composite for i in s.args)
_eval_is_even = lambda s: _torf(i.is_even for i in s.args)
_eval_is_finite = lambda s: _torf(i.is_finite for i in s.args)
_eval_is_hermitian = lambda s: _torf(i.is_hermitian for i in s.args)
_eval_is_imaginary = lambda s: _torf(i.is_imaginary for i in s.args)
_eval_is_infinite = lambda s: _torf(i.is_infinite for i in s.args)
_eval_is_integer = lambda s: _torf(i.is_integer for i in s.args)
_eval_is_irrational = lambda s: _torf(i.is_irrational for i in s.args)
_eval_is_negative = lambda s: _torf(i.is_negative for i in s.args)
_eval_is_noninteger = lambda s: _torf(i.is_noninteger for i in s.args)
_eval_is_nonnegative = lambda s: _torf(i.is_nonnegative for i in s.args)
_eval_is_nonpositive = lambda s: _torf(i.is_nonpositive for i in s.args)
_eval_is_nonzero = lambda s: _torf(i.is_nonzero for i in s.args)
_eval_is_odd = lambda s: _torf(i.is_odd for i in s.args)
_eval_is_polar = lambda s: _torf(i.is_polar for i in s.args)
_eval_is_positive = lambda s: _torf(i.is_positive for i in s.args)
_eval_is_prime = lambda s: _torf(i.is_prime for i in s.args)
_eval_is_rational = lambda s: _torf(i.is_rational for i in s.args)
_eval_is_real = lambda s: _torf(i.is_real for i in s.args)
_eval_is_extended_real = lambda s: _torf(i.is_extended_real for i in s.args)
_eval_is_transcendental = lambda s: _torf(i.is_transcendental for i in s.args)
_eval_is_zero = lambda s: _torf(i.is_zero for i in s.args)
class Max(MinMaxBase, Application):
"""
Return, if possible, the maximum value of the list.
When number of arguments is equal one, then
return this argument.
When number of arguments is equal two, then
return, if possible, the value from (a, b) that is >= the other.
In common case, when the length of list greater than 2, the task
is more complicated. Return only the arguments, which are greater
than others, if it is possible to determine directional relation.
If is not possible to determine such a relation, return a partially
evaluated result.
Assumptions are used to make the decision too.
Also, only comparable arguments are permitted.
It is named ``Max`` and not ``max`` to avoid conflicts
with the built-in function ``max``.
Examples
========
>>> from sympy import Max, Symbol, oo
>>> from sympy.abc import x, y, z
>>> p = Symbol('p', positive=True)
>>> n = Symbol('n', negative=True)
>>> Max(x, -2)
Max(-2, x)
>>> Max(x, -2).subs(x, 3)
3
>>> Max(p, -2)
p
>>> Max(x, y)
Max(x, y)
>>> Max(x, y) == Max(y, x)
True
>>> Max(x, Max(y, z))
Max(x, y, z)
>>> Max(n, 8, p, 7, -oo)
Max(8, p)
>>> Max (1, x, oo)
oo
* Algorithm
The task can be considered as searching of supremums in the
directed complete partial orders [1]_.
The source values are sequentially allocated by the isolated subsets
in which supremums are searched and result as Max arguments.
If the resulted supremum is single, then it is returned.
The isolated subsets are the sets of values which are only the comparable
with each other in the current set. E.g. natural numbers are comparable with
each other, but not comparable with the `x` symbol. Another example: the
symbol `x` with negative assumption is comparable with a natural number.
Also there are "least" elements, which are comparable with all others,
and have a zero property (maximum or minimum for all elements). E.g. `oo`.
In case of it the allocation operation is terminated and only this value is
returned.
Assumption:
- if A > B > C then A > C
- if A == B then B can be removed
References
==========
.. [1] https://en.wikipedia.org/wiki/Directed_complete_partial_order
.. [2] https://en.wikipedia.org/wiki/Lattice_%28order%29
See Also
========
Min : find minimum values
"""
zero = S.Infinity
identity = S.NegativeInfinity
def fdiff( self, argindex ):
from sympy.functions.special.delta_functions import Heaviside
n = len(self.args)
if 0 < argindex and argindex <= n:
argindex -= 1
if n == 2:
return Heaviside(self.args[argindex] - self.args[1 - argindex])
newargs = tuple([self.args[i] for i in range(n) if i != argindex])
return Heaviside(self.args[argindex] - Max(*newargs))
else:
raise ArgumentIndexError(self, argindex)
def _eval_rewrite_as_Heaviside(self, *args, **kwargs):
from sympy.functions.special.delta_functions import Heaviside
return Add(*[j*Mul(*[Heaviside(j - i) for i in args if i!=j]) \
for j in args])
def _eval_rewrite_as_Piecewise(self, *args, **kwargs):
return _minmax_as_Piecewise('>=', *args)
def _eval_is_positive(self):
return fuzzy_or(a.is_positive for a in self.args)
def _eval_is_nonnegative(self):
return fuzzy_or(a.is_nonnegative for a in self.args)
def _eval_is_negative(self):
return fuzzy_and(a.is_negative for a in self.args)
class Min(MinMaxBase, Application):
"""
Return, if possible, the minimum value of the list.
It is named ``Min`` and not ``min`` to avoid conflicts
with the built-in function ``min``.
Examples
========
>>> from sympy import Min, Symbol, oo
>>> from sympy.abc import x, y
>>> p = Symbol('p', positive=True)
>>> n = Symbol('n', negative=True)
>>> Min(x, -2)
Min(-2, x)
>>> Min(x, -2).subs(x, 3)
-2
>>> Min(p, -3)
-3
>>> Min(x, y)
Min(x, y)
>>> Min(n, 8, p, -7, p, oo)
Min(-7, n)
See Also
========
Max : find maximum values
"""
zero = S.NegativeInfinity
identity = S.Infinity
def fdiff( self, argindex ):
from sympy.functions.special.delta_functions import Heaviside
n = len(self.args)
if 0 < argindex and argindex <= n:
argindex -= 1
if n == 2:
return Heaviside( self.args[1-argindex] - self.args[argindex] )
newargs = tuple([ self.args[i] for i in range(n) if i != argindex])
return Heaviside( Min(*newargs) - self.args[argindex] )
else:
raise ArgumentIndexError(self, argindex)
def _eval_rewrite_as_Heaviside(self, *args, **kwargs):
from sympy.functions.special.delta_functions import Heaviside
return Add(*[j*Mul(*[Heaviside(i-j) for i in args if i!=j]) \
for j in args])
def _eval_rewrite_as_Piecewise(self, *args, **kwargs):
return _minmax_as_Piecewise('<=', *args)
def _eval_is_positive(self):
return fuzzy_and(a.is_positive for a in self.args)
def _eval_is_nonnegative(self):
return fuzzy_and(a.is_nonnegative for a in self.args)
def _eval_is_negative(self):
return fuzzy_or(a.is_negative for a in self.args)
class Rem(Function):
"""Returns the remainder when ``p`` is divided by ``q`` where ``p`` is finite
and ``q`` is not equal to zero. The result, ``p - int(p/q)*q``, has the same sign
as the divisor.
Parameters
==========
p : Expr
Dividend.
q : Expr
Divisor.
Notes
=====
``Rem`` corresponds to the ``%`` operator in C.
Examples
========
>>> from sympy.abc import x, y
>>> from sympy import Rem
>>> Rem(x**3, y)
Rem(x**3, y)
>>> Rem(x**3, y).subs({x: -5, y: 3})
-2
See Also
========
Mod
"""
kind = NumberKind
@classmethod
def eval(cls, p, q):
def doit(p, q):
""" the function remainder if both p,q are numbers
and q is not zero
"""
if q.is_zero:
raise ZeroDivisionError("Division by zero")
if p is S.NaN or q is S.NaN or p.is_finite is False or q.is_finite is False:
return S.NaN
if p is S.Zero or p in (q, -q) or (p.is_integer and q == 1):
return S.Zero
if q.is_Number:
if p.is_Number:
return p - Integer(p/q)*q
rv = doit(p, q)
if rv is not None:
return rv
|
f519f1665ccece26438d621651719099e3d6ede911082f3ea59cb918053ae3d0 | from sympy.core import S, Function, diff, Tuple, Dummy
from sympy.core.basic import Basic, as_Basic
from sympy.core.numbers import Rational, NumberSymbol
from sympy.core.parameters import global_parameters
from sympy.core.relational import (Lt, Gt, Eq, Ne, Relational,
_canonical, _canonical_coeff)
from sympy.core.sorting import ordered
from sympy.functions.elementary.miscellaneous import Max, Min
from sympy.logic.boolalg import (And, Boolean, distribute_and_over_or, Not,
true, false, Or, ITE, simplify_logic, to_cnf, distribute_or_over_and)
from sympy.utilities.iterables import uniq, sift, common_prefix
from sympy.utilities.misc import filldedent, func_name
from itertools import product
Undefined = S.NaN # Piecewise()
class ExprCondPair(Tuple):
"""Represents an expression, condition pair."""
def __new__(cls, expr, cond):
expr = as_Basic(expr)
if cond == True:
return Tuple.__new__(cls, expr, true)
elif cond == False:
return Tuple.__new__(cls, expr, false)
elif isinstance(cond, Basic) and cond.has(Piecewise):
cond = piecewise_fold(cond)
if isinstance(cond, Piecewise):
cond = cond.rewrite(ITE)
if not isinstance(cond, Boolean):
raise TypeError(filldedent('''
Second argument must be a Boolean,
not `%s`''' % func_name(cond)))
return Tuple.__new__(cls, expr, cond)
@property
def expr(self):
"""
Returns the expression of this pair.
"""
return self.args[0]
@property
def cond(self):
"""
Returns the condition of this pair.
"""
return self.args[1]
@property
def is_commutative(self):
return self.expr.is_commutative
def __iter__(self):
yield self.expr
yield self.cond
def _eval_simplify(self, **kwargs):
return self.func(*[a.simplify(**kwargs) for a in self.args])
class Piecewise(Function):
"""
Represents a piecewise function.
Usage:
Piecewise( (expr,cond), (expr,cond), ... )
- Each argument is a 2-tuple defining an expression and condition
- The conds are evaluated in turn returning the first that is True.
If any of the evaluated conds are not explicitly False,
e.g. ``x < 1``, the function is returned in symbolic form.
- If the function is evaluated at a place where all conditions are False,
nan will be returned.
- Pairs where the cond is explicitly False, will be removed and no pair
appearing after a True condition will ever be retained. If a single
pair with a True condition remains, it will be returned, even when
evaluation is False.
Examples
========
>>> from sympy import Piecewise, log, piecewise_fold
>>> from sympy.abc import x, y
>>> f = x**2
>>> g = log(x)
>>> p = Piecewise((0, x < -1), (f, x <= 1), (g, True))
>>> p.subs(x,1)
1
>>> p.subs(x,5)
log(5)
Booleans can contain Piecewise elements:
>>> cond = (x < y).subs(x, Piecewise((2, x < 0), (3, True))); cond
Piecewise((2, x < 0), (3, True)) < y
The folded version of this results in a Piecewise whose
expressions are Booleans:
>>> folded_cond = piecewise_fold(cond); folded_cond
Piecewise((2 < y, x < 0), (3 < y, True))
When a Boolean containing Piecewise (like cond) or a Piecewise
with Boolean expressions (like folded_cond) is used as a condition,
it is converted to an equivalent ITE object:
>>> Piecewise((1, folded_cond))
Piecewise((1, ITE(x < 0, y > 2, y > 3)))
When a condition is an ITE, it will be converted to a simplified
Boolean expression:
>>> piecewise_fold(_)
Piecewise((1, ((x >= 0) | (y > 2)) & ((y > 3) | (x < 0))))
See Also
========
piecewise_fold, ITE
"""
nargs = None
is_Piecewise = True
def __new__(cls, *args, **options):
if len(args) == 0:
raise TypeError("At least one (expr, cond) pair expected.")
# (Try to) sympify args first
newargs = []
for ec in args:
# ec could be a ExprCondPair or a tuple
pair = ExprCondPair(*getattr(ec, 'args', ec))
cond = pair.cond
if cond is false:
continue
newargs.append(pair)
if cond is true:
break
eval = options.pop('evaluate', global_parameters.evaluate)
if eval:
r = cls.eval(*newargs)
if r is not None:
return r
elif len(newargs) == 1 and newargs[0].cond == True:
return newargs[0].expr
return Basic.__new__(cls, *newargs, **options)
@classmethod
def eval(cls, *_args):
"""Either return a modified version of the args or, if no
modifications were made, return None.
Modifications that are made here:
1) relationals are made canonical
2) any False conditions are dropped
3) any repeat of a previous condition is ignored
3) any args past one with a true condition are dropped
If there are no args left, nan will be returned.
If there is a single arg with a True condition, its
corresponding expression will be returned.
EXAMPLES
========
>>> from sympy import Piecewise
>>> from sympy.abc import x
>>> cond = -x < -1
>>> args = [(1, cond), (4, cond), (3, False), (2, True), (5, x < 1)]
>>> Piecewise(*args, evaluate=False)
Piecewise((1, -x < -1), (4, -x < -1), (2, True))
>>> Piecewise(*args)
Piecewise((1, x > 1), (2, True))
"""
if not _args:
return Undefined
if len(_args) == 1 and _args[0][-1] == True:
return _args[0][0]
newargs = [] # the unevaluated conditions
current_cond = set() # the conditions up to a given e, c pair
for expr, cond in _args:
cond = cond.replace(
lambda _: _.is_Relational, _canonical_coeff)
# Check here if expr is a Piecewise and collapse if one of
# the conds in expr matches cond. This allows the collapsing
# of Piecewise((Piecewise((x,x<0)),x<0)) to Piecewise((x,x<0)).
# This is important when using piecewise_fold to simplify
# multiple Piecewise instances having the same conds.
# Eventually, this code should be able to collapse Piecewise's
# having different intervals, but this will probably require
# using the new assumptions.
if isinstance(expr, Piecewise):
unmatching = []
for i, (e, c) in enumerate(expr.args):
if c in current_cond:
# this would already have triggered
continue
if c == cond:
if c != True:
# nothing past this condition will ever
# trigger and only those args before this
# that didn't match a previous condition
# could possibly trigger
if unmatching:
expr = Piecewise(*(
unmatching + [(e, c)]))
else:
expr = e
break
else:
unmatching.append((e, c))
# check for condition repeats
got = False
# -- if an And contains a condition that was
# already encountered, then the And will be
# False: if the previous condition was False
# then the And will be False and if the previous
# condition is True then then we wouldn't get to
# this point. In either case, we can skip this condition.
for i in ([cond] +
(list(cond.args) if isinstance(cond, And) else
[])):
if i in current_cond:
got = True
break
if got:
continue
# -- if not(c) is already in current_cond then c is
# a redundant condition in an And. This does not
# apply to Or, however: (e1, c), (e2, Or(~c, d))
# is not (e1, c), (e2, d) because if c and d are
# both False this would give no results when the
# true answer should be (e2, True)
if isinstance(cond, And):
nonredundant = []
for c in cond.args:
if isinstance(c, Relational):
if c.negated.canonical in current_cond:
continue
# if a strict inequality appears after
# a non-strict one, then the condition is
# redundant
if isinstance(c, (Lt, Gt)) and (
c.weak in current_cond):
cond = False
break
nonredundant.append(c)
else:
cond = cond.func(*nonredundant)
elif isinstance(cond, Relational):
if cond.negated.canonical in current_cond:
cond = S.true
current_cond.add(cond)
# collect successive e,c pairs when exprs or cond match
if newargs:
if newargs[-1].expr == expr:
orcond = Or(cond, newargs[-1].cond)
if isinstance(orcond, (And, Or)):
orcond = distribute_and_over_or(orcond)
newargs[-1] = ExprCondPair(expr, orcond)
continue
elif newargs[-1].cond == cond:
newargs[-1] = ExprCondPair(expr, cond)
continue
newargs.append(ExprCondPair(expr, cond))
# some conditions may have been redundant
missing = len(newargs) != len(_args)
# some conditions may have changed
same = all(a == b for a, b in zip(newargs, _args))
# if either change happened we return the expr with the
# updated args
if not newargs:
raise ValueError(filldedent('''
There are no conditions (or none that
are not trivially false) to define an
expression.'''))
if missing or not same:
return cls(*newargs)
def doit(self, **hints):
"""
Evaluate this piecewise function.
"""
newargs = []
for e, c in self.args:
if hints.get('deep', True):
if isinstance(e, Basic):
newe = e.doit(**hints)
if newe != self:
e = newe
if isinstance(c, Basic):
c = c.doit(**hints)
newargs.append((e, c))
return self.func(*newargs)
def _eval_simplify(self, **kwargs):
return piecewise_simplify(self, **kwargs)
def _eval_as_leading_term(self, x, logx=None, cdir=0):
for e, c in self.args:
if c == True or c.subs(x, 0) == True:
return e.as_leading_term(x)
def _eval_adjoint(self):
return self.func(*[(e.adjoint(), c) for e, c in self.args])
def _eval_conjugate(self):
return self.func(*[(e.conjugate(), c) for e, c in self.args])
def _eval_derivative(self, x):
return self.func(*[(diff(e, x), c) for e, c in self.args])
def _eval_evalf(self, prec):
return self.func(*[(e._evalf(prec), c) for e, c in self.args])
def piecewise_integrate(self, x, **kwargs):
"""Return the Piecewise with each expression being
replaced with its antiderivative. To obtain a continuous
antiderivative, use the `integrate` function or method.
Examples
========
>>> from sympy import Piecewise
>>> from sympy.abc import x
>>> p = Piecewise((0, x < 0), (1, x < 1), (2, True))
>>> p.piecewise_integrate(x)
Piecewise((0, x < 0), (x, x < 1), (2*x, True))
Note that this does not give a continuous function, e.g.
at x = 1 the 3rd condition applies and the antiderivative
there is 2*x so the value of the antiderivative is 2:
>>> anti = _
>>> anti.subs(x, 1)
2
The continuous derivative accounts for the integral *up to*
the point of interest, however:
>>> p.integrate(x)
Piecewise((0, x < 0), (x, x < 1), (2*x - 1, True))
>>> _.subs(x, 1)
1
See Also
========
Piecewise._eval_integral
"""
from sympy.integrals import integrate
return self.func(*[(integrate(e, x, **kwargs), c) for e, c in self.args])
def _handle_irel(self, x, handler):
"""Return either None (if the conditions of self depend only on x) else
a Piecewise expression whose expressions (handled by the handler that
was passed) are paired with the governing x-independent relationals,
e.g. Piecewise((A, a(x) & b(y)), (B, c(x) | c(y)) ->
Piecewise(
(handler(Piecewise((A, a(x) & True), (B, c(x) | True)), b(y) & c(y)),
(handler(Piecewise((A, a(x) & True), (B, c(x) | False)), b(y)),
(handler(Piecewise((A, a(x) & False), (B, c(x) | True)), c(y)),
(handler(Piecewise((A, a(x) & False), (B, c(x) | False)), True))
"""
# identify governing relationals
rel = self.atoms(Relational)
irel = list(ordered([r for r in rel if x not in r.free_symbols
and r not in (S.true, S.false)]))
if irel:
args = {}
exprinorder = []
for truth in product((1, 0), repeat=len(irel)):
reps = dict(zip(irel, truth))
# only store the true conditions since the false are implied
# when they appear lower in the Piecewise args
if 1 not in truth:
cond = None # flag this one so it doesn't get combined
else:
andargs = Tuple(*[i for i in reps if reps[i]])
free = list(andargs.free_symbols)
if len(free) == 1:
from sympy.solvers.inequalities import (
reduce_inequalities, _solve_inequality)
try:
t = reduce_inequalities(andargs, free[0])
# ValueError when there are potentially
# nonvanishing imaginary parts
except (ValueError, NotImplementedError):
# at least isolate free symbol on left
t = And(*[_solve_inequality(
a, free[0], linear=True)
for a in andargs])
else:
t = And(*andargs)
if t is S.false:
continue # an impossible combination
cond = t
expr = handler(self.xreplace(reps))
if isinstance(expr, self.func) and len(expr.args) == 1:
expr, econd = expr.args[0]
cond = And(econd, True if cond is None else cond)
# the ec pairs are being collected since all possibilities
# are being enumerated, but don't put the last one in since
# its expr might match a previous expression and it
# must appear last in the args
if cond is not None:
args.setdefault(expr, []).append(cond)
# but since we only store the true conditions we must maintain
# the order so that the expression with the most true values
# comes first
exprinorder.append(expr)
# convert collected conditions as args of Or
for k in args:
args[k] = Or(*args[k])
# take them in the order obtained
args = [(e, args[e]) for e in uniq(exprinorder)]
# add in the last arg
args.append((expr, True))
return Piecewise(*args)
def _eval_integral(self, x, _first=True, **kwargs):
"""Return the indefinite integral of the
Piecewise such that subsequent substitution of x with a
value will give the value of the integral (not including
the constant of integration) up to that point. To only
integrate the individual parts of Piecewise, use the
`piecewise_integrate` method.
Examples
========
>>> from sympy import Piecewise
>>> from sympy.abc import x
>>> p = Piecewise((0, x < 0), (1, x < 1), (2, True))
>>> p.integrate(x)
Piecewise((0, x < 0), (x, x < 1), (2*x - 1, True))
>>> p.piecewise_integrate(x)
Piecewise((0, x < 0), (x, x < 1), (2*x, True))
See Also
========
Piecewise.piecewise_integrate
"""
from sympy.integrals.integrals import integrate
if _first:
def handler(ipw):
if isinstance(ipw, self.func):
return ipw._eval_integral(x, _first=False, **kwargs)
else:
return ipw.integrate(x, **kwargs)
irv = self._handle_irel(x, handler)
if irv is not None:
return irv
# handle a Piecewise from -oo to oo with and no x-independent relationals
# -----------------------------------------------------------------------
ok, abei = self._intervals(x)
if not ok:
from sympy.integrals.integrals import Integral
return Integral(self, x) # unevaluated
pieces = [(a, b) for a, b, _, _ in abei]
oo = S.Infinity
done = [(-oo, oo, -1)]
for k, p in enumerate(pieces):
if p == (-oo, oo):
# all undone intervals will get this key
for j, (a, b, i) in enumerate(done):
if i == -1:
done[j] = a, b, k
break # nothing else to consider
N = len(done) - 1
for j, (a, b, i) in enumerate(reversed(done)):
if i == -1:
j = N - j
done[j: j + 1] = _clip(p, (a, b), k)
done = [(a, b, i) for a, b, i in done if a != b]
# append an arg if there is a hole so a reference to
# argument -1 will give Undefined
if any(i == -1 for (a, b, i) in done):
abei.append((-oo, oo, Undefined, -1))
# return the sum of the intervals
args = []
sum = None
for a, b, i in done:
anti = integrate(abei[i][-2], x, **kwargs)
if sum is None:
sum = anti
else:
sum = sum.subs(x, a)
if sum == Undefined:
sum = 0
sum += anti._eval_interval(x, a, x)
# see if we know whether b is contained in original
# condition
if b is S.Infinity:
cond = True
elif self.args[abei[i][-1]].cond.subs(x, b) == False:
cond = (x < b)
else:
cond = (x <= b)
args.append((sum, cond))
return Piecewise(*args)
def _eval_interval(self, sym, a, b, _first=True):
"""Evaluates the function along the sym in a given interval [a, b]"""
# FIXME: Currently complex intervals are not supported. A possible
# replacement algorithm, discussed in issue 5227, can be found in the
# following papers;
# http://portal.acm.org/citation.cfm?id=281649
# http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.70.4127&rep=rep1&type=pdf
if a is None or b is None:
# In this case, it is just simple substitution
return super()._eval_interval(sym, a, b)
else:
x, lo, hi = map(as_Basic, (sym, a, b))
if _first: # get only x-dependent relationals
def handler(ipw):
if isinstance(ipw, self.func):
return ipw._eval_interval(x, lo, hi, _first=None)
else:
return ipw._eval_interval(x, lo, hi)
irv = self._handle_irel(x, handler)
if irv is not None:
return irv
if (lo < hi) is S.false or (
lo is S.Infinity or hi is S.NegativeInfinity):
rv = self._eval_interval(x, hi, lo, _first=False)
if isinstance(rv, Piecewise):
rv = Piecewise(*[(-e, c) for e, c in rv.args])
else:
rv = -rv
return rv
if (lo < hi) is S.true or (
hi is S.Infinity or lo is S.NegativeInfinity):
pass
else:
_a = Dummy('lo')
_b = Dummy('hi')
a = lo if lo.is_comparable else _a
b = hi if hi.is_comparable else _b
pos = self._eval_interval(x, a, b, _first=False)
if a == _a and b == _b:
# it's purely symbolic so just swap lo and hi and
# change the sign to get the value for when lo > hi
neg, pos = (-pos.xreplace({_a: hi, _b: lo}),
pos.xreplace({_a: lo, _b: hi}))
else:
# at least one of the bounds was comparable, so allow
# _eval_interval to use that information when computing
# the interval with lo and hi reversed
neg, pos = (-self._eval_interval(x, hi, lo, _first=False),
pos.xreplace({_a: lo, _b: hi}))
# allow simplification based on ordering of lo and hi
p = Dummy('', positive=True)
if lo.is_Symbol:
pos = pos.xreplace({lo: hi - p}).xreplace({p: hi - lo})
neg = neg.xreplace({lo: hi + p}).xreplace({p: lo - hi})
elif hi.is_Symbol:
pos = pos.xreplace({hi: lo + p}).xreplace({p: hi - lo})
neg = neg.xreplace({hi: lo - p}).xreplace({p: lo - hi})
# evaluate limits that may have unevaluate Min/Max
touch = lambda _: _.replace(
lambda x: isinstance(x, (Min, Max)),
lambda x: x.func(*x.args))
neg = touch(neg)
pos = touch(pos)
# assemble return expression; make the first condition be Lt
# b/c then the first expression will look the same whether
# the lo or hi limit is symbolic
if a == _a: # the lower limit was symbolic
rv = Piecewise(
(pos,
lo < hi),
(neg,
True))
else:
rv = Piecewise(
(neg,
hi < lo),
(pos,
True))
if rv == Undefined:
raise ValueError("Can't integrate across undefined region.")
if any(isinstance(i, Piecewise) for i in (pos, neg)):
rv = piecewise_fold(rv)
return rv
# handle a Piecewise with lo <= hi and no x-independent relationals
# -----------------------------------------------------------------
ok, abei = self._intervals(x)
if not ok:
from sympy.integrals.integrals import Integral
# not being able to do the interval of f(x) can
# be stated as not being able to do the integral
# of f'(x) over the same range
return Integral(self.diff(x), (x, lo, hi)) # unevaluated
pieces = [(a, b) for a, b, _, _ in abei]
done = [(lo, hi, -1)]
oo = S.Infinity
for k, p in enumerate(pieces):
if p[:2] == (-oo, oo):
# all undone intervals will get this key
for j, (a, b, i) in enumerate(done):
if i == -1:
done[j] = a, b, k
break # nothing else to consider
N = len(done) - 1
for j, (a, b, i) in enumerate(reversed(done)):
if i == -1:
j = N - j
done[j: j + 1] = _clip(p, (a, b), k)
done = [(a, b, i) for a, b, i in done if a != b]
# return the sum of the intervals
sum = S.Zero
upto = None
for a, b, i in done:
if i == -1:
if upto is None:
return Undefined
# TODO simplify hi <= upto
return Piecewise((sum, hi <= upto), (Undefined, True))
sum += abei[i][-2]._eval_interval(x, a, b)
upto = b
return sum
def _intervals(self, sym, err_on_Eq=False):
"""Return a bool and a message (when bool is False), else a
list of unique tuples, (a, b, e, i), where a and b
are the lower and upper bounds in which the expression e of
argument i in self is defined and a < b (when involving
numbers) or a <= b when involving symbols.
If there are any relationals not involving sym, or any
relational cannot be solved for sym, the bool will be False
a message be given as the second return value. The calling
routine should have removed such relationals before calling
this routine.
The evaluated conditions will be returned as ranges.
Discontinuous ranges will be returned separately with
identical expressions. The first condition that evaluates to
True will be returned as the last tuple with a, b = -oo, oo.
"""
from sympy.solvers.inequalities import _solve_inequality
assert isinstance(self, Piecewise)
def nonsymfail(cond):
return False, filldedent('''
A condition not involving
%s appeared: %s''' % (sym, cond))
def _solve_relational(r):
if sym not in r.free_symbols:
return nonsymfail(r)
try:
rv = _solve_inequality(r, sym)
except NotImplementedError:
return False, 'Unable to solve relational %s for %s.' % (r, sym)
if isinstance(rv, Relational):
free = rv.args[1].free_symbols
if rv.args[0] != sym or sym in free:
return False, 'Unable to solve relational %s for %s.' % (r, sym)
if rv.rel_op == '==':
# this equality has been affirmed to have the form
# Eq(sym, rhs) where rhs is sym-free; it represents
# a zero-width interval which will be ignored
# whether it is an isolated condition or contained
# within an And or an Or
rv = S.false
elif rv.rel_op == '!=':
try:
rv = Or(sym < rv.rhs, sym > rv.rhs)
except TypeError:
# e.g. x != I ==> all real x satisfy
rv = S.true
elif rv == (S.NegativeInfinity < sym) & (sym < S.Infinity):
rv = S.true
return True, rv
args = list(self.args)
# make self canonical wrt Relationals
keys = self.atoms(Relational)
reps = {}
for r in keys:
ok, s = _solve_relational(r)
if ok != True:
return False, ok
reps[r] = s
# process args individually so if any evaluate, their position
# in the original Piecewise will be known
args = [i.xreplace(reps) for i in self.args]
# precondition args
expr_cond = []
default = idefault = None
for i, (expr, cond) in enumerate(args):
if cond is S.false:
continue
if cond is S.true:
default = expr
idefault = i
break
if isinstance(cond, Eq):
# unanticipated condition, but it is here in case a
# replacement caused an Eq to appear
if err_on_Eq:
return False, 'encountered Eq condition: %s' % cond
continue # zero width interval
cond = to_cnf(cond)
if isinstance(cond, And):
cond = distribute_or_over_and(cond)
if isinstance(cond, Or):
expr_cond.extend(
[(i, expr, o) for o in cond.args
if not isinstance(o, Eq)])
elif cond is not S.false:
expr_cond.append((i, expr, cond))
elif cond is S.true:
default = expr
idefault = i
break
# determine intervals represented by conditions
int_expr = []
for iarg, expr, cond in expr_cond:
if isinstance(cond, And):
lower = S.NegativeInfinity
upper = S.Infinity
exclude = []
for cond2 in cond.args:
if not isinstance(cond2, Relational):
return False, 'expecting only Relationals'
if isinstance(cond2, Eq):
lower = upper # ignore
if err_on_Eq:
return False, 'encountered secondary Eq condition'
break
elif isinstance(cond2, Ne):
l, r = cond2.args
if l == sym:
exclude.append(r)
elif r == sym:
exclude.append(l)
else:
return nonsymfail(cond2)
continue
elif cond2.lts == sym:
upper = Min(cond2.gts, upper)
elif cond2.gts == sym:
lower = Max(cond2.lts, lower)
else:
return nonsymfail(cond2) # should never get here
if exclude:
exclude = list(ordered(exclude))
newcond = []
for i, e in enumerate(exclude):
if e < lower == True or e > upper == True:
continue
if not newcond:
newcond.append((None, lower)) # add a primer
newcond.append((newcond[-1][1], e))
newcond.append((newcond[-1][1], upper))
newcond.pop(0) # remove the primer
expr_cond.extend([(iarg, expr, And(i[0] < sym, sym < i[1])) for i in newcond])
continue
elif isinstance(cond, Relational) and cond.rel_op != '!=':
lower, upper = cond.lts, cond.gts # part 1: initialize with givens
if cond.lts == sym: # part 1a: expand the side ...
lower = S.NegativeInfinity # e.g. x <= 0 ---> -oo <= 0
elif cond.gts == sym: # part 1a: ... that can be expanded
upper = S.Infinity # e.g. x >= 0 ---> oo >= 0
else:
return nonsymfail(cond)
else:
return False, 'unrecognized condition: %s' % cond
lower, upper = lower, Max(lower, upper)
if err_on_Eq and lower == upper:
return False, 'encountered Eq condition'
if (lower >= upper) is not S.true:
int_expr.append((lower, upper, expr, iarg))
if default is not None:
int_expr.append(
(S.NegativeInfinity, S.Infinity, default, idefault))
return True, list(uniq(int_expr))
def _eval_nseries(self, x, n, logx, cdir=0):
args = [(ec.expr._eval_nseries(x, n, logx), ec.cond) for ec in self.args]
return self.func(*args)
def _eval_power(self, s):
return self.func(*[(e**s, c) for e, c in self.args])
def _eval_subs(self, old, new):
# this is strictly not necessary, but we can keep track
# of whether True or False conditions arise and be
# somewhat more efficient by avoiding other substitutions
# and avoiding invalid conditions that appear after a
# True condition
args = list(self.args)
args_exist = False
for i, (e, c) in enumerate(args):
c = c._subs(old, new)
if c != False:
args_exist = True
e = e._subs(old, new)
args[i] = (e, c)
if c == True:
break
if not args_exist:
args = ((Undefined, True),)
return self.func(*args)
def _eval_transpose(self):
return self.func(*[(e.transpose(), c) for e, c in self.args])
def _eval_template_is_attr(self, is_attr):
b = None
for expr, _ in self.args:
a = getattr(expr, is_attr)
if a is None:
return
if b is None:
b = a
elif b is not a:
return
return b
_eval_is_finite = lambda self: self._eval_template_is_attr(
'is_finite')
_eval_is_complex = lambda self: self._eval_template_is_attr('is_complex')
_eval_is_even = lambda self: self._eval_template_is_attr('is_even')
_eval_is_imaginary = lambda self: self._eval_template_is_attr(
'is_imaginary')
_eval_is_integer = lambda self: self._eval_template_is_attr('is_integer')
_eval_is_irrational = lambda self: self._eval_template_is_attr(
'is_irrational')
_eval_is_negative = lambda self: self._eval_template_is_attr('is_negative')
_eval_is_nonnegative = lambda self: self._eval_template_is_attr(
'is_nonnegative')
_eval_is_nonpositive = lambda self: self._eval_template_is_attr(
'is_nonpositive')
_eval_is_nonzero = lambda self: self._eval_template_is_attr(
'is_nonzero')
_eval_is_odd = lambda self: self._eval_template_is_attr('is_odd')
_eval_is_polar = lambda self: self._eval_template_is_attr('is_polar')
_eval_is_positive = lambda self: self._eval_template_is_attr('is_positive')
_eval_is_extended_real = lambda self: self._eval_template_is_attr(
'is_extended_real')
_eval_is_extended_positive = lambda self: self._eval_template_is_attr(
'is_extended_positive')
_eval_is_extended_negative = lambda self: self._eval_template_is_attr(
'is_extended_negative')
_eval_is_extended_nonzero = lambda self: self._eval_template_is_attr(
'is_extended_nonzero')
_eval_is_extended_nonpositive = lambda self: self._eval_template_is_attr(
'is_extended_nonpositive')
_eval_is_extended_nonnegative = lambda self: self._eval_template_is_attr(
'is_extended_nonnegative')
_eval_is_real = lambda self: self._eval_template_is_attr('is_real')
_eval_is_zero = lambda self: self._eval_template_is_attr(
'is_zero')
@classmethod
def __eval_cond(cls, cond):
"""Return the truth value of the condition."""
if cond == True:
return True
if isinstance(cond, Eq):
try:
diff = cond.lhs - cond.rhs
if diff.is_commutative:
return diff.is_zero
except TypeError:
pass
def as_expr_set_pairs(self, domain=None):
"""Return tuples for each argument of self that give
the expression and the interval in which it is valid
which is contained within the given domain.
If a condition cannot be converted to a set, an error
will be raised. The variable of the conditions is
assumed to be real; sets of real values are returned.
Examples
========
>>> from sympy import Piecewise, Interval
>>> from sympy.abc import x
>>> p = Piecewise(
... (1, x < 2),
... (2,(x > 0) & (x < 4)),
... (3, True))
>>> p.as_expr_set_pairs()
[(1, Interval.open(-oo, 2)),
(2, Interval.Ropen(2, 4)),
(3, Interval(4, oo))]
>>> p.as_expr_set_pairs(Interval(0, 3))
[(1, Interval.Ropen(0, 2)),
(2, Interval(2, 3))]
"""
if domain is None:
domain = S.Reals
exp_sets = []
U = domain
complex = not domain.is_subset(S.Reals)
cond_free = set()
for expr, cond in self.args:
cond_free |= cond.free_symbols
if len(cond_free) > 1:
raise NotImplementedError(filldedent('''
multivariate conditions are not handled.'''))
if complex:
for i in cond.atoms(Relational):
if not isinstance(i, (Eq, Ne)):
raise ValueError(filldedent('''
Inequalities in the complex domain are
not supported. Try the real domain by
setting domain=S.Reals'''))
cond_int = U.intersect(cond.as_set())
U = U - cond_int
if cond_int != S.EmptySet:
exp_sets.append((expr, cond_int))
return exp_sets
def _eval_rewrite_as_ITE(self, *args, **kwargs):
byfree = {}
args = list(args)
default = any(c == True for b, c in args)
for i, (b, c) in enumerate(args):
if not isinstance(b, Boolean) and b != True:
raise TypeError(filldedent('''
Expecting Boolean or bool but got `%s`
''' % func_name(b)))
if c == True:
break
# loop over independent conditions for this b
for c in c.args if isinstance(c, Or) else [c]:
free = c.free_symbols
x = free.pop()
try:
byfree[x] = byfree.setdefault(
x, S.EmptySet).union(c.as_set())
except NotImplementedError:
if not default:
raise NotImplementedError(filldedent('''
A method to determine whether a multivariate
conditional is consistent with a complete coverage
of all variables has not been implemented so the
rewrite is being stopped after encountering `%s`.
This error would not occur if a default expression
like `(foo, True)` were given.
''' % c))
if byfree[x] in (S.UniversalSet, S.Reals):
# collapse the ith condition to True and break
args[i] = list(args[i])
c = args[i][1] = True
break
if c == True:
break
if c != True:
raise ValueError(filldedent('''
Conditions must cover all reals or a final default
condition `(foo, True)` must be given.
'''))
last, _ = args[i] # ignore all past ith arg
for a, c in reversed(args[:i]):
last = ITE(c, a, last)
return _canonical(last)
def _eval_rewrite_as_KroneckerDelta(self, *args):
from sympy.functions.special.tensor_functions import KroneckerDelta
rules = {
And: [False, False],
Or: [True, True],
Not: [True, False],
Eq: [None, None],
Ne: [None, None]
}
class UnrecognizedCondition(Exception):
pass
def rewrite(cond):
if isinstance(cond, Eq):
return KroneckerDelta(*cond.args)
if isinstance(cond, Ne):
return 1 - KroneckerDelta(*cond.args)
cls, args = type(cond), cond.args
if cls not in rules:
raise UnrecognizedCondition(cls)
b1, b2 = rules[cls]
k = 1
for c in args:
if b1:
k *= 1 - rewrite(c)
else:
k *= rewrite(c)
if b2:
return 1 - k
return k
conditions = []
true_value = None
for value, cond in args:
if type(cond) in rules:
conditions.append((value, cond))
elif cond is S.true:
if true_value is None:
true_value = value
else:
return
if true_value is not None:
result = true_value
for value, cond in conditions[::-1]:
try:
k = rewrite(cond)
result = k * value + (1 - k) * result
except UnrecognizedCondition:
return
return result
def piecewise_fold(expr, evaluate=True):
"""
Takes an expression containing a piecewise function and returns the
expression in piecewise form. In addition, any ITE conditions are
rewritten in negation normal form and simplified.
The final Piecewise is evaluated (default) but if the raw form
is desired, send ``evaluate=False``; if trivial evaluation is
desired, send ``evaluate=None`` and duplicate conditions and
processing of True and False will be handled.
Examples
========
>>> from sympy import Piecewise, piecewise_fold, sympify as S
>>> from sympy.abc import x
>>> p = Piecewise((x, x < 1), (1, S(1) <= x))
>>> piecewise_fold(x*p)
Piecewise((x**2, x < 1), (x, True))
See Also
========
Piecewise
"""
if not isinstance(expr, Basic) or not expr.has(Piecewise):
return expr
new_args = []
if isinstance(expr, (ExprCondPair, Piecewise)):
for e, c in expr.args:
if not isinstance(e, Piecewise):
e = piecewise_fold(e)
# we don't keep Piecewise in condition because
# it has to be checked to see that it's complete
# and we convert it to ITE at that time
assert not c.has(Piecewise) # pragma: no cover
if isinstance(c, ITE):
c = c.to_nnf()
c = simplify_logic(c, form='cnf')
if isinstance(e, Piecewise):
new_args.extend([(piecewise_fold(ei), And(ci, c))
for ei, ci in e.args])
else:
new_args.append((e, c))
else:
# Given
# P1 = Piecewise((e11, c1), (e12, c2), A)
# P2 = Piecewise((e21, c1), (e22, c2), B)
# ...
# the folding of f(P1, P2) is trivially
# Piecewise(
# (f(e11, e21), c1),
# (f(e12, e22), c2),
# (f(Piecewise(A), Piecewise(B)), True))
# Certain objects end up rewriting themselves as thus, so
# we do that grouping before the more generic folding.
# The following applies this idea when f = Add or f = Mul
# (and the expression is commutative).
if expr.is_Add or expr.is_Mul and expr.is_commutative:
p, args = sift(expr.args, lambda x: x.is_Piecewise, binary=True)
pc = sift(p, lambda x: tuple([c for e,c in x.args]))
for c in list(ordered(pc)):
if len(pc[c]) > 1:
pargs = [list(i.args) for i in pc[c]]
# the first one is the same; there may be more
com = common_prefix(*[
[i.cond for i in j] for j in pargs])
n = len(com)
collected = []
for i in range(n):
collected.append((
expr.func(*[ai[i].expr for ai in pargs]),
com[i]))
remains = []
for a in pargs:
if n == len(a): # no more args
continue
if a[n].cond == True: # no longer Piecewise
remains.append(a[n].expr)
else: # restore the remaining Piecewise
remains.append(
Piecewise(*a[n:], evaluate=False))
if remains:
collected.append((expr.func(*remains), True))
args.append(Piecewise(*collected, evaluate=False))
continue
args.extend(pc[c])
else:
args = expr.args
# fold
folded = list(map(piecewise_fold, args))
for ec in product(*[
(i.args if isinstance(i, Piecewise) else
[(i, true)]) for i in folded]):
e, c = zip(*ec)
new_args.append((expr.func(*e), And(*c)))
if evaluate is None:
# don't return duplicate conditions, otherwise don't evaluate
new_args = list(reversed([(e, c) for c, e in {
c: e for e, c in reversed(new_args)}.items()]))
rv = Piecewise(*new_args, evaluate=evaluate)
if evaluate is None and len(rv.args) == 1 and rv.args[0].cond == True:
return rv.args[0].expr
return rv
def _clip(A, B, k):
"""Return interval B as intervals that are covered by A (keyed
to k) and all other intervals of B not covered by A keyed to -1.
The reference point of each interval is the rhs; if the lhs is
greater than the rhs then an interval of zero width interval will
result, e.g. (4, 1) is treated like (1, 1).
Examples
========
>>> from sympy.functions.elementary.piecewise import _clip
>>> from sympy import Tuple
>>> A = Tuple(1, 3)
>>> B = Tuple(2, 4)
>>> _clip(A, B, 0)
[(2, 3, 0), (3, 4, -1)]
Interpretation: interval portion (2, 3) of interval (2, 4) is
covered by interval (1, 3) and is keyed to 0 as requested;
interval (3, 4) was not covered by (1, 3) and is keyed to -1.
"""
a, b = B
c, d = A
c, d = Min(Max(c, a), b), Min(Max(d, a), b)
a, b = Min(a, b), b
p = []
if a != c:
p.append((a, c, -1))
else:
pass
if c != d:
p.append((c, d, k))
else:
pass
if b != d:
if d == c and p and p[-1][-1] == -1:
p[-1] = p[-1][0], b, -1
else:
p.append((d, b, -1))
else:
pass
return p
def piecewise_simplify_arguments(expr, **kwargs):
from sympy.simplify.simplify import simplify
args = []
f1 = expr.args[0].cond.free_symbols
if len(f1) == 1 and not expr.atoms(Eq):
x = f1.pop()
# this won't return intervals involving Eq
# and it won't handle symbols treated as
# booleans
ok, abe_ = expr._intervals(x, err_on_Eq=True)
if ok:
args = []
for a, b, e, i in abe_:
c = expr.args[i].cond
if a is S.NegativeInfinity:
if b is S.Infinity:
c = S.true
else:
if c.subs(x, b) == True:
c = (x <= b)
else:
c = (x < b)
else:
incl_a = (c.subs(x, a) == True)
incl_b = (c.subs(x, b) == True)
if incl_a and incl_b:
if b.is_infinite:
c = (x >= a)
else:
c = And(a <= x, x <= b)
elif incl_a:
c = And(a <= x, x < b)
elif incl_b:
if b.is_infinite:
c = (x > a)
else:
c = And(a < x, x <= b)
else:
c = And(a < x, x < b)
args.append((e, c))
args.append((Undefined, True))
expr = Piecewise(*args)
for e, c in expr.args:
if isinstance(e, Basic):
doit = kwargs.pop('doit', None)
# Skip doit to avoid growth at every call for some integrals
# and sums, see sympy/sympy#17165
newe = simplify(e, doit=False, **kwargs)
if newe != expr:
e = newe
if isinstance(c, Basic):
c = simplify(c, doit=doit, **kwargs)
args.append((e, c))
return Piecewise(*args)
def piecewise_simplify(expr, **kwargs):
expr = piecewise_simplify_arguments(expr, **kwargs)
if not isinstance(expr, Piecewise):
return expr
args = list(expr.args)
_blessed = lambda e: getattr(e.lhs, '_diff_wrt', False) and (
getattr(e.rhs, '_diff_wrt', None) or
isinstance(e.rhs, (Rational, NumberSymbol)))
for i, (expr, cond) in enumerate(args):
# try to simplify conditions and the expression for
# equalities that are part of the condition, e.g.
# Piecewise((n, And(Eq(n,0), Eq(n + m, 0))), (1, True))
# -> Piecewise((0, And(Eq(n, 0), Eq(m, 0))), (1, True))
if isinstance(cond, And):
eqs, other = sift(cond.args,
lambda i: isinstance(i, Eq), binary=True)
elif isinstance(cond, Eq):
eqs, other = [cond], []
else:
eqs = other = []
if eqs:
eqs = list(ordered(eqs))
for j, e in enumerate(eqs):
# these blessed lhs objects behave like Symbols
# and the rhs are simple replacements for the "symbols"
if _blessed(e):
expr = expr.subs(*e.args)
eqs[j + 1:] = [ei.subs(*e.args) for ei in eqs[j + 1:]]
other = [ei.subs(*e.args) for ei in other]
cond = And(*(eqs + other))
args[i] = args[i].func(expr, cond)
# See if expressions valid for an Equal expression happens to evaluate
# to the same function as in the next piecewise segment, see:
# https://github.com/sympy/sympy/issues/8458
prevexpr = None
for i, (expr, cond) in reversed(list(enumerate(args))):
if prevexpr is not None:
if isinstance(cond, And):
eqs, other = sift(cond.args,
lambda i: isinstance(i, Eq), binary=True)
elif isinstance(cond, Eq):
eqs, other = [cond], []
else:
eqs = other = []
_prevexpr = prevexpr
_expr = expr
if eqs and not other:
eqs = list(ordered(eqs))
for e in eqs:
# allow 2 args to collapse into 1 for any e
# otherwise limit simplification to only simple-arg
# Eq instances
if len(args) == 2 or _blessed(e):
_prevexpr = _prevexpr.subs(*e.args)
_expr = _expr.subs(*e.args)
# Did it evaluate to the same?
if _prevexpr == _expr:
# Set the expression for the Not equal section to the same
# as the next. These will be merged when creating the new
# Piecewise
args[i] = args[i].func(args[i+1][0], cond)
else:
# Update the expression that we compare against
prevexpr = expr
else:
prevexpr = expr
return Piecewise(*args)
|
2bca0e8d69dfdb3865d9fead736818f86d059e94c72df9da96884fd4da5753d1 | from typing import Tuple as tTuple
from sympy.core.basic import Basic
from sympy.core.expr import Expr
from sympy.core import Add, S
from sympy.core.evalf import get_integer_part, PrecisionExhausted
from sympy.core.function import Function
from sympy.core.logic import fuzzy_or
from sympy.core.numbers import Integer
from sympy.core.relational import Gt, Lt, Ge, Le, Relational, is_eq
from sympy.core.symbol import Symbol
from sympy.core.sympify import _sympify
from sympy.multipledispatch import dispatch
###############################################################################
######################### FLOOR and CEILING FUNCTIONS #########################
###############################################################################
class RoundFunction(Function):
"""The base class for rounding functions."""
args: tTuple[Expr]
@classmethod
def eval(cls, arg):
from sympy.functions.elementary.complexes import im
v = cls._eval_number(arg)
if v is not None:
return v
if arg.is_integer or arg.is_finite is False:
return arg
if arg.is_imaginary or (S.ImaginaryUnit*arg).is_real:
i = im(arg)
if not i.has(S.ImaginaryUnit):
return cls(i)*S.ImaginaryUnit
return cls(arg, evaluate=False)
# Integral, numerical, symbolic part
ipart = npart = spart = S.Zero
# Extract integral (or complex integral) terms
terms = Add.make_args(arg)
for t in terms:
if t.is_integer or (t.is_imaginary and im(t).is_integer):
ipart += t
elif t.has(Symbol):
spart += t
else:
npart += t
if not (npart or spart):
return ipart
# Evaluate npart numerically if independent of spart
if npart and (
not spart or
npart.is_real and (spart.is_imaginary or (S.ImaginaryUnit*spart).is_real) or
npart.is_imaginary and spart.is_real):
try:
r, i = get_integer_part(
npart, cls._dir, {}, return_ints=True)
ipart += Integer(r) + Integer(i)*S.ImaginaryUnit
npart = S.Zero
except (PrecisionExhausted, NotImplementedError):
pass
spart += npart
if not spart:
return ipart
elif spart.is_imaginary or (S.ImaginaryUnit*spart).is_real:
return ipart + cls(im(spart), evaluate=False)*S.ImaginaryUnit
elif isinstance(spart, (floor, ceiling)):
return ipart + spart
else:
return ipart + cls(spart, evaluate=False)
def _eval_is_finite(self):
return self.args[0].is_finite
def _eval_is_real(self):
return self.args[0].is_real
def _eval_is_integer(self):
return self.args[0].is_real
class floor(RoundFunction):
"""
Floor is a univariate function which returns the largest integer
value not greater than its argument. This implementation
generalizes floor to complex numbers by taking the floor of the
real and imaginary parts separately.
Examples
========
>>> from sympy import floor, E, I, S, Float, Rational
>>> floor(17)
17
>>> floor(Rational(23, 10))
2
>>> floor(2*E)
5
>>> floor(-Float(0.567))
-1
>>> floor(-I/2)
-I
>>> floor(S(5)/2 + 5*I/2)
2 + 2*I
See Also
========
sympy.functions.elementary.integers.ceiling
References
==========
.. [1] "Concrete mathematics" by Graham, pp. 87
.. [2] http://mathworld.wolfram.com/FloorFunction.html
"""
_dir = -1
@classmethod
def _eval_number(cls, arg):
if arg.is_Number:
return arg.floor()
elif any(isinstance(i, j)
for i in (arg, -arg) for j in (floor, ceiling)):
return arg
if arg.is_NumberSymbol:
return arg.approximation_interval(Integer)[0]
def _eval_as_leading_term(self, x, logx=None, cdir=0):
arg = self.args[0]
arg0 = arg.subs(x, 0)
r = self.subs(x, 0)
if arg0.is_finite:
if arg0 == r:
if cdir == 0:
ndirl = arg.dir(x, cdir=-1)
ndir = arg.dir(x, cdir=1)
if ndir != ndirl:
raise ValueError("Two sided limit of %s around 0"
"does not exist" % self)
else:
ndir = arg.dir(x, cdir=cdir)
return r - 1 if ndir.is_negative else r
else:
return r
return arg.as_leading_term(x, logx=logx, cdir=cdir)
def _eval_nseries(self, x, n, logx, cdir=0):
arg = self.args[0]
arg0 = arg.subs(x, 0)
if arg0.is_infinite:
from sympy.calculus.util import AccumBounds
from sympy.series.order import Order
s = arg._eval_nseries(x, n, logx, cdir)
o = Order(1, (x, 0)) if n <= 0 else AccumBounds(-1, 0)
return s + o
r = self.subs(x, 0)
if arg0 == r:
ndir = arg.dir(x, cdir=cdir if cdir != 0 else 1)
return r - 1 if ndir.is_negative else r
else:
return r
def _eval_is_negative(self):
return self.args[0].is_negative
def _eval_is_nonnegative(self):
return self.args[0].is_nonnegative
def _eval_rewrite_as_ceiling(self, arg, **kwargs):
return -ceiling(-arg)
def _eval_rewrite_as_frac(self, arg, **kwargs):
return arg - frac(arg)
def __le__(self, other):
other = S(other)
if self.args[0].is_real:
if other.is_integer:
return self.args[0] < other + 1
if other.is_number and other.is_real:
return self.args[0] < ceiling(other)
if self.args[0] == other and other.is_real:
return S.true
if other is S.Infinity and self.is_finite:
return S.true
return Le(self, other, evaluate=False)
def __ge__(self, other):
other = S(other)
if self.args[0].is_real:
if other.is_integer:
return self.args[0] >= other
if other.is_number and other.is_real:
return self.args[0] >= ceiling(other)
if self.args[0] == other and other.is_real:
return S.false
if other is S.NegativeInfinity and self.is_finite:
return S.true
return Ge(self, other, evaluate=False)
def __gt__(self, other):
other = S(other)
if self.args[0].is_real:
if other.is_integer:
return self.args[0] >= other + 1
if other.is_number and other.is_real:
return self.args[0] >= ceiling(other)
if self.args[0] == other and other.is_real:
return S.false
if other is S.NegativeInfinity and self.is_finite:
return S.true
return Gt(self, other, evaluate=False)
def __lt__(self, other):
other = S(other)
if self.args[0].is_real:
if other.is_integer:
return self.args[0] < other
if other.is_number and other.is_real:
return self.args[0] < ceiling(other)
if self.args[0] == other and other.is_real:
return S.false
if other is S.Infinity and self.is_finite:
return S.true
return Lt(self, other, evaluate=False)
@dispatch(floor, Expr)
def _eval_is_eq(lhs, rhs): # noqa:F811
return is_eq(lhs.rewrite(ceiling), rhs) or \
is_eq(lhs.rewrite(frac),rhs)
class ceiling(RoundFunction):
"""
Ceiling is a univariate function which returns the smallest integer
value not less than its argument. This implementation
generalizes ceiling to complex numbers by taking the ceiling of the
real and imaginary parts separately.
Examples
========
>>> from sympy import ceiling, E, I, S, Float, Rational
>>> ceiling(17)
17
>>> ceiling(Rational(23, 10))
3
>>> ceiling(2*E)
6
>>> ceiling(-Float(0.567))
0
>>> ceiling(I/2)
I
>>> ceiling(S(5)/2 + 5*I/2)
3 + 3*I
See Also
========
sympy.functions.elementary.integers.floor
References
==========
.. [1] "Concrete mathematics" by Graham, pp. 87
.. [2] http://mathworld.wolfram.com/CeilingFunction.html
"""
_dir = 1
@classmethod
def _eval_number(cls, arg):
if arg.is_Number:
return arg.ceiling()
elif any(isinstance(i, j)
for i in (arg, -arg) for j in (floor, ceiling)):
return arg
if arg.is_NumberSymbol:
return arg.approximation_interval(Integer)[1]
def _eval_as_leading_term(self, x, logx=None, cdir=0):
arg = self.args[0]
arg0 = arg.subs(x, 0)
r = self.subs(x, 0)
if arg0.is_finite:
if arg0 == r:
if cdir == 0:
ndirl = arg.dir(x, cdir=-1)
ndir = arg.dir(x, cdir=1)
if ndir != ndirl:
raise ValueError("Two sided limit of %s around 0"
"does not exist" % self)
else:
ndir = arg.dir(x, cdir=cdir)
return r if ndir.is_negative else r + 1
else:
return r
return arg.as_leading_term(x, logx=logx, cdir=cdir)
def _eval_nseries(self, x, n, logx, cdir=0):
arg = self.args[0]
arg0 = arg.subs(x, 0)
if arg0.is_infinite:
from sympy.calculus.util import AccumBounds
from sympy.series.order import Order
s = arg._eval_nseries(x, n, logx, cdir)
o = Order(1, (x, 0)) if n <= 0 else AccumBounds(0, 1)
return s + o
r = self.subs(x, 0)
if arg0 == r:
ndir = arg.dir(x, cdir=cdir if cdir != 0 else 1)
return r if ndir.is_negative else r + 1
else:
return r
def _eval_rewrite_as_floor(self, arg, **kwargs):
return -floor(-arg)
def _eval_rewrite_as_frac(self, arg, **kwargs):
return arg + frac(-arg)
def _eval_is_positive(self):
return self.args[0].is_positive
def _eval_is_nonpositive(self):
return self.args[0].is_nonpositive
def __lt__(self, other):
other = S(other)
if self.args[0].is_real:
if other.is_integer:
return self.args[0] <= other - 1
if other.is_number and other.is_real:
return self.args[0] <= floor(other)
if self.args[0] == other and other.is_real:
return S.false
if other is S.Infinity and self.is_finite:
return S.true
return Lt(self, other, evaluate=False)
def __gt__(self, other):
other = S(other)
if self.args[0].is_real:
if other.is_integer:
return self.args[0] > other
if other.is_number and other.is_real:
return self.args[0] > floor(other)
if self.args[0] == other and other.is_real:
return S.false
if other is S.NegativeInfinity and self.is_finite:
return S.true
return Gt(self, other, evaluate=False)
def __ge__(self, other):
other = S(other)
if self.args[0].is_real:
if other.is_integer:
return self.args[0] > other - 1
if other.is_number and other.is_real:
return self.args[0] > floor(other)
if self.args[0] == other and other.is_real:
return S.true
if other is S.NegativeInfinity and self.is_finite:
return S.true
return Ge(self, other, evaluate=False)
def __le__(self, other):
other = S(other)
if self.args[0].is_real:
if other.is_integer:
return self.args[0] <= other
if other.is_number and other.is_real:
return self.args[0] <= floor(other)
if self.args[0] == other and other.is_real:
return S.false
if other is S.Infinity and self.is_finite:
return S.true
return Le(self, other, evaluate=False)
@dispatch(ceiling, Basic) # type:ignore
def _eval_is_eq(lhs, rhs): # noqa:F811
return is_eq(lhs.rewrite(floor), rhs) or is_eq(lhs.rewrite(frac),rhs)
class frac(Function):
r"""Represents the fractional part of x
For real numbers it is defined [1]_ as
.. math::
x - \left\lfloor{x}\right\rfloor
Examples
========
>>> from sympy import Symbol, frac, Rational, floor, I
>>> frac(Rational(4, 3))
1/3
>>> frac(-Rational(4, 3))
2/3
returns zero for integer arguments
>>> n = Symbol('n', integer=True)
>>> frac(n)
0
rewrite as floor
>>> x = Symbol('x')
>>> frac(x).rewrite(floor)
x - floor(x)
for complex arguments
>>> r = Symbol('r', real=True)
>>> t = Symbol('t', real=True)
>>> frac(t + I*r)
I*frac(r) + frac(t)
See Also
========
sympy.functions.elementary.integers.floor
sympy.functions.elementary.integers.ceiling
References
===========
.. [1] https://en.wikipedia.org/wiki/Fractional_part
.. [2] http://mathworld.wolfram.com/FractionalPart.html
"""
@classmethod
def eval(cls, arg):
from sympy.calculus.util import AccumBounds
from sympy.functions.elementary.complexes import im
def _eval(arg):
if arg in (S.Infinity, S.NegativeInfinity):
return AccumBounds(0, 1)
if arg.is_integer:
return S.Zero
if arg.is_number:
if arg is S.NaN:
return S.NaN
elif arg is S.ComplexInfinity:
return S.NaN
else:
return arg - floor(arg)
return cls(arg, evaluate=False)
terms = Add.make_args(arg)
real, imag = S.Zero, S.Zero
for t in terms:
# Two checks are needed for complex arguments
# see issue-7649 for details
if t.is_imaginary or (S.ImaginaryUnit*t).is_real:
i = im(t)
if not i.has(S.ImaginaryUnit):
imag += i
else:
real += t
else:
real += t
real = _eval(real)
imag = _eval(imag)
return real + S.ImaginaryUnit*imag
def _eval_rewrite_as_floor(self, arg, **kwargs):
return arg - floor(arg)
def _eval_rewrite_as_ceiling(self, arg, **kwargs):
return arg + ceiling(-arg)
def _eval_is_finite(self):
return True
def _eval_is_real(self):
return self.args[0].is_extended_real
def _eval_is_imaginary(self):
return self.args[0].is_imaginary
def _eval_is_integer(self):
return self.args[0].is_integer
def _eval_is_zero(self):
return fuzzy_or([self.args[0].is_zero, self.args[0].is_integer])
def _eval_is_negative(self):
return False
def __ge__(self, other):
if self.is_extended_real:
other = _sympify(other)
# Check if other <= 0
if other.is_extended_nonpositive:
return S.true
# Check if other >= 1
res = self._value_one_or_more(other)
if res is not None:
return not(res)
return Ge(self, other, evaluate=False)
def __gt__(self, other):
if self.is_extended_real:
other = _sympify(other)
# Check if other < 0
res = self._value_one_or_more(other)
if res is not None:
return not(res)
# Check if other >= 1
if other.is_extended_negative:
return S.true
return Gt(self, other, evaluate=False)
def __le__(self, other):
if self.is_extended_real:
other = _sympify(other)
# Check if other < 0
if other.is_extended_negative:
return S.false
# Check if other >= 1
res = self._value_one_or_more(other)
if res is not None:
return res
return Le(self, other, evaluate=False)
def __lt__(self, other):
if self.is_extended_real:
other = _sympify(other)
# Check if other <= 0
if other.is_extended_nonpositive:
return S.false
# Check if other >= 1
res = self._value_one_or_more(other)
if res is not None:
return res
return Lt(self, other, evaluate=False)
def _value_one_or_more(self, other):
if other.is_extended_real:
if other.is_number:
res = other >= 1
if res and not isinstance(res, Relational):
return S.true
if other.is_integer and other.is_positive:
return S.true
@dispatch(frac, Basic) # type:ignore
def _eval_is_eq(lhs, rhs): # noqa:F811
if (lhs.rewrite(floor) == rhs) or \
(lhs.rewrite(ceiling) == rhs):
return True
# Check if other < 0
if rhs.is_extended_negative:
return False
# Check if other >= 1
res = lhs._value_one_or_more(rhs)
if res is not None:
return False
|
ba7457dc5816f3576a1e1ad961921530a40346d4c618a15e53f52b61d36e385c | from typing import Tuple as tTuple
from sympy.core.expr import Expr
from sympy.core import sympify
from sympy.core.add import Add
from sympy.core.cache import cacheit
from sympy.core.function import (Function, ArgumentIndexError, expand_log,
expand_mul, FunctionClass, PoleError, expand_multinomial, expand_complex)
from sympy.core.logic import fuzzy_and, fuzzy_not, fuzzy_or
from sympy.core.mul import Mul
from sympy.core.numbers import Integer, Rational, pi, I
from sympy.core.parameters import global_parameters
from sympy.core.power import Pow
from sympy.core.singleton import S
from sympy.core.symbol import Wild, Dummy
from sympy.functions.combinatorial.factorials import factorial
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.ntheory import multiplicity, perfect_power
# NOTE IMPORTANT
# The series expansion code in this file is an important part of the gruntz
# algorithm for determining limits. _eval_nseries has to return a generalized
# power series with coefficients in C(log(x), log).
# In more detail, the result of _eval_nseries(self, x, n) must be
# c_0*x**e_0 + ... (finitely many terms)
# where e_i are numbers (not necessarily integers) and c_i involve only
# numbers, the function log, and log(x). [This also means it must not contain
# log(x(1+p)), this *has* to be expanded to log(x)+log(1+p) if x.is_positive and
# p.is_positive.]
class ExpBase(Function):
unbranched = True
_singularities = (S.ComplexInfinity,)
@property
def kind(self):
return self.exp.kind
def inverse(self, argindex=1):
"""
Returns the inverse function of ``exp(x)``.
"""
return log
def as_numer_denom(self):
"""
Returns this with a positive exponent as a 2-tuple (a fraction).
Examples
========
>>> from sympy import exp
>>> from sympy.abc import x
>>> exp(-x).as_numer_denom()
(1, exp(x))
>>> exp(x).as_numer_denom()
(exp(x), 1)
"""
# this should be the same as Pow.as_numer_denom wrt
# exponent handling
exp = self.exp
neg_exp = exp.is_negative
if not neg_exp and not (-exp).is_negative:
neg_exp = exp.could_extract_minus_sign()
if neg_exp:
return S.One, self.func(-exp)
return self, S.One
@property
def exp(self):
"""
Returns the exponent of the function.
"""
return self.args[0]
def as_base_exp(self):
"""
Returns the 2-tuple (base, exponent).
"""
return self.func(1), Mul(*self.args)
def _eval_adjoint(self):
return self.func(self.exp.adjoint())
def _eval_conjugate(self):
return self.func(self.exp.conjugate())
def _eval_transpose(self):
return self.func(self.exp.transpose())
def _eval_is_finite(self):
arg = self.exp
if arg.is_infinite:
if arg.is_extended_negative:
return True
if arg.is_extended_positive:
return False
if arg.is_finite:
return True
def _eval_is_rational(self):
s = self.func(*self.args)
if s.func == self.func:
z = s.exp.is_zero
if z:
return True
elif s.exp.is_rational and fuzzy_not(z):
return False
else:
return s.is_rational
def _eval_is_zero(self):
return self.exp is S.NegativeInfinity
def _eval_power(self, other):
"""exp(arg)**e -> exp(arg*e) if assumptions allow it.
"""
b, e = self.as_base_exp()
return Pow._eval_power(Pow(b, e, evaluate=False), other)
def _eval_expand_power_exp(self, **hints):
from sympy.concrete.products import Product
from sympy.concrete.summations import Sum
arg = self.args[0]
if arg.is_Add and arg.is_commutative:
return Mul.fromiter(self.func(x) for x in arg.args)
elif isinstance(arg, Sum) and arg.is_commutative:
return Product(self.func(arg.function), *arg.limits)
return self.func(arg)
class exp_polar(ExpBase):
r"""
Represent a 'polar number' (see g-function Sphinx documentation).
Explanation
===========
``exp_polar`` represents the function
`Exp: \mathbb{C} \rightarrow \mathcal{S}`, sending the complex number
`z = a + bi` to the polar number `r = exp(a), \theta = b`. It is one of
the main functions to construct polar numbers.
Examples
========
>>> from sympy import exp_polar, pi, I, exp
The main difference is that polar numbers don't "wrap around" at `2 \pi`:
>>> exp(2*pi*I)
1
>>> exp_polar(2*pi*I)
exp_polar(2*I*pi)
apart from that they behave mostly like classical complex numbers:
>>> exp_polar(2)*exp_polar(3)
exp_polar(5)
See Also
========
sympy.simplify.powsimp.powsimp
polar_lift
periodic_argument
principal_branch
"""
is_polar = True
is_comparable = False # cannot be evalf'd
def _eval_Abs(self): # Abs is never a polar number
from sympy.functions.elementary.complexes import re
return exp(re(self.args[0]))
def _eval_evalf(self, prec):
""" Careful! any evalf of polar numbers is flaky """
from sympy.functions.elementary.complexes import (im, re)
i = im(self.args[0])
try:
bad = (i <= -pi or i > pi)
except TypeError:
bad = True
if bad:
return self # cannot evalf for this argument
res = exp(self.args[0])._eval_evalf(prec)
if i > 0 and im(res) < 0:
# i ~ pi, but exp(I*i) evaluated to argument slightly bigger than pi
return re(res)
return res
def _eval_power(self, other):
return self.func(self.args[0]*other)
def _eval_is_extended_real(self):
if self.args[0].is_extended_real:
return True
def as_base_exp(self):
# XXX exp_polar(0) is special!
if self.args[0] == 0:
return self, S.One
return ExpBase.as_base_exp(self)
class ExpMeta(FunctionClass):
def __instancecheck__(cls, instance):
if exp in instance.__class__.__mro__:
return True
return isinstance(instance, Pow) and instance.base is S.Exp1
class exp(ExpBase, metaclass=ExpMeta):
"""
The exponential function, :math:`e^x`.
Examples
========
>>> from sympy import exp, I, pi
>>> from sympy.abc import x
>>> exp(x)
exp(x)
>>> exp(x).diff(x)
exp(x)
>>> exp(I*pi)
-1
Parameters
==========
arg : Expr
See Also
========
log
"""
def fdiff(self, argindex=1):
"""
Returns the first derivative of this function.
"""
if argindex == 1:
return self
else:
raise ArgumentIndexError(self, argindex)
def _eval_refine(self, assumptions):
from sympy.assumptions import ask, Q
arg = self.args[0]
if arg.is_Mul:
Ioo = S.ImaginaryUnit*S.Infinity
if arg in [Ioo, -Ioo]:
return S.NaN
coeff = arg.as_coefficient(S.Pi*S.ImaginaryUnit)
if coeff:
if ask(Q.integer(2*coeff)):
if ask(Q.even(coeff)):
return S.One
elif ask(Q.odd(coeff)):
return S.NegativeOne
elif ask(Q.even(coeff + S.Half)):
return -S.ImaginaryUnit
elif ask(Q.odd(coeff + S.Half)):
return S.ImaginaryUnit
@classmethod
def eval(cls, arg):
from sympy.calculus import AccumBounds
from sympy.sets.setexpr import SetExpr
from sympy.matrices.matrices import MatrixBase
from sympy.functions.elementary.complexes import (im, re)
from sympy.simplify.simplify import logcombine
if isinstance(arg, MatrixBase):
return arg.exp()
elif global_parameters.exp_is_pow:
return Pow(S.Exp1, arg)
elif arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg.is_zero:
return S.One
elif arg is S.One:
return S.Exp1
elif arg is S.Infinity:
return S.Infinity
elif arg is S.NegativeInfinity:
return S.Zero
elif arg is S.ComplexInfinity:
return S.NaN
elif isinstance(arg, log):
return arg.args[0]
elif isinstance(arg, AccumBounds):
return AccumBounds(exp(arg.min), exp(arg.max))
elif isinstance(arg, SetExpr):
return arg._eval_func(cls)
elif arg.is_Mul:
coeff = arg.as_coefficient(S.Pi*S.ImaginaryUnit)
if coeff:
if (2*coeff).is_integer:
if coeff.is_even:
return S.One
elif coeff.is_odd:
return S.NegativeOne
elif (coeff + S.Half).is_even:
return -S.ImaginaryUnit
elif (coeff + S.Half).is_odd:
return S.ImaginaryUnit
elif coeff.is_Rational:
ncoeff = coeff % 2 # restrict to [0, 2pi)
if ncoeff > 1: # restrict to (-pi, pi]
ncoeff -= 2
if ncoeff != coeff:
return cls(ncoeff*S.Pi*S.ImaginaryUnit)
# Warning: code in risch.py will be very sensitive to changes
# in this (see DifferentialExtension).
# look for a single log factor
coeff, terms = arg.as_coeff_Mul()
# but it can't be multiplied by oo
if coeff in [S.NegativeInfinity, S.Infinity]:
if terms.is_number:
if coeff is S.NegativeInfinity:
terms = -terms
if re(terms).is_zero and terms is not S.Zero:
return S.NaN
if re(terms).is_positive and im(terms) is not S.Zero:
return S.ComplexInfinity
if re(terms).is_negative:
return S.Zero
return None
coeffs, log_term = [coeff], None
for term in Mul.make_args(terms):
term_ = logcombine(term)
if isinstance(term_, log):
if log_term is None:
log_term = term_.args[0]
else:
return None
elif term.is_comparable:
coeffs.append(term)
else:
return None
return log_term**Mul(*coeffs) if log_term else None
elif arg.is_Add:
out = []
add = []
argchanged = False
for a in arg.args:
if a is S.One:
add.append(a)
continue
newa = cls(a)
if isinstance(newa, cls):
if newa.args[0] != a:
add.append(newa.args[0])
argchanged = True
else:
add.append(a)
else:
out.append(newa)
if out or argchanged:
return Mul(*out)*cls(Add(*add), evaluate=False)
if arg.is_zero:
return S.One
@property
def base(self):
"""
Returns the base of the exponential function.
"""
return S.Exp1
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
"""
Calculates the next term in the Taylor series expansion.
"""
if n < 0:
return S.Zero
if n == 0:
return S.One
x = sympify(x)
if previous_terms:
p = previous_terms[-1]
if p is not None:
return p * x / n
return x**n/factorial(n)
def as_real_imag(self, deep=True, **hints):
"""
Returns this function as a 2-tuple representing a complex number.
Examples
========
>>> from sympy import exp, I
>>> from sympy.abc import x
>>> exp(x).as_real_imag()
(exp(re(x))*cos(im(x)), exp(re(x))*sin(im(x)))
>>> exp(1).as_real_imag()
(E, 0)
>>> exp(I).as_real_imag()
(cos(1), sin(1))
>>> exp(1+I).as_real_imag()
(E*cos(1), E*sin(1))
See Also
========
sympy.functions.elementary.complexes.re
sympy.functions.elementary.complexes.im
"""
from sympy.functions.elementary.trigonometric import cos, sin
re, im = self.args[0].as_real_imag()
if deep:
re = re.expand(deep, **hints)
im = im.expand(deep, **hints)
cos, sin = cos(im), sin(im)
return (exp(re)*cos, exp(re)*sin)
def _eval_subs(self, old, new):
# keep processing of power-like args centralized in Pow
if old.is_Pow: # handle (exp(3*log(x))).subs(x**2, z) -> z**(3/2)
old = exp(old.exp*log(old.base))
elif old is S.Exp1 and new.is_Function:
old = exp
if isinstance(old, exp) or old is S.Exp1:
f = lambda a: Pow(*a.as_base_exp(), evaluate=False) if (
a.is_Pow or isinstance(a, exp)) else a
return Pow._eval_subs(f(self), f(old), new)
if old is exp and not new.is_Function:
return new**self.exp._subs(old, new)
return Function._eval_subs(self, old, new)
def _eval_is_extended_real(self):
if self.args[0].is_extended_real:
return True
elif self.args[0].is_imaginary:
arg2 = -S(2) * S.ImaginaryUnit * self.args[0] / S.Pi
return arg2.is_even
def _eval_is_complex(self):
def complex_extended_negative(arg):
yield arg.is_complex
yield arg.is_extended_negative
return fuzzy_or(complex_extended_negative(self.args[0]))
def _eval_is_algebraic(self):
if (self.exp / S.Pi / S.ImaginaryUnit).is_rational:
return True
if fuzzy_not(self.exp.is_zero):
if self.exp.is_algebraic:
return False
elif (self.exp / S.Pi).is_rational:
return False
def _eval_is_extended_positive(self):
if self.exp.is_extended_real:
return not self.args[0] is S.NegativeInfinity
elif self.exp.is_imaginary:
arg2 = -S.ImaginaryUnit * self.args[0] / S.Pi
return arg2.is_even
def _eval_nseries(self, x, n, logx, cdir=0):
# NOTE Please see the comment at the beginning of this file, labelled
# IMPORTANT.
from sympy.functions.elementary.integers import ceiling
from sympy.series.limits import limit
from sympy.series.order import Order
from sympy.simplify.powsimp import powsimp
arg = self.exp
arg_series = arg._eval_nseries(x, n=n, logx=logx)
if arg_series.is_Order:
return 1 + arg_series
arg0 = limit(arg_series.removeO(), x, 0)
if arg0 is S.NegativeInfinity:
return Order(x**n, x)
if arg0 is S.Infinity:
return self
t = Dummy("t")
nterms = n
try:
cf = Order(arg.as_leading_term(x, logx=logx), x).getn()
except (NotImplementedError, PoleError):
cf = 0
if cf and cf > 0:
nterms = ceiling(n/cf)
exp_series = exp(t)._taylor(t, nterms)
r = exp(arg0)*exp_series.subs(t, arg_series - arg0)
if cf and cf > 1:
r += Order((arg_series - arg0)**n, x)/x**((cf-1)*n)
else:
r += Order((arg_series - arg0)**n, x)
r = r.expand()
r = powsimp(r, deep=True, combine='exp')
# powsimp may introduce unexpanded (-1)**Rational; see PR #17201
simplerat = lambda x: x.is_Rational and x.q in [3, 4, 6]
w = Wild('w', properties=[simplerat])
r = r.replace(S.NegativeOne**w, expand_complex(S.NegativeOne**w))
return r
def _taylor(self, x, n):
l = []
g = None
for i in range(n):
g = self.taylor_term(i, self.args[0], g)
g = g.nseries(x, n=n)
l.append(g.removeO())
return Add(*l)
def _eval_as_leading_term(self, x, logx=None, cdir=0):
arg = self.args[0].cancel().as_leading_term(x, logx=logx)
arg0 = arg.subs(x, 0)
if arg0 is S.NaN:
arg0 = arg.limit(x, 0)
if arg0.is_infinite is False:
return exp(arg0)
raise PoleError("Cannot expand %s around 0" % (self))
def _eval_rewrite_as_sin(self, arg, **kwargs):
from sympy.functions.elementary.trigonometric import sin
I = S.ImaginaryUnit
return sin(I*arg + S.Pi/2) - I*sin(I*arg)
def _eval_rewrite_as_cos(self, arg, **kwargs):
from sympy.functions.elementary.trigonometric import cos
I = S.ImaginaryUnit
return cos(I*arg) + I*cos(I*arg + S.Pi/2)
def _eval_rewrite_as_tanh(self, arg, **kwargs):
from sympy.functions.elementary.hyperbolic import tanh
return (1 + tanh(arg/2))/(1 - tanh(arg/2))
def _eval_rewrite_as_sqrt(self, arg, **kwargs):
from sympy.functions.elementary.trigonometric import sin, cos
if arg.is_Mul:
coeff = arg.coeff(S.Pi*S.ImaginaryUnit)
if coeff and coeff.is_number:
cosine, sine = cos(S.Pi*coeff), sin(S.Pi*coeff)
if not isinstance(cosine, cos) and not isinstance (sine, sin):
return cosine + S.ImaginaryUnit*sine
def _eval_rewrite_as_Pow(self, arg, **kwargs):
if arg.is_Mul:
logs = [a for a in arg.args if isinstance(a, log) and len(a.args) == 1]
if logs:
return Pow(logs[0].args[0], arg.coeff(logs[0]))
def match_real_imag(expr):
"""
Try to match expr with a + b*I for real a and b.
``match_real_imag`` returns a tuple containing the real and imaginary
parts of expr or (None, None) if direct matching is not possible. Contrary
to ``re()``, ``im()``, ``as_real_imag()``, this helper will not force things
by returning expressions themselves containing ``re()`` or ``im()`` and it
does not expand its argument either.
"""
r_, i_ = expr.as_independent(S.ImaginaryUnit, as_Add=True)
if i_ == 0 and r_.is_real:
return (r_, i_)
i_ = i_.as_coefficient(S.ImaginaryUnit)
if i_ and i_.is_real and r_.is_real:
return (r_, i_)
else:
return (None, None) # simpler to check for than None
class log(Function):
r"""
The natural logarithm function `\ln(x)` or `\log(x)`.
Explanation
===========
Logarithms are taken with the natural base, `e`. To get
a logarithm of a different base ``b``, use ``log(x, b)``,
which is essentially short-hand for ``log(x)/log(b)``.
``log`` represents the principal branch of the natural
logarithm. As such it has a branch cut along the negative
real axis and returns values having a complex argument in
`(-\pi, \pi]`.
Examples
========
>>> from sympy import log, sqrt, S, I
>>> log(8, 2)
3
>>> log(S(8)/3, 2)
-log(3)/log(2) + 3
>>> log(-1 + I*sqrt(3))
log(2) + 2*I*pi/3
See Also
========
exp
"""
args: tTuple[Expr]
_singularities = (S.Zero, S.ComplexInfinity)
def fdiff(self, argindex=1):
"""
Returns the first derivative of the function.
"""
if argindex == 1:
return 1/self.args[0]
else:
raise ArgumentIndexError(self, argindex)
def inverse(self, argindex=1):
r"""
Returns `e^x`, the inverse function of `\log(x)`.
"""
return exp
@classmethod
def eval(cls, arg, base=None):
from sympy.functions.elementary.complexes import unpolarify
from sympy.calculus import AccumBounds
from sympy.sets.setexpr import SetExpr
from sympy.functions.elementary.complexes import Abs
arg = sympify(arg)
if base is not None:
base = sympify(base)
if base == 1:
if arg == 1:
return S.NaN
else:
return S.ComplexInfinity
try:
# handle extraction of powers of the base now
# or else expand_log in Mul would have to handle this
n = multiplicity(base, arg)
if n:
return n + log(arg / base**n) / log(base)
else:
return log(arg)/log(base)
except ValueError:
pass
if base is not S.Exp1:
return cls(arg)/cls(base)
else:
return cls(arg)
if arg.is_Number:
if arg.is_zero:
return S.ComplexInfinity
elif arg is S.One:
return S.Zero
elif arg is S.Infinity:
return S.Infinity
elif arg is S.NegativeInfinity:
return S.Infinity
elif arg is S.NaN:
return S.NaN
elif arg.is_Rational and arg.p == 1:
return -cls(arg.q)
if arg.is_Pow and arg.base is S.Exp1 and arg.exp.is_extended_real:
return arg.exp
I = S.ImaginaryUnit
if isinstance(arg, exp) and arg.exp.is_extended_real:
return arg.exp
elif isinstance(arg, exp) and arg.exp.is_number:
r_, i_ = match_real_imag(arg.exp)
if i_ and i_.is_comparable:
i_ %= 2*S.Pi
if i_ > S.Pi:
i_ -= 2*S.Pi
return r_ + expand_mul(i_ * I, deep=False)
elif isinstance(arg, exp_polar):
return unpolarify(arg.exp)
elif isinstance(arg, AccumBounds):
if arg.min.is_positive:
return AccumBounds(log(arg.min), log(arg.max))
else:
return
elif isinstance(arg, SetExpr):
return arg._eval_func(cls)
if arg.is_number:
if arg.is_negative:
return S.Pi * I + cls(-arg)
elif arg is S.ComplexInfinity:
return S.ComplexInfinity
elif arg is S.Exp1:
return S.One
if arg.is_zero:
return S.ComplexInfinity
# don't autoexpand Pow or Mul (see the issue 3351):
if not arg.is_Add:
coeff = arg.as_coefficient(I)
if coeff is not None:
if coeff is S.Infinity:
return S.Infinity
elif coeff is S.NegativeInfinity:
return S.Infinity
elif coeff.is_Rational:
if coeff.is_nonnegative:
return S.Pi * I * S.Half + cls(coeff)
else:
return -S.Pi * I * S.Half + cls(-coeff)
if arg.is_number and arg.is_algebraic:
# Match arg = coeff*(r_ + i_*I) with coeff>0, r_ and i_ real.
coeff, arg_ = arg.as_independent(I, as_Add=False)
if coeff.is_negative:
coeff *= -1
arg_ *= -1
arg_ = expand_mul(arg_, deep=False)
r_, i_ = arg_.as_independent(I, as_Add=True)
i_ = i_.as_coefficient(I)
if coeff.is_real and i_ and i_.is_real and r_.is_real:
if r_.is_zero:
if i_.is_positive:
return S.Pi * I * S.Half + cls(coeff * i_)
elif i_.is_negative:
return -S.Pi * I * S.Half + cls(coeff * -i_)
else:
from sympy.simplify import ratsimp
# Check for arguments involving rational multiples of pi
t = (i_/r_).cancel()
t1 = (-t).cancel()
atan_table = {
# first quadrant only
sqrt(3): S.Pi/3,
1: S.Pi/4,
sqrt(5 - 2*sqrt(5)): S.Pi/5,
sqrt(2)*sqrt(5 - sqrt(5))/(1 + sqrt(5)): S.Pi/5,
sqrt(5 + 2*sqrt(5)): S.Pi*Rational(2, 5),
sqrt(2)*sqrt(sqrt(5) + 5)/(-1 + sqrt(5)): S.Pi*Rational(2, 5),
sqrt(3)/3: S.Pi/6,
sqrt(2) - 1: S.Pi/8,
sqrt(2 - sqrt(2))/sqrt(sqrt(2) + 2): S.Pi/8,
sqrt(2) + 1: S.Pi*Rational(3, 8),
sqrt(sqrt(2) + 2)/sqrt(2 - sqrt(2)): S.Pi*Rational(3, 8),
sqrt(1 - 2*sqrt(5)/5): S.Pi/10,
(-sqrt(2) + sqrt(10))/(2*sqrt(sqrt(5) + 5)): S.Pi/10,
sqrt(1 + 2*sqrt(5)/5): S.Pi*Rational(3, 10),
(sqrt(2) + sqrt(10))/(2*sqrt(5 - sqrt(5))): S.Pi*Rational(3, 10),
2 - sqrt(3): S.Pi/12,
(-1 + sqrt(3))/(1 + sqrt(3)): S.Pi/12,
2 + sqrt(3): S.Pi*Rational(5, 12),
(1 + sqrt(3))/(-1 + sqrt(3)): S.Pi*Rational(5, 12)
}
if t in atan_table:
modulus = ratsimp(coeff * Abs(arg_))
if r_.is_positive:
return cls(modulus) + I * atan_table[t]
else:
return cls(modulus) + I * (atan_table[t] - S.Pi)
elif t1 in atan_table:
modulus = ratsimp(coeff * Abs(arg_))
if r_.is_positive:
return cls(modulus) + I * (-atan_table[t1])
else:
return cls(modulus) + I * (S.Pi - atan_table[t1])
def as_base_exp(self):
"""
Returns this function in the form (base, exponent).
"""
return self, S.One
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms): # of log(1+x)
r"""
Returns the next term in the Taylor series expansion of `\log(1+x)`.
"""
from sympy.simplify.powsimp import powsimp
if n < 0:
return S.Zero
x = sympify(x)
if n == 0:
return x
if previous_terms:
p = previous_terms[-1]
if p is not None:
return powsimp((-n) * p * x / (n + 1), deep=True, combine='exp')
return (1 - 2*(n % 2)) * x**(n + 1)/(n + 1)
def _eval_expand_log(self, deep=True, **hints):
from sympy.functions.elementary.complexes import unpolarify
from sympy.ntheory.factor_ import factorint
from sympy.concrete import Sum, Product
force = hints.get('force', False)
factor = hints.get('factor', False)
if (len(self.args) == 2):
return expand_log(self.func(*self.args), deep=deep, force=force)
arg = self.args[0]
if arg.is_Integer:
# remove perfect powers
p = perfect_power(arg)
logarg = None
coeff = 1
if p is not False:
arg, coeff = p
logarg = self.func(arg)
# expand as product of its prime factors if factor=True
if factor:
p = factorint(arg)
if arg not in p.keys():
logarg = sum(n*log(val) for val, n in p.items())
if logarg is not None:
return coeff*logarg
elif arg.is_Rational:
return log(arg.p) - log(arg.q)
elif arg.is_Mul:
expr = []
nonpos = []
for x in arg.args:
if force or x.is_positive or x.is_polar:
a = self.func(x)
if isinstance(a, log):
expr.append(self.func(x)._eval_expand_log(**hints))
else:
expr.append(a)
elif x.is_negative:
a = self.func(-x)
expr.append(a)
nonpos.append(S.NegativeOne)
else:
nonpos.append(x)
return Add(*expr) + log(Mul(*nonpos))
elif arg.is_Pow or isinstance(arg, exp):
if force or (arg.exp.is_extended_real and (arg.base.is_positive or ((arg.exp+1)
.is_positive and (arg.exp-1).is_nonpositive))) or arg.base.is_polar:
b = arg.base
e = arg.exp
a = self.func(b)
if isinstance(a, log):
return unpolarify(e) * a._eval_expand_log(**hints)
else:
return unpolarify(e) * a
elif isinstance(arg, Product):
if force or arg.function.is_positive:
return Sum(log(arg.function), *arg.limits)
return self.func(arg)
def _eval_simplify(self, **kwargs):
from sympy.simplify.simplify import expand_log, simplify, inversecombine
if len(self.args) == 2: # it's unevaluated
return simplify(self.func(*self.args), **kwargs)
expr = self.func(simplify(self.args[0], **kwargs))
if kwargs['inverse']:
expr = inversecombine(expr)
expr = expand_log(expr, deep=True)
return min([expr, self], key=kwargs['measure'])
def as_real_imag(self, deep=True, **hints):
"""
Returns this function as a complex coordinate.
Examples
========
>>> from sympy import I, log
>>> from sympy.abc import x
>>> log(x).as_real_imag()
(log(Abs(x)), arg(x))
>>> log(I).as_real_imag()
(0, pi/2)
>>> log(1 + I).as_real_imag()
(log(sqrt(2)), pi/4)
>>> log(I*x).as_real_imag()
(log(Abs(x)), arg(I*x))
"""
from sympy.functions.elementary.complexes import (Abs, arg)
sarg = self.args[0]
if deep:
sarg = self.args[0].expand(deep, **hints)
abs = Abs(sarg)
if abs == sarg:
return self, S.Zero
arg = arg(sarg)
if hints.get('log', False): # Expand the log
hints['complex'] = False
return (log(abs).expand(deep, **hints), arg)
else:
return log(abs), arg
def _eval_is_rational(self):
s = self.func(*self.args)
if s.func == self.func:
if (self.args[0] - 1).is_zero:
return True
if s.args[0].is_rational and fuzzy_not((self.args[0] - 1).is_zero):
return False
else:
return s.is_rational
def _eval_is_algebraic(self):
s = self.func(*self.args)
if s.func == self.func:
if (self.args[0] - 1).is_zero:
return True
elif fuzzy_not((self.args[0] - 1).is_zero):
if self.args[0].is_algebraic:
return False
else:
return s.is_algebraic
def _eval_is_extended_real(self):
return self.args[0].is_extended_positive
def _eval_is_complex(self):
z = self.args[0]
return fuzzy_and([z.is_complex, fuzzy_not(z.is_zero)])
def _eval_is_finite(self):
arg = self.args[0]
if arg.is_zero:
return False
return arg.is_finite
def _eval_is_extended_positive(self):
return (self.args[0] - 1).is_extended_positive
def _eval_is_zero(self):
return (self.args[0] - 1).is_zero
def _eval_is_extended_nonnegative(self):
return (self.args[0] - 1).is_extended_nonnegative
def _eval_nseries(self, x, n, logx, cdir=0):
# NOTE Please see the comment at the beginning of this file, labelled
# IMPORTANT.
from sympy.functions.elementary.complexes import im
from sympy.polys.polytools import cancel
from sympy.series.order import Order
from sympy.simplify.simplify import logcombine
from itertools import product
if not logx:
logx = log(x)
if self.args[0] == x:
return logx
arg = self.args[0]
k, l = Wild("k"), Wild("l")
r = arg.match(k*x**l)
if r is not None:
k, l = r[k], r[l]
if l != 0 and not l.has(x) and not k.has(x):
r = log(k) + l*logx # XXX true regardless of assumptions?
return r
def coeff_exp(term, x):
coeff, exp = S.One, S.Zero
for factor in Mul.make_args(term):
if factor.has(x):
base, exp = factor.as_base_exp()
if base != x:
try:
return term.leadterm(x)
except ValueError:
return term, S.Zero
else:
coeff *= factor
return coeff, exp
# TODO new and probably slow
try:
a, b = arg.leadterm(x)
s = arg.nseries(x, n=n+b, logx=logx)
except (ValueError, NotImplementedError, PoleError):
s = arg.nseries(x, n=n, logx=logx)
while s.is_Order:
n += 1
s = arg.nseries(x, n=n, logx=logx)
a, b = s.removeO().leadterm(x)
p = cancel(s/(a*x**b) - 1).expand().powsimp()
if p.has(exp):
p = logcombine(p)
if isinstance(p, Order):
n = p.getn()
_, d = coeff_exp(p, x)
if not d.is_positive:
return log(a) + b*logx + Order(x**n, x)
def mul(d1, d2):
res = {}
for e1, e2 in product(d1, d2):
ex = e1 + e2
if ex < n:
res[ex] = res.get(ex, S.Zero) + d1[e1]*d2[e2]
return res
pterms = {}
for term in Add.make_args(p):
co1, e1 = coeff_exp(term, x)
pterms[e1] = pterms.get(e1, S.Zero) + co1.removeO()
k = S.One
terms = {}
pk = pterms
while k*d < n:
coeff = -S.NegativeOne**k/k
for ex in pk:
terms[ex] = terms.get(ex, S.Zero) + coeff*pk[ex]
pk = mul(pk, pterms)
k += S.One
res = log(a) + b*logx
for ex in terms:
res += terms[ex]*x**(ex)
if cdir != 0:
cdir = self.args[0].dir(x, cdir)
if a.is_real and a.is_negative and im(cdir) < 0:
res -= 2*I*S.Pi
return res + Order(x**n, x)
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.functions.elementary.complexes import (im, re)
arg0 = self.args[0].together()
arg = arg0.as_leading_term(x, cdir=cdir)
x0 = arg0.subs(x, 0)
if (x0 is S.NaN and logx is None):
x0 = arg.limit(x, 0, dir='-' if re(cdir).is_negative else '+')
if x0 in (S.NegativeInfinity, S.Infinity):
raise PoleError("Cannot expand %s around 0" % (self))
if x0 == 1:
return (arg0 - S.One).as_leading_term(x)
if cdir != 0:
cdir = arg0.dir(x, cdir)
if x0.is_real and x0.is_negative and im(cdir).is_negative:
return self.func(x0) - 2*I*S.Pi
return self.func(arg)
class LambertW(Function):
r"""
The Lambert W function `W(z)` is defined as the inverse
function of `w \exp(w)` [1]_.
Explanation
===========
In other words, the value of `W(z)` is such that `z = W(z) \exp(W(z))`
for any complex number `z`. The Lambert W function is a multivalued
function with infinitely many branches `W_k(z)`, indexed by
`k \in \mathbb{Z}`. Each branch gives a different solution `w`
of the equation `z = w \exp(w)`.
The Lambert W function has two partially real branches: the
principal branch (`k = 0`) is real for real `z > -1/e`, and the
`k = -1` branch is real for `-1/e < z < 0`. All branches except
`k = 0` have a logarithmic singularity at `z = 0`.
Examples
========
>>> from sympy import LambertW
>>> LambertW(1.2)
0.635564016364870
>>> LambertW(1.2, -1).n()
-1.34747534407696 - 4.41624341514535*I
>>> LambertW(-1).is_real
False
References
==========
.. [1] https://en.wikipedia.org/wiki/Lambert_W_function
"""
_singularities = (-Pow(S.Exp1, -1, evaluate=False), S.ComplexInfinity)
@classmethod
def eval(cls, x, k=None):
if k == S.Zero:
return cls(x)
elif k is None:
k = S.Zero
if k.is_zero:
if x.is_zero:
return S.Zero
if x is S.Exp1:
return S.One
if x == -1/S.Exp1:
return S.NegativeOne
if x == -log(2)/2:
return -log(2)
if x == 2*log(2):
return log(2)
if x == -S.Pi/2:
return S.ImaginaryUnit*S.Pi/2
if x == exp(1 + S.Exp1):
return S.Exp1
if x is S.Infinity:
return S.Infinity
if x.is_zero:
return S.Zero
if fuzzy_not(k.is_zero):
if x.is_zero:
return S.NegativeInfinity
if k is S.NegativeOne:
if x == -S.Pi/2:
return -S.ImaginaryUnit*S.Pi/2
elif x == -1/S.Exp1:
return S.NegativeOne
elif x == -2*exp(-2):
return -Integer(2)
def fdiff(self, argindex=1):
"""
Return the first derivative of this function.
"""
x = self.args[0]
if len(self.args) == 1:
if argindex == 1:
return LambertW(x)/(x*(1 + LambertW(x)))
else:
k = self.args[1]
if argindex == 1:
return LambertW(x, k)/(x*(1 + LambertW(x, k)))
raise ArgumentIndexError(self, argindex)
def _eval_is_extended_real(self):
x = self.args[0]
if len(self.args) == 1:
k = S.Zero
else:
k = self.args[1]
if k.is_zero:
if (x + 1/S.Exp1).is_positive:
return True
elif (x + 1/S.Exp1).is_nonpositive:
return False
elif (k + 1).is_zero:
if x.is_negative and (x + 1/S.Exp1).is_positive:
return True
elif x.is_nonpositive or (x + 1/S.Exp1).is_nonnegative:
return False
elif fuzzy_not(k.is_zero) and fuzzy_not((k + 1).is_zero):
if x.is_extended_real:
return False
def _eval_is_finite(self):
return self.args[0].is_finite
def _eval_is_algebraic(self):
s = self.func(*self.args)
if s.func == self.func:
if fuzzy_not(self.args[0].is_zero) and self.args[0].is_algebraic:
return False
else:
return s.is_algebraic
def _eval_as_leading_term(self, x, logx=None, cdir=0):
if len(self.args) == 1:
arg = self.args[0]
arg0 = arg.subs(x, 0).cancel()
if not arg0.is_zero:
return self.func(arg0)
return arg.as_leading_term(x)
def _eval_nseries(self, x, n, logx, cdir=0):
if len(self.args) == 1:
from sympy.functions.elementary.integers import ceiling
from sympy.series.order import Order
arg = self.args[0].nseries(x, n=n, logx=logx)
lt = arg.compute_leading_term(x, logx=logx)
lte = 1
if lt.is_Pow:
lte = lt.exp
if ceiling(n/lte) >= 1:
s = Add(*[(-S.One)**(k - 1)*Integer(k)**(k - 2)/
factorial(k - 1)*arg**k for k in range(1, ceiling(n/lte))])
s = expand_multinomial(s)
else:
s = S.Zero
return s + Order(x**n, x)
return super()._eval_nseries(x, n, logx)
def _eval_is_zero(self):
x = self.args[0]
if len(self.args) == 1:
return x.is_zero
else:
return fuzzy_and([x.is_zero, self.args[1].is_zero])
|
65e740e218f41240602b009851e687bab931479e56cb98448ba38b581e0ad5f1 | from sympy.core.logic import FuzzyBool
from sympy.core import S, sympify, cacheit, pi, I, Rational
from sympy.core.add import Add
from sympy.core.function import Function, ArgumentIndexError
from sympy.functions.combinatorial.factorials import factorial, RisingFactorial
from sympy.functions.elementary.exponential import exp, log, match_real_imag
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.integers import floor
from sympy.core.logic import fuzzy_or, fuzzy_and
def _rewrite_hyperbolics_as_exp(expr):
expr = sympify(expr)
return expr.xreplace({h: h.rewrite(exp)
for h in expr.atoms(HyperbolicFunction)})
###############################################################################
########################### HYPERBOLIC FUNCTIONS ##############################
###############################################################################
class HyperbolicFunction(Function):
"""
Base class for hyperbolic functions.
See Also
========
sinh, cosh, tanh, coth
"""
unbranched = True
def _peeloff_ipi(arg):
"""
Split ARG into two parts, a "rest" and a multiple of I*pi.
This assumes ARG to be an Add.
The multiple of I*pi returned in the second position is always a Rational.
Examples
========
>>> from sympy.functions.elementary.hyperbolic import _peeloff_ipi as peel
>>> from sympy import pi, I
>>> from sympy.abc import x, y
>>> peel(x + I*pi/2)
(x, 1/2)
>>> peel(x + I*2*pi/3 + I*pi*y)
(x + I*pi*y + I*pi/6, 1/2)
"""
ipi = S.Pi*S.ImaginaryUnit
for a in Add.make_args(arg):
if a == ipi:
K = S.One
break
elif a.is_Mul:
K, p = a.as_two_terms()
if p == ipi and K.is_Rational:
break
else:
return arg, S.Zero
m1 = (K % S.Half)
m2 = K - m1
return arg - m2*ipi, m2
class sinh(HyperbolicFunction):
r"""
sinh(x) is the hyperbolic sine of x.
The hyperbolic sine function is $\frac{e^x - e^{-x}}{2}$.
Examples
========
>>> from sympy import sinh
>>> from sympy.abc import x
>>> sinh(x)
sinh(x)
See Also
========
cosh, tanh, asinh
"""
def fdiff(self, argindex=1):
"""
Returns the first derivative of this function.
"""
if argindex == 1:
return cosh(self.args[0])
else:
raise ArgumentIndexError(self, argindex)
def inverse(self, argindex=1):
"""
Returns the inverse of this function.
"""
return asinh
@classmethod
def eval(cls, arg):
from sympy.functions.elementary.trigonometric import sin
arg = sympify(arg)
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.Infinity
elif arg is S.NegativeInfinity:
return S.NegativeInfinity
elif arg.is_zero:
return S.Zero
elif arg.is_negative:
return -cls(-arg)
else:
if arg is S.ComplexInfinity:
return S.NaN
i_coeff = arg.as_coefficient(S.ImaginaryUnit)
if i_coeff is not None:
return S.ImaginaryUnit * sin(i_coeff)
else:
if arg.could_extract_minus_sign():
return -cls(-arg)
if arg.is_Add:
x, m = _peeloff_ipi(arg)
if m:
m = m*S.Pi*S.ImaginaryUnit
return sinh(m)*cosh(x) + cosh(m)*sinh(x)
if arg.is_zero:
return S.Zero
if arg.func == asinh:
return arg.args[0]
if arg.func == acosh:
x = arg.args[0]
return sqrt(x - 1) * sqrt(x + 1)
if arg.func == atanh:
x = arg.args[0]
return x/sqrt(1 - x**2)
if arg.func == acoth:
x = arg.args[0]
return 1/(sqrt(x - 1) * sqrt(x + 1))
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
"""
Returns the next term in the Taylor series expansion.
"""
if n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
if len(previous_terms) > 2:
p = previous_terms[-2]
return p * x**2 / (n*(n - 1))
else:
return x**(n) / factorial(n)
def _eval_conjugate(self):
return self.func(self.args[0].conjugate())
def as_real_imag(self, deep=True, **hints):
"""
Returns this function as a complex coordinate.
"""
from sympy.functions.elementary.trigonometric import (cos, sin)
if self.args[0].is_extended_real:
if deep:
hints['complex'] = False
return (self.expand(deep, **hints), S.Zero)
else:
return (self, S.Zero)
if deep:
re, im = self.args[0].expand(deep, **hints).as_real_imag()
else:
re, im = self.args[0].as_real_imag()
return (sinh(re)*cos(im), cosh(re)*sin(im))
def _eval_expand_complex(self, deep=True, **hints):
re_part, im_part = self.as_real_imag(deep=deep, **hints)
return re_part + im_part*S.ImaginaryUnit
def _eval_expand_trig(self, deep=True, **hints):
if deep:
arg = self.args[0].expand(deep, **hints)
else:
arg = self.args[0]
x = None
if arg.is_Add: # TODO, implement more if deep stuff here
x, y = arg.as_two_terms()
else:
coeff, terms = arg.as_coeff_Mul(rational=True)
if coeff is not S.One and coeff.is_Integer and terms is not S.One:
x = terms
y = (coeff - 1)*x
if x is not None:
return (sinh(x)*cosh(y) + sinh(y)*cosh(x)).expand(trig=True)
return sinh(arg)
def _eval_rewrite_as_tractable(self, arg, limitvar=None, **kwargs):
return (exp(arg) - exp(-arg)) / 2
def _eval_rewrite_as_exp(self, arg, **kwargs):
return (exp(arg) - exp(-arg)) / 2
def _eval_rewrite_as_cosh(self, arg, **kwargs):
return -S.ImaginaryUnit*cosh(arg + S.Pi*S.ImaginaryUnit/2)
def _eval_rewrite_as_tanh(self, arg, **kwargs):
tanh_half = tanh(S.Half*arg)
return 2*tanh_half/(1 - tanh_half**2)
def _eval_rewrite_as_coth(self, arg, **kwargs):
coth_half = coth(S.Half*arg)
return 2*coth_half/(coth_half**2 - 1)
def _eval_as_leading_term(self, x, logx=None, cdir=0):
arg = self.args[0].as_leading_term(x, logx=logx, cdir=cdir)
arg0 = arg.subs(x, 0)
if arg0 is S.NaN:
arg0 = arg.limit(x, 0, dir='-' if cdir.is_negative else '+')
if arg0.is_zero:
return arg
elif arg0.is_finite:
return self.func(arg0)
else:
return self
def _eval_is_real(self):
arg = self.args[0]
if arg.is_real:
return True
# if `im` is of the form n*pi
# else, check if it is a number
re, im = arg.as_real_imag()
return (im%pi).is_zero
def _eval_is_extended_real(self):
if self.args[0].is_extended_real:
return True
def _eval_is_positive(self):
if self.args[0].is_extended_real:
return self.args[0].is_positive
def _eval_is_negative(self):
if self.args[0].is_extended_real:
return self.args[0].is_negative
def _eval_is_finite(self):
arg = self.args[0]
return arg.is_finite
def _eval_is_zero(self):
rest, ipi_mult = _peeloff_ipi(self.args[0])
if rest.is_zero:
return ipi_mult.is_integer
class cosh(HyperbolicFunction):
r"""
cosh(x) is the hyperbolic cosine of x.
The hyperbolic cosine function is $\frac{e^x + e^{-x}}{2}$.
Examples
========
>>> from sympy import cosh
>>> from sympy.abc import x
>>> cosh(x)
cosh(x)
See Also
========
sinh, tanh, acosh
"""
def fdiff(self, argindex=1):
if argindex == 1:
return sinh(self.args[0])
else:
raise ArgumentIndexError(self, argindex)
@classmethod
def eval(cls, arg):
from sympy.functions.elementary.trigonometric import cos
arg = sympify(arg)
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.Infinity
elif arg is S.NegativeInfinity:
return S.Infinity
elif arg.is_zero:
return S.One
elif arg.is_negative:
return cls(-arg)
else:
if arg is S.ComplexInfinity:
return S.NaN
i_coeff = arg.as_coefficient(S.ImaginaryUnit)
if i_coeff is not None:
return cos(i_coeff)
else:
if arg.could_extract_minus_sign():
return cls(-arg)
if arg.is_Add:
x, m = _peeloff_ipi(arg)
if m:
m = m*S.Pi*S.ImaginaryUnit
return cosh(m)*cosh(x) + sinh(m)*sinh(x)
if arg.is_zero:
return S.One
if arg.func == asinh:
return sqrt(1 + arg.args[0]**2)
if arg.func == acosh:
return arg.args[0]
if arg.func == atanh:
return 1/sqrt(1 - arg.args[0]**2)
if arg.func == acoth:
x = arg.args[0]
return x/(sqrt(x - 1) * sqrt(x + 1))
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
if n < 0 or n % 2 == 1:
return S.Zero
else:
x = sympify(x)
if len(previous_terms) > 2:
p = previous_terms[-2]
return p * x**2 / (n*(n - 1))
else:
return x**(n)/factorial(n)
def _eval_conjugate(self):
return self.func(self.args[0].conjugate())
def as_real_imag(self, deep=True, **hints):
from sympy.functions.elementary.trigonometric import (cos, sin)
if self.args[0].is_extended_real:
if deep:
hints['complex'] = False
return (self.expand(deep, **hints), S.Zero)
else:
return (self, S.Zero)
if deep:
re, im = self.args[0].expand(deep, **hints).as_real_imag()
else:
re, im = self.args[0].as_real_imag()
return (cosh(re)*cos(im), sinh(re)*sin(im))
def _eval_expand_complex(self, deep=True, **hints):
re_part, im_part = self.as_real_imag(deep=deep, **hints)
return re_part + im_part*S.ImaginaryUnit
def _eval_expand_trig(self, deep=True, **hints):
if deep:
arg = self.args[0].expand(deep, **hints)
else:
arg = self.args[0]
x = None
if arg.is_Add: # TODO, implement more if deep stuff here
x, y = arg.as_two_terms()
else:
coeff, terms = arg.as_coeff_Mul(rational=True)
if coeff is not S.One and coeff.is_Integer and terms is not S.One:
x = terms
y = (coeff - 1)*x
if x is not None:
return (cosh(x)*cosh(y) + sinh(x)*sinh(y)).expand(trig=True)
return cosh(arg)
def _eval_rewrite_as_tractable(self, arg, limitvar=None, **kwargs):
return (exp(arg) + exp(-arg)) / 2
def _eval_rewrite_as_exp(self, arg, **kwargs):
return (exp(arg) + exp(-arg)) / 2
def _eval_rewrite_as_sinh(self, arg, **kwargs):
return -S.ImaginaryUnit*sinh(arg + S.Pi*S.ImaginaryUnit/2)
def _eval_rewrite_as_tanh(self, arg, **kwargs):
tanh_half = tanh(S.Half*arg)**2
return (1 + tanh_half)/(1 - tanh_half)
def _eval_rewrite_as_coth(self, arg, **kwargs):
coth_half = coth(S.Half*arg)**2
return (coth_half + 1)/(coth_half - 1)
def _eval_as_leading_term(self, x, logx=None, cdir=0):
arg = self.args[0].as_leading_term(x, logx=logx, cdir=cdir)
arg0 = arg.subs(x, 0)
if arg0 is S.NaN:
arg0 = arg.limit(x, 0, dir='-' if cdir.is_negative else '+')
if arg0.is_zero:
return S.One
elif arg0.is_finite:
return self.func(arg0)
else:
return self
def _eval_is_real(self):
arg = self.args[0]
# `cosh(x)` is real for real OR purely imaginary `x`
if arg.is_real or arg.is_imaginary:
return True
# cosh(a+ib) = cos(b)*cosh(a) + i*sin(b)*sinh(a)
# the imaginary part can be an expression like n*pi
# if not, check if the imaginary part is a number
re, im = arg.as_real_imag()
return (im%pi).is_zero
def _eval_is_positive(self):
# cosh(x+I*y) = cos(y)*cosh(x) + I*sin(y)*sinh(x)
# cosh(z) is positive iff it is real and the real part is positive.
# So we need sin(y)*sinh(x) = 0 which gives x=0 or y=n*pi
# Case 1 (y=n*pi): cosh(z) = (-1)**n * cosh(x) -> positive for n even
# Case 2 (x=0): cosh(z) = cos(y) -> positive when cos(y) is positive
z = self.args[0]
x, y = z.as_real_imag()
ymod = y % (2*pi)
yzero = ymod.is_zero
# shortcut if ymod is zero
if yzero:
return True
xzero = x.is_zero
# shortcut x is not zero
if xzero is False:
return yzero
return fuzzy_or([
# Case 1:
yzero,
# Case 2:
fuzzy_and([
xzero,
fuzzy_or([ymod < pi/2, ymod > 3*pi/2])
])
])
def _eval_is_nonnegative(self):
z = self.args[0]
x, y = z.as_real_imag()
ymod = y % (2*pi)
yzero = ymod.is_zero
# shortcut if ymod is zero
if yzero:
return True
xzero = x.is_zero
# shortcut x is not zero
if xzero is False:
return yzero
return fuzzy_or([
# Case 1:
yzero,
# Case 2:
fuzzy_and([
xzero,
fuzzy_or([ymod <= pi/2, ymod >= 3*pi/2])
])
])
def _eval_is_finite(self):
arg = self.args[0]
return arg.is_finite
def _eval_is_zero(self):
rest, ipi_mult = _peeloff_ipi(self.args[0])
if ipi_mult and rest.is_zero:
return (ipi_mult - S.Half).is_integer
class tanh(HyperbolicFunction):
r"""
tanh(x) is the hyperbolic tangent of x.
The hyperbolic tangent function is $\frac{\sinh(x)}{\cosh(x)}$.
Examples
========
>>> from sympy import tanh
>>> from sympy.abc import x
>>> tanh(x)
tanh(x)
See Also
========
sinh, cosh, atanh
"""
def fdiff(self, argindex=1):
if argindex == 1:
return S.One - tanh(self.args[0])**2
else:
raise ArgumentIndexError(self, argindex)
def inverse(self, argindex=1):
"""
Returns the inverse of this function.
"""
return atanh
@classmethod
def eval(cls, arg):
from sympy.functions.elementary.trigonometric import tan
arg = sympify(arg)
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.One
elif arg is S.NegativeInfinity:
return S.NegativeOne
elif arg.is_zero:
return S.Zero
elif arg.is_negative:
return -cls(-arg)
else:
if arg is S.ComplexInfinity:
return S.NaN
i_coeff = arg.as_coefficient(S.ImaginaryUnit)
if i_coeff is not None:
if i_coeff.could_extract_minus_sign():
return -S.ImaginaryUnit * tan(-i_coeff)
return S.ImaginaryUnit * tan(i_coeff)
else:
if arg.could_extract_minus_sign():
return -cls(-arg)
if arg.is_Add:
x, m = _peeloff_ipi(arg)
if m:
tanhm = tanh(m*S.Pi*S.ImaginaryUnit)
if tanhm is S.ComplexInfinity:
return coth(x)
else: # tanhm == 0
return tanh(x)
if arg.is_zero:
return S.Zero
if arg.func == asinh:
x = arg.args[0]
return x/sqrt(1 + x**2)
if arg.func == acosh:
x = arg.args[0]
return sqrt(x - 1) * sqrt(x + 1) / x
if arg.func == atanh:
return arg.args[0]
if arg.func == acoth:
return 1/arg.args[0]
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
from sympy.functions.combinatorial.numbers import bernoulli
if n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
a = 2**(n + 1)
B = bernoulli(n + 1)
F = factorial(n + 1)
return a*(a - 1) * B/F * x**n
def _eval_conjugate(self):
return self.func(self.args[0].conjugate())
def as_real_imag(self, deep=True, **hints):
from sympy.functions.elementary.trigonometric import (cos, sin)
if self.args[0].is_extended_real:
if deep:
hints['complex'] = False
return (self.expand(deep, **hints), S.Zero)
else:
return (self, S.Zero)
if deep:
re, im = self.args[0].expand(deep, **hints).as_real_imag()
else:
re, im = self.args[0].as_real_imag()
denom = sinh(re)**2 + cos(im)**2
return (sinh(re)*cosh(re)/denom, sin(im)*cos(im)/denom)
def _eval_expand_trig(self, **hints):
arg = self.args[0]
if arg.is_Add:
from sympy.polys.specialpolys import symmetric_poly
n = len(arg.args)
TX = [tanh(x, evaluate=False)._eval_expand_trig()
for x in arg.args]
p = [0, 0] # [den, num]
for i in range(n + 1):
p[i % 2] += symmetric_poly(i, TX)
return p[1]/p[0]
elif arg.is_Mul:
from sympy.functions.combinatorial.numbers import nC
coeff, terms = arg.as_coeff_Mul()
if coeff.is_Integer and coeff > 1:
n = []
d = []
T = tanh(terms)
for k in range(1, coeff + 1, 2):
n.append(nC(range(coeff), k)*T**k)
for k in range(0, coeff + 1, 2):
d.append(nC(range(coeff), k)*T**k)
return Add(*n)/Add(*d)
return tanh(arg)
def _eval_rewrite_as_tractable(self, arg, limitvar=None, **kwargs):
neg_exp, pos_exp = exp(-arg), exp(arg)
return (pos_exp - neg_exp)/(pos_exp + neg_exp)
def _eval_rewrite_as_exp(self, arg, **kwargs):
neg_exp, pos_exp = exp(-arg), exp(arg)
return (pos_exp - neg_exp)/(pos_exp + neg_exp)
def _eval_rewrite_as_sinh(self, arg, **kwargs):
return S.ImaginaryUnit*sinh(arg)/sinh(S.Pi*S.ImaginaryUnit/2 - arg)
def _eval_rewrite_as_cosh(self, arg, **kwargs):
return S.ImaginaryUnit*cosh(S.Pi*S.ImaginaryUnit/2 - arg)/cosh(arg)
def _eval_rewrite_as_coth(self, arg, **kwargs):
return 1/coth(arg)
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.series.order import Order
arg = self.args[0].as_leading_term(x)
if x in arg.free_symbols and Order(1, x).contains(arg):
return arg
else:
return self.func(arg)
def _eval_is_real(self):
arg = self.args[0]
if arg.is_real:
return True
re, im = arg.as_real_imag()
# if denom = 0, tanh(arg) = zoo
if re == 0 and im % pi == pi/2:
return None
# check if im is of the form n*pi/2 to make sin(2*im) = 0
# if not, im could be a number, return False in that case
return (im % (pi/2)).is_zero
def _eval_is_extended_real(self):
if self.args[0].is_extended_real:
return True
def _eval_is_positive(self):
if self.args[0].is_extended_real:
return self.args[0].is_positive
def _eval_is_negative(self):
if self.args[0].is_extended_real:
return self.args[0].is_negative
def _eval_is_finite(self):
from sympy.functions.elementary.trigonometric import cos
arg = self.args[0]
re, im = arg.as_real_imag()
denom = cos(im)**2 + sinh(re)**2
if denom == 0:
return False
elif denom.is_number:
return True
if arg.is_extended_real:
return True
def _eval_is_zero(self):
arg = self.args[0]
if arg.is_zero:
return True
class coth(HyperbolicFunction):
r"""
coth(x) is the hyperbolic cotangent of x.
The hyperbolic cotangent function is $\frac{\cosh(x)}{\sinh(x)}$.
Examples
========
>>> from sympy import coth
>>> from sympy.abc import x
>>> coth(x)
coth(x)
See Also
========
sinh, cosh, acoth
"""
def fdiff(self, argindex=1):
if argindex == 1:
return -1/sinh(self.args[0])**2
else:
raise ArgumentIndexError(self, argindex)
def inverse(self, argindex=1):
"""
Returns the inverse of this function.
"""
return acoth
@classmethod
def eval(cls, arg):
from sympy.functions.elementary.trigonometric import cot
arg = sympify(arg)
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.One
elif arg is S.NegativeInfinity:
return S.NegativeOne
elif arg.is_zero:
return S.ComplexInfinity
elif arg.is_negative:
return -cls(-arg)
else:
if arg is S.ComplexInfinity:
return S.NaN
i_coeff = arg.as_coefficient(S.ImaginaryUnit)
if i_coeff is not None:
if i_coeff.could_extract_minus_sign():
return S.ImaginaryUnit * cot(-i_coeff)
return -S.ImaginaryUnit * cot(i_coeff)
else:
if arg.could_extract_minus_sign():
return -cls(-arg)
if arg.is_Add:
x, m = _peeloff_ipi(arg)
if m:
cothm = coth(m*S.Pi*S.ImaginaryUnit)
if cothm is S.ComplexInfinity:
return coth(x)
else: # cothm == 0
return tanh(x)
if arg.is_zero:
return S.ComplexInfinity
if arg.func == asinh:
x = arg.args[0]
return sqrt(1 + x**2)/x
if arg.func == acosh:
x = arg.args[0]
return x/(sqrt(x - 1) * sqrt(x + 1))
if arg.func == atanh:
return 1/arg.args[0]
if arg.func == acoth:
return arg.args[0]
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
from sympy.functions.combinatorial.numbers import bernoulli
if n == 0:
return 1 / sympify(x)
elif n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
B = bernoulli(n + 1)
F = factorial(n + 1)
return 2**(n + 1) * B/F * x**n
def _eval_conjugate(self):
return self.func(self.args[0].conjugate())
def as_real_imag(self, deep=True, **hints):
from sympy.functions.elementary.trigonometric import (cos, sin)
if self.args[0].is_extended_real:
if deep:
hints['complex'] = False
return (self.expand(deep, **hints), S.Zero)
else:
return (self, S.Zero)
if deep:
re, im = self.args[0].expand(deep, **hints).as_real_imag()
else:
re, im = self.args[0].as_real_imag()
denom = sinh(re)**2 + sin(im)**2
return (sinh(re)*cosh(re)/denom, -sin(im)*cos(im)/denom)
def _eval_rewrite_as_tractable(self, arg, limitvar=None, **kwargs):
neg_exp, pos_exp = exp(-arg), exp(arg)
return (pos_exp + neg_exp)/(pos_exp - neg_exp)
def _eval_rewrite_as_exp(self, arg, **kwargs):
neg_exp, pos_exp = exp(-arg), exp(arg)
return (pos_exp + neg_exp)/(pos_exp - neg_exp)
def _eval_rewrite_as_sinh(self, arg, **kwargs):
return -S.ImaginaryUnit*sinh(S.Pi*S.ImaginaryUnit/2 - arg)/sinh(arg)
def _eval_rewrite_as_cosh(self, arg, **kwargs):
return -S.ImaginaryUnit*cosh(arg)/cosh(S.Pi*S.ImaginaryUnit/2 - arg)
def _eval_rewrite_as_tanh(self, arg, **kwargs):
return 1/tanh(arg)
def _eval_is_positive(self):
if self.args[0].is_extended_real:
return self.args[0].is_positive
def _eval_is_negative(self):
if self.args[0].is_extended_real:
return self.args[0].is_negative
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.series.order import Order
arg = self.args[0].as_leading_term(x)
if x in arg.free_symbols and Order(1, x).contains(arg):
return 1/arg
else:
return self.func(arg)
def _eval_expand_trig(self, **hints):
arg = self.args[0]
if arg.is_Add:
from sympy.polys.specialpolys import symmetric_poly
CX = [coth(x, evaluate=False)._eval_expand_trig() for x in arg.args]
p = [[], []]
n = len(arg.args)
for i in range(n, -1, -1):
p[(n - i) % 2].append(symmetric_poly(i, CX))
return Add(*p[0])/Add(*p[1])
elif arg.is_Mul:
from sympy.functions.combinatorial.factorials import binomial
coeff, x = arg.as_coeff_Mul(rational=True)
if coeff.is_Integer and coeff > 1:
c = coth(x, evaluate=False)
p = [[], []]
for i in range(coeff, -1, -1):
p[(coeff - i) % 2].append(binomial(coeff, i)*c**i)
return Add(*p[0])/Add(*p[1])
return coth(arg)
class ReciprocalHyperbolicFunction(HyperbolicFunction):
"""Base class for reciprocal functions of hyperbolic functions. """
#To be defined in class
_reciprocal_of = None
_is_even = None # type: FuzzyBool
_is_odd = None # type: FuzzyBool
@classmethod
def eval(cls, arg):
if arg.could_extract_minus_sign():
if cls._is_even:
return cls(-arg)
if cls._is_odd:
return -cls(-arg)
t = cls._reciprocal_of.eval(arg)
if hasattr(arg, 'inverse') and arg.inverse() == cls:
return arg.args[0]
return 1/t if t is not None else t
def _call_reciprocal(self, method_name, *args, **kwargs):
# Calls method_name on _reciprocal_of
o = self._reciprocal_of(self.args[0])
return getattr(o, method_name)(*args, **kwargs)
def _calculate_reciprocal(self, method_name, *args, **kwargs):
# If calling method_name on _reciprocal_of returns a value != None
# then return the reciprocal of that value
t = self._call_reciprocal(method_name, *args, **kwargs)
return 1/t if t is not None else t
def _rewrite_reciprocal(self, method_name, arg):
# Special handling for rewrite functions. If reciprocal rewrite returns
# unmodified expression, then return None
t = self._call_reciprocal(method_name, arg)
if t is not None and t != self._reciprocal_of(arg):
return 1/t
def _eval_rewrite_as_exp(self, arg, **kwargs):
return self._rewrite_reciprocal("_eval_rewrite_as_exp", arg)
def _eval_rewrite_as_tractable(self, arg, limitvar=None, **kwargs):
return self._rewrite_reciprocal("_eval_rewrite_as_tractable", arg)
def _eval_rewrite_as_tanh(self, arg, **kwargs):
return self._rewrite_reciprocal("_eval_rewrite_as_tanh", arg)
def _eval_rewrite_as_coth(self, arg, **kwargs):
return self._rewrite_reciprocal("_eval_rewrite_as_coth", arg)
def as_real_imag(self, deep = True, **hints):
return (1 / self._reciprocal_of(self.args[0])).as_real_imag(deep, **hints)
def _eval_conjugate(self):
return self.func(self.args[0].conjugate())
def _eval_expand_complex(self, deep=True, **hints):
re_part, im_part = self.as_real_imag(deep=True, **hints)
return re_part + S.ImaginaryUnit*im_part
def _eval_expand_trig(self, **hints):
return self._calculate_reciprocal("_eval_expand_trig", **hints)
def _eval_as_leading_term(self, x, logx=None, cdir=0):
return (1/self._reciprocal_of(self.args[0]))._eval_as_leading_term(x)
def _eval_is_extended_real(self):
return self._reciprocal_of(self.args[0]).is_extended_real
def _eval_is_finite(self):
return (1/self._reciprocal_of(self.args[0])).is_finite
class csch(ReciprocalHyperbolicFunction):
r"""
csch(x) is the hyperbolic cosecant of x.
The hyperbolic cosecant function is $\frac{2}{e^x - e^{-x}}$
Examples
========
>>> from sympy import csch
>>> from sympy.abc import x
>>> csch(x)
csch(x)
See Also
========
sinh, cosh, tanh, sech, asinh, acosh
"""
_reciprocal_of = sinh
_is_odd = True
def fdiff(self, argindex=1):
"""
Returns the first derivative of this function
"""
if argindex == 1:
return -coth(self.args[0]) * csch(self.args[0])
else:
raise ArgumentIndexError(self, argindex)
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
"""
Returns the next term in the Taylor series expansion
"""
from sympy.functions.combinatorial.numbers import bernoulli
if n == 0:
return 1/sympify(x)
elif n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
B = bernoulli(n + 1)
F = factorial(n + 1)
return 2 * (1 - 2**n) * B/F * x**n
def _eval_rewrite_as_cosh(self, arg, **kwargs):
return S.ImaginaryUnit / cosh(arg + S.ImaginaryUnit * S.Pi / 2)
def _eval_is_positive(self):
if self.args[0].is_extended_real:
return self.args[0].is_positive
def _eval_is_negative(self):
if self.args[0].is_extended_real:
return self.args[0].is_negative
class sech(ReciprocalHyperbolicFunction):
r"""
sech(x) is the hyperbolic secant of x.
The hyperbolic secant function is $\frac{2}{e^x + e^{-x}}$
Examples
========
>>> from sympy import sech
>>> from sympy.abc import x
>>> sech(x)
sech(x)
See Also
========
sinh, cosh, tanh, coth, csch, asinh, acosh
"""
_reciprocal_of = cosh
_is_even = True
def fdiff(self, argindex=1):
if argindex == 1:
return - tanh(self.args[0])*sech(self.args[0])
else:
raise ArgumentIndexError(self, argindex)
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
from sympy.functions.combinatorial.numbers import euler
if n < 0 or n % 2 == 1:
return S.Zero
else:
x = sympify(x)
return euler(n) / factorial(n) * x**(n)
def _eval_rewrite_as_sinh(self, arg, **kwargs):
return S.ImaginaryUnit / sinh(arg + S.ImaginaryUnit * S.Pi /2)
def _eval_is_positive(self):
if self.args[0].is_extended_real:
return True
###############################################################################
############################# HYPERBOLIC INVERSES #############################
###############################################################################
class InverseHyperbolicFunction(Function):
"""Base class for inverse hyperbolic functions."""
pass
class asinh(InverseHyperbolicFunction):
"""
asinh(x) is the inverse hyperbolic sine of x.
The inverse hyperbolic sine function.
Examples
========
>>> from sympy import asinh
>>> from sympy.abc import x
>>> asinh(x).diff(x)
1/sqrt(x**2 + 1)
>>> asinh(1)
log(1 + sqrt(2))
See Also
========
acosh, atanh, sinh
"""
def fdiff(self, argindex=1):
if argindex == 1:
return 1/sqrt(self.args[0]**2 + 1)
else:
raise ArgumentIndexError(self, argindex)
@classmethod
def eval(cls, arg):
from sympy.functions.elementary.trigonometric import asin
arg = sympify(arg)
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.Infinity
elif arg is S.NegativeInfinity:
return S.NegativeInfinity
elif arg.is_zero:
return S.Zero
elif arg is S.One:
return log(sqrt(2) + 1)
elif arg is S.NegativeOne:
return log(sqrt(2) - 1)
elif arg.is_negative:
return -cls(-arg)
else:
if arg is S.ComplexInfinity:
return S.ComplexInfinity
if arg.is_zero:
return S.Zero
i_coeff = arg.as_coefficient(S.ImaginaryUnit)
if i_coeff is not None:
return S.ImaginaryUnit * asin(i_coeff)
else:
if arg.could_extract_minus_sign():
return -cls(-arg)
if isinstance(arg, sinh) and arg.args[0].is_number:
z = arg.args[0]
if z.is_real:
return z
r, i = match_real_imag(z)
if r is not None and i is not None:
f = floor((i + pi/2)/pi)
m = z - I*pi*f
even = f.is_even
if even is True:
return m
elif even is False:
return -m
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
if n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
if len(previous_terms) >= 2 and n > 2:
p = previous_terms[-2]
return -p * (n - 2)**2/(n*(n - 1)) * x**2
else:
k = (n - 1) // 2
R = RisingFactorial(S.Half, k)
F = factorial(k)
return S.NegativeOne**k * R / F * x**n / n
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.series.order import Order
arg = self.args[0].as_leading_term(x)
if x in arg.free_symbols and Order(1, x).contains(arg):
return arg
else:
return self.func(arg)
def _eval_rewrite_as_log(self, x, **kwargs):
return log(x + sqrt(x**2 + 1))
def inverse(self, argindex=1):
"""
Returns the inverse of this function.
"""
return sinh
def _eval_is_zero(self):
return self.args[0].is_zero
class acosh(InverseHyperbolicFunction):
"""
acosh(x) is the inverse hyperbolic cosine of x.
The inverse hyperbolic cosine function.
Examples
========
>>> from sympy import acosh
>>> from sympy.abc import x
>>> acosh(x).diff(x)
1/sqrt(x**2 - 1)
>>> acosh(1)
0
See Also
========
asinh, atanh, cosh
"""
def fdiff(self, argindex=1):
if argindex == 1:
return 1/sqrt(self.args[0]**2 - 1)
else:
raise ArgumentIndexError(self, argindex)
@classmethod
def eval(cls, arg):
arg = sympify(arg)
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.Infinity
elif arg is S.NegativeInfinity:
return S.Infinity
elif arg.is_zero:
return S.Pi*S.ImaginaryUnit / 2
elif arg is S.One:
return S.Zero
elif arg is S.NegativeOne:
return S.Pi*S.ImaginaryUnit
if arg.is_number:
cst_table = {
S.ImaginaryUnit: log(S.ImaginaryUnit*(1 + sqrt(2))),
-S.ImaginaryUnit: log(-S.ImaginaryUnit*(1 + sqrt(2))),
S.Half: S.Pi/3,
Rational(-1, 2): S.Pi*Rational(2, 3),
sqrt(2)/2: S.Pi/4,
-sqrt(2)/2: S.Pi*Rational(3, 4),
1/sqrt(2): S.Pi/4,
-1/sqrt(2): S.Pi*Rational(3, 4),
sqrt(3)/2: S.Pi/6,
-sqrt(3)/2: S.Pi*Rational(5, 6),
(sqrt(3) - 1)/sqrt(2**3): S.Pi*Rational(5, 12),
-(sqrt(3) - 1)/sqrt(2**3): S.Pi*Rational(7, 12),
sqrt(2 + sqrt(2))/2: S.Pi/8,
-sqrt(2 + sqrt(2))/2: S.Pi*Rational(7, 8),
sqrt(2 - sqrt(2))/2: S.Pi*Rational(3, 8),
-sqrt(2 - sqrt(2))/2: S.Pi*Rational(5, 8),
(1 + sqrt(3))/(2*sqrt(2)): S.Pi/12,
-(1 + sqrt(3))/(2*sqrt(2)): S.Pi*Rational(11, 12),
(sqrt(5) + 1)/4: S.Pi/5,
-(sqrt(5) + 1)/4: S.Pi*Rational(4, 5)
}
if arg in cst_table:
if arg.is_extended_real:
return cst_table[arg]*S.ImaginaryUnit
return cst_table[arg]
if arg is S.ComplexInfinity:
return S.ComplexInfinity
if arg == S.ImaginaryUnit*S.Infinity:
return S.Infinity + S.ImaginaryUnit*S.Pi/2
if arg == -S.ImaginaryUnit*S.Infinity:
return S.Infinity - S.ImaginaryUnit*S.Pi/2
if arg.is_zero:
return S.Pi*S.ImaginaryUnit*S.Half
if isinstance(arg, cosh) and arg.args[0].is_number:
z = arg.args[0]
if z.is_real:
from sympy.functions.elementary.complexes import Abs
return Abs(z)
r, i = match_real_imag(z)
if r is not None and i is not None:
f = floor(i/pi)
m = z - I*pi*f
even = f.is_even
if even is True:
if r.is_nonnegative:
return m
elif r.is_negative:
return -m
elif even is False:
m -= I*pi
if r.is_nonpositive:
return -m
elif r.is_positive:
return m
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
if n == 0:
return S.Pi*S.ImaginaryUnit / 2
elif n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
if len(previous_terms) >= 2 and n > 2:
p = previous_terms[-2]
return p * (n - 2)**2/(n*(n - 1)) * x**2
else:
k = (n - 1) // 2
R = RisingFactorial(S.Half, k)
F = factorial(k)
return -R / F * S.ImaginaryUnit * x**n / n
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.series.order import Order
arg = self.args[0].as_leading_term(x)
if x in arg.free_symbols and Order(1, x).contains(arg):
return S.ImaginaryUnit*S.Pi/2
else:
return self.func(arg)
def _eval_rewrite_as_log(self, x, **kwargs):
return log(x + sqrt(x + 1) * sqrt(x - 1))
def inverse(self, argindex=1):
"""
Returns the inverse of this function.
"""
return cosh
def _eval_is_zero(self):
if (self.args[0] - 1).is_zero:
return True
class atanh(InverseHyperbolicFunction):
"""
atanh(x) is the inverse hyperbolic tangent of x.
The inverse hyperbolic tangent function.
Examples
========
>>> from sympy import atanh
>>> from sympy.abc import x
>>> atanh(x).diff(x)
1/(1 - x**2)
See Also
========
asinh, acosh, tanh
"""
def fdiff(self, argindex=1):
if argindex == 1:
return 1/(1 - self.args[0]**2)
else:
raise ArgumentIndexError(self, argindex)
@classmethod
def eval(cls, arg):
from sympy.functions.elementary.trigonometric import atan
arg = sympify(arg)
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg.is_zero:
return S.Zero
elif arg is S.One:
return S.Infinity
elif arg is S.NegativeOne:
return S.NegativeInfinity
elif arg is S.Infinity:
return -S.ImaginaryUnit * atan(arg)
elif arg is S.NegativeInfinity:
return S.ImaginaryUnit * atan(-arg)
elif arg.is_negative:
return -cls(-arg)
else:
if arg is S.ComplexInfinity:
from sympy.calculus.util import AccumBounds
return S.ImaginaryUnit*AccumBounds(-S.Pi/2, S.Pi/2)
i_coeff = arg.as_coefficient(S.ImaginaryUnit)
if i_coeff is not None:
return S.ImaginaryUnit * atan(i_coeff)
else:
if arg.could_extract_minus_sign():
return -cls(-arg)
if arg.is_zero:
return S.Zero
if isinstance(arg, tanh) and arg.args[0].is_number:
z = arg.args[0]
if z.is_real:
return z
r, i = match_real_imag(z)
if r is not None and i is not None:
f = floor(2*i/pi)
even = f.is_even
m = z - I*f*pi/2
if even is True:
return m
elif even is False:
return m - I*pi/2
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
if n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
return x**n / n
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.series.order import Order
arg = self.args[0].as_leading_term(x)
if x in arg.free_symbols and Order(1, x).contains(arg):
return arg
else:
return self.func(arg)
def _eval_rewrite_as_log(self, x, **kwargs):
return (log(1 + x) - log(1 - x)) / 2
def _eval_is_zero(self):
if self.args[0].is_zero:
return True
def _eval_is_imaginary(self):
return self.args[0].is_imaginary
def inverse(self, argindex=1):
"""
Returns the inverse of this function.
"""
return tanh
class acoth(InverseHyperbolicFunction):
"""
acoth(x) is the inverse hyperbolic cotangent of x.
The inverse hyperbolic cotangent function.
Examples
========
>>> from sympy import acoth
>>> from sympy.abc import x
>>> acoth(x).diff(x)
1/(1 - x**2)
See Also
========
asinh, acosh, coth
"""
def fdiff(self, argindex=1):
if argindex == 1:
return 1/(1 - self.args[0]**2)
else:
raise ArgumentIndexError(self, argindex)
@classmethod
def eval(cls, arg):
from sympy.functions.elementary.trigonometric import acot
arg = sympify(arg)
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.Zero
elif arg is S.NegativeInfinity:
return S.Zero
elif arg.is_zero:
return S.Pi*S.ImaginaryUnit / 2
elif arg is S.One:
return S.Infinity
elif arg is S.NegativeOne:
return S.NegativeInfinity
elif arg.is_negative:
return -cls(-arg)
else:
if arg is S.ComplexInfinity:
return S.Zero
i_coeff = arg.as_coefficient(S.ImaginaryUnit)
if i_coeff is not None:
return -S.ImaginaryUnit * acot(i_coeff)
else:
if arg.could_extract_minus_sign():
return -cls(-arg)
if arg.is_zero:
return S.Pi*S.ImaginaryUnit*S.Half
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
if n == 0:
return S.Pi*S.ImaginaryUnit / 2
elif n < 0 or n % 2 == 0:
return S.Zero
else:
x = sympify(x)
return x**n / n
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.series.order import Order
arg = self.args[0].as_leading_term(x)
if x in arg.free_symbols and Order(1, x).contains(arg):
return S.ImaginaryUnit*S.Pi/2
else:
return self.func(arg)
def _eval_rewrite_as_log(self, x, **kwargs):
return (log(1 + 1/x) - log(1 - 1/x)) / 2
def inverse(self, argindex=1):
"""
Returns the inverse of this function.
"""
return coth
class asech(InverseHyperbolicFunction):
"""
asech(x) is the inverse hyperbolic secant of x.
The inverse hyperbolic secant function.
Examples
========
>>> from sympy import asech, sqrt, S
>>> from sympy.abc import x
>>> asech(x).diff(x)
-1/(x*sqrt(1 - x**2))
>>> asech(1).diff(x)
0
>>> asech(1)
0
>>> asech(S(2))
I*pi/3
>>> asech(-sqrt(2))
3*I*pi/4
>>> asech((sqrt(6) - sqrt(2)))
I*pi/12
See Also
========
asinh, atanh, cosh, acoth
References
==========
.. [1] https://en.wikipedia.org/wiki/Hyperbolic_function
.. [2] http://dlmf.nist.gov/4.37
.. [3] http://functions.wolfram.com/ElementaryFunctions/ArcSech/
"""
def fdiff(self, argindex=1):
if argindex == 1:
z = self.args[0]
return -1/(z*sqrt(1 - z**2))
else:
raise ArgumentIndexError(self, argindex)
@classmethod
def eval(cls, arg):
arg = sympify(arg)
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.Pi*S.ImaginaryUnit / 2
elif arg is S.NegativeInfinity:
return S.Pi*S.ImaginaryUnit / 2
elif arg.is_zero:
return S.Infinity
elif arg is S.One:
return S.Zero
elif arg is S.NegativeOne:
return S.Pi*S.ImaginaryUnit
if arg.is_number:
cst_table = {
S.ImaginaryUnit: - (S.Pi*S.ImaginaryUnit / 2) + log(1 + sqrt(2)),
-S.ImaginaryUnit: (S.Pi*S.ImaginaryUnit / 2) + log(1 + sqrt(2)),
(sqrt(6) - sqrt(2)): S.Pi / 12,
(sqrt(2) - sqrt(6)): 11*S.Pi / 12,
sqrt(2 - 2/sqrt(5)): S.Pi / 10,
-sqrt(2 - 2/sqrt(5)): 9*S.Pi / 10,
2 / sqrt(2 + sqrt(2)): S.Pi / 8,
-2 / sqrt(2 + sqrt(2)): 7*S.Pi / 8,
2 / sqrt(3): S.Pi / 6,
-2 / sqrt(3): 5*S.Pi / 6,
(sqrt(5) - 1): S.Pi / 5,
(1 - sqrt(5)): 4*S.Pi / 5,
sqrt(2): S.Pi / 4,
-sqrt(2): 3*S.Pi / 4,
sqrt(2 + 2/sqrt(5)): 3*S.Pi / 10,
-sqrt(2 + 2/sqrt(5)): 7*S.Pi / 10,
S(2): S.Pi / 3,
-S(2): 2*S.Pi / 3,
sqrt(2*(2 + sqrt(2))): 3*S.Pi / 8,
-sqrt(2*(2 + sqrt(2))): 5*S.Pi / 8,
(1 + sqrt(5)): 2*S.Pi / 5,
(-1 - sqrt(5)): 3*S.Pi / 5,
(sqrt(6) + sqrt(2)): 5*S.Pi / 12,
(-sqrt(6) - sqrt(2)): 7*S.Pi / 12,
}
if arg in cst_table:
if arg.is_extended_real:
return cst_table[arg]*S.ImaginaryUnit
return cst_table[arg]
if arg is S.ComplexInfinity:
from sympy.calculus.util import AccumBounds
return S.ImaginaryUnit*AccumBounds(-S.Pi/2, S.Pi/2)
if arg.is_zero:
return S.Infinity
@staticmethod
@cacheit
def expansion_term(n, x, *previous_terms):
if n == 0:
return log(2 / x)
elif n < 0 or n % 2 == 1:
return S.Zero
else:
x = sympify(x)
if len(previous_terms) > 2 and n > 2:
p = previous_terms[-2]
return p * (n - 1)**2 // (n // 2)**2 * x**2 / 4
else:
k = n // 2
R = RisingFactorial(S.Half, k) * n
F = factorial(k) * n // 2 * n // 2
return -1 * R / F * x**n / 4
def inverse(self, argindex=1):
"""
Returns the inverse of this function.
"""
return sech
def _eval_rewrite_as_log(self, arg, **kwargs):
return log(1/arg + sqrt(1/arg - 1) * sqrt(1/arg + 1))
class acsch(InverseHyperbolicFunction):
"""
acsch(x) is the inverse hyperbolic cosecant of x.
The inverse hyperbolic cosecant function.
Examples
========
>>> from sympy import acsch, sqrt, S
>>> from sympy.abc import x
>>> acsch(x).diff(x)
-1/(x**2*sqrt(1 + x**(-2)))
>>> acsch(1).diff(x)
0
>>> acsch(1)
log(1 + sqrt(2))
>>> acsch(S.ImaginaryUnit)
-I*pi/2
>>> acsch(-2*S.ImaginaryUnit)
I*pi/6
>>> acsch(S.ImaginaryUnit*(sqrt(6) - sqrt(2)))
-5*I*pi/12
See Also
========
asinh
References
==========
.. [1] https://en.wikipedia.org/wiki/Hyperbolic_function
.. [2] http://dlmf.nist.gov/4.37
.. [3] http://functions.wolfram.com/ElementaryFunctions/ArcCsch/
"""
def fdiff(self, argindex=1):
if argindex == 1:
z = self.args[0]
return -1/(z**2*sqrt(1 + 1/z**2))
else:
raise ArgumentIndexError(self, argindex)
@classmethod
def eval(cls, arg):
arg = sympify(arg)
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.Zero
elif arg is S.NegativeInfinity:
return S.Zero
elif arg.is_zero:
return S.ComplexInfinity
elif arg is S.One:
return log(1 + sqrt(2))
elif arg is S.NegativeOne:
return - log(1 + sqrt(2))
if arg.is_number:
cst_table = {
S.ImaginaryUnit: -S.Pi / 2,
S.ImaginaryUnit*(sqrt(2) + sqrt(6)): -S.Pi / 12,
S.ImaginaryUnit*(1 + sqrt(5)): -S.Pi / 10,
S.ImaginaryUnit*2 / sqrt(2 - sqrt(2)): -S.Pi / 8,
S.ImaginaryUnit*2: -S.Pi / 6,
S.ImaginaryUnit*sqrt(2 + 2/sqrt(5)): -S.Pi / 5,
S.ImaginaryUnit*sqrt(2): -S.Pi / 4,
S.ImaginaryUnit*(sqrt(5)-1): -3*S.Pi / 10,
S.ImaginaryUnit*2 / sqrt(3): -S.Pi / 3,
S.ImaginaryUnit*2 / sqrt(2 + sqrt(2)): -3*S.Pi / 8,
S.ImaginaryUnit*sqrt(2 - 2/sqrt(5)): -2*S.Pi / 5,
S.ImaginaryUnit*(sqrt(6) - sqrt(2)): -5*S.Pi / 12,
S(2): -S.ImaginaryUnit*log((1+sqrt(5))/2),
}
if arg in cst_table:
return cst_table[arg]*S.ImaginaryUnit
if arg is S.ComplexInfinity:
return S.Zero
if arg.is_zero:
return S.ComplexInfinity
if arg.could_extract_minus_sign():
return -cls(-arg)
def inverse(self, argindex=1):
"""
Returns the inverse of this function.
"""
return csch
def _eval_rewrite_as_log(self, arg, **kwargs):
return log(1/arg + sqrt(1/arg**2 + 1))
def _eval_is_zero(self):
return self.args[0].is_infinite
|
7f2eb3a394e54321860c9ea7a19918bfad588f3b1fbccb08654ebb6aab4ecafd | from typing import Tuple as tTuple
from sympy.core import S, Add, Mul, sympify, Symbol, Dummy, Basic
from sympy.core.expr import Expr
from sympy.core.exprtools import factor_terms
from sympy.core.function import (Function, Derivative, ArgumentIndexError,
AppliedUndef, expand_mul)
from sympy.core.logic import fuzzy_not, fuzzy_or
from sympy.core.numbers import pi, I, oo
from sympy.core.power import Pow
from sympy.core.relational import Eq
from sympy.functions.elementary.exponential import exp, exp_polar, log
from sympy.functions.elementary.integers import ceiling
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.piecewise import Piecewise
from sympy.functions.elementary.trigonometric import atan, atan2
###############################################################################
######################### REAL and IMAGINARY PARTS ############################
###############################################################################
class re(Function):
"""
Returns real part of expression. This function performs only
elementary analysis and so it will fail to decompose properly
more complicated expressions. If completely simplified result
is needed then use Basic.as_real_imag() or perform complex
expansion on instance of this function.
Examples
========
>>> from sympy import re, im, I, E, symbols
>>> x, y = symbols('x y', real=True)
>>> re(2*E)
2*E
>>> re(2*I + 17)
17
>>> re(2*I)
0
>>> re(im(x) + x*I + 2)
2
>>> re(5 + I + 2)
7
Parameters
==========
arg : Expr
Real or complex expression.
Returns
=======
expr : Expr
Real part of expression.
See Also
========
im
"""
args: tTuple[Expr]
is_extended_real = True
unbranched = True # implicitly works on the projection to C
_singularities = True # non-holomorphic
@classmethod
def eval(cls, arg):
if arg is S.NaN:
return S.NaN
elif arg is S.ComplexInfinity:
return S.NaN
elif arg.is_extended_real:
return arg
elif arg.is_imaginary or (S.ImaginaryUnit*arg).is_extended_real:
return S.Zero
elif arg.is_Matrix:
return arg.as_real_imag()[0]
elif arg.is_Function and isinstance(arg, conjugate):
return re(arg.args[0])
else:
included, reverted, excluded = [], [], []
args = Add.make_args(arg)
for term in args:
coeff = term.as_coefficient(S.ImaginaryUnit)
if coeff is not None:
if not coeff.is_extended_real:
reverted.append(coeff)
elif not term.has(S.ImaginaryUnit) and term.is_extended_real:
excluded.append(term)
else:
# Try to do some advanced expansion. If
# impossible, don't try to do re(arg) again
# (because this is what we are trying to do now).
real_imag = term.as_real_imag(ignore=arg)
if real_imag:
excluded.append(real_imag[0])
else:
included.append(term)
if len(args) != len(included):
a, b, c = (Add(*xs) for xs in [included, reverted, excluded])
return cls(a) - im(b) + c
def as_real_imag(self, deep=True, **hints):
"""
Returns the real number with a zero imaginary part.
"""
return (self, S.Zero)
def _eval_derivative(self, x):
if x.is_extended_real or self.args[0].is_extended_real:
return re(Derivative(self.args[0], x, evaluate=True))
if x.is_imaginary or self.args[0].is_imaginary:
return -S.ImaginaryUnit \
* im(Derivative(self.args[0], x, evaluate=True))
def _eval_rewrite_as_im(self, arg, **kwargs):
return self.args[0] - S.ImaginaryUnit*im(self.args[0])
def _eval_is_algebraic(self):
return self.args[0].is_algebraic
def _eval_is_zero(self):
# is_imaginary implies nonzero
return fuzzy_or([self.args[0].is_imaginary, self.args[0].is_zero])
def _eval_is_finite(self):
if self.args[0].is_finite:
return True
def _eval_is_complex(self):
if self.args[0].is_finite:
return True
class im(Function):
"""
Returns imaginary part of expression. This function performs only
elementary analysis and so it will fail to decompose properly more
complicated expressions. If completely simplified result is needed then
use Basic.as_real_imag() or perform complex expansion on instance of
this function.
Examples
========
>>> from sympy import re, im, E, I
>>> from sympy.abc import x, y
>>> im(2*E)
0
>>> im(2*I + 17)
2
>>> im(x*I)
re(x)
>>> im(re(x) + y)
im(y)
>>> im(2 + 3*I)
3
Parameters
==========
arg : Expr
Real or complex expression.
Returns
=======
expr : Expr
Imaginary part of expression.
See Also
========
re
"""
args: tTuple[Expr]
is_extended_real = True
unbranched = True # implicitly works on the projection to C
_singularities = True # non-holomorphic
@classmethod
def eval(cls, arg):
if arg is S.NaN:
return S.NaN
elif arg is S.ComplexInfinity:
return S.NaN
elif arg.is_extended_real:
return S.Zero
elif arg.is_imaginary or (S.ImaginaryUnit*arg).is_extended_real:
return -S.ImaginaryUnit * arg
elif arg.is_Matrix:
return arg.as_real_imag()[1]
elif arg.is_Function and isinstance(arg, conjugate):
return -im(arg.args[0])
else:
included, reverted, excluded = [], [], []
args = Add.make_args(arg)
for term in args:
coeff = term.as_coefficient(S.ImaginaryUnit)
if coeff is not None:
if not coeff.is_extended_real:
reverted.append(coeff)
else:
excluded.append(coeff)
elif term.has(S.ImaginaryUnit) or not term.is_extended_real:
# Try to do some advanced expansion. If
# impossible, don't try to do im(arg) again
# (because this is what we are trying to do now).
real_imag = term.as_real_imag(ignore=arg)
if real_imag:
excluded.append(real_imag[1])
else:
included.append(term)
if len(args) != len(included):
a, b, c = (Add(*xs) for xs in [included, reverted, excluded])
return cls(a) + re(b) + c
def as_real_imag(self, deep=True, **hints):
"""
Return the imaginary part with a zero real part.
"""
return (self, S.Zero)
def _eval_derivative(self, x):
if x.is_extended_real or self.args[0].is_extended_real:
return im(Derivative(self.args[0], x, evaluate=True))
if x.is_imaginary or self.args[0].is_imaginary:
return -S.ImaginaryUnit \
* re(Derivative(self.args[0], x, evaluate=True))
def _eval_rewrite_as_re(self, arg, **kwargs):
return -S.ImaginaryUnit*(self.args[0] - re(self.args[0]))
def _eval_is_algebraic(self):
return self.args[0].is_algebraic
def _eval_is_zero(self):
return self.args[0].is_extended_real
def _eval_is_finite(self):
if self.args[0].is_finite:
return True
def _eval_is_complex(self):
if self.args[0].is_finite:
return True
###############################################################################
############### SIGN, ABSOLUTE VALUE, ARGUMENT and CONJUGATION ################
###############################################################################
class sign(Function):
"""
Returns the complex sign of an expression:
Explanation
===========
If the expression is real the sign will be:
* 1 if expression is positive
* 0 if expression is equal to zero
* -1 if expression is negative
If the expression is imaginary the sign will be:
* I if im(expression) is positive
* -I if im(expression) is negative
Otherwise an unevaluated expression will be returned. When evaluated, the
result (in general) will be ``cos(arg(expr)) + I*sin(arg(expr))``.
Examples
========
>>> from sympy import sign, I
>>> sign(-1)
-1
>>> sign(0)
0
>>> sign(-3*I)
-I
>>> sign(1 + I)
sign(1 + I)
>>> _.evalf()
0.707106781186548 + 0.707106781186548*I
Parameters
==========
arg : Expr
Real or imaginary expression.
Returns
=======
expr : Expr
Complex sign of expression.
See Also
========
Abs, conjugate
"""
is_complex = True
_singularities = True
def doit(self, **hints):
s = super().doit()
if s == self and self.args[0].is_zero is False:
return self.args[0] / Abs(self.args[0])
return s
@classmethod
def eval(cls, arg):
# handle what we can
if arg.is_Mul:
c, args = arg.as_coeff_mul()
unk = []
s = sign(c)
for a in args:
if a.is_extended_negative:
s = -s
elif a.is_extended_positive:
pass
else:
if a.is_imaginary:
ai = im(a)
if ai.is_comparable: # i.e. a = I*real
s *= S.ImaginaryUnit
if ai.is_extended_negative:
# can't use sign(ai) here since ai might not be
# a Number
s = -s
else:
unk.append(a)
else:
unk.append(a)
if c is S.One and len(unk) == len(args):
return None
return s * cls(arg._new_rawargs(*unk))
if arg is S.NaN:
return S.NaN
if arg.is_zero: # it may be an Expr that is zero
return S.Zero
if arg.is_extended_positive:
return S.One
if arg.is_extended_negative:
return S.NegativeOne
if arg.is_Function:
if isinstance(arg, sign):
return arg
if arg.is_imaginary:
if arg.is_Pow and arg.exp is S.Half:
# we catch this because non-trivial sqrt args are not expanded
# e.g. sqrt(1-sqrt(2)) --x--> to I*sqrt(sqrt(2) - 1)
return S.ImaginaryUnit
arg2 = -S.ImaginaryUnit * arg
if arg2.is_extended_positive:
return S.ImaginaryUnit
if arg2.is_extended_negative:
return -S.ImaginaryUnit
def _eval_Abs(self):
if fuzzy_not(self.args[0].is_zero):
return S.One
def _eval_conjugate(self):
return sign(conjugate(self.args[0]))
def _eval_derivative(self, x):
if self.args[0].is_extended_real:
from sympy.functions.special.delta_functions import DiracDelta
return 2 * Derivative(self.args[0], x, evaluate=True) \
* DiracDelta(self.args[0])
elif self.args[0].is_imaginary:
from sympy.functions.special.delta_functions import DiracDelta
return 2 * Derivative(self.args[0], x, evaluate=True) \
* DiracDelta(-S.ImaginaryUnit * self.args[0])
def _eval_is_nonnegative(self):
if self.args[0].is_nonnegative:
return True
def _eval_is_nonpositive(self):
if self.args[0].is_nonpositive:
return True
def _eval_is_imaginary(self):
return self.args[0].is_imaginary
def _eval_is_integer(self):
return self.args[0].is_extended_real
def _eval_is_zero(self):
return self.args[0].is_zero
def _eval_power(self, other):
if (
fuzzy_not(self.args[0].is_zero) and
other.is_integer and
other.is_even
):
return S.One
def _eval_nseries(self, x, n, logx, cdir=0):
arg0 = self.args[0]
x0 = arg0.subs(x, 0)
if x0 != 0:
return self.func(x0)
if cdir != 0:
cdir = arg0.dir(x, cdir)
return -S.One if re(cdir) < 0 else S.One
def _eval_rewrite_as_Piecewise(self, arg, **kwargs):
if arg.is_extended_real:
return Piecewise((1, arg > 0), (-1, arg < 0), (0, True))
def _eval_rewrite_as_Heaviside(self, arg, **kwargs):
from sympy.functions.special.delta_functions import Heaviside
if arg.is_extended_real:
return Heaviside(arg) * 2 - 1
def _eval_rewrite_as_Abs(self, arg, **kwargs):
return Piecewise((0, Eq(arg, 0)), (arg / Abs(arg), True))
def _eval_simplify(self, **kwargs):
return self.func(factor_terms(self.args[0])) # XXX include doit?
class Abs(Function):
"""
Return the absolute value of the argument.
Explanation
===========
This is an extension of the built-in function abs() to accept symbolic
values. If you pass a SymPy expression to the built-in abs(), it will
pass it automatically to Abs().
Examples
========
>>> from sympy import Abs, Symbol, S, I
>>> Abs(-1)
1
>>> x = Symbol('x', real=True)
>>> Abs(-x)
Abs(x)
>>> Abs(x**2)
x**2
>>> abs(-x) # The Python built-in
Abs(x)
>>> Abs(3*x + 2*I)
sqrt(9*x**2 + 4)
>>> Abs(8*I)
8
Note that the Python built-in will return either an Expr or int depending on
the argument::
>>> type(abs(-1))
<... 'int'>
>>> type(abs(S.NegativeOne))
<class 'sympy.core.numbers.One'>
Abs will always return a SymPy object.
Parameters
==========
arg : Expr
Real or complex expression.
Returns
=======
expr : Expr
Absolute value returned can be an expression or integer depending on
input arg.
See Also
========
sign, conjugate
"""
args: tTuple[Expr]
is_extended_real = True
is_extended_negative = False
is_extended_nonnegative = True
unbranched = True
_singularities = True # non-holomorphic
def fdiff(self, argindex=1):
"""
Get the first derivative of the argument to Abs().
"""
if argindex == 1:
return sign(self.args[0])
else:
raise ArgumentIndexError(self, argindex)
@classmethod
def eval(cls, arg):
from sympy.simplify.simplify import signsimp
if hasattr(arg, '_eval_Abs'):
obj = arg._eval_Abs()
if obj is not None:
return obj
if not isinstance(arg, Expr):
raise TypeError("Bad argument type for Abs(): %s" % type(arg))
# handle what we can
arg = signsimp(arg, evaluate=False)
n, d = arg.as_numer_denom()
if d.free_symbols and not n.free_symbols:
return cls(n)/cls(d)
if arg.is_Mul:
known = []
unk = []
for t in arg.args:
if t.is_Pow and t.exp.is_integer and t.exp.is_negative:
bnew = cls(t.base)
if isinstance(bnew, cls):
unk.append(t)
else:
known.append(Pow(bnew, t.exp))
else:
tnew = cls(t)
if isinstance(tnew, cls):
unk.append(t)
else:
known.append(tnew)
known = Mul(*known)
unk = cls(Mul(*unk), evaluate=False) if unk else S.One
return known*unk
if arg is S.NaN:
return S.NaN
if arg is S.ComplexInfinity:
return S.Infinity
if arg.is_Pow:
base, exponent = arg.as_base_exp()
if base.is_extended_real:
if exponent.is_integer:
if exponent.is_even:
return arg
if base is S.NegativeOne:
return S.One
return Abs(base)**exponent
if base.is_extended_nonnegative:
return base**re(exponent)
if base.is_extended_negative:
return (-base)**re(exponent)*exp(-S.Pi*im(exponent))
return
elif not base.has(Symbol): # complex base
# express base**exponent as exp(exponent*log(base))
a, b = log(base).as_real_imag()
z = a + I*b
return exp(re(exponent*z))
if isinstance(arg, exp):
return exp(re(arg.args[0]))
if isinstance(arg, AppliedUndef):
if arg.is_positive:
return arg
elif arg.is_negative:
return -arg
return
if arg.is_Add and arg.has(S.Infinity, S.NegativeInfinity):
if any(a.is_infinite for a in arg.as_real_imag()):
return S.Infinity
if arg.is_zero:
return S.Zero
if arg.is_extended_nonnegative:
return arg
if arg.is_extended_nonpositive:
return -arg
if arg.is_imaginary:
arg2 = -S.ImaginaryUnit * arg
if arg2.is_extended_nonnegative:
return arg2
if arg.is_extended_real:
return
# reject result if all new conjugates are just wrappers around
# an expression that was already in the arg
conj = signsimp(arg.conjugate(), evaluate=False)
new_conj = conj.atoms(conjugate) - arg.atoms(conjugate)
if new_conj and all(arg.has(i.args[0]) for i in new_conj):
return
if arg != conj and arg != -conj:
ignore = arg.atoms(Abs)
abs_free_arg = arg.xreplace({i: Dummy(real=True) for i in ignore})
unk = [a for a in abs_free_arg.free_symbols if a.is_extended_real is None]
if not unk or not all(conj.has(conjugate(u)) for u in unk):
return sqrt(expand_mul(arg*conj))
def _eval_is_real(self):
if self.args[0].is_finite:
return True
def _eval_is_integer(self):
if self.args[0].is_extended_real:
return self.args[0].is_integer
def _eval_is_extended_nonzero(self):
return fuzzy_not(self._args[0].is_zero)
def _eval_is_zero(self):
return self._args[0].is_zero
def _eval_is_extended_positive(self):
is_z = self.is_zero
if is_z is not None:
return not is_z
def _eval_is_rational(self):
if self.args[0].is_extended_real:
return self.args[0].is_rational
def _eval_is_even(self):
if self.args[0].is_extended_real:
return self.args[0].is_even
def _eval_is_odd(self):
if self.args[0].is_extended_real:
return self.args[0].is_odd
def _eval_is_algebraic(self):
return self.args[0].is_algebraic
def _eval_power(self, exponent):
if self.args[0].is_extended_real and exponent.is_integer:
if exponent.is_even:
return self.args[0]**exponent
elif exponent is not S.NegativeOne and exponent.is_Integer:
return self.args[0]**(exponent - 1)*self
return
def _eval_nseries(self, x, n, logx, cdir=0):
direction = self.args[0].leadterm(x)[0]
if direction.has(log(x)):
direction = direction.subs(log(x), logx)
s = self.args[0]._eval_nseries(x, n=n, logx=logx)
return (sign(direction)*s).expand()
def _eval_derivative(self, x):
if self.args[0].is_extended_real or self.args[0].is_imaginary:
return Derivative(self.args[0], x, evaluate=True) \
* sign(conjugate(self.args[0]))
rv = (re(self.args[0]) * Derivative(re(self.args[0]), x,
evaluate=True) + im(self.args[0]) * Derivative(im(self.args[0]),
x, evaluate=True)) / Abs(self.args[0])
return rv.rewrite(sign)
def _eval_rewrite_as_Heaviside(self, arg, **kwargs):
# Note this only holds for real arg (since Heaviside is not defined
# for complex arguments).
from sympy.functions.special.delta_functions import Heaviside
if arg.is_extended_real:
return arg*(Heaviside(arg) - Heaviside(-arg))
def _eval_rewrite_as_Piecewise(self, arg, **kwargs):
if arg.is_extended_real:
return Piecewise((arg, arg >= 0), (-arg, True))
elif arg.is_imaginary:
return Piecewise((I*arg, I*arg >= 0), (-I*arg, True))
def _eval_rewrite_as_sign(self, arg, **kwargs):
return arg/sign(arg)
def _eval_rewrite_as_conjugate(self, arg, **kwargs):
return (arg*conjugate(arg))**S.Half
class arg(Function):
"""
returns the argument (in radians) of a complex number. The argument is
evaluated in consistent convention with atan2 where the branch-cut is
taken along the negative real axis and arg(z) is in the interval
(-pi,pi]. For a positive number, the argument is always 0; the
argument of a negative number is pi; and the argument of 0
is undefined and returns nan. So the ``arg`` function will never nest
greater than 3 levels since at the 4th application, the result must be
nan; for a real number, nan is returned on the 3rd application.
Examples
========
>>> from sympy import arg, I, sqrt, Dummy
>>> from sympy.abc import x
>>> arg(2.0)
0
>>> arg(I)
pi/2
>>> arg(sqrt(2) + I*sqrt(2))
pi/4
>>> arg(sqrt(3)/2 + I/2)
pi/6
>>> arg(4 + 3*I)
atan(3/4)
>>> arg(0.8 + 0.6*I)
0.643501108793284
>>> arg(arg(arg(arg(x))))
nan
>>> real = Dummy(real=True)
>>> arg(arg(arg(real)))
nan
Parameters
==========
arg : Expr
Real or complex expression.
Returns
=======
value : Expr
Returns arc tangent of arg measured in radians.
"""
is_extended_real = True
is_real = True
is_finite = True
_singularities = True # non-holomorphic
@classmethod
def eval(cls, arg):
a = arg
for i in range(3):
if isinstance(a, cls):
a = a.args[0]
else:
if i == 2 and a.is_extended_real:
return S.NaN
break
else:
return S.NaN
if isinstance(arg, exp_polar):
return periodic_argument(arg, oo)
if not arg.is_Atom:
c, arg_ = factor_terms(arg).as_coeff_Mul()
if arg_.is_Mul:
arg_ = Mul(*[a if (sign(a) not in (-1, 1)) else
sign(a) for a in arg_.args])
arg_ = sign(c)*arg_
else:
arg_ = arg
if any(i.is_extended_positive is None for i in arg_.atoms(AppliedUndef)):
return
x, y = arg_.as_real_imag()
rv = atan2(y, x)
if rv.is_number:
return rv
if arg_ != arg:
return cls(arg_, evaluate=False)
def _eval_derivative(self, t):
x, y = self.args[0].as_real_imag()
return (x * Derivative(y, t, evaluate=True) - y *
Derivative(x, t, evaluate=True)) / (x**2 + y**2)
def _eval_rewrite_as_atan2(self, arg, **kwargs):
x, y = self.args[0].as_real_imag()
return atan2(y, x)
class conjugate(Function):
"""
Returns the `complex conjugate` Ref[1] of an argument.
In mathematics, the complex conjugate of a complex number
is given by changing the sign of the imaginary part.
Thus, the conjugate of the complex number
:math:`a + ib` (where a and b are real numbers) is :math:`a - ib`
Examples
========
>>> from sympy import conjugate, I
>>> conjugate(2)
2
>>> conjugate(I)
-I
>>> conjugate(3 + 2*I)
3 - 2*I
>>> conjugate(5 - I)
5 + I
Parameters
==========
arg : Expr
Real or complex expression.
Returns
=======
arg : Expr
Complex conjugate of arg as real, imaginary or mixed expression.
See Also
========
sign, Abs
References
==========
.. [1] https://en.wikipedia.org/wiki/Complex_conjugation
"""
_singularities = True # non-holomorphic
@classmethod
def eval(cls, arg):
obj = arg._eval_conjugate()
if obj is not None:
return obj
def inverse(self):
return conjugate
def _eval_Abs(self):
return Abs(self.args[0], evaluate=True)
def _eval_adjoint(self):
return transpose(self.args[0])
def _eval_conjugate(self):
return self.args[0]
def _eval_derivative(self, x):
if x.is_real:
return conjugate(Derivative(self.args[0], x, evaluate=True))
elif x.is_imaginary:
return -conjugate(Derivative(self.args[0], x, evaluate=True))
def _eval_transpose(self):
return adjoint(self.args[0])
def _eval_is_algebraic(self):
return self.args[0].is_algebraic
class transpose(Function):
"""
Linear map transposition.
Examples
========
>>> from sympy import transpose, Matrix, MatrixSymbol
>>> A = MatrixSymbol('A', 25, 9)
>>> transpose(A)
A.T
>>> B = MatrixSymbol('B', 9, 22)
>>> transpose(B)
B.T
>>> transpose(A*B)
B.T*A.T
>>> M = Matrix([[4, 5], [2, 1], [90, 12]])
>>> M
Matrix([
[ 4, 5],
[ 2, 1],
[90, 12]])
>>> transpose(M)
Matrix([
[4, 2, 90],
[5, 1, 12]])
Parameters
==========
arg : Matrix
Matrix or matrix expression to take the transpose of.
Returns
=======
value : Matrix
Transpose of arg.
"""
@classmethod
def eval(cls, arg):
obj = arg._eval_transpose()
if obj is not None:
return obj
def _eval_adjoint(self):
return conjugate(self.args[0])
def _eval_conjugate(self):
return adjoint(self.args[0])
def _eval_transpose(self):
return self.args[0]
class adjoint(Function):
"""
Conjugate transpose or Hermite conjugation.
Examples
========
>>> from sympy import adjoint, MatrixSymbol
>>> A = MatrixSymbol('A', 10, 5)
>>> adjoint(A)
Adjoint(A)
Parameters
==========
arg : Matrix
Matrix or matrix expression to take the adjoint of.
Returns
=======
value : Matrix
Represents the conjugate transpose or Hermite
conjugation of arg.
"""
@classmethod
def eval(cls, arg):
obj = arg._eval_adjoint()
if obj is not None:
return obj
obj = arg._eval_transpose()
if obj is not None:
return conjugate(obj)
def _eval_adjoint(self):
return self.args[0]
def _eval_conjugate(self):
return transpose(self.args[0])
def _eval_transpose(self):
return conjugate(self.args[0])
def _latex(self, printer, exp=None, *args):
arg = printer._print(self.args[0])
tex = r'%s^{\dagger}' % arg
if exp:
tex = r'\left(%s\right)^{%s}' % (tex, exp)
return tex
def _pretty(self, printer, *args):
from sympy.printing.pretty.stringpict import prettyForm
pform = printer._print(self.args[0], *args)
if printer._use_unicode:
pform = pform**prettyForm('\N{DAGGER}')
else:
pform = pform**prettyForm('+')
return pform
###############################################################################
############### HANDLING OF POLAR NUMBERS #####################################
###############################################################################
class polar_lift(Function):
"""
Lift argument to the Riemann surface of the logarithm, using the
standard branch.
Examples
========
>>> from sympy import Symbol, polar_lift, I
>>> p = Symbol('p', polar=True)
>>> x = Symbol('x')
>>> polar_lift(4)
4*exp_polar(0)
>>> polar_lift(-4)
4*exp_polar(I*pi)
>>> polar_lift(-I)
exp_polar(-I*pi/2)
>>> polar_lift(I + 2)
polar_lift(2 + I)
>>> polar_lift(4*x)
4*polar_lift(x)
>>> polar_lift(4*p)
4*p
Parameters
==========
arg : Expr
Real or complex expression.
See Also
========
sympy.functions.elementary.exponential.exp_polar
periodic_argument
"""
is_polar = True
is_comparable = False # Cannot be evalf'd.
@classmethod
def eval(cls, arg):
from sympy.functions.elementary.complexes import arg as argument
if arg.is_number:
ar = argument(arg)
# In general we want to affirm that something is known,
# e.g. `not ar.has(argument) and not ar.has(atan)`
# but for now we will just be more restrictive and
# see that it has evaluated to one of the known values.
if ar in (0, pi/2, -pi/2, pi):
return exp_polar(I*ar)*abs(arg)
if arg.is_Mul:
args = arg.args
else:
args = [arg]
included = []
excluded = []
positive = []
for arg in args:
if arg.is_polar:
included += [arg]
elif arg.is_positive:
positive += [arg]
else:
excluded += [arg]
if len(excluded) < len(args):
if excluded:
return Mul(*(included + positive))*polar_lift(Mul(*excluded))
elif included:
return Mul(*(included + positive))
else:
return Mul(*positive)*exp_polar(0)
def _eval_evalf(self, prec):
""" Careful! any evalf of polar numbers is flaky """
return self.args[0]._eval_evalf(prec)
def _eval_Abs(self):
return Abs(self.args[0], evaluate=True)
class periodic_argument(Function):
"""
Represent the argument on a quotient of the Riemann surface of the
logarithm. That is, given a period $P$, always return a value in
(-P/2, P/2], by using exp(P*I) == 1.
Examples
========
>>> from sympy import exp_polar, periodic_argument
>>> from sympy import I, pi
>>> periodic_argument(exp_polar(10*I*pi), 2*pi)
0
>>> periodic_argument(exp_polar(5*I*pi), 4*pi)
pi
>>> from sympy import exp_polar, periodic_argument
>>> from sympy import I, pi
>>> periodic_argument(exp_polar(5*I*pi), 2*pi)
pi
>>> periodic_argument(exp_polar(5*I*pi), 3*pi)
-pi
>>> periodic_argument(exp_polar(5*I*pi), pi)
0
Parameters
==========
ar : Expr
A polar number.
period : ExprT
The period $P$.
See Also
========
sympy.functions.elementary.exponential.exp_polar
polar_lift : Lift argument to the Riemann surface of the logarithm
principal_branch
"""
@classmethod
def _getunbranched(cls, ar):
if ar.is_Mul:
args = ar.args
else:
args = [ar]
unbranched = 0
for a in args:
if not a.is_polar:
unbranched += arg(a)
elif isinstance(a, exp_polar):
unbranched += a.exp.as_real_imag()[1]
elif a.is_Pow:
re, im = a.exp.as_real_imag()
unbranched += re*unbranched_argument(
a.base) + im*log(abs(a.base))
elif isinstance(a, polar_lift):
unbranched += arg(a.args[0])
else:
return None
return unbranched
@classmethod
def eval(cls, ar, period):
# Our strategy is to evaluate the argument on the Riemann surface of the
# logarithm, and then reduce.
# NOTE evidently this means it is a rather bad idea to use this with
# period != 2*pi and non-polar numbers.
if not period.is_extended_positive:
return None
if period == oo and isinstance(ar, principal_branch):
return periodic_argument(*ar.args)
if isinstance(ar, polar_lift) and period >= 2*pi:
return periodic_argument(ar.args[0], period)
if ar.is_Mul:
newargs = [x for x in ar.args if not x.is_positive]
if len(newargs) != len(ar.args):
return periodic_argument(Mul(*newargs), period)
unbranched = cls._getunbranched(ar)
if unbranched is None:
return None
if unbranched.has(periodic_argument, atan2, atan):
return None
if period == oo:
return unbranched
if period != oo:
n = ceiling(unbranched/period - S.Half)*period
if not n.has(ceiling):
return unbranched - n
def _eval_evalf(self, prec):
z, period = self.args
if period == oo:
unbranched = periodic_argument._getunbranched(z)
if unbranched is None:
return self
return unbranched._eval_evalf(prec)
ub = periodic_argument(z, oo)._eval_evalf(prec)
return (ub - ceiling(ub/period - S.Half)*period)._eval_evalf(prec)
def unbranched_argument(arg):
'''
Returns periodic argument of arg with period as infinity.
Examples
========
>>> from sympy import exp_polar, unbranched_argument
>>> from sympy import I, pi
>>> unbranched_argument(exp_polar(15*I*pi))
15*pi
>>> unbranched_argument(exp_polar(7*I*pi))
7*pi
See also
========
periodic_argument
'''
return periodic_argument(arg, oo)
class principal_branch(Function):
"""
Represent a polar number reduced to its principal branch on a quotient
of the Riemann surface of the logarithm.
Explanation
===========
This is a function of two arguments. The first argument is a polar
number `z`, and the second one a positive real number or infinity, `p`.
The result is "z mod exp_polar(I*p)".
Examples
========
>>> from sympy import exp_polar, principal_branch, oo, I, pi
>>> from sympy.abc import z
>>> principal_branch(z, oo)
z
>>> principal_branch(exp_polar(2*pi*I)*3, 2*pi)
3*exp_polar(0)
>>> principal_branch(exp_polar(2*pi*I)*3*z, 2*pi)
3*principal_branch(z, 2*pi)
Parameters
==========
x : Expr
A polar number.
period : Expr
Positive real number or infinity.
See Also
========
sympy.functions.elementary.exponential.exp_polar
polar_lift : Lift argument to the Riemann surface of the logarithm
periodic_argument
"""
is_polar = True
is_comparable = False # cannot always be evalf'd
@classmethod
def eval(self, x, period):
if isinstance(x, polar_lift):
return principal_branch(x.args[0], period)
if period == oo:
return x
ub = periodic_argument(x, oo)
barg = periodic_argument(x, period)
if ub != barg and not ub.has(periodic_argument) \
and not barg.has(periodic_argument):
pl = polar_lift(x)
def mr(expr):
if not isinstance(expr, Symbol):
return polar_lift(expr)
return expr
pl = pl.replace(polar_lift, mr)
# Recompute unbranched argument
ub = periodic_argument(pl, oo)
if not pl.has(polar_lift):
if ub != barg:
res = exp_polar(I*(barg - ub))*pl
else:
res = pl
if not res.is_polar and not res.has(exp_polar):
res *= exp_polar(0)
return res
if not x.free_symbols:
c, m = x, ()
else:
c, m = x.as_coeff_mul(*x.free_symbols)
others = []
for y in m:
if y.is_positive:
c *= y
else:
others += [y]
m = tuple(others)
arg = periodic_argument(c, period)
if arg.has(periodic_argument):
return None
if arg.is_number and (unbranched_argument(c) != arg or
(arg == 0 and m != () and c != 1)):
if arg == 0:
return abs(c)*principal_branch(Mul(*m), period)
return principal_branch(exp_polar(I*arg)*Mul(*m), period)*abs(c)
if arg.is_number and ((abs(arg) < period/2) == True or arg == period/2) \
and m == ():
return exp_polar(arg*I)*abs(c)
def _eval_evalf(self, prec):
z, period = self.args
p = periodic_argument(z, period)._eval_evalf(prec)
if abs(p) > pi or p == -pi:
return self # Cannot evalf for this argument.
return (abs(z)*exp(I*p))._eval_evalf(prec)
def _polarify(eq, lift, pause=False):
from sympy.integrals.integrals import Integral
if eq.is_polar:
return eq
if eq.is_number and not pause:
return polar_lift(eq)
if isinstance(eq, Symbol) and not pause and lift:
return polar_lift(eq)
elif eq.is_Atom:
return eq
elif eq.is_Add:
r = eq.func(*[_polarify(arg, lift, pause=True) for arg in eq.args])
if lift:
return polar_lift(r)
return r
elif eq.is_Pow and eq.base == S.Exp1:
return eq.func(S.Exp1, _polarify(eq.exp, lift, pause=False))
elif eq.is_Function:
return eq.func(*[_polarify(arg, lift, pause=False) for arg in eq.args])
elif isinstance(eq, Integral):
# Don't lift the integration variable
func = _polarify(eq.function, lift, pause=pause)
limits = []
for limit in eq.args[1:]:
var = _polarify(limit[0], lift=False, pause=pause)
rest = _polarify(limit[1:], lift=lift, pause=pause)
limits.append((var,) + rest)
return Integral(*((func,) + tuple(limits)))
else:
return eq.func(*[_polarify(arg, lift, pause=pause)
if isinstance(arg, Expr) else arg for arg in eq.args])
def polarify(eq, subs=True, lift=False):
"""
Turn all numbers in eq into their polar equivalents (under the standard
choice of argument).
Note that no attempt is made to guess a formal convention of adding
polar numbers, expressions like 1 + x will generally not be altered.
Note also that this function does not promote exp(x) to exp_polar(x).
If ``subs`` is True, all symbols which are not already polar will be
substituted for polar dummies; in this case the function behaves much
like posify.
If ``lift`` is True, both addition statements and non-polar symbols are
changed to their polar_lift()ed versions.
Note that lift=True implies subs=False.
Examples
========
>>> from sympy import polarify, sin, I
>>> from sympy.abc import x, y
>>> expr = (-x)**y
>>> expr.expand()
(-x)**y
>>> polarify(expr)
((_x*exp_polar(I*pi))**_y, {_x: x, _y: y})
>>> polarify(expr)[0].expand()
_x**_y*exp_polar(_y*I*pi)
>>> polarify(x, lift=True)
polar_lift(x)
>>> polarify(x*(1+y), lift=True)
polar_lift(x)*polar_lift(y + 1)
Adds are treated carefully:
>>> polarify(1 + sin((1 + I)*x))
(sin(_x*polar_lift(1 + I)) + 1, {_x: x})
"""
if lift:
subs = False
eq = _polarify(sympify(eq), lift)
if not subs:
return eq
reps = {s: Dummy(s.name, polar=True) for s in eq.free_symbols}
eq = eq.subs(reps)
return eq, {r: s for s, r in reps.items()}
def _unpolarify(eq, exponents_only, pause=False):
if not isinstance(eq, Basic) or eq.is_Atom:
return eq
if not pause:
if isinstance(eq, exp_polar):
return exp(_unpolarify(eq.exp, exponents_only))
if isinstance(eq, principal_branch) and eq.args[1] == 2*pi:
return _unpolarify(eq.args[0], exponents_only)
if (
eq.is_Add or eq.is_Mul or eq.is_Boolean or
eq.is_Relational and (
eq.rel_op in ('==', '!=') and 0 in eq.args or
eq.rel_op not in ('==', '!='))
):
return eq.func(*[_unpolarify(x, exponents_only) for x in eq.args])
if isinstance(eq, polar_lift):
return _unpolarify(eq.args[0], exponents_only)
if eq.is_Pow:
expo = _unpolarify(eq.exp, exponents_only)
base = _unpolarify(eq.base, exponents_only,
not (expo.is_integer and not pause))
return base**expo
if eq.is_Function and getattr(eq.func, 'unbranched', False):
return eq.func(*[_unpolarify(x, exponents_only, exponents_only)
for x in eq.args])
return eq.func(*[_unpolarify(x, exponents_only, True) for x in eq.args])
def unpolarify(eq, subs=None, exponents_only=False):
"""
If p denotes the projection from the Riemann surface of the logarithm to
the complex line, return a simplified version eq' of `eq` such that
p(eq') == p(eq).
Also apply the substitution subs in the end. (This is a convenience, since
``unpolarify``, in a certain sense, undoes polarify.)
Examples
========
>>> from sympy import unpolarify, polar_lift, sin, I
>>> unpolarify(polar_lift(I + 2))
2 + I
>>> unpolarify(sin(polar_lift(I + 7)))
sin(7 + I)
"""
if isinstance(eq, bool):
return eq
eq = sympify(eq)
if subs is not None:
return unpolarify(eq.subs(subs))
changed = True
pause = False
if exponents_only:
pause = True
while changed:
changed = False
res = _unpolarify(eq, exponents_only, pause)
if res != eq:
changed = True
eq = res
if isinstance(res, bool):
return res
# Finally, replacing Exp(0) by 1 is always correct.
# So is polar_lift(0) -> 0.
return res.subs({exp_polar(0): 1, polar_lift(0): 0})
|
5cc30db9aad93426b08f535ba96a63cf5372c7b3674b8bb8da5070f621cf65f9 | """Hypergeometric and Meijer G-functions"""
from functools import reduce
from sympy.core import S, I, pi, oo, zoo, ilcm, Mod
from sympy.core.add import Add
from sympy.core.expr import Expr
from sympy.core.function import Function, Derivative, ArgumentIndexError
from sympy.core.containers import Tuple
from sympy.core.mul import Mul
from sympy.core.relational import Ne
from sympy.core.sorting import default_sort_key
from sympy.core.symbol import Dummy
from sympy.functions import (sqrt, exp, log, sin, cos, asin, atan,
sinh, cosh, asinh, acosh, atanh, acoth, Abs, re, factorial, RisingFactorial)
from sympy.logic.boolalg import (And, Or)
class TupleArg(Tuple):
def limit(self, x, xlim, dir='+'):
""" Compute limit x->xlim.
"""
from sympy.series.limits import limit
return TupleArg(*[limit(f, x, xlim, dir) for f in self.args])
# TODO should __new__ accept **options?
# TODO should constructors should check if parameters are sensible?
def _prep_tuple(v):
"""
Turn an iterable argument *v* into a tuple and unpolarify, since both
hypergeometric and meijer g-functions are unbranched in their parameters.
Examples
========
>>> from sympy.functions.special.hyper import _prep_tuple
>>> _prep_tuple([1, 2, 3])
(1, 2, 3)
>>> _prep_tuple((4, 5))
(4, 5)
>>> _prep_tuple((7, 8, 9))
(7, 8, 9)
"""
from sympy.functions.elementary.complexes import unpolarify
return TupleArg(*[unpolarify(x) for x in v])
class TupleParametersBase(Function):
""" Base class that takes care of differentiation, when some of
the arguments are actually tuples. """
# This is not deduced automatically since there are Tuples as arguments.
is_commutative = True
def _eval_derivative(self, s):
try:
res = 0
if self.args[0].has(s) or self.args[1].has(s):
for i, p in enumerate(self._diffargs):
m = self._diffargs[i].diff(s)
if m != 0:
res += self.fdiff((1, i))*m
return res + self.fdiff(3)*self.args[2].diff(s)
except (ArgumentIndexError, NotImplementedError):
return Derivative(self, s)
class hyper(TupleParametersBase):
r"""
The generalized hypergeometric function is defined by a series where
the ratios of successive terms are a rational function of the summation
index. When convergent, it is continued analytically to the largest
possible domain.
Explanation
===========
The hypergeometric function depends on two vectors of parameters, called
the numerator parameters $a_p$, and the denominator parameters
$b_q$. It also has an argument $z$. The series definition is
.. math ::
{}_pF_q\left(\begin{matrix} a_1, \cdots, a_p \\ b_1, \cdots, b_q \end{matrix}
\middle| z \right)
= \sum_{n=0}^\infty \frac{(a_1)_n \cdots (a_p)_n}{(b_1)_n \cdots (b_q)_n}
\frac{z^n}{n!},
where $(a)_n = (a)(a+1)\cdots(a+n-1)$ denotes the rising factorial.
If one of the $b_q$ is a non-positive integer then the series is
undefined unless one of the $a_p$ is a larger (i.e., smaller in
magnitude) non-positive integer. If none of the $b_q$ is a
non-positive integer and one of the $a_p$ is a non-positive
integer, then the series reduces to a polynomial. To simplify the
following discussion, we assume that none of the $a_p$ or
$b_q$ is a non-positive integer. For more details, see the
references.
The series converges for all $z$ if $p \le q$, and thus
defines an entire single-valued function in this case. If $p =
q+1$ the series converges for $|z| < 1$, and can be continued
analytically into a half-plane. If $p > q+1$ the series is
divergent for all $z$.
Please note the hypergeometric function constructor currently does *not*
check if the parameters actually yield a well-defined function.
Examples
========
The parameters $a_p$ and $b_q$ can be passed as arbitrary
iterables, for example:
>>> from sympy import hyper
>>> from sympy.abc import x, n, a
>>> hyper((1, 2, 3), [3, 4], x)
hyper((1, 2, 3), (3, 4), x)
There is also pretty printing (it looks better using Unicode):
>>> from sympy import pprint
>>> pprint(hyper((1, 2, 3), [3, 4], x), use_unicode=False)
_
|_ /1, 2, 3 | \
| | | x|
3 2 \ 3, 4 | /
The parameters must always be iterables, even if they are vectors of
length one or zero:
>>> hyper((1, ), [], x)
hyper((1,), (), x)
But of course they may be variables (but if they depend on $x$ then you
should not expect much implemented functionality):
>>> hyper((n, a), (n**2,), x)
hyper((n, a), (n**2,), x)
The hypergeometric function generalizes many named special functions.
The function ``hyperexpand()`` tries to express a hypergeometric function
using named special functions. For example:
>>> from sympy import hyperexpand
>>> hyperexpand(hyper([], [], x))
exp(x)
You can also use ``expand_func()``:
>>> from sympy import expand_func
>>> expand_func(x*hyper([1, 1], [2], -x))
log(x + 1)
More examples:
>>> from sympy import S
>>> hyperexpand(hyper([], [S(1)/2], -x**2/4))
cos(x)
>>> hyperexpand(x*hyper([S(1)/2, S(1)/2], [S(3)/2], x**2))
asin(x)
We can also sometimes ``hyperexpand()`` parametric functions:
>>> from sympy.abc import a
>>> hyperexpand(hyper([-a], [], x))
(1 - x)**a
See Also
========
sympy.simplify.hyperexpand
gamma
meijerg
References
==========
.. [1] Luke, Y. L. (1969), The Special Functions and Their Approximations,
Volume 1
.. [2] https://en.wikipedia.org/wiki/Generalized_hypergeometric_function
"""
def __new__(cls, ap, bq, z, **kwargs):
# TODO should we check convergence conditions?
return Function.__new__(cls, _prep_tuple(ap), _prep_tuple(bq), z, **kwargs)
@classmethod
def eval(cls, ap, bq, z):
from sympy.functions.elementary.complexes import unpolarify
if len(ap) <= len(bq) or (len(ap) == len(bq) + 1 and (Abs(z) <= 1) == True):
nz = unpolarify(z)
if z != nz:
return hyper(ap, bq, nz)
def fdiff(self, argindex=3):
if argindex != 3:
raise ArgumentIndexError(self, argindex)
nap = Tuple(*[a + 1 for a in self.ap])
nbq = Tuple(*[b + 1 for b in self.bq])
fac = Mul(*self.ap)/Mul(*self.bq)
return fac*hyper(nap, nbq, self.argument)
def _eval_expand_func(self, **hints):
from sympy.functions.special.gamma_functions import gamma
from sympy.simplify.hyperexpand import hyperexpand
if len(self.ap) == 2 and len(self.bq) == 1 and self.argument == 1:
a, b = self.ap
c = self.bq[0]
return gamma(c)*gamma(c - a - b)/gamma(c - a)/gamma(c - b)
return hyperexpand(self)
def _eval_rewrite_as_Sum(self, ap, bq, z, **kwargs):
from sympy.functions import factorial, RisingFactorial, Piecewise
from sympy.concrete.summations import Sum
n = Dummy("n", integer=True)
rfap = Tuple(*[RisingFactorial(a, n) for a in ap])
rfbq = Tuple(*[RisingFactorial(b, n) for b in bq])
coeff = Mul(*rfap) / Mul(*rfbq)
return Piecewise((Sum(coeff * z**n / factorial(n), (n, 0, oo)),
self.convergence_statement), (self, True))
def _eval_as_leading_term(self, x, logx=None, cdir=0):
arg = self.args[2]
x0 = arg.subs(x, 0)
if x0 is S.NaN:
x0 = arg.limit(x, 0, dir='-' if re(cdir).is_negative else '+')
if x0 is S.Zero:
return S.One
return super()._eval_as_leading_term(x, logx=logx, cdir=cdir)
def _eval_nseries(self, x, n, logx, cdir=0):
from sympy.series.order import Order
arg = self.args[2]
x0 = arg.limit(x, 0)
ap = self.args[0]
bq = self.args[1]
if x0 != 0:
return super()._eval_nseries(x, n, logx)
terms = []
for i in range(n):
num = 1
den = 1
for a in ap:
num *= RisingFactorial(a, i)
for b in bq:
den *= RisingFactorial(b, i)
terms.append(((num/den) * (arg**i)) / factorial(i))
return (Add(*terms) + Order(x**n,x))
@property
def argument(self):
""" Argument of the hypergeometric function. """
return self.args[2]
@property
def ap(self):
""" Numerator parameters of the hypergeometric function. """
return Tuple(*self.args[0])
@property
def bq(self):
""" Denominator parameters of the hypergeometric function. """
return Tuple(*self.args[1])
@property
def _diffargs(self):
return self.ap + self.bq
@property
def eta(self):
""" A quantity related to the convergence of the series. """
return sum(self.ap) - sum(self.bq)
@property
def radius_of_convergence(self):
"""
Compute the radius of convergence of the defining series.
Explanation
===========
Note that even if this is not ``oo``, the function may still be
evaluated outside of the radius of convergence by analytic
continuation. But if this is zero, then the function is not actually
defined anywhere else.
Examples
========
>>> from sympy import hyper
>>> from sympy.abc import z
>>> hyper((1, 2), [3], z).radius_of_convergence
1
>>> hyper((1, 2, 3), [4], z).radius_of_convergence
0
>>> hyper((1, 2), (3, 4), z).radius_of_convergence
oo
"""
if any(a.is_integer and (a <= 0) == True for a in self.ap + self.bq):
aints = [a for a in self.ap if a.is_Integer and (a <= 0) == True]
bints = [a for a in self.bq if a.is_Integer and (a <= 0) == True]
if len(aints) < len(bints):
return S.Zero
popped = False
for b in bints:
cancelled = False
while aints:
a = aints.pop()
if a >= b:
cancelled = True
break
popped = True
if not cancelled:
return S.Zero
if aints or popped:
# There are still non-positive numerator parameters.
# This is a polynomial.
return oo
if len(self.ap) == len(self.bq) + 1:
return S.One
elif len(self.ap) <= len(self.bq):
return oo
else:
return S.Zero
@property
def convergence_statement(self):
""" Return a condition on z under which the series converges. """
R = self.radius_of_convergence
if R == 0:
return False
if R == oo:
return True
# The special functions and their approximations, page 44
e = self.eta
z = self.argument
c1 = And(re(e) < 0, abs(z) <= 1)
c2 = And(0 <= re(e), re(e) < 1, abs(z) <= 1, Ne(z, 1))
c3 = And(re(e) >= 1, abs(z) < 1)
return Or(c1, c2, c3)
def _eval_simplify(self, **kwargs):
from sympy.simplify.hyperexpand import hyperexpand
return hyperexpand(self)
class meijerg(TupleParametersBase):
r"""
The Meijer G-function is defined by a Mellin-Barnes type integral that
resembles an inverse Mellin transform. It generalizes the hypergeometric
functions.
Explanation
===========
The Meijer G-function depends on four sets of parameters. There are
"*numerator parameters*"
$a_1, \ldots, a_n$ and $a_{n+1}, \ldots, a_p$, and there are
"*denominator parameters*"
$b_1, \ldots, b_m$ and $b_{m+1}, \ldots, b_q$.
Confusingly, it is traditionally denoted as follows (note the position
of $m$, $n$, $p$, $q$, and how they relate to the lengths of the four
parameter vectors):
.. math ::
G_{p,q}^{m,n} \left(\begin{matrix}a_1, \cdots, a_n & a_{n+1}, \cdots, a_p \\
b_1, \cdots, b_m & b_{m+1}, \cdots, b_q
\end{matrix} \middle| z \right).
However, in SymPy the four parameter vectors are always available
separately (see examples), so that there is no need to keep track of the
decorating sub- and super-scripts on the G symbol.
The G function is defined as the following integral:
.. math ::
\frac{1}{2 \pi i} \int_L \frac{\prod_{j=1}^m \Gamma(b_j - s)
\prod_{j=1}^n \Gamma(1 - a_j + s)}{\prod_{j=m+1}^q \Gamma(1- b_j +s)
\prod_{j=n+1}^p \Gamma(a_j - s)} z^s \mathrm{d}s,
where $\Gamma(z)$ is the gamma function. There are three possible
contours which we will not describe in detail here (see the references).
If the integral converges along more than one of them, the definitions
agree. The contours all separate the poles of $\Gamma(1-a_j+s)$
from the poles of $\Gamma(b_k-s)$, so in particular the G function
is undefined if $a_j - b_k \in \mathbb{Z}_{>0}$ for some
$j \le n$ and $k \le m$.
The conditions under which one of the contours yields a convergent integral
are complicated and we do not state them here, see the references.
Please note currently the Meijer G-function constructor does *not* check any
convergence conditions.
Examples
========
You can pass the parameters either as four separate vectors:
>>> from sympy import meijerg, Tuple, pprint
>>> from sympy.abc import x, a
>>> pprint(meijerg((1, 2), (a, 4), (5,), [], x), use_unicode=False)
__1, 2 /1, 2 a, 4 | \
/__ | | x|
\_|4, 1 \ 5 | /
Or as two nested vectors:
>>> pprint(meijerg([(1, 2), (3, 4)], ([5], Tuple()), x), use_unicode=False)
__1, 2 /1, 2 3, 4 | \
/__ | | x|
\_|4, 1 \ 5 | /
As with the hypergeometric function, the parameters may be passed as
arbitrary iterables. Vectors of length zero and one also have to be
passed as iterables. The parameters need not be constants, but if they
depend on the argument then not much implemented functionality should be
expected.
All the subvectors of parameters are available:
>>> from sympy import pprint
>>> g = meijerg([1], [2], [3], [4], x)
>>> pprint(g, use_unicode=False)
__1, 1 /1 2 | \
/__ | | x|
\_|2, 2 \3 4 | /
>>> g.an
(1,)
>>> g.ap
(1, 2)
>>> g.aother
(2,)
>>> g.bm
(3,)
>>> g.bq
(3, 4)
>>> g.bother
(4,)
The Meijer G-function generalizes the hypergeometric functions.
In some cases it can be expressed in terms of hypergeometric functions,
using Slater's theorem. For example:
>>> from sympy import hyperexpand
>>> from sympy.abc import a, b, c
>>> hyperexpand(meijerg([a], [], [c], [b], x), allow_hyper=True)
x**c*gamma(-a + c + 1)*hyper((-a + c + 1,),
(-b + c + 1,), -x)/gamma(-b + c + 1)
Thus the Meijer G-function also subsumes many named functions as special
cases. You can use ``expand_func()`` or ``hyperexpand()`` to (try to)
rewrite a Meijer G-function in terms of named special functions. For
example:
>>> from sympy import expand_func, S
>>> expand_func(meijerg([[],[]], [[0],[]], -x))
exp(x)
>>> hyperexpand(meijerg([[],[]], [[S(1)/2],[0]], (x/2)**2))
sin(x)/sqrt(pi)
See Also
========
hyper
sympy.simplify.hyperexpand
References
==========
.. [1] Luke, Y. L. (1969), The Special Functions and Their Approximations,
Volume 1
.. [2] https://en.wikipedia.org/wiki/Meijer_G-function
"""
def __new__(cls, *args, **kwargs):
if len(args) == 5:
args = [(args[0], args[1]), (args[2], args[3]), args[4]]
if len(args) != 3:
raise TypeError("args must be either as, as', bs, bs', z or "
"as, bs, z")
def tr(p):
if len(p) != 2:
raise TypeError("wrong argument")
return TupleArg(_prep_tuple(p[0]), _prep_tuple(p[1]))
arg0, arg1 = tr(args[0]), tr(args[1])
if Tuple(arg0, arg1).has(oo, zoo, -oo):
raise ValueError("G-function parameters must be finite")
if any((a - b).is_Integer and a - b > 0
for a in arg0[0] for b in arg1[0]):
raise ValueError("no parameter a1, ..., an may differ from "
"any b1, ..., bm by a positive integer")
# TODO should we check convergence conditions?
return Function.__new__(cls, arg0, arg1, args[2], **kwargs)
def fdiff(self, argindex=3):
if argindex != 3:
return self._diff_wrt_parameter(argindex[1])
if len(self.an) >= 1:
a = list(self.an)
a[0] -= 1
G = meijerg(a, self.aother, self.bm, self.bother, self.argument)
return 1/self.argument * ((self.an[0] - 1)*self + G)
elif len(self.bm) >= 1:
b = list(self.bm)
b[0] += 1
G = meijerg(self.an, self.aother, b, self.bother, self.argument)
return 1/self.argument * (self.bm[0]*self - G)
else:
return S.Zero
def _diff_wrt_parameter(self, idx):
# Differentiation wrt a parameter can only be done in very special
# cases. In particular, if we want to differentiate with respect to
# `a`, all other gamma factors have to reduce to rational functions.
#
# Let MT denote mellin transform. Suppose T(-s) is the gamma factor
# appearing in the definition of G. Then
#
# MT(log(z)G(z)) = d/ds T(s) = d/da T(s) + ...
#
# Thus d/da G(z) = log(z)G(z) - ...
# The ... can be evaluated as a G function under the above conditions,
# the formula being most easily derived by using
#
# d Gamma(s + n) Gamma(s + n) / 1 1 1 \
# -- ------------ = ------------ | - + ---- + ... + --------- |
# ds Gamma(s) Gamma(s) \ s s + 1 s + n - 1 /
#
# which follows from the difference equation of the digamma function.
# (There is a similar equation for -n instead of +n).
# We first figure out how to pair the parameters.
an = list(self.an)
ap = list(self.aother)
bm = list(self.bm)
bq = list(self.bother)
if idx < len(an):
an.pop(idx)
else:
idx -= len(an)
if idx < len(ap):
ap.pop(idx)
else:
idx -= len(ap)
if idx < len(bm):
bm.pop(idx)
else:
bq.pop(idx - len(bm))
pairs1 = []
pairs2 = []
for l1, l2, pairs in [(an, bq, pairs1), (ap, bm, pairs2)]:
while l1:
x = l1.pop()
found = None
for i, y in enumerate(l2):
if not Mod((x - y).simplify(), 1):
found = i
break
if found is None:
raise NotImplementedError('Derivative not expressible '
'as G-function?')
y = l2[i]
l2.pop(i)
pairs.append((x, y))
# Now build the result.
res = log(self.argument)*self
for a, b in pairs1:
sign = 1
n = a - b
base = b
if n < 0:
sign = -1
n = b - a
base = a
for k in range(n):
res -= sign*meijerg(self.an + (base + k + 1,), self.aother,
self.bm, self.bother + (base + k + 0,),
self.argument)
for a, b in pairs2:
sign = 1
n = b - a
base = a
if n < 0:
sign = -1
n = a - b
base = b
for k in range(n):
res -= sign*meijerg(self.an, self.aother + (base + k + 1,),
self.bm + (base + k + 0,), self.bother,
self.argument)
return res
def get_period(self):
"""
Return a number $P$ such that $G(x*exp(I*P)) == G(x)$.
Examples
========
>>> from sympy import meijerg, pi, S
>>> from sympy.abc import z
>>> meijerg([1], [], [], [], z).get_period()
2*pi
>>> meijerg([pi], [], [], [], z).get_period()
oo
>>> meijerg([1, 2], [], [], [], z).get_period()
oo
>>> meijerg([1,1], [2], [1, S(1)/2, S(1)/3], [1], z).get_period()
12*pi
"""
# This follows from slater's theorem.
def compute(l):
# first check that no two differ by an integer
for i, b in enumerate(l):
if not b.is_Rational:
return oo
for j in range(i + 1, len(l)):
if not Mod((b - l[j]).simplify(), 1):
return oo
return reduce(ilcm, (x.q for x in l), 1)
beta = compute(self.bm)
alpha = compute(self.an)
p, q = len(self.ap), len(self.bq)
if p == q:
if oo in (alpha, beta):
return oo
return 2*pi*ilcm(alpha, beta)
elif p < q:
return 2*pi*beta
else:
return 2*pi*alpha
def _eval_expand_func(self, **hints):
from sympy.simplify.hyperexpand import hyperexpand
return hyperexpand(self)
def _eval_evalf(self, prec):
# The default code is insufficient for polar arguments.
# mpmath provides an optional argument "r", which evaluates
# G(z**(1/r)). I am not sure what its intended use is, but we hijack it
# here in the following way: to evaluate at a number z of |argument|
# less than (say) n*pi, we put r=1/n, compute z' = root(z, n)
# (carefully so as not to loose the branch information), and evaluate
# G(z'**(1/r)) = G(z'**n) = G(z).
from sympy.functions import exp_polar, ceiling
import mpmath
znum = self.argument._eval_evalf(prec)
if znum.has(exp_polar):
znum, branch = znum.as_coeff_mul(exp_polar)
if len(branch) != 1:
return
branch = branch[0].args[0]/I
else:
branch = S.Zero
n = ceiling(abs(branch/S.Pi)) + 1
znum = znum**(S.One/n)*exp(I*branch / n)
# Convert all args to mpf or mpc
try:
[z, r, ap, bq] = [arg._to_mpmath(prec)
for arg in [znum, 1/n, self.args[0], self.args[1]]]
except ValueError:
return
with mpmath.workprec(prec):
v = mpmath.meijerg(ap, bq, z, r)
return Expr._from_mpmath(v, prec)
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.simplify.hyperexpand import hyperexpand
return hyperexpand(self).as_leading_term(x, logx=logx, cdir=cdir)
def integrand(self, s):
""" Get the defining integrand D(s). """
from sympy.functions.special.gamma_functions import gamma
return self.argument**s \
* Mul(*(gamma(b - s) for b in self.bm)) \
* Mul(*(gamma(1 - a + s) for a in self.an)) \
/ Mul(*(gamma(1 - b + s) for b in self.bother)) \
/ Mul(*(gamma(a - s) for a in self.aother))
@property
def argument(self):
""" Argument of the Meijer G-function. """
return self.args[2]
@property
def an(self):
""" First set of numerator parameters. """
return Tuple(*self.args[0][0])
@property
def ap(self):
""" Combined numerator parameters. """
return Tuple(*(self.args[0][0] + self.args[0][1]))
@property
def aother(self):
""" Second set of numerator parameters. """
return Tuple(*self.args[0][1])
@property
def bm(self):
""" First set of denominator parameters. """
return Tuple(*self.args[1][0])
@property
def bq(self):
""" Combined denominator parameters. """
return Tuple(*(self.args[1][0] + self.args[1][1]))
@property
def bother(self):
""" Second set of denominator parameters. """
return Tuple(*self.args[1][1])
@property
def _diffargs(self):
return self.ap + self.bq
@property
def nu(self):
""" A quantity related to the convergence region of the integral,
c.f. references. """
return sum(self.bq) - sum(self.ap)
@property
def delta(self):
""" A quantity related to the convergence region of the integral,
c.f. references. """
return len(self.bm) + len(self.an) - S(len(self.ap) + len(self.bq))/2
@property
def is_number(self):
""" Returns true if expression has numeric data only. """
return not self.free_symbols
class HyperRep(Function):
"""
A base class for "hyper representation functions".
This is used exclusively in ``hyperexpand()``, but fits more logically here.
pFq is branched at 1 if p == q+1. For use with slater-expansion, we want
define an "analytic continuation" to all polar numbers, which is
continuous on circles and on the ray t*exp_polar(I*pi). Moreover, we want
a "nice" expression for the various cases.
This base class contains the core logic, concrete derived classes only
supply the actual functions.
"""
@classmethod
def eval(cls, *args):
from sympy.functions.elementary.complexes import unpolarify
newargs = tuple(map(unpolarify, args[:-1])) + args[-1:]
if args != newargs:
return cls(*newargs)
@classmethod
def _expr_small(cls, x):
""" An expression for F(x) which holds for |x| < 1. """
raise NotImplementedError
@classmethod
def _expr_small_minus(cls, x):
""" An expression for F(-x) which holds for |x| < 1. """
raise NotImplementedError
@classmethod
def _expr_big(cls, x, n):
""" An expression for F(exp_polar(2*I*pi*n)*x), |x| > 1. """
raise NotImplementedError
@classmethod
def _expr_big_minus(cls, x, n):
""" An expression for F(exp_polar(2*I*pi*n + pi*I)*x), |x| > 1. """
raise NotImplementedError
def _eval_rewrite_as_nonrep(self, *args, **kwargs):
from sympy.functions.elementary.piecewise import Piecewise
x, n = self.args[-1].extract_branch_factor(allow_half=True)
minus = False
newargs = self.args[:-1] + (x,)
if not n.is_Integer:
minus = True
n -= S.Half
newerargs = newargs + (n,)
if minus:
small = self._expr_small_minus(*newargs)
big = self._expr_big_minus(*newerargs)
else:
small = self._expr_small(*newargs)
big = self._expr_big(*newerargs)
if big == small:
return small
return Piecewise((big, abs(x) > 1), (small, True))
def _eval_rewrite_as_nonrepsmall(self, *args, **kwargs):
x, n = self.args[-1].extract_branch_factor(allow_half=True)
args = self.args[:-1] + (x,)
if not n.is_Integer:
return self._expr_small_minus(*args)
return self._expr_small(*args)
class HyperRep_power1(HyperRep):
""" Return a representative for hyper([-a], [], z) == (1 - z)**a. """
@classmethod
def _expr_small(cls, a, x):
return (1 - x)**a
@classmethod
def _expr_small_minus(cls, a, x):
return (1 + x)**a
@classmethod
def _expr_big(cls, a, x, n):
if a.is_integer:
return cls._expr_small(a, x)
return (x - 1)**a*exp((2*n - 1)*pi*I*a)
@classmethod
def _expr_big_minus(cls, a, x, n):
if a.is_integer:
return cls._expr_small_minus(a, x)
return (1 + x)**a*exp(2*n*pi*I*a)
class HyperRep_power2(HyperRep):
""" Return a representative for hyper([a, a - 1/2], [2*a], z). """
@classmethod
def _expr_small(cls, a, x):
return 2**(2*a - 1)*(1 + sqrt(1 - x))**(1 - 2*a)
@classmethod
def _expr_small_minus(cls, a, x):
return 2**(2*a - 1)*(1 + sqrt(1 + x))**(1 - 2*a)
@classmethod
def _expr_big(cls, a, x, n):
sgn = -1
if n.is_odd:
sgn = 1
n -= 1
return 2**(2*a - 1)*(1 + sgn*I*sqrt(x - 1))**(1 - 2*a) \
*exp(-2*n*pi*I*a)
@classmethod
def _expr_big_minus(cls, a, x, n):
sgn = 1
if n.is_odd:
sgn = -1
return sgn*2**(2*a - 1)*(sqrt(1 + x) + sgn)**(1 - 2*a)*exp(-2*pi*I*a*n)
class HyperRep_log1(HyperRep):
""" Represent -z*hyper([1, 1], [2], z) == log(1 - z). """
@classmethod
def _expr_small(cls, x):
return log(1 - x)
@classmethod
def _expr_small_minus(cls, x):
return log(1 + x)
@classmethod
def _expr_big(cls, x, n):
return log(x - 1) + (2*n - 1)*pi*I
@classmethod
def _expr_big_minus(cls, x, n):
return log(1 + x) + 2*n*pi*I
class HyperRep_atanh(HyperRep):
""" Represent hyper([1/2, 1], [3/2], z) == atanh(sqrt(z))/sqrt(z). """
@classmethod
def _expr_small(cls, x):
return atanh(sqrt(x))/sqrt(x)
def _expr_small_minus(cls, x):
return atan(sqrt(x))/sqrt(x)
def _expr_big(cls, x, n):
if n.is_even:
return (acoth(sqrt(x)) + I*pi/2)/sqrt(x)
else:
return (acoth(sqrt(x)) - I*pi/2)/sqrt(x)
def _expr_big_minus(cls, x, n):
if n.is_even:
return atan(sqrt(x))/sqrt(x)
else:
return (atan(sqrt(x)) - pi)/sqrt(x)
class HyperRep_asin1(HyperRep):
""" Represent hyper([1/2, 1/2], [3/2], z) == asin(sqrt(z))/sqrt(z). """
@classmethod
def _expr_small(cls, z):
return asin(sqrt(z))/sqrt(z)
@classmethod
def _expr_small_minus(cls, z):
return asinh(sqrt(z))/sqrt(z)
@classmethod
def _expr_big(cls, z, n):
return S.NegativeOne**n*((S.Half - n)*pi/sqrt(z) + I*acosh(sqrt(z))/sqrt(z))
@classmethod
def _expr_big_minus(cls, z, n):
return S.NegativeOne**n*(asinh(sqrt(z))/sqrt(z) + n*pi*I/sqrt(z))
class HyperRep_asin2(HyperRep):
""" Represent hyper([1, 1], [3/2], z) == asin(sqrt(z))/sqrt(z)/sqrt(1-z). """
# TODO this can be nicer
@classmethod
def _expr_small(cls, z):
return HyperRep_asin1._expr_small(z) \
/HyperRep_power1._expr_small(S.Half, z)
@classmethod
def _expr_small_minus(cls, z):
return HyperRep_asin1._expr_small_minus(z) \
/HyperRep_power1._expr_small_minus(S.Half, z)
@classmethod
def _expr_big(cls, z, n):
return HyperRep_asin1._expr_big(z, n) \
/HyperRep_power1._expr_big(S.Half, z, n)
@classmethod
def _expr_big_minus(cls, z, n):
return HyperRep_asin1._expr_big_minus(z, n) \
/HyperRep_power1._expr_big_minus(S.Half, z, n)
class HyperRep_sqrts1(HyperRep):
""" Return a representative for hyper([-a, 1/2 - a], [1/2], z). """
@classmethod
def _expr_small(cls, a, z):
return ((1 - sqrt(z))**(2*a) + (1 + sqrt(z))**(2*a))/2
@classmethod
def _expr_small_minus(cls, a, z):
return (1 + z)**a*cos(2*a*atan(sqrt(z)))
@classmethod
def _expr_big(cls, a, z, n):
if n.is_even:
return ((sqrt(z) + 1)**(2*a)*exp(2*pi*I*n*a) +
(sqrt(z) - 1)**(2*a)*exp(2*pi*I*(n - 1)*a))/2
else:
n -= 1
return ((sqrt(z) - 1)**(2*a)*exp(2*pi*I*a*(n + 1)) +
(sqrt(z) + 1)**(2*a)*exp(2*pi*I*a*n))/2
@classmethod
def _expr_big_minus(cls, a, z, n):
if n.is_even:
return (1 + z)**a*exp(2*pi*I*n*a)*cos(2*a*atan(sqrt(z)))
else:
return (1 + z)**a*exp(2*pi*I*n*a)*cos(2*a*atan(sqrt(z)) - 2*pi*a)
class HyperRep_sqrts2(HyperRep):
""" Return a representative for
sqrt(z)/2*[(1-sqrt(z))**2a - (1 + sqrt(z))**2a]
== -2*z/(2*a+1) d/dz hyper([-a - 1/2, -a], [1/2], z)"""
@classmethod
def _expr_small(cls, a, z):
return sqrt(z)*((1 - sqrt(z))**(2*a) - (1 + sqrt(z))**(2*a))/2
@classmethod
def _expr_small_minus(cls, a, z):
return sqrt(z)*(1 + z)**a*sin(2*a*atan(sqrt(z)))
@classmethod
def _expr_big(cls, a, z, n):
if n.is_even:
return sqrt(z)/2*((sqrt(z) - 1)**(2*a)*exp(2*pi*I*a*(n - 1)) -
(sqrt(z) + 1)**(2*a)*exp(2*pi*I*a*n))
else:
n -= 1
return sqrt(z)/2*((sqrt(z) - 1)**(2*a)*exp(2*pi*I*a*(n + 1)) -
(sqrt(z) + 1)**(2*a)*exp(2*pi*I*a*n))
def _expr_big_minus(cls, a, z, n):
if n.is_even:
return (1 + z)**a*exp(2*pi*I*n*a)*sqrt(z)*sin(2*a*atan(sqrt(z)))
else:
return (1 + z)**a*exp(2*pi*I*n*a)*sqrt(z) \
*sin(2*a*atan(sqrt(z)) - 2*pi*a)
class HyperRep_log2(HyperRep):
""" Represent log(1/2 + sqrt(1 - z)/2) == -z/4*hyper([3/2, 1, 1], [2, 2], z) """
@classmethod
def _expr_small(cls, z):
return log(S.Half + sqrt(1 - z)/2)
@classmethod
def _expr_small_minus(cls, z):
return log(S.Half + sqrt(1 + z)/2)
@classmethod
def _expr_big(cls, z, n):
if n.is_even:
return (n - S.Half)*pi*I + log(sqrt(z)/2) + I*asin(1/sqrt(z))
else:
return (n - S.Half)*pi*I + log(sqrt(z)/2) - I*asin(1/sqrt(z))
def _expr_big_minus(cls, z, n):
if n.is_even:
return pi*I*n + log(S.Half + sqrt(1 + z)/2)
else:
return pi*I*n + log(sqrt(1 + z)/2 - S.Half)
class HyperRep_cosasin(HyperRep):
""" Represent hyper([a, -a], [1/2], z) == cos(2*a*asin(sqrt(z))). """
# Note there are many alternative expressions, e.g. as powers of a sum of
# square roots.
@classmethod
def _expr_small(cls, a, z):
return cos(2*a*asin(sqrt(z)))
@classmethod
def _expr_small_minus(cls, a, z):
return cosh(2*a*asinh(sqrt(z)))
@classmethod
def _expr_big(cls, a, z, n):
return cosh(2*a*acosh(sqrt(z)) + a*pi*I*(2*n - 1))
@classmethod
def _expr_big_minus(cls, a, z, n):
return cosh(2*a*asinh(sqrt(z)) + 2*a*pi*I*n)
class HyperRep_sinasin(HyperRep):
""" Represent 2*a*z*hyper([1 - a, 1 + a], [3/2], z)
== sqrt(z)/sqrt(1-z)*sin(2*a*asin(sqrt(z))) """
@classmethod
def _expr_small(cls, a, z):
return sqrt(z)/sqrt(1 - z)*sin(2*a*asin(sqrt(z)))
@classmethod
def _expr_small_minus(cls, a, z):
return -sqrt(z)/sqrt(1 + z)*sinh(2*a*asinh(sqrt(z)))
@classmethod
def _expr_big(cls, a, z, n):
return -1/sqrt(1 - 1/z)*sinh(2*a*acosh(sqrt(z)) + a*pi*I*(2*n - 1))
@classmethod
def _expr_big_minus(cls, a, z, n):
return -1/sqrt(1 + 1/z)*sinh(2*a*asinh(sqrt(z)) + 2*a*pi*I*n)
class appellf1(Function):
r"""
This is the Appell hypergeometric function of two variables as:
.. math ::
F_1(a,b_1,b_2,c,x,y) = \sum_{m=0}^{\infty} \sum_{n=0}^{\infty}
\frac{(a)_{m+n} (b_1)_m (b_2)_n}{(c)_{m+n}}
\frac{x^m y^n}{m! n!}.
Examples
========
>>> from sympy import appellf1, symbols
>>> x, y, a, b1, b2, c = symbols('x y a b1 b2 c')
>>> appellf1(2., 1., 6., 4., 5., 6.)
0.0063339426292673
>>> appellf1(12., 12., 6., 4., 0.5, 0.12)
172870711.659936
>>> appellf1(40, 2, 6, 4, 15, 60)
appellf1(40, 2, 6, 4, 15, 60)
>>> appellf1(20., 12., 10., 3., 0.5, 0.12)
15605338197184.4
>>> appellf1(40, 2, 6, 4, x, y)
appellf1(40, 2, 6, 4, x, y)
>>> appellf1(a, b1, b2, c, x, y)
appellf1(a, b1, b2, c, x, y)
References
==========
.. [1] https://en.wikipedia.org/wiki/Appell_series
.. [2] http://functions.wolfram.com/HypergeometricFunctions/AppellF1/
"""
@classmethod
def eval(cls, a, b1, b2, c, x, y):
if default_sort_key(b1) > default_sort_key(b2):
b1, b2 = b2, b1
x, y = y, x
return cls(a, b1, b2, c, x, y)
elif b1 == b2 and default_sort_key(x) > default_sort_key(y):
x, y = y, x
return cls(a, b1, b2, c, x, y)
if x == 0 and y == 0:
return S.One
def fdiff(self, argindex=5):
a, b1, b2, c, x, y = self.args
if argindex == 5:
return (a*b1/c)*appellf1(a + 1, b1 + 1, b2, c + 1, x, y)
elif argindex == 6:
return (a*b2/c)*appellf1(a + 1, b1, b2 + 1, c + 1, x, y)
elif argindex in (1, 2, 3, 4):
return Derivative(self, self.args[argindex-1])
else:
raise ArgumentIndexError(self, argindex)
|
2ecf31945c1d95b237bc6bb588739951f7d269f94564109627572d14ad011d79 | from sympy.core import Add, S, sympify, Dummy, expand_func
from sympy.core.expr import Expr
from sympy.core.function import Function, ArgumentIndexError, PoleError
from sympy.core.logic import fuzzy_and, fuzzy_not
from sympy.core.numbers import Rational, pi, oo, I
from sympy.core.power import Pow
from sympy.functions.special.zeta_functions import zeta
from sympy.functions.special.error_functions import erf, erfc, Ei
from sympy.functions.elementary.complexes import re, unpolarify
from sympy.functions.elementary.exponential import exp, log
from sympy.functions.elementary.integers import ceiling, floor
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.trigonometric import sin, cos, cot
from sympy.functions.combinatorial.numbers import bernoulli, harmonic
from sympy.functions.combinatorial.factorials import factorial, rf, RisingFactorial
from sympy.utilities.misc import as_int
from mpmath import mp, workprec
from mpmath.libmp.libmpf import prec_to_dps
def intlike(n):
try:
as_int(n, strict=False)
return True
except ValueError:
return False
###############################################################################
############################ COMPLETE GAMMA FUNCTION ##########################
###############################################################################
class gamma(Function):
r"""
The gamma function
.. math::
\Gamma(x) := \int^{\infty}_{0} t^{x-1} e^{-t} \mathrm{d}t.
Explanation
===========
The ``gamma`` function implements the function which passes through the
values of the factorial function (i.e., $\Gamma(n) = (n - 1)!$ when n is
an integer). More generally, $\Gamma(z)$ is defined in the whole complex
plane except at the negative integers where there are simple poles.
Examples
========
>>> from sympy import S, I, pi, gamma
>>> from sympy.abc import x
Several special values are known:
>>> gamma(1)
1
>>> gamma(4)
6
>>> gamma(S(3)/2)
sqrt(pi)/2
The ``gamma`` function obeys the mirror symmetry:
>>> from sympy import conjugate
>>> conjugate(gamma(x))
gamma(conjugate(x))
Differentiation with respect to $x$ is supported:
>>> from sympy import diff
>>> diff(gamma(x), x)
gamma(x)*polygamma(0, x)
Series expansion is also supported:
>>> from sympy import series
>>> series(gamma(x), x, 0, 3)
1/x - EulerGamma + x*(EulerGamma**2/2 + pi**2/12) + x**2*(-EulerGamma*pi**2/12 + polygamma(2, 1)/6 - EulerGamma**3/6) + O(x**3)
We can numerically evaluate the ``gamma`` function to arbitrary precision
on the whole complex plane:
>>> gamma(pi).evalf(40)
2.288037795340032417959588909060233922890
>>> gamma(1+I).evalf(20)
0.49801566811835604271 - 0.15494982830181068512*I
See Also
========
lowergamma: Lower incomplete gamma function.
uppergamma: Upper incomplete gamma function.
polygamma: Polygamma function.
loggamma: Log Gamma function.
digamma: Digamma function.
trigamma: Trigamma function.
beta: Euler Beta function.
References
==========
.. [1] https://en.wikipedia.org/wiki/Gamma_function
.. [2] http://dlmf.nist.gov/5
.. [3] http://mathworld.wolfram.com/GammaFunction.html
.. [4] http://functions.wolfram.com/GammaBetaErf/Gamma/
"""
unbranched = True
_singularities = (S.ComplexInfinity,)
def fdiff(self, argindex=1):
if argindex == 1:
return self.func(self.args[0])*polygamma(0, self.args[0])
else:
raise ArgumentIndexError(self, argindex)
@classmethod
def eval(cls, arg):
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.Infinity
elif intlike(arg):
if arg.is_positive:
return factorial(arg - 1)
else:
return S.ComplexInfinity
elif arg.is_Rational:
if arg.q == 2:
n = abs(arg.p) // arg.q
if arg.is_positive:
k, coeff = n, S.One
else:
n = k = n + 1
if n & 1 == 0:
coeff = S.One
else:
coeff = S.NegativeOne
for i in range(3, 2*k, 2):
coeff *= i
if arg.is_positive:
return coeff*sqrt(S.Pi) / 2**n
else:
return 2**n*sqrt(S.Pi) / coeff
def _eval_expand_func(self, **hints):
arg = self.args[0]
if arg.is_Rational:
if abs(arg.p) > arg.q:
x = Dummy('x')
n = arg.p // arg.q
p = arg.p - n*arg.q
return self.func(x + n)._eval_expand_func().subs(x, Rational(p, arg.q))
if arg.is_Add:
coeff, tail = arg.as_coeff_add()
if coeff and coeff.q != 1:
intpart = floor(coeff)
tail = (coeff - intpart,) + tail
coeff = intpart
tail = arg._new_rawargs(*tail, reeval=False)
return self.func(tail)*RisingFactorial(tail, coeff)
return self.func(*self.args)
def _eval_conjugate(self):
return self.func(self.args[0].conjugate())
def _eval_is_real(self):
x = self.args[0]
if x.is_nonpositive and x.is_integer:
return False
if intlike(x) and x <= 0:
return False
if x.is_positive or x.is_noninteger:
return True
def _eval_is_positive(self):
x = self.args[0]
if x.is_positive:
return True
elif x.is_noninteger:
return floor(x).is_even
def _eval_rewrite_as_tractable(self, z, limitvar=None, **kwargs):
return exp(loggamma(z))
def _eval_rewrite_as_factorial(self, z, **kwargs):
return factorial(z - 1)
def _eval_nseries(self, x, n, logx, cdir=0):
x0 = self.args[0].limit(x, 0)
if not (x0.is_Integer and x0 <= 0):
return super()._eval_nseries(x, n, logx)
t = self.args[0] - x0
return (self.func(t + 1)/rf(self.args[0], -x0 + 1))._eval_nseries(x, n, logx)
def _eval_as_leading_term(self, x, logx=None, cdir=0):
arg = self.args[0]
x0 = arg.subs(x, 0)
if x0.is_integer and x0.is_nonpositive:
n = -x0
res = S.NegativeOne**n/self.func(n + 1)
return res/(arg + n).as_leading_term(x)
elif not x0.is_infinite:
return self.func(x0)
raise PoleError()
###############################################################################
################## LOWER and UPPER INCOMPLETE GAMMA FUNCTIONS #################
###############################################################################
class lowergamma(Function):
r"""
The lower incomplete gamma function.
Explanation
===========
It can be defined as the meromorphic continuation of
.. math::
\gamma(s, x) := \int_0^x t^{s-1} e^{-t} \mathrm{d}t = \Gamma(s) - \Gamma(s, x).
This can be shown to be the same as
.. math::
\gamma(s, x) = \frac{x^s}{s} {}_1F_1\left({s \atop s+1} \middle| -x\right),
where ${}_1F_1$ is the (confluent) hypergeometric function.
Examples
========
>>> from sympy import lowergamma, S
>>> from sympy.abc import s, x
>>> lowergamma(s, x)
lowergamma(s, x)
>>> lowergamma(3, x)
-2*(x**2/2 + x + 1)*exp(-x) + 2
>>> lowergamma(-S(1)/2, x)
-2*sqrt(pi)*erf(sqrt(x)) - 2*exp(-x)/sqrt(x)
See Also
========
gamma: Gamma function.
uppergamma: Upper incomplete gamma function.
polygamma: Polygamma function.
loggamma: Log Gamma function.
digamma: Digamma function.
trigamma: Trigamma function.
beta: Euler Beta function.
References
==========
.. [1] https://en.wikipedia.org/wiki/Incomplete_gamma_function#Lower_incomplete_Gamma_function
.. [2] Abramowitz, Milton; Stegun, Irene A., eds. (1965), Chapter 6,
Section 5, Handbook of Mathematical Functions with Formulas, Graphs,
and Mathematical Tables
.. [3] http://dlmf.nist.gov/8
.. [4] http://functions.wolfram.com/GammaBetaErf/Gamma2/
.. [5] http://functions.wolfram.com/GammaBetaErf/Gamma3/
"""
def fdiff(self, argindex=2):
from sympy.functions.special.hyper import meijerg
if argindex == 2:
a, z = self.args
return exp(-unpolarify(z))*z**(a - 1)
elif argindex == 1:
a, z = self.args
return gamma(a)*digamma(a) - log(z)*uppergamma(a, z) \
- meijerg([], [1, 1], [0, 0, a], [], z)
else:
raise ArgumentIndexError(self, argindex)
@classmethod
def eval(cls, a, x):
# For lack of a better place, we use this one to extract branching
# information. The following can be
# found in the literature (c/f references given above), albeit scattered:
# 1) For fixed x != 0, lowergamma(s, x) is an entire function of s
# 2) For fixed positive integers s, lowergamma(s, x) is an entire
# function of x.
# 3) For fixed non-positive integers s,
# lowergamma(s, exp(I*2*pi*n)*x) =
# 2*pi*I*n*(-1)**(-s)/factorial(-s) + lowergamma(s, x)
# (this follows from lowergamma(s, x).diff(x) = x**(s-1)*exp(-x)).
# 4) For fixed non-integral s,
# lowergamma(s, x) = x**s*gamma(s)*lowergamma_unbranched(s, x),
# where lowergamma_unbranched(s, x) is an entire function (in fact
# of both s and x), i.e.
# lowergamma(s, exp(2*I*pi*n)*x) = exp(2*pi*I*n*a)*lowergamma(a, x)
if x is S.Zero:
return S.Zero
nx, n = x.extract_branch_factor()
if a.is_integer and a.is_positive:
nx = unpolarify(x)
if nx != x:
return lowergamma(a, nx)
elif a.is_integer and a.is_nonpositive:
if n != 0:
return 2*pi*I*n*S.NegativeOne**(-a)/factorial(-a) + lowergamma(a, nx)
elif n != 0:
return exp(2*pi*I*n*a)*lowergamma(a, nx)
# Special values.
if a.is_Number:
if a is S.One:
return S.One - exp(-x)
elif a is S.Half:
return sqrt(pi)*erf(sqrt(x))
elif a.is_Integer or (2*a).is_Integer:
b = a - 1
if b.is_positive:
if a.is_integer:
return factorial(b) - exp(-x) * factorial(b) * Add(*[x ** k / factorial(k) for k in range(a)])
else:
return gamma(a)*(lowergamma(S.Half, x)/sqrt(pi) - exp(-x)*Add(*[x**(k - S.Half)/gamma(S.Half + k) for k in range(1, a + S.Half)]))
if not a.is_Integer:
return S.NegativeOne**(S.Half - a)*pi*erf(sqrt(x))/gamma(1 - a) + exp(-x)*Add(*[x**(k + a - 1)*gamma(a)/gamma(a + k) for k in range(1, Rational(3, 2) - a)])
if x.is_zero:
return S.Zero
def _eval_evalf(self, prec):
if all(x.is_number for x in self.args):
a = self.args[0]._to_mpmath(prec)
z = self.args[1]._to_mpmath(prec)
with workprec(prec):
res = mp.gammainc(a, 0, z)
return Expr._from_mpmath(res, prec)
else:
return self
def _eval_conjugate(self):
x = self.args[1]
if x not in (S.Zero, S.NegativeInfinity):
return self.func(self.args[0].conjugate(), x.conjugate())
def _eval_is_meromorphic(self, x, a):
# By https://en.wikipedia.org/wiki/Incomplete_gamma_function#Holomorphic_extension,
# lowergamma(s, z) = z**s*gamma(s)*gammastar(s, z),
# where gammastar(s, z) is holomorphic for all s and z.
# Hence the singularities of lowergamma are z = 0 (branch
# point) and nonpositive integer values of s (poles of gamma(s)).
s, z = self.args
args_merom = fuzzy_and([z._eval_is_meromorphic(x, a),
s._eval_is_meromorphic(x, a)])
if not args_merom:
return args_merom
z0 = z.subs(x, a)
if s.is_integer:
return fuzzy_and([s.is_positive, z0.is_finite])
s0 = s.subs(x, a)
return fuzzy_and([s0.is_finite, z0.is_finite, fuzzy_not(z0.is_zero)])
def _eval_aseries(self, n, args0, x, logx):
from sympy.series.order import O
s, z = self.args
if args0[0] is S.Infinity and not z.has(x):
coeff = z**s*exp(-z)
sum_expr = sum(z**k/rf(s, k + 1) for k in range(n - 1))
o = O(z**s*s**(-n))
return coeff*sum_expr + o
return super()._eval_aseries(n, args0, x, logx)
def _eval_rewrite_as_uppergamma(self, s, x, **kwargs):
return gamma(s) - uppergamma(s, x)
def _eval_rewrite_as_expint(self, s, x, **kwargs):
from sympy.functions.special.error_functions import expint
if s.is_integer and s.is_nonpositive:
return self
return self.rewrite(uppergamma).rewrite(expint)
def _eval_is_zero(self):
x = self.args[1]
if x.is_zero:
return True
class uppergamma(Function):
r"""
The upper incomplete gamma function.
Explanation
===========
It can be defined as the meromorphic continuation of
.. math::
\Gamma(s, x) := \int_x^\infty t^{s-1} e^{-t} \mathrm{d}t = \Gamma(s) - \gamma(s, x).
where $\gamma(s, x)$ is the lower incomplete gamma function,
:class:`lowergamma`. This can be shown to be the same as
.. math::
\Gamma(s, x) = \Gamma(s) - \frac{x^s}{s} {}_1F_1\left({s \atop s+1} \middle| -x\right),
where ${}_1F_1$ is the (confluent) hypergeometric function.
The upper incomplete gamma function is also essentially equivalent to the
generalized exponential integral:
.. math::
\operatorname{E}_{n}(x) = \int_{1}^{\infty}{\frac{e^{-xt}}{t^n} \, dt} = x^{n-1}\Gamma(1-n,x).
Examples
========
>>> from sympy import uppergamma, S
>>> from sympy.abc import s, x
>>> uppergamma(s, x)
uppergamma(s, x)
>>> uppergamma(3, x)
2*(x**2/2 + x + 1)*exp(-x)
>>> uppergamma(-S(1)/2, x)
-2*sqrt(pi)*erfc(sqrt(x)) + 2*exp(-x)/sqrt(x)
>>> uppergamma(-2, x)
expint(3, x)/x**2
See Also
========
gamma: Gamma function.
lowergamma: Lower incomplete gamma function.
polygamma: Polygamma function.
loggamma: Log Gamma function.
digamma: Digamma function.
trigamma: Trigamma function.
beta: Euler Beta function.
References
==========
.. [1] https://en.wikipedia.org/wiki/Incomplete_gamma_function#Upper_incomplete_Gamma_function
.. [2] Abramowitz, Milton; Stegun, Irene A., eds. (1965), Chapter 6,
Section 5, Handbook of Mathematical Functions with Formulas, Graphs,
and Mathematical Tables
.. [3] http://dlmf.nist.gov/8
.. [4] http://functions.wolfram.com/GammaBetaErf/Gamma2/
.. [5] http://functions.wolfram.com/GammaBetaErf/Gamma3/
.. [6] https://en.wikipedia.org/wiki/Exponential_integral#Relation_with_other_functions
"""
def fdiff(self, argindex=2):
from sympy.functions.special.hyper import meijerg
if argindex == 2:
a, z = self.args
return -exp(-unpolarify(z))*z**(a - 1)
elif argindex == 1:
a, z = self.args
return uppergamma(a, z)*log(z) + meijerg([], [1, 1], [0, 0, a], [], z)
else:
raise ArgumentIndexError(self, argindex)
def _eval_evalf(self, prec):
if all(x.is_number for x in self.args):
a = self.args[0]._to_mpmath(prec)
z = self.args[1]._to_mpmath(prec)
with workprec(prec):
res = mp.gammainc(a, z, mp.inf)
return Expr._from_mpmath(res, prec)
return self
@classmethod
def eval(cls, a, z):
from sympy.functions.special.error_functions import expint
if z.is_Number:
if z is S.NaN:
return S.NaN
elif z is S.Infinity:
return S.Zero
elif z.is_zero:
if re(a).is_positive:
return gamma(a)
# We extract branching information here. C/f lowergamma.
nx, n = z.extract_branch_factor()
if a.is_integer and a.is_positive:
nx = unpolarify(z)
if z != nx:
return uppergamma(a, nx)
elif a.is_integer and a.is_nonpositive:
if n != 0:
return -2*pi*I*n*S.NegativeOne**(-a)/factorial(-a) + uppergamma(a, nx)
elif n != 0:
return gamma(a)*(1 - exp(2*pi*I*n*a)) + exp(2*pi*I*n*a)*uppergamma(a, nx)
# Special values.
if a.is_Number:
if a is S.Zero and z.is_positive:
return -Ei(-z)
elif a is S.One:
return exp(-z)
elif a is S.Half:
return sqrt(pi)*erfc(sqrt(z))
elif a.is_Integer or (2*a).is_Integer:
b = a - 1
if b.is_positive:
if a.is_integer:
return exp(-z) * factorial(b) * Add(*[z**k / factorial(k)
for k in range(a)])
else:
return (gamma(a) * erfc(sqrt(z)) +
S.NegativeOne**(a - S(3)/2) * exp(-z) * sqrt(z)
* Add(*[gamma(-S.Half - k) * (-z)**k / gamma(1-a)
for k in range(a - S.Half)]))
elif b.is_Integer:
return expint(-b, z)*unpolarify(z)**(b + 1)
if not a.is_Integer:
return (S.NegativeOne**(S.Half - a) * pi*erfc(sqrt(z))/gamma(1-a)
- z**a * exp(-z) * Add(*[z**k * gamma(a) / gamma(a+k+1)
for k in range(S.Half - a)]))
if a.is_zero and z.is_positive:
return -Ei(-z)
if z.is_zero and re(a).is_positive:
return gamma(a)
def _eval_conjugate(self):
z = self.args[1]
if not z in (S.Zero, S.NegativeInfinity):
return self.func(self.args[0].conjugate(), z.conjugate())
def _eval_is_meromorphic(self, x, a):
return lowergamma._eval_is_meromorphic(self, x, a)
def _eval_rewrite_as_lowergamma(self, s, x, **kwargs):
return gamma(s) - lowergamma(s, x)
def _eval_rewrite_as_tractable(self, s, x, **kwargs):
return exp(loggamma(s)) - lowergamma(s, x)
def _eval_rewrite_as_expint(self, s, x, **kwargs):
from sympy.functions.special.error_functions import expint
return expint(1 - s, x)*x**s
###############################################################################
###################### POLYGAMMA and LOGGAMMA FUNCTIONS #######################
###############################################################################
class polygamma(Function):
r"""
The function ``polygamma(n, z)`` returns ``log(gamma(z)).diff(n + 1)``.
Explanation
===========
It is a meromorphic function on $\mathbb{C}$ and defined as the $(n+1)$-th
derivative of the logarithm of the gamma function:
.. math::
\psi^{(n)} (z) := \frac{\mathrm{d}^{n+1}}{\mathrm{d} z^{n+1}} \log\Gamma(z).
Examples
========
Several special values are known:
>>> from sympy import S, polygamma
>>> polygamma(0, 1)
-EulerGamma
>>> polygamma(0, 1/S(2))
-2*log(2) - EulerGamma
>>> polygamma(0, 1/S(3))
-log(3) - sqrt(3)*pi/6 - EulerGamma - log(sqrt(3))
>>> polygamma(0, 1/S(4))
-pi/2 - log(4) - log(2) - EulerGamma
>>> polygamma(0, 2)
1 - EulerGamma
>>> polygamma(0, 23)
19093197/5173168 - EulerGamma
>>> from sympy import oo, I
>>> polygamma(0, oo)
oo
>>> polygamma(0, -oo)
oo
>>> polygamma(0, I*oo)
oo
>>> polygamma(0, -I*oo)
oo
Differentiation with respect to $x$ is supported:
>>> from sympy import Symbol, diff
>>> x = Symbol("x")
>>> diff(polygamma(0, x), x)
polygamma(1, x)
>>> diff(polygamma(0, x), x, 2)
polygamma(2, x)
>>> diff(polygamma(0, x), x, 3)
polygamma(3, x)
>>> diff(polygamma(1, x), x)
polygamma(2, x)
>>> diff(polygamma(1, x), x, 2)
polygamma(3, x)
>>> diff(polygamma(2, x), x)
polygamma(3, x)
>>> diff(polygamma(2, x), x, 2)
polygamma(4, x)
>>> n = Symbol("n")
>>> diff(polygamma(n, x), x)
polygamma(n + 1, x)
>>> diff(polygamma(n, x), x, 2)
polygamma(n + 2, x)
We can rewrite ``polygamma`` functions in terms of harmonic numbers:
>>> from sympy import harmonic
>>> polygamma(0, x).rewrite(harmonic)
harmonic(x - 1) - EulerGamma
>>> polygamma(2, x).rewrite(harmonic)
2*harmonic(x - 1, 3) - 2*zeta(3)
>>> ni = Symbol("n", integer=True)
>>> polygamma(ni, x).rewrite(harmonic)
(-1)**(n + 1)*(-harmonic(x - 1, n + 1) + zeta(n + 1))*factorial(n)
See Also
========
gamma: Gamma function.
lowergamma: Lower incomplete gamma function.
uppergamma: Upper incomplete gamma function.
loggamma: Log Gamma function.
digamma: Digamma function.
trigamma: Trigamma function.
beta: Euler Beta function.
References
==========
.. [1] https://en.wikipedia.org/wiki/Polygamma_function
.. [2] http://mathworld.wolfram.com/PolygammaFunction.html
.. [3] http://functions.wolfram.com/GammaBetaErf/PolyGamma/
.. [4] http://functions.wolfram.com/GammaBetaErf/PolyGamma2/
"""
def _eval_evalf(self, prec):
n = self.args[0]
# the mpmath polygamma implementation valid only for nonnegative integers
if n.is_number and n.is_real:
if (n.is_integer or n == int(n)) and n.is_nonnegative:
return super()._eval_evalf(prec)
def fdiff(self, argindex=2):
if argindex == 2:
n, z = self.args[:2]
return polygamma(n + 1, z)
else:
raise ArgumentIndexError(self, argindex)
def _eval_is_real(self):
if self.args[0].is_positive and self.args[1].is_positive:
return True
def _eval_is_complex(self):
z = self.args[1]
is_negative_integer = fuzzy_and([z.is_negative, z.is_integer])
return fuzzy_and([z.is_complex, fuzzy_not(is_negative_integer)])
def _eval_is_positive(self):
if self.args[0].is_positive and self.args[1].is_positive:
return self.args[0].is_odd
def _eval_is_negative(self):
if self.args[0].is_positive and self.args[1].is_positive:
return self.args[0].is_even
def _eval_aseries(self, n, args0, x, logx):
from sympy.series.order import Order
if args0[1] != oo or not \
(self.args[0].is_Integer and self.args[0].is_nonnegative):
return super()._eval_aseries(n, args0, x, logx)
z = self.args[1]
N = self.args[0]
if N == 0:
# digamma function series
# Abramowitz & Stegun, p. 259, 6.3.18
r = log(z) - 1/(2*z)
o = None
if n < 2:
o = Order(1/z, x)
else:
m = ceiling((n + 1)//2)
l = [bernoulli(2*k) / (2*k*z**(2*k)) for k in range(1, m)]
r -= Add(*l)
o = Order(1/z**n, x)
return r._eval_nseries(x, n, logx) + o
else:
# proper polygamma function
# Abramowitz & Stegun, p. 260, 6.4.10
# We return terms to order higher than O(x**n) on purpose
# -- otherwise we would not be able to return any terms for
# quite a long time!
fac = gamma(N)
e0 = fac + N*fac/(2*z)
m = ceiling((n + 1)//2)
for k in range(1, m):
fac = fac*(2*k + N - 1)*(2*k + N - 2) / ((2*k)*(2*k - 1))
e0 += bernoulli(2*k)*fac/z**(2*k)
o = Order(1/z**(2*m), x)
if n == 0:
o = Order(1/z, x)
elif n == 1:
o = Order(1/z**2, x)
r = e0._eval_nseries(z, n, logx) + o
return (-1 * (-1/z)**N * r)._eval_nseries(x, n, logx)
@classmethod
def eval(cls, n, z):
n, z = map(sympify, (n, z))
if n.is_integer:
if n.is_nonnegative:
nz = unpolarify(z)
if z != nz:
return polygamma(n, nz)
if n.is_positive:
if z is S.Half:
return S.NegativeOne**(n + 1)*factorial(n)*(2**(n + 1) - 1)*zeta(n + 1)
if n is S.NegativeOne:
return loggamma(z)
else:
if z.is_Number:
if z is S.NaN:
return S.NaN
elif z is S.Infinity:
if n.is_Number:
if n.is_zero:
return S.Infinity
else:
return S.Zero
if n.is_zero:
return S.Infinity
elif z.is_Integer:
if z.is_nonpositive:
return S.ComplexInfinity
else:
if n.is_zero:
return harmonic(z - 1, 1) - S.EulerGamma
elif n.is_odd:
return S.NegativeOne**(n + 1)*factorial(n)*zeta(n + 1, z)
if n.is_zero:
if z is S.NaN:
return S.NaN
elif z.is_Rational:
p, q = z.as_numer_denom()
# only expand for small denominators to avoid creating long expressions
if q <= 5:
return expand_func(polygamma(S.Zero, z, evaluate=False))
elif z in (S.Infinity, S.NegativeInfinity):
return S.Infinity
else:
t = z.extract_multiplicatively(S.ImaginaryUnit)
if t in (S.Infinity, S.NegativeInfinity):
return S.Infinity
# TODO n == 1 also can do some rational z
def _eval_expand_func(self, **hints):
n, z = self.args
if n.is_Integer and n.is_nonnegative:
if z.is_Add:
coeff = z.args[0]
if coeff.is_Integer:
e = -(n + 1)
if coeff > 0:
tail = Add(*[Pow(
z - i, e) for i in range(1, int(coeff) + 1)])
else:
tail = -Add(*[Pow(
z + i, e) for i in range(0, int(-coeff))])
return polygamma(n, z - coeff) + S.NegativeOne**n*factorial(n)*tail
elif z.is_Mul:
coeff, z = z.as_two_terms()
if coeff.is_Integer and coeff.is_positive:
tail = [ polygamma(n, z + Rational(
i, coeff)) for i in range(0, int(coeff)) ]
if n == 0:
return Add(*tail)/coeff + log(coeff)
else:
return Add(*tail)/coeff**(n + 1)
z *= coeff
if n == 0 and z.is_Rational:
p, q = z.as_numer_denom()
# Reference:
# Values of the polygamma functions at rational arguments, J. Choi, 2007
part_1 = -S.EulerGamma - pi * cot(p * pi / q) / 2 - log(q) + Add(
*[cos(2 * k * pi * p / q) * log(2 * sin(k * pi / q)) for k in range(1, q)])
if z > 0:
n = floor(z)
z0 = z - n
return part_1 + Add(*[1 / (z0 + k) for k in range(n)])
elif z < 0:
n = floor(1 - z)
z0 = z + n
return part_1 - Add(*[1 / (z0 - 1 - k) for k in range(n)])
return polygamma(n, z)
def _eval_rewrite_as_zeta(self, n, z, **kwargs):
if n.is_integer:
if (n - S.One).is_nonnegative:
return S.NegativeOne**(n + 1)*factorial(n)*zeta(n + 1, z)
def _eval_rewrite_as_harmonic(self, n, z, **kwargs):
if n.is_integer:
if n.is_zero:
return harmonic(z - 1) - S.EulerGamma
else:
return S.NegativeOne**(n+1) * factorial(n) * (zeta(n+1) - harmonic(z-1, n+1))
def _eval_as_leading_term(self, x, logx=None, cdir=0):
from sympy.series.order import Order
n, z = [a.as_leading_term(x) for a in self.args]
o = Order(z, x)
if n == 0 and o.contains(1/x):
return o.getn() * log(x)
else:
return self.func(n, z)
class loggamma(Function):
r"""
The ``loggamma`` function implements the logarithm of the
gamma function (i.e., $\log\Gamma(x)$).
Examples
========
Several special values are known. For numerical integral
arguments we have:
>>> from sympy import loggamma
>>> loggamma(-2)
oo
>>> loggamma(0)
oo
>>> loggamma(1)
0
>>> loggamma(2)
0
>>> loggamma(3)
log(2)
And for symbolic values:
>>> from sympy import Symbol
>>> n = Symbol("n", integer=True, positive=True)
>>> loggamma(n)
log(gamma(n))
>>> loggamma(-n)
oo
For half-integral values:
>>> from sympy import S
>>> loggamma(S(5)/2)
log(3*sqrt(pi)/4)
>>> loggamma(n/2)
log(2**(1 - n)*sqrt(pi)*gamma(n)/gamma(n/2 + 1/2))
And general rational arguments:
>>> from sympy import expand_func
>>> L = loggamma(S(16)/3)
>>> expand_func(L).doit()
-5*log(3) + loggamma(1/3) + log(4) + log(7) + log(10) + log(13)
>>> L = loggamma(S(19)/4)
>>> expand_func(L).doit()
-4*log(4) + loggamma(3/4) + log(3) + log(7) + log(11) + log(15)
>>> L = loggamma(S(23)/7)
>>> expand_func(L).doit()
-3*log(7) + log(2) + loggamma(2/7) + log(9) + log(16)
The ``loggamma`` function has the following limits towards infinity:
>>> from sympy import oo
>>> loggamma(oo)
oo
>>> loggamma(-oo)
zoo
The ``loggamma`` function obeys the mirror symmetry
if $x \in \mathbb{C} \setminus \{-\infty, 0\}$:
>>> from sympy.abc import x
>>> from sympy import conjugate
>>> conjugate(loggamma(x))
loggamma(conjugate(x))
Differentiation with respect to $x$ is supported:
>>> from sympy import diff
>>> diff(loggamma(x), x)
polygamma(0, x)
Series expansion is also supported:
>>> from sympy import series
>>> series(loggamma(x), x, 0, 4).cancel()
-log(x) - EulerGamma*x + pi**2*x**2/12 + x**3*polygamma(2, 1)/6 + O(x**4)
We can numerically evaluate the ``gamma`` function to arbitrary precision
on the whole complex plane:
>>> from sympy import I
>>> loggamma(5).evalf(30)
3.17805383034794561964694160130
>>> loggamma(I).evalf(20)
-0.65092319930185633889 - 1.8724366472624298171*I
See Also
========
gamma: Gamma function.
lowergamma: Lower incomplete gamma function.
uppergamma: Upper incomplete gamma function.
polygamma: Polygamma function.
digamma: Digamma function.
trigamma: Trigamma function.
beta: Euler Beta function.
References
==========
.. [1] https://en.wikipedia.org/wiki/Gamma_function
.. [2] http://dlmf.nist.gov/5
.. [3] http://mathworld.wolfram.com/LogGammaFunction.html
.. [4] http://functions.wolfram.com/GammaBetaErf/LogGamma/
"""
@classmethod
def eval(cls, z):
z = sympify(z)
if z.is_integer:
if z.is_nonpositive:
return S.Infinity
elif z.is_positive:
return log(gamma(z))
elif z.is_rational:
p, q = z.as_numer_denom()
# Half-integral values:
if p.is_positive and q == 2:
return log(sqrt(S.Pi) * 2**(1 - p) * gamma(p) / gamma((p + 1)*S.Half))
if z is S.Infinity:
return S.Infinity
elif abs(z) is S.Infinity:
return S.ComplexInfinity
if z is S.NaN:
return S.NaN
def _eval_expand_func(self, **hints):
from sympy.concrete.summations import Sum
z = self.args[0]
if z.is_Rational:
p, q = z.as_numer_denom()
# General rational arguments (u + p/q)
# Split z as n + p/q with p < q
n = p // q
p = p - n*q
if p.is_positive and q.is_positive and p < q:
k = Dummy("k")
if n.is_positive:
return loggamma(p / q) - n*log(q) + Sum(log((k - 1)*q + p), (k, 1, n))
elif n.is_negative:
return loggamma(p / q) - n*log(q) + S.Pi*S.ImaginaryUnit*n - Sum(log(k*q - p), (k, 1, -n))
elif n.is_zero:
return loggamma(p / q)
return self
def _eval_nseries(self, x, n, logx=None, cdir=0):
x0 = self.args[0].limit(x, 0)
if x0.is_zero:
f = self._eval_rewrite_as_intractable(*self.args)
return f._eval_nseries(x, n, logx)
return super()._eval_nseries(x, n, logx)
def _eval_aseries(self, n, args0, x, logx):
from sympy.series.order import Order
if args0[0] != oo:
return super()._eval_aseries(n, args0, x, logx)
z = self.args[0]
r = log(z)*(z - S.Half) - z + log(2*pi)/2
l = [bernoulli(2*k) / (2*k*(2*k - 1)*z**(2*k - 1)) for k in range(1, n)]
o = None
if n == 0:
o = Order(1, x)
else:
o = Order(1/z**n, x)
# It is very inefficient to first add the order and then do the nseries
return (r + Add(*l))._eval_nseries(x, n, logx) + o
def _eval_rewrite_as_intractable(self, z, **kwargs):
return log(gamma(z))
def _eval_is_real(self):
z = self.args[0]
if z.is_positive:
return True
elif z.is_nonpositive:
return False
def _eval_conjugate(self):
z = self.args[0]
if not z in (S.Zero, S.NegativeInfinity):
return self.func(z.conjugate())
def fdiff(self, argindex=1):
if argindex == 1:
return polygamma(0, self.args[0])
else:
raise ArgumentIndexError(self, argindex)
class digamma(Function):
r"""
The ``digamma`` function is the first derivative of the ``loggamma``
function
.. math::
\psi(x) := \frac{\mathrm{d}}{\mathrm{d} z} \log\Gamma(z)
= \frac{\Gamma'(z)}{\Gamma(z) }.
In this case, ``digamma(z) = polygamma(0, z)``.
Examples
========
>>> from sympy import digamma
>>> digamma(0)
zoo
>>> from sympy import Symbol
>>> z = Symbol('z')
>>> digamma(z)
polygamma(0, z)
To retain ``digamma`` as it is:
>>> digamma(0, evaluate=False)
digamma(0)
>>> digamma(z, evaluate=False)
digamma(z)
See Also
========
gamma: Gamma function.
lowergamma: Lower incomplete gamma function.
uppergamma: Upper incomplete gamma function.
polygamma: Polygamma function.
loggamma: Log Gamma function.
trigamma: Trigamma function.
beta: Euler Beta function.
References
==========
.. [1] https://en.wikipedia.org/wiki/Digamma_function
.. [2] http://mathworld.wolfram.com/DigammaFunction.html
.. [3] http://functions.wolfram.com/GammaBetaErf/PolyGamma2/
"""
def _eval_evalf(self, prec):
z = self.args[0]
nprec = prec_to_dps(prec)
return polygamma(0, z).evalf(n=nprec)
def fdiff(self, argindex=1):
z = self.args[0]
return polygamma(0, z).fdiff()
def _eval_is_real(self):
z = self.args[0]
return polygamma(0, z).is_real
def _eval_is_positive(self):
z = self.args[0]
return polygamma(0, z).is_positive
def _eval_is_negative(self):
z = self.args[0]
return polygamma(0, z).is_negative
def _eval_aseries(self, n, args0, x, logx):
as_polygamma = self.rewrite(polygamma)
args0 = [S.Zero,] + args0
return as_polygamma._eval_aseries(n, args0, x, logx)
@classmethod
def eval(cls, z):
return polygamma(0, z)
def _eval_expand_func(self, **hints):
z = self.args[0]
return polygamma(0, z).expand(func=True)
def _eval_rewrite_as_harmonic(self, z, **kwargs):
return harmonic(z - 1) - S.EulerGamma
def _eval_rewrite_as_polygamma(self, z, **kwargs):
return polygamma(0, z)
def _eval_as_leading_term(self, x, logx=None, cdir=0):
z = self.args[0]
return polygamma(0, z).as_leading_term(x)
class trigamma(Function):
r"""
The ``trigamma`` function is the second derivative of the ``loggamma``
function
.. math::
\psi^{(1)}(z) := \frac{\mathrm{d}^{2}}{\mathrm{d} z^{2}} \log\Gamma(z).
In this case, ``trigamma(z) = polygamma(1, z)``.
Examples
========
>>> from sympy import trigamma
>>> trigamma(0)
zoo
>>> from sympy import Symbol
>>> z = Symbol('z')
>>> trigamma(z)
polygamma(1, z)
To retain ``trigamma`` as it is:
>>> trigamma(0, evaluate=False)
trigamma(0)
>>> trigamma(z, evaluate=False)
trigamma(z)
See Also
========
gamma: Gamma function.
lowergamma: Lower incomplete gamma function.
uppergamma: Upper incomplete gamma function.
polygamma: Polygamma function.
loggamma: Log Gamma function.
digamma: Digamma function.
beta: Euler Beta function.
References
==========
.. [1] https://en.wikipedia.org/wiki/Trigamma_function
.. [2] http://mathworld.wolfram.com/TrigammaFunction.html
.. [3] http://functions.wolfram.com/GammaBetaErf/PolyGamma2/
"""
def _eval_evalf(self, prec):
z = self.args[0]
nprec = prec_to_dps(prec)
return polygamma(1, z).evalf(n=nprec)
def fdiff(self, argindex=1):
z = self.args[0]
return polygamma(1, z).fdiff()
def _eval_is_real(self):
z = self.args[0]
return polygamma(1, z).is_real
def _eval_is_positive(self):
z = self.args[0]
return polygamma(1, z).is_positive
def _eval_is_negative(self):
z = self.args[0]
return polygamma(1, z).is_negative
def _eval_aseries(self, n, args0, x, logx):
as_polygamma = self.rewrite(polygamma)
args0 = [S.One,] + args0
return as_polygamma._eval_aseries(n, args0, x, logx)
@classmethod
def eval(cls, z):
return polygamma(1, z)
def _eval_expand_func(self, **hints):
z = self.args[0]
return polygamma(1, z).expand(func=True)
def _eval_rewrite_as_zeta(self, z, **kwargs):
return zeta(2, z)
def _eval_rewrite_as_polygamma(self, z, **kwargs):
return polygamma(1, z)
def _eval_rewrite_as_harmonic(self, z, **kwargs):
return -harmonic(z - 1, 2) + S.Pi**2 / 6
def _eval_as_leading_term(self, x, logx=None, cdir=0):
z = self.args[0]
return polygamma(1, z).as_leading_term(x)
###############################################################################
##################### COMPLETE MULTIVARIATE GAMMA FUNCTION ####################
###############################################################################
class multigamma(Function):
r"""
The multivariate gamma function is a generalization of the gamma function
.. math::
\Gamma_p(z) = \pi^{p(p-1)/4}\prod_{k=1}^p \Gamma[z + (1 - k)/2].
In a special case, ``multigamma(x, 1) = gamma(x)``.
Examples
========
>>> from sympy import S, multigamma
>>> from sympy import Symbol
>>> x = Symbol('x')
>>> p = Symbol('p', positive=True, integer=True)
>>> multigamma(x, p)
pi**(p*(p - 1)/4)*Product(gamma(-_k/2 + x + 1/2), (_k, 1, p))
Several special values are known:
>>> multigamma(1, 1)
1
>>> multigamma(4, 1)
6
>>> multigamma(S(3)/2, 1)
sqrt(pi)/2
Writing ``multigamma`` in terms of the ``gamma`` function:
>>> multigamma(x, 1)
gamma(x)
>>> multigamma(x, 2)
sqrt(pi)*gamma(x)*gamma(x - 1/2)
>>> multigamma(x, 3)
pi**(3/2)*gamma(x)*gamma(x - 1)*gamma(x - 1/2)
Parameters
==========
p : order or dimension of the multivariate gamma function
See Also
========
gamma, lowergamma, uppergamma, polygamma, loggamma, digamma, trigamma,
beta
References
==========
.. [1] https://en.wikipedia.org/wiki/Multivariate_gamma_function
"""
unbranched = True
def fdiff(self, argindex=2):
from sympy.concrete.summations import Sum
if argindex == 2:
x, p = self.args
k = Dummy("k")
return self.func(x, p)*Sum(polygamma(0, x + (1 - k)/2), (k, 1, p))
else:
raise ArgumentIndexError(self, argindex)
@classmethod
def eval(cls, x, p):
from sympy.concrete.products import Product
x, p = map(sympify, (x, p))
if p.is_positive is False or p.is_integer is False:
raise ValueError('Order parameter p must be positive integer.')
k = Dummy("k")
return (pi**(p*(p - 1)/4)*Product(gamma(x + (1 - k)/2),
(k, 1, p))).doit()
def _eval_conjugate(self):
x, p = self.args
return self.func(x.conjugate(), p)
def _eval_is_real(self):
x, p = self.args
y = 2*x
if y.is_integer and (y <= (p - 1)) is True:
return False
if intlike(y) and (y <= (p - 1)):
return False
if y > (p - 1) or y.is_noninteger:
return True
|
53aa32236aead5cf231020905d44baf7d4daaac6c26c3cd7c6b37f56fe828e08 | from sympy.core import S, sympify, diff
from sympy.core.function import Function, ArgumentIndexError
from sympy.core.logic import fuzzy_not
from sympy.core.relational import Eq, Ne
from sympy.functions.elementary.complexes import im, sign
from sympy.functions.elementary.piecewise import Piecewise
from sympy.polys.polyerrors import PolynomialError
from sympy.utilities.decorator import deprecated
from sympy.utilities.misc import filldedent
###############################################################################
################################ DELTA FUNCTION ###############################
###############################################################################
class DiracDelta(Function):
r"""
The DiracDelta function and its derivatives.
Explanation
===========
DiracDelta is not an ordinary function. It can be rigorously defined either
as a distribution or as a measure.
DiracDelta only makes sense in definite integrals, and in particular,
integrals of the form ``Integral(f(x)*DiracDelta(x - x0), (x, a, b))``,
where it equals ``f(x0)`` if ``a <= x0 <= b`` and ``0`` otherwise. Formally,
DiracDelta acts in some ways like a function that is ``0`` everywhere except
at ``0``, but in many ways it also does not. It can often be useful to treat
DiracDelta in formal ways, building up and manipulating expressions with
delta functions (which may eventually be integrated), but care must be taken
to not treat it as a real function. SymPy's ``oo`` is similar. It only
truly makes sense formally in certain contexts (such as integration limits),
but SymPy allows its use everywhere, and it tries to be consistent with
operations on it (like ``1/oo``), but it is easy to get into trouble and get
wrong results if ``oo`` is treated too much like a number. Similarly, if
DiracDelta is treated too much like a function, it is easy to get wrong or
nonsensical results.
DiracDelta function has the following properties:
1) $\frac{d}{d x} \theta(x) = \delta(x)$
2) $\int_{-\infty}^\infty \delta(x - a)f(x)\, dx = f(a)$ and $\int_{a-
\epsilon}^{a+\epsilon} \delta(x - a)f(x)\, dx = f(a)$
3) $\delta(x) = 0$ for all $x \neq 0$
4) $\delta(g(x)) = \sum_i \frac{\delta(x - x_i)}{\|g'(x_i)\|}$ where $x_i$
are the roots of $g$
5) $\delta(-x) = \delta(x)$
Derivatives of ``k``-th order of DiracDelta have the following properties:
6) $\delta(x, k) = 0$ for all $x \neq 0$
7) $\delta(-x, k) = -\delta(x, k)$ for odd $k$
8) $\delta(-x, k) = \delta(x, k)$ for even $k$
Examples
========
>>> from sympy import DiracDelta, diff, pi
>>> from sympy.abc import x, y
>>> DiracDelta(x)
DiracDelta(x)
>>> DiracDelta(1)
0
>>> DiracDelta(-1)
0
>>> DiracDelta(pi)
0
>>> DiracDelta(x - 4).subs(x, 4)
DiracDelta(0)
>>> diff(DiracDelta(x))
DiracDelta(x, 1)
>>> diff(DiracDelta(x - 1),x,2)
DiracDelta(x - 1, 2)
>>> diff(DiracDelta(x**2 - 1),x,2)
2*(2*x**2*DiracDelta(x**2 - 1, 2) + DiracDelta(x**2 - 1, 1))
>>> DiracDelta(3*x).is_simple(x)
True
>>> DiracDelta(x**2).is_simple(x)
False
>>> DiracDelta((x**2 - 1)*y).expand(diracdelta=True, wrt=x)
DiracDelta(x - 1)/(2*Abs(y)) + DiracDelta(x + 1)/(2*Abs(y))
See Also
========
Heaviside
sympy.simplify.simplify.simplify, is_simple
sympy.functions.special.tensor_functions.KroneckerDelta
References
==========
.. [1] http://mathworld.wolfram.com/DeltaFunction.html
"""
is_real = True
def fdiff(self, argindex=1):
"""
Returns the first derivative of a DiracDelta Function.
Explanation
===========
The difference between ``diff()`` and ``fdiff()`` is: ``diff()`` is the
user-level function and ``fdiff()`` is an object method. ``fdiff()`` is
a convenience method available in the ``Function`` class. It returns
the derivative of the function without considering the chain rule.
``diff(function, x)`` calls ``Function._eval_derivative`` which in turn
calls ``fdiff()`` internally to compute the derivative of the function.
Examples
========
>>> from sympy import DiracDelta, diff
>>> from sympy.abc import x
>>> DiracDelta(x).fdiff()
DiracDelta(x, 1)
>>> DiracDelta(x, 1).fdiff()
DiracDelta(x, 2)
>>> DiracDelta(x**2 - 1).fdiff()
DiracDelta(x**2 - 1, 1)
>>> diff(DiracDelta(x, 1)).fdiff()
DiracDelta(x, 3)
Parameters
==========
argindex : integer
degree of derivative
"""
if argindex == 1:
#I didn't know if there is a better way to handle default arguments
k = 0
if len(self.args) > 1:
k = self.args[1]
return self.func(self.args[0], k + 1)
else:
raise ArgumentIndexError(self, argindex)
@classmethod
def eval(cls, arg, k=0):
"""
Returns a simplified form or a value of DiracDelta depending on the
argument passed by the DiracDelta object.
Explanation
===========
The ``eval()`` method is automatically called when the ``DiracDelta``
class is about to be instantiated and it returns either some simplified
instance or the unevaluated instance depending on the argument passed.
In other words, ``eval()`` method is not needed to be called explicitly,
it is being called and evaluated once the object is called.
Examples
========
>>> from sympy import DiracDelta, S
>>> from sympy.abc import x
>>> DiracDelta(x)
DiracDelta(x)
>>> DiracDelta(-x, 1)
-DiracDelta(x, 1)
>>> DiracDelta(1)
0
>>> DiracDelta(5, 1)
0
>>> DiracDelta(0)
DiracDelta(0)
>>> DiracDelta(-1)
0
>>> DiracDelta(S.NaN)
nan
>>> DiracDelta(x).eval(1)
0
>>> DiracDelta(x - 100).subs(x, 5)
0
>>> DiracDelta(x - 100).subs(x, 100)
DiracDelta(0)
Parameters
==========
k : integer
order of derivative
arg : argument passed to DiracDelta
"""
k = sympify(k)
if not k.is_Integer or k.is_negative:
raise ValueError("Error: the second argument of DiracDelta must be \
a non-negative integer, %s given instead." % (k,))
arg = sympify(arg)
if arg is S.NaN:
return S.NaN
if arg.is_nonzero:
return S.Zero
if fuzzy_not(im(arg).is_zero):
raise ValueError(filldedent('''
Function defined only for Real Values.
Complex part: %s found in %s .''' % (
repr(im(arg)), repr(arg))))
c, nc = arg.args_cnc()
if c and c[0] is S.NegativeOne:
# keep this fast and simple instead of using
# could_extract_minus_sign
if k.is_odd:
return -cls(-arg, k)
elif k.is_even:
return cls(-arg, k) if k else cls(-arg)
@deprecated(useinstead="expand(diracdelta=True, wrt=x)", issue=12859, deprecated_since_version="1.1")
def simplify(self, x, **kwargs):
return self.expand(diracdelta=True, wrt=x)
def _eval_expand_diracdelta(self, **hints):
"""
Compute a simplified representation of the function using
property number 4. Pass ``wrt`` as a hint to expand the expression
with respect to a particular variable.
Explanation
===========
``wrt`` is:
- a variable with respect to which a DiracDelta expression will
get expanded.
Examples
========
>>> from sympy import DiracDelta
>>> from sympy.abc import x, y
>>> DiracDelta(x*y).expand(diracdelta=True, wrt=x)
DiracDelta(x)/Abs(y)
>>> DiracDelta(x*y).expand(diracdelta=True, wrt=y)
DiracDelta(y)/Abs(x)
>>> DiracDelta(x**2 + x - 2).expand(diracdelta=True, wrt=x)
DiracDelta(x - 1)/3 + DiracDelta(x + 2)/3
See Also
========
is_simple, Diracdelta
"""
from sympy.polys.polyroots import roots
wrt = hints.get('wrt', None)
if wrt is None:
free = self.free_symbols
if len(free) == 1:
wrt = free.pop()
else:
raise TypeError(filldedent('''
When there is more than 1 free symbol or variable in the expression,
the 'wrt' keyword is required as a hint to expand when using the
DiracDelta hint.'''))
if not self.args[0].has(wrt) or (len(self.args) > 1 and self.args[1] != 0 ):
return self
try:
argroots = roots(self.args[0], wrt)
result = 0
valid = True
darg = abs(diff(self.args[0], wrt))
for r, m in argroots.items():
if r.is_real is not False and m == 1:
result += self.func(wrt - r)/darg.subs(wrt, r)
else:
# don't handle non-real and if m != 1 then
# a polynomial will have a zero in the derivative (darg)
# at r
valid = False
break
if valid:
return result
except PolynomialError:
pass
return self
def is_simple(self, x):
"""
Tells whether the argument(args[0]) of DiracDelta is a linear
expression in *x*.
Examples
========
>>> from sympy import DiracDelta, cos
>>> from sympy.abc import x, y
>>> DiracDelta(x*y).is_simple(x)
True
>>> DiracDelta(x*y).is_simple(y)
True
>>> DiracDelta(x**2 + x - 2).is_simple(x)
False
>>> DiracDelta(cos(x)).is_simple(x)
False
Parameters
==========
x : can be a symbol
See Also
========
sympy.simplify.simplify.simplify, DiracDelta
"""
p = self.args[0].as_poly(x)
if p:
return p.degree() == 1
return False
def _eval_rewrite_as_Piecewise(self, *args, **kwargs):
"""
Represents DiracDelta in a piecewise form.
Examples
========
>>> from sympy import DiracDelta, Piecewise, Symbol
>>> x = Symbol('x')
>>> DiracDelta(x).rewrite(Piecewise)
Piecewise((DiracDelta(0), Eq(x, 0)), (0, True))
>>> DiracDelta(x - 5).rewrite(Piecewise)
Piecewise((DiracDelta(0), Eq(x, 5)), (0, True))
>>> DiracDelta(x**2 - 5).rewrite(Piecewise)
Piecewise((DiracDelta(0), Eq(x**2, 5)), (0, True))
>>> DiracDelta(x - 5, 4).rewrite(Piecewise)
DiracDelta(x - 5, 4)
"""
if len(args) == 1:
return Piecewise((DiracDelta(0), Eq(args[0], 0)), (0, True))
def _eval_rewrite_as_SingularityFunction(self, *args, **kwargs):
"""
Returns the DiracDelta expression written in the form of Singularity
Functions.
"""
from sympy.solvers import solve
from sympy.functions import SingularityFunction
if self == DiracDelta(0):
return SingularityFunction(0, 0, -1)
if self == DiracDelta(0, 1):
return SingularityFunction(0, 0, -2)
free = self.free_symbols
if len(free) == 1:
x = (free.pop())
if len(args) == 1:
return SingularityFunction(x, solve(args[0], x)[0], -1)
return SingularityFunction(x, solve(args[0], x)[0], -args[1] - 1)
else:
# I don't know how to handle the case for DiracDelta expressions
# having arguments with more than one variable.
raise TypeError(filldedent('''
rewrite(SingularityFunction) doesn't support
arguments with more that 1 variable.'''))
###############################################################################
############################## HEAVISIDE FUNCTION #############################
###############################################################################
class Heaviside(Function):
r"""
Heaviside step function.
Explanation
===========
The Heaviside step function has the following properties:
1) $\frac{d}{d x} \theta(x) = \delta(x)$
2) $\theta(x) = \begin{cases} 0 & \text{for}\: x < 0 \\ \frac{1}{2} &
\text{for}\: x = 0 \\1 & \text{for}\: x > 0 \end{cases}$
3) $\frac{d}{d x} \max(x, 0) = \theta(x)$
Heaviside(x) is printed as $\theta(x)$ with the SymPy LaTeX printer.
The value at 0 is set differently in different fields. SymPy uses 1/2,
which is a convention from electronics and signal processing, and is
consistent with solving improper integrals by Fourier transform and
convolution.
To specify a different value of Heaviside at ``x=0``, a second argument
can be given. Using ``Heaviside(x, nan)`` gives an expression that will
evaluate to nan for x=0.
.. versionchanged:: 1.9 ``Heaviside(0)`` now returns 1/2 (before: undefined)
Examples
========
>>> from sympy import Heaviside, nan
>>> from sympy.abc import x
>>> Heaviside(9)
1
>>> Heaviside(-9)
0
>>> Heaviside(0)
1/2
>>> Heaviside(0, nan)
nan
>>> (Heaviside(x) + 1).replace(Heaviside(x), Heaviside(x, 1))
Heaviside(x, 1) + 1
See Also
========
DiracDelta
References
==========
.. [1] http://mathworld.wolfram.com/HeavisideStepFunction.html
.. [2] http://dlmf.nist.gov/1.16#iv
"""
is_real = True
def fdiff(self, argindex=1):
"""
Returns the first derivative of a Heaviside Function.
Examples
========
>>> from sympy import Heaviside, diff
>>> from sympy.abc import x
>>> Heaviside(x).fdiff()
DiracDelta(x)
>>> Heaviside(x**2 - 1).fdiff()
DiracDelta(x**2 - 1)
>>> diff(Heaviside(x)).fdiff()
DiracDelta(x, 1)
Parameters
==========
argindex : integer
order of derivative
"""
if argindex == 1:
return DiracDelta(self.args[0])
else:
raise ArgumentIndexError(self, argindex)
def __new__(cls, arg, H0=S.Half, **options):
if isinstance(H0, Heaviside) and len(H0.args) == 1:
H0 = S.Half
return super(cls, cls).__new__(cls, arg, H0, **options)
@property
def pargs(self):
"""Args without default S.Half"""
args = self.args
if args[1] is S.Half:
args = args[:1]
return args
@classmethod
def eval(cls, arg, H0=S.Half):
"""
Returns a simplified form or a value of Heaviside depending on the
argument passed by the Heaviside object.
Explanation
===========
The ``eval()`` method is automatically called when the ``Heaviside``
class is about to be instantiated and it returns either some simplified
instance or the unevaluated instance depending on the argument passed.
In other words, ``eval()`` method is not needed to be called explicitly,
it is being called and evaluated once the object is called.
Examples
========
>>> from sympy import Heaviside, S
>>> from sympy.abc import x
>>> Heaviside(x)
Heaviside(x)
>>> Heaviside(19)
1
>>> Heaviside(0)
1/2
>>> Heaviside(0, 1)
1
>>> Heaviside(-5)
0
>>> Heaviside(S.NaN)
nan
>>> Heaviside(x).eval(42)
1
>>> Heaviside(x - 100).subs(x, 5)
0
>>> Heaviside(x - 100).subs(x, 105)
1
Parameters
==========
arg : argument passed by Heaviside object
H0 : value of Heaviside(0)
"""
H0 = sympify(H0)
arg = sympify(arg)
if arg.is_extended_negative:
return S.Zero
elif arg.is_extended_positive:
return S.One
elif arg.is_zero:
return H0
elif arg is S.NaN:
return S.NaN
elif fuzzy_not(im(arg).is_zero):
raise ValueError("Function defined only for Real Values. Complex part: %s found in %s ." % (repr(im(arg)), repr(arg)) )
def _eval_rewrite_as_Piecewise(self, arg, H0=None, **kwargs):
"""
Represents Heaviside in a Piecewise form.
Examples
========
>>> from sympy import Heaviside, Piecewise, Symbol, nan
>>> x = Symbol('x')
>>> Heaviside(x).rewrite(Piecewise)
Piecewise((0, x < 0), (1/2, Eq(x, 0)), (1, x > 0))
>>> Heaviside(x,nan).rewrite(Piecewise)
Piecewise((0, x < 0), (nan, Eq(x, 0)), (1, x > 0))
>>> Heaviside(x - 5).rewrite(Piecewise)
Piecewise((0, x < 5), (1/2, Eq(x, 5)), (1, x > 5))
>>> Heaviside(x**2 - 1).rewrite(Piecewise)
Piecewise((0, x**2 < 1), (1/2, Eq(x**2, 1)), (1, x**2 > 1))
"""
if H0 == 0:
return Piecewise((0, arg <= 0), (1, arg > 0))
if H0 == 1:
return Piecewise((0, arg < 0), (1, arg >= 0))
return Piecewise((0, arg < 0), (H0, Eq(arg, 0)), (1, arg > 0))
def _eval_rewrite_as_sign(self, arg, H0=S.Half, **kwargs):
"""
Represents the Heaviside function in the form of sign function.
Explanation
===========
The value of Heaviside(0) must be 1/2 for rewritting as sign to be
strictly equivalent. For easier usage, we also allow this rewriting
when Heaviside(0) is undefined.
Examples
========
>>> from sympy import Heaviside, Symbol, sign, nan
>>> x = Symbol('x', real=True)
>>> y = Symbol('y')
>>> Heaviside(x).rewrite(sign)
sign(x)/2 + 1/2
>>> Heaviside(x, 0).rewrite(sign)
Piecewise((sign(x)/2 + 1/2, Ne(x, 0)), (0, True))
>>> Heaviside(x, nan).rewrite(sign)
Piecewise((sign(x)/2 + 1/2, Ne(x, 0)), (nan, True))
>>> Heaviside(x - 2).rewrite(sign)
sign(x - 2)/2 + 1/2
>>> Heaviside(x**2 - 2*x + 1).rewrite(sign)
sign(x**2 - 2*x + 1)/2 + 1/2
>>> Heaviside(y).rewrite(sign)
Heaviside(y)
>>> Heaviside(y**2 - 2*y + 1).rewrite(sign)
Heaviside(y**2 - 2*y + 1)
See Also
========
sign
"""
if arg.is_extended_real:
pw1 = Piecewise(
((sign(arg) + 1)/2, Ne(arg, 0)),
(Heaviside(0, H0=H0), True))
pw2 = Piecewise(
((sign(arg) + 1)/2, Eq(Heaviside(0, H0=H0), S.Half)),
(pw1, True))
return pw2
def _eval_rewrite_as_SingularityFunction(self, args, H0=S.Half, **kwargs):
"""
Returns the Heaviside expression written in the form of Singularity
Functions.
"""
from sympy.solvers import solve
from sympy.functions import SingularityFunction
if self == Heaviside(0):
return SingularityFunction(0, 0, 0)
free = self.free_symbols
if len(free) == 1:
x = (free.pop())
return SingularityFunction(x, solve(args, x)[0], 0)
# TODO
# ((x - 5)**3*Heaviside(x - 5)).rewrite(SingularityFunction) should output
# SingularityFunction(x, 5, 0) instead of (x - 5)**3*SingularityFunction(x, 5, 0)
else:
# I don't know how to handle the case for Heaviside expressions
# having arguments with more than one variable.
raise TypeError(filldedent('''
rewrite(SingularityFunction) doesn't
support arguments with more that 1 variable.'''))
|
d3dd9cb2699e1067b9e944302315d1b9b122d7b25f18f6b649c6ec41d000568f | from sympy.core.expr import Expr
from sympy.core.function import Function, ArgumentIndexError
from sympy.core.numbers import I, pi
from sympy.core.singleton import S
from sympy.core.symbol import Dummy
from sympy.core.sympify import sympify
from sympy.functions import assoc_legendre
from sympy.functions.combinatorial.factorials import factorial
from sympy.functions.elementary.complexes import Abs
from sympy.functions.elementary.exponential import exp
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.functions.elementary.trigonometric import sin, cos, cot
_x = Dummy("x")
class Ynm(Function):
r"""
Spherical harmonics defined as
.. math::
Y_n^m(\theta, \varphi) := \sqrt{\frac{(2n+1)(n-m)!}{4\pi(n+m)!}}
\exp(i m \varphi)
\mathrm{P}_n^m\left(\cos(\theta)\right)
Explanation
===========
``Ynm()`` gives the spherical harmonic function of order $n$ and $m$
in $\theta$ and $\varphi$, $Y_n^m(\theta, \varphi)$. The four
parameters are as follows: $n \geq 0$ an integer and $m$ an integer
such that $-n \leq m \leq n$ holds. The two angles are real-valued
with $\theta \in [0, \pi]$ and $\varphi \in [0, 2\pi]$.
Examples
========
>>> from sympy import Ynm, Symbol, simplify
>>> from sympy.abc import n,m
>>> theta = Symbol("theta")
>>> phi = Symbol("phi")
>>> Ynm(n, m, theta, phi)
Ynm(n, m, theta, phi)
Several symmetries are known, for the order:
>>> Ynm(n, -m, theta, phi)
(-1)**m*exp(-2*I*m*phi)*Ynm(n, m, theta, phi)
As well as for the angles:
>>> Ynm(n, m, -theta, phi)
Ynm(n, m, theta, phi)
>>> Ynm(n, m, theta, -phi)
exp(-2*I*m*phi)*Ynm(n, m, theta, phi)
For specific integers $n$ and $m$ we can evaluate the harmonics
to more useful expressions:
>>> simplify(Ynm(0, 0, theta, phi).expand(func=True))
1/(2*sqrt(pi))
>>> simplify(Ynm(1, -1, theta, phi).expand(func=True))
sqrt(6)*exp(-I*phi)*sin(theta)/(4*sqrt(pi))
>>> simplify(Ynm(1, 0, theta, phi).expand(func=True))
sqrt(3)*cos(theta)/(2*sqrt(pi))
>>> simplify(Ynm(1, 1, theta, phi).expand(func=True))
-sqrt(6)*exp(I*phi)*sin(theta)/(4*sqrt(pi))
>>> simplify(Ynm(2, -2, theta, phi).expand(func=True))
sqrt(30)*exp(-2*I*phi)*sin(theta)**2/(8*sqrt(pi))
>>> simplify(Ynm(2, -1, theta, phi).expand(func=True))
sqrt(30)*exp(-I*phi)*sin(2*theta)/(8*sqrt(pi))
>>> simplify(Ynm(2, 0, theta, phi).expand(func=True))
sqrt(5)*(3*cos(theta)**2 - 1)/(4*sqrt(pi))
>>> simplify(Ynm(2, 1, theta, phi).expand(func=True))
-sqrt(30)*exp(I*phi)*sin(2*theta)/(8*sqrt(pi))
>>> simplify(Ynm(2, 2, theta, phi).expand(func=True))
sqrt(30)*exp(2*I*phi)*sin(theta)**2/(8*sqrt(pi))
We can differentiate the functions with respect
to both angles:
>>> from sympy import Ynm, Symbol, diff
>>> from sympy.abc import n,m
>>> theta = Symbol("theta")
>>> phi = Symbol("phi")
>>> diff(Ynm(n, m, theta, phi), theta)
m*cot(theta)*Ynm(n, m, theta, phi) + sqrt((-m + n)*(m + n + 1))*exp(-I*phi)*Ynm(n, m + 1, theta, phi)
>>> diff(Ynm(n, m, theta, phi), phi)
I*m*Ynm(n, m, theta, phi)
Further we can compute the complex conjugation:
>>> from sympy import Ynm, Symbol, conjugate
>>> from sympy.abc import n,m
>>> theta = Symbol("theta")
>>> phi = Symbol("phi")
>>> conjugate(Ynm(n, m, theta, phi))
(-1)**(2*m)*exp(-2*I*m*phi)*Ynm(n, m, theta, phi)
To get back the well known expressions in spherical
coordinates, we use full expansion:
>>> from sympy import Ynm, Symbol, expand_func
>>> from sympy.abc import n,m
>>> theta = Symbol("theta")
>>> phi = Symbol("phi")
>>> expand_func(Ynm(n, m, theta, phi))
sqrt((2*n + 1)*factorial(-m + n)/factorial(m + n))*exp(I*m*phi)*assoc_legendre(n, m, cos(theta))/(2*sqrt(pi))
See Also
========
Ynm_c, Znm
References
==========
.. [1] https://en.wikipedia.org/wiki/Spherical_harmonics
.. [2] http://mathworld.wolfram.com/SphericalHarmonic.html
.. [3] http://functions.wolfram.com/Polynomials/SphericalHarmonicY/
.. [4] http://dlmf.nist.gov/14.30
"""
@classmethod
def eval(cls, n, m, theta, phi):
n, m, theta, phi = [sympify(x) for x in (n, m, theta, phi)]
# Handle negative index m and arguments theta, phi
if m.could_extract_minus_sign():
m = -m
return S.NegativeOne**m * exp(-2*I*m*phi) * Ynm(n, m, theta, phi)
if theta.could_extract_minus_sign():
theta = -theta
return Ynm(n, m, theta, phi)
if phi.could_extract_minus_sign():
phi = -phi
return exp(-2*I*m*phi) * Ynm(n, m, theta, phi)
# TODO Add more simplififcation here
def _eval_expand_func(self, **hints):
n, m, theta, phi = self.args
rv = (sqrt((2*n + 1)/(4*pi) * factorial(n - m)/factorial(n + m)) *
exp(I*m*phi) * assoc_legendre(n, m, cos(theta)))
# We can do this because of the range of theta
return rv.subs(sqrt(-cos(theta)**2 + 1), sin(theta))
def fdiff(self, argindex=4):
if argindex == 1:
# Diff wrt n
raise ArgumentIndexError(self, argindex)
elif argindex == 2:
# Diff wrt m
raise ArgumentIndexError(self, argindex)
elif argindex == 3:
# Diff wrt theta
n, m, theta, phi = self.args
return (m * cot(theta) * Ynm(n, m, theta, phi) +
sqrt((n - m)*(n + m + 1)) * exp(-I*phi) * Ynm(n, m + 1, theta, phi))
elif argindex == 4:
# Diff wrt phi
n, m, theta, phi = self.args
return I * m * Ynm(n, m, theta, phi)
else:
raise ArgumentIndexError(self, argindex)
def _eval_rewrite_as_polynomial(self, n, m, theta, phi, **kwargs):
# TODO: Make sure n \in N
# TODO: Assert |m| <= n ortherwise we should return 0
return self.expand(func=True)
def _eval_rewrite_as_sin(self, n, m, theta, phi, **kwargs):
return self.rewrite(cos)
def _eval_rewrite_as_cos(self, n, m, theta, phi, **kwargs):
# This method can be expensive due to extensive use of simplification!
from sympy.simplify import simplify, trigsimp
# TODO: Make sure n \in N
# TODO: Assert |m| <= n ortherwise we should return 0
term = simplify(self.expand(func=True))
# We can do this because of the range of theta
term = term.xreplace({Abs(sin(theta)):sin(theta)})
return simplify(trigsimp(term))
def _eval_conjugate(self):
# TODO: Make sure theta \in R and phi \in R
n, m, theta, phi = self.args
return S.NegativeOne**m * self.func(n, -m, theta, phi)
def as_real_imag(self, deep=True, **hints):
# TODO: Handle deep and hints
n, m, theta, phi = self.args
re = (sqrt((2*n + 1)/(4*pi) * factorial(n - m)/factorial(n + m)) *
cos(m*phi) * assoc_legendre(n, m, cos(theta)))
im = (sqrt((2*n + 1)/(4*pi) * factorial(n - m)/factorial(n + m)) *
sin(m*phi) * assoc_legendre(n, m, cos(theta)))
return (re, im)
def _eval_evalf(self, prec):
# Note: works without this function by just calling
# mpmath for Legendre polynomials. But using
# the dedicated function directly is cleaner.
from mpmath import mp, workprec
n = self.args[0]._to_mpmath(prec)
m = self.args[1]._to_mpmath(prec)
theta = self.args[2]._to_mpmath(prec)
phi = self.args[3]._to_mpmath(prec)
with workprec(prec):
res = mp.spherharm(n, m, theta, phi)
return Expr._from_mpmath(res, prec)
def Ynm_c(n, m, theta, phi):
r"""
Conjugate spherical harmonics defined as
.. math::
\overline{Y_n^m(\theta, \varphi)} := (-1)^m Y_n^{-m}(\theta, \varphi).
Examples
========
>>> from sympy import Ynm_c, Symbol, simplify
>>> from sympy.abc import n,m
>>> theta = Symbol("theta")
>>> phi = Symbol("phi")
>>> Ynm_c(n, m, theta, phi)
(-1)**(2*m)*exp(-2*I*m*phi)*Ynm(n, m, theta, phi)
>>> Ynm_c(n, m, -theta, phi)
(-1)**(2*m)*exp(-2*I*m*phi)*Ynm(n, m, theta, phi)
For specific integers $n$ and $m$ we can evaluate the harmonics
to more useful expressions:
>>> simplify(Ynm_c(0, 0, theta, phi).expand(func=True))
1/(2*sqrt(pi))
>>> simplify(Ynm_c(1, -1, theta, phi).expand(func=True))
sqrt(6)*exp(I*(-phi + 2*conjugate(phi)))*sin(theta)/(4*sqrt(pi))
See Also
========
Ynm, Znm
References
==========
.. [1] https://en.wikipedia.org/wiki/Spherical_harmonics
.. [2] http://mathworld.wolfram.com/SphericalHarmonic.html
.. [3] http://functions.wolfram.com/Polynomials/SphericalHarmonicY/
"""
from sympy.functions.elementary.complexes import conjugate
return conjugate(Ynm(n, m, theta, phi))
class Znm(Function):
r"""
Real spherical harmonics defined as
.. math::
Z_n^m(\theta, \varphi) :=
\begin{cases}
\frac{Y_n^m(\theta, \varphi) + \overline{Y_n^m(\theta, \varphi)}}{\sqrt{2}} &\quad m > 0 \\
Y_n^m(\theta, \varphi) &\quad m = 0 \\
\frac{Y_n^m(\theta, \varphi) - \overline{Y_n^m(\theta, \varphi)}}{i \sqrt{2}} &\quad m < 0 \\
\end{cases}
which gives in simplified form
.. math::
Z_n^m(\theta, \varphi) =
\begin{cases}
\frac{Y_n^m(\theta, \varphi) + (-1)^m Y_n^{-m}(\theta, \varphi)}{\sqrt{2}} &\quad m > 0 \\
Y_n^m(\theta, \varphi) &\quad m = 0 \\
\frac{Y_n^m(\theta, \varphi) - (-1)^m Y_n^{-m}(\theta, \varphi)}{i \sqrt{2}} &\quad m < 0 \\
\end{cases}
Examples
========
>>> from sympy import Znm, Symbol, simplify
>>> from sympy.abc import n, m
>>> theta = Symbol("theta")
>>> phi = Symbol("phi")
>>> Znm(n, m, theta, phi)
Znm(n, m, theta, phi)
For specific integers n and m we can evaluate the harmonics
to more useful expressions:
>>> simplify(Znm(0, 0, theta, phi).expand(func=True))
1/(2*sqrt(pi))
>>> simplify(Znm(1, 1, theta, phi).expand(func=True))
-sqrt(3)*sin(theta)*cos(phi)/(2*sqrt(pi))
>>> simplify(Znm(2, 1, theta, phi).expand(func=True))
-sqrt(15)*sin(2*theta)*cos(phi)/(4*sqrt(pi))
See Also
========
Ynm, Ynm_c
References
==========
.. [1] https://en.wikipedia.org/wiki/Spherical_harmonics
.. [2] http://mathworld.wolfram.com/SphericalHarmonic.html
.. [3] http://functions.wolfram.com/Polynomials/SphericalHarmonicY/
"""
@classmethod
def eval(cls, n, m, theta, phi):
n, m, th, ph = [sympify(x) for x in (n, m, theta, phi)]
if m.is_positive:
zz = (Ynm(n, m, th, ph) + Ynm_c(n, m, th, ph)) / sqrt(2)
return zz
elif m.is_zero:
return Ynm(n, m, th, ph)
elif m.is_negative:
zz = (Ynm(n, m, th, ph) - Ynm_c(n, m, th, ph)) / (sqrt(2)*I)
return zz
|
475c3d7ebc5008ff3f09d2cd7bbf53e044a48a8bfb0e57f33d7c4a6afd9351e9 | from sympy.core import S, sympify
from sympy.core.symbol import (Dummy, symbols)
from sympy.functions import Piecewise, piecewise_fold
from sympy.sets.sets import Interval
from functools import lru_cache
def _ivl(cond, x):
"""return the interval corresponding to the condition
Conditions in spline's Piecewise give the range over
which an expression is valid like (lo <= x) & (x <= hi).
This function returns (lo, hi).
"""
from sympy.logic.boolalg import And
if isinstance(cond, And) and len(cond.args) == 2:
a, b = cond.args
if a.lts == x:
a, b = b, a
return a.lts, b.gts
raise TypeError('unexpected cond type: %s' % cond)
def _add_splines(c, b1, d, b2, x):
"""Construct c*b1 + d*b2."""
if S.Zero in (b1, c):
rv = piecewise_fold(d * b2)
elif S.Zero in (b2, d):
rv = piecewise_fold(c * b1)
else:
new_args = []
# Just combining the Piecewise without any fancy optimization
p1 = piecewise_fold(c * b1)
p2 = piecewise_fold(d * b2)
# Search all Piecewise arguments except (0, True)
p2args = list(p2.args[:-1])
# This merging algorithm assumes the conditions in
# p1 and p2 are sorted
for arg in p1.args[:-1]:
expr = arg.expr
cond = arg.cond
lower = _ivl(cond, x)[0]
# Check p2 for matching conditions that can be merged
for i, arg2 in enumerate(p2args):
expr2 = arg2.expr
cond2 = arg2.cond
lower_2, upper_2 = _ivl(cond2, x)
if cond2 == cond:
# Conditions match, join expressions
expr += expr2
# Remove matching element
del p2args[i]
# No need to check the rest
break
elif lower_2 < lower and upper_2 <= lower:
# Check if arg2 condition smaller than arg1,
# add to new_args by itself (no match expected
# in p1)
new_args.append(arg2)
del p2args[i]
break
# Checked all, add expr and cond
new_args.append((expr, cond))
# Add remaining items from p2args
new_args.extend(p2args)
# Add final (0, True)
new_args.append((0, True))
rv = Piecewise(*new_args, evaluate=False)
return rv.expand()
@lru_cache(maxsize=128)
def bspline_basis(d, knots, n, x):
"""
The $n$-th B-spline at $x$ of degree $d$ with knots.
Explanation
===========
B-Splines are piecewise polynomials of degree $d$. They are defined on a
set of knots, which is a sequence of integers or floats.
Examples
========
The 0th degree splines have a value of 1 on a single interval:
>>> from sympy import bspline_basis
>>> from sympy.abc import x
>>> d = 0
>>> knots = tuple(range(5))
>>> bspline_basis(d, knots, 0, x)
Piecewise((1, (x >= 0) & (x <= 1)), (0, True))
For a given ``(d, knots)`` there are ``len(knots)-d-1`` B-splines
defined, that are indexed by ``n`` (starting at 0).
Here is an example of a cubic B-spline:
>>> bspline_basis(3, tuple(range(5)), 0, x)
Piecewise((x**3/6, (x >= 0) & (x <= 1)),
(-x**3/2 + 2*x**2 - 2*x + 2/3,
(x >= 1) & (x <= 2)),
(x**3/2 - 4*x**2 + 10*x - 22/3,
(x >= 2) & (x <= 3)),
(-x**3/6 + 2*x**2 - 8*x + 32/3,
(x >= 3) & (x <= 4)),
(0, True))
By repeating knot points, you can introduce discontinuities in the
B-splines and their derivatives:
>>> d = 1
>>> knots = (0, 0, 2, 3, 4)
>>> bspline_basis(d, knots, 0, x)
Piecewise((1 - x/2, (x >= 0) & (x <= 2)), (0, True))
It is quite time consuming to construct and evaluate B-splines. If
you need to evaluate a B-spline many times, it is best to lambdify them
first:
>>> from sympy import lambdify
>>> d = 3
>>> knots = tuple(range(10))
>>> b0 = bspline_basis(d, knots, 0, x)
>>> f = lambdify(x, b0)
>>> y = f(0.5)
Parameters
==========
d : integer
degree of bspline
knots : list of integer values
list of knots points of bspline
n : integer
$n$-th B-spline
x : symbol
See Also
========
bspline_basis_set
References
==========
.. [1] https://en.wikipedia.org/wiki/B-spline
"""
# make sure x has no assumptions so conditions don't evaluate
xvar = x
x = Dummy()
knots = tuple(sympify(k) for k in knots)
d = int(d)
n = int(n)
n_knots = len(knots)
n_intervals = n_knots - 1
if n + d + 1 > n_intervals:
raise ValueError("n + d + 1 must not exceed len(knots) - 1")
if d == 0:
result = Piecewise(
(S.One, Interval(knots[n], knots[n + 1]).contains(x)), (0, True)
)
elif d > 0:
denom = knots[n + d + 1] - knots[n + 1]
if denom != S.Zero:
B = (knots[n + d + 1] - x) / denom
b2 = bspline_basis(d - 1, knots, n + 1, x)
else:
b2 = B = S.Zero
denom = knots[n + d] - knots[n]
if denom != S.Zero:
A = (x - knots[n]) / denom
b1 = bspline_basis(d - 1, knots, n, x)
else:
b1 = A = S.Zero
result = _add_splines(A, b1, B, b2, x)
else:
raise ValueError("degree must be non-negative: %r" % n)
# return result with user-given x
return result.xreplace({x: xvar})
def bspline_basis_set(d, knots, x):
"""
Return the ``len(knots)-d-1`` B-splines at *x* of degree *d*
with *knots*.
Explanation
===========
This function returns a list of piecewise polynomials that are the
``len(knots)-d-1`` B-splines of degree *d* for the given knots.
This function calls ``bspline_basis(d, knots, n, x)`` for different
values of *n*.
Examples
========
>>> from sympy import bspline_basis_set
>>> from sympy.abc import x
>>> d = 2
>>> knots = range(5)
>>> splines = bspline_basis_set(d, knots, x)
>>> splines
[Piecewise((x**2/2, (x >= 0) & (x <= 1)),
(-x**2 + 3*x - 3/2, (x >= 1) & (x <= 2)),
(x**2/2 - 3*x + 9/2, (x >= 2) & (x <= 3)),
(0, True)),
Piecewise((x**2/2 - x + 1/2, (x >= 1) & (x <= 2)),
(-x**2 + 5*x - 11/2, (x >= 2) & (x <= 3)),
(x**2/2 - 4*x + 8, (x >= 3) & (x <= 4)),
(0, True))]
Parameters
==========
d : integer
degree of bspline
knots : list of integers
list of knots points of bspline
x : symbol
See Also
========
bspline_basis
"""
n_splines = len(knots) - d - 1
return [bspline_basis(d, tuple(knots), i, x) for i in range(n_splines)]
def interpolating_spline(d, x, X, Y):
"""
Return spline of degree *d*, passing through the given *X*
and *Y* values.
Explanation
===========
This function returns a piecewise function such that each part is
a polynomial of degree not greater than *d*. The value of *d*
must be 1 or greater and the values of *X* must be strictly
increasing.
Examples
========
>>> from sympy import interpolating_spline
>>> from sympy.abc import x
>>> interpolating_spline(1, x, [1, 2, 4, 7], [3, 6, 5, 7])
Piecewise((3*x, (x >= 1) & (x <= 2)),
(7 - x/2, (x >= 2) & (x <= 4)),
(2*x/3 + 7/3, (x >= 4) & (x <= 7)))
>>> interpolating_spline(3, x, [-2, 0, 1, 3, 4], [4, 2, 1, 1, 3])
Piecewise((7*x**3/117 + 7*x**2/117 - 131*x/117 + 2, (x >= -2) & (x <= 1)),
(10*x**3/117 - 2*x**2/117 - 122*x/117 + 77/39, (x >= 1) & (x <= 4)))
Parameters
==========
d : integer
Degree of Bspline strictly greater than equal to one
x : symbol
X : list of strictly increasing integer values
list of X coordinates through which the spline passes
Y : list of strictly increasing integer values
list of Y coordinates through which the spline passes
See Also
========
bspline_basis_set, interpolating_poly
"""
from sympy.solvers.solveset import linsolve
from sympy.matrices.dense import Matrix
# Input sanitization
d = sympify(d)
if not (d.is_Integer and d.is_positive):
raise ValueError("Spline degree must be a positive integer, not %s." % d)
if len(X) != len(Y):
raise ValueError("Number of X and Y coordinates must be the same.")
if len(X) < d + 1:
raise ValueError("Degree must be less than the number of control points.")
if not all(a < b for a, b in zip(X, X[1:])):
raise ValueError("The x-coordinates must be strictly increasing.")
X = [sympify(i) for i in X]
# Evaluating knots value
if d.is_odd:
j = (d + 1) // 2
interior_knots = X[j:-j]
else:
j = d // 2
interior_knots = [
(a + b)/2 for a, b in zip(X[j : -j - 1], X[j + 1 : -j])
]
knots = [X[0]] * (d + 1) + list(interior_knots) + [X[-1]] * (d + 1)
basis = bspline_basis_set(d, knots, x)
A = [[b.subs(x, v) for b in basis] for v in X]
coeff = linsolve((Matrix(A), Matrix(Y)), symbols("c0:{}".format(len(X)), cls=Dummy))
coeff = list(coeff)[0]
intervals = {c for b in basis for (e, c) in b.args if c != True}
# Sorting the intervals
# ival contains the end-points of each interval
ival = [_ivl(c, x) for c in intervals]
com = zip(ival, intervals)
com = sorted(com, key=lambda x: x[0])
intervals = [y for x, y in com]
basis_dicts = [{c: e for (e, c) in b.args} for b in basis]
spline = []
for i in intervals:
piece = sum(
[c * d.get(i, S.Zero) for (c, d) in zip(coeff, basis_dicts)], S.Zero
)
spline.append((piece, i))
return Piecewise(*spline)
|
88b579d92885537b776d7b2af91cb5ddce882006bc31f3c2e111ba0d4f7f9eda | """ Riemann zeta and related function. """
from sympy.core.add import Add
from sympy.core import Function, S, sympify, pi, I
from sympy.core.function import ArgumentIndexError, expand_mul
from sympy.core.symbol import Dummy
from sympy.functions.combinatorial.numbers import bernoulli, factorial, harmonic
from sympy.functions.elementary.complexes import re, unpolarify, Abs, polar_lift
from sympy.functions.elementary.exponential import log, exp_polar, exp
from sympy.functions.elementary.integers import floor
from sympy.functions.elementary.miscellaneous import sqrt
###############################################################################
###################### LERCH TRANSCENDENT #####################################
###############################################################################
class lerchphi(Function):
r"""
Lerch transcendent (Lerch phi function).
Explanation
===========
For $\operatorname{Re}(a) > 0$, $|z| < 1$ and $s \in \mathbb{C}$, the
Lerch transcendent is defined as
.. math :: \Phi(z, s, a) = \sum_{n=0}^\infty \frac{z^n}{(n + a)^s},
where the standard branch of the argument is used for $n + a$,
and by analytic continuation for other values of the parameters.
A commonly used related function is the Lerch zeta function, defined by
.. math:: L(q, s, a) = \Phi(e^{2\pi i q}, s, a).
**Analytic Continuation and Branching Behavior**
It can be shown that
.. math:: \Phi(z, s, a) = z\Phi(z, s, a+1) + a^{-s}.
This provides the analytic continuation to $\operatorname{Re}(a) \le 0$.
Assume now $\operatorname{Re}(a) > 0$. The integral representation
.. math:: \Phi_0(z, s, a) = \int_0^\infty \frac{t^{s-1} e^{-at}}{1 - ze^{-t}}
\frac{\mathrm{d}t}{\Gamma(s)}
provides an analytic continuation to $\mathbb{C} - [1, \infty)$.
Finally, for $x \in (1, \infty)$ we find
.. math:: \lim_{\epsilon \to 0^+} \Phi_0(x + i\epsilon, s, a)
-\lim_{\epsilon \to 0^+} \Phi_0(x - i\epsilon, s, a)
= \frac{2\pi i \log^{s-1}{x}}{x^a \Gamma(s)},
using the standard branch for both $\log{x}$ and
$\log{\log{x}}$ (a branch of $\log{\log{x}}$ is needed to
evaluate $\log{x}^{s-1}$).
This concludes the analytic continuation. The Lerch transcendent is thus
branched at $z \in \{0, 1, \infty\}$ and
$a \in \mathbb{Z}_{\le 0}$. For fixed $z, a$ outside these
branch points, it is an entire function of $s$.
Examples
========
The Lerch transcendent is a fairly general function, for this reason it does
not automatically evaluate to simpler functions. Use ``expand_func()`` to
achieve this.
If $z=1$, the Lerch transcendent reduces to the Hurwitz zeta function:
>>> from sympy import lerchphi, expand_func
>>> from sympy.abc import z, s, a
>>> expand_func(lerchphi(1, s, a))
zeta(s, a)
More generally, if $z$ is a root of unity, the Lerch transcendent
reduces to a sum of Hurwitz zeta functions:
>>> expand_func(lerchphi(-1, s, a))
zeta(s, a/2)/2**s - zeta(s, a/2 + 1/2)/2**s
If $a=1$, the Lerch transcendent reduces to the polylogarithm:
>>> expand_func(lerchphi(z, s, 1))
polylog(s, z)/z
More generally, if $a$ is rational, the Lerch transcendent reduces
to a sum of polylogarithms:
>>> from sympy import S
>>> expand_func(lerchphi(z, s, S(1)/2))
2**(s - 1)*(polylog(s, sqrt(z))/sqrt(z) -
polylog(s, sqrt(z)*exp_polar(I*pi))/sqrt(z))
>>> expand_func(lerchphi(z, s, S(3)/2))
-2**s/z + 2**(s - 1)*(polylog(s, sqrt(z))/sqrt(z) -
polylog(s, sqrt(z)*exp_polar(I*pi))/sqrt(z))/z
The derivatives with respect to $z$ and $a$ can be computed in
closed form:
>>> lerchphi(z, s, a).diff(z)
(-a*lerchphi(z, s, a) + lerchphi(z, s - 1, a))/z
>>> lerchphi(z, s, a).diff(a)
-s*lerchphi(z, s + 1, a)
See Also
========
polylog, zeta
References
==========
.. [1] Bateman, H.; Erdelyi, A. (1953), Higher Transcendental Functions,
Vol. I, New York: McGraw-Hill. Section 1.11.
.. [2] http://dlmf.nist.gov/25.14
.. [3] https://en.wikipedia.org/wiki/Lerch_transcendent
"""
def _eval_expand_func(self, **hints):
from sympy.polys.polytools import Poly
z, s, a = self.args
if z == 1:
return zeta(s, a)
if s.is_Integer and s <= 0:
t = Dummy('t')
p = Poly((t + a)**(-s), t)
start = 1/(1 - t)
res = S.Zero
for c in reversed(p.all_coeffs()):
res += c*start
start = t*start.diff(t)
return res.subs(t, z)
if a.is_Rational:
# See section 18 of
# Kelly B. Roach. Hypergeometric Function Representations.
# In: Proceedings of the 1997 International Symposium on Symbolic and
# Algebraic Computation, pages 205-211, New York, 1997. ACM.
# TODO should something be polarified here?
add = S.Zero
mul = S.One
# First reduce a to the interaval (0, 1]
if a > 1:
n = floor(a)
if n == a:
n -= 1
a -= n
mul = z**(-n)
add = Add(*[-z**(k - n)/(a + k)**s for k in range(n)])
elif a <= 0:
n = floor(-a) + 1
a += n
mul = z**n
add = Add(*[z**(n - 1 - k)/(a - k - 1)**s for k in range(n)])
m, n = S([a.p, a.q])
zet = exp_polar(2*pi*I/n)
root = z**(1/n)
return add + mul*n**(s - 1)*Add(
*[polylog(s, zet**k*root)._eval_expand_func(**hints)
/ (unpolarify(zet)**k*root)**m for k in range(n)])
# TODO use minpoly instead of ad-hoc methods when issue 5888 is fixed
if isinstance(z, exp) and (z.args[0]/(pi*I)).is_Rational or z in [-1, I, -I]:
# TODO reference?
if z == -1:
p, q = S([1, 2])
elif z == I:
p, q = S([1, 4])
elif z == -I:
p, q = S([-1, 4])
else:
arg = z.args[0]/(2*pi*I)
p, q = S([arg.p, arg.q])
return Add(*[exp(2*pi*I*k*p/q)/q**s*zeta(s, (k + a)/q)
for k in range(q)])
return lerchphi(z, s, a)
def fdiff(self, argindex=1):
z, s, a = self.args
if argindex == 3:
return -s*lerchphi(z, s + 1, a)
elif argindex == 1:
return (lerchphi(z, s - 1, a) - a*lerchphi(z, s, a))/z
else:
raise ArgumentIndexError
def _eval_rewrite_helper(self, z, s, a, target):
res = self._eval_expand_func()
if res.has(target):
return res
else:
return self
def _eval_rewrite_as_zeta(self, z, s, a, **kwargs):
return self._eval_rewrite_helper(z, s, a, zeta)
def _eval_rewrite_as_polylog(self, z, s, a, **kwargs):
return self._eval_rewrite_helper(z, s, a, polylog)
###############################################################################
###################### POLYLOGARITHM ##########################################
###############################################################################
class polylog(Function):
r"""
Polylogarithm function.
Explanation
===========
For $|z| < 1$ and $s \in \mathbb{C}$, the polylogarithm is
defined by
.. math:: \operatorname{Li}_s(z) = \sum_{n=1}^\infty \frac{z^n}{n^s},
where the standard branch of the argument is used for $n$. It admits
an analytic continuation which is branched at $z=1$ (notably not on the
sheet of initial definition), $z=0$ and $z=\infty$.
The name polylogarithm comes from the fact that for $s=1$, the
polylogarithm is related to the ordinary logarithm (see examples), and that
.. math:: \operatorname{Li}_{s+1}(z) =
\int_0^z \frac{\operatorname{Li}_s(t)}{t} \mathrm{d}t.
The polylogarithm is a special case of the Lerch transcendent:
.. math:: \operatorname{Li}_{s}(z) = z \Phi(z, s, 1).
Examples
========
For $z \in \{0, 1, -1\}$, the polylogarithm is automatically expressed
using other functions:
>>> from sympy import polylog
>>> from sympy.abc import s
>>> polylog(s, 0)
0
>>> polylog(s, 1)
zeta(s)
>>> polylog(s, -1)
-dirichlet_eta(s)
If $s$ is a negative integer, $0$ or $1$, the polylogarithm can be
expressed using elementary functions. This can be done using
``expand_func()``:
>>> from sympy import expand_func
>>> from sympy.abc import z
>>> expand_func(polylog(1, z))
-log(1 - z)
>>> expand_func(polylog(0, z))
z/(1 - z)
The derivative with respect to $z$ can be computed in closed form:
>>> polylog(s, z).diff(z)
polylog(s - 1, z)/z
The polylogarithm can be expressed in terms of the lerch transcendent:
>>> from sympy import lerchphi
>>> polylog(s, z).rewrite(lerchphi)
z*lerchphi(z, s, 1)
See Also
========
zeta, lerchphi
"""
@classmethod
def eval(cls, s, z):
s, z = sympify((s, z))
if z is S.One:
return zeta(s)
elif z is S.NegativeOne:
return -dirichlet_eta(s)
elif z is S.Zero:
return S.Zero
elif s == 2:
if z == S.Half:
return pi**2/12 - log(2)**2/2
elif z == 2:
return pi**2/4 - I*pi*log(2)
elif z == -(sqrt(5) - 1)/2:
return -pi**2/15 + log((sqrt(5)-1)/2)**2/2
elif z == -(sqrt(5) + 1)/2:
return -pi**2/10 - log((sqrt(5)+1)/2)**2
elif z == (3 - sqrt(5))/2:
return pi**2/15 - log((sqrt(5)-1)/2)**2
elif z == (sqrt(5) - 1)/2:
return pi**2/10 - log((sqrt(5)-1)/2)**2
if z.is_zero:
return S.Zero
# Make an effort to determine if z is 1 to avoid replacing into
# expression with singularity
zone = z.equals(S.One)
if zone:
return zeta(s)
elif zone is False:
# For s = 0 or -1 use explicit formulas to evaluate, but
# automatically expanding polylog(1, z) to -log(1-z) seems
# undesirable for summation methods based on hypergeometric
# functions
if s is S.Zero:
return z/(1 - z)
elif s is S.NegativeOne:
return z/(1 - z)**2
if s.is_zero:
return z/(1 - z)
# polylog is branched, but not over the unit disk
if z.has(exp_polar, polar_lift) and (zone or (Abs(z) <= S.One) == True):
return cls(s, unpolarify(z))
def fdiff(self, argindex=1):
s, z = self.args
if argindex == 2:
return polylog(s - 1, z)/z
raise ArgumentIndexError
def _eval_rewrite_as_lerchphi(self, s, z, **kwargs):
return z*lerchphi(z, s, 1)
def _eval_expand_func(self, **hints):
s, z = self.args
if s == 1:
return -log(1 - z)
if s.is_Integer and s <= 0:
u = Dummy('u')
start = u/(1 - u)
for _ in range(-s):
start = u*start.diff(u)
return expand_mul(start).subs(u, z)
return polylog(s, z)
def _eval_is_zero(self):
z = self.args[1]
if z.is_zero:
return True
def _eval_nseries(self, x, n, logx, cdir=0):
from sympy.functions.elementary.integers import ceiling
from sympy.series.order import Order
nu, z = self.args
z0 = z.subs(x, 0)
if z0 is S.NaN:
z0 = z.limit(x, 0, dir='-' if re(cdir).is_negative else '+')
if z0.is_zero:
# In case of powers less than 1, number of terms need to be computed
# separately to avoid repeated callings of _eval_nseries with wrong n
try:
_, exp = z.leadterm(x)
except (ValueError, NotImplementedError):
return self
if exp.is_positive:
newn = ceiling(n/exp)
o = Order(x**n, x)
r = z._eval_nseries(x, n, logx, cdir).removeO()
if r is S.Zero:
return o
term = r
s = [term]
for k in range(2, newn):
term *= r
s.append(term/k**nu)
return Add(*s) + o
return super(polylog, self)._eval_nseries(x, n, logx, cdir)
###############################################################################
###################### HURWITZ GENERALIZED ZETA FUNCTION ######################
###############################################################################
class zeta(Function):
r"""
Hurwitz zeta function (or Riemann zeta function).
Explanation
===========
For $\operatorname{Re}(a) > 0$ and $\operatorname{Re}(s) > 1$, this
function is defined as
.. math:: \zeta(s, a) = \sum_{n=0}^\infty \frac{1}{(n + a)^s},
where the standard choice of argument for $n + a$ is used. For fixed
$a$ with $\operatorname{Re}(a) > 0$ the Hurwitz zeta function admits a
meromorphic continuation to all of $\mathbb{C}$, it is an unbranched
function with a simple pole at $s = 1$.
Analytic continuation to other $a$ is possible under some circumstances,
but this is not typically done.
The Hurwitz zeta function is a special case of the Lerch transcendent:
.. math:: \zeta(s, a) = \Phi(1, s, a).
This formula defines an analytic continuation for all possible values of
$s$ and $a$ (also $\operatorname{Re}(a) < 0$), see the documentation of
:class:`lerchphi` for a description of the branching behavior.
If no value is passed for $a$, by this function assumes a default value
of $a = 1$, yielding the Riemann zeta function.
Examples
========
For $a = 1$ the Hurwitz zeta function reduces to the famous Riemann
zeta function:
.. math:: \zeta(s, 1) = \zeta(s) = \sum_{n=1}^\infty \frac{1}{n^s}.
>>> from sympy import zeta
>>> from sympy.abc import s
>>> zeta(s, 1)
zeta(s)
>>> zeta(s)
zeta(s)
The Riemann zeta function can also be expressed using the Dirichlet eta
function:
>>> from sympy import dirichlet_eta
>>> zeta(s).rewrite(dirichlet_eta)
dirichlet_eta(s)/(1 - 2**(1 - s))
The Riemann zeta function at positive even integer and negative odd integer
values is related to the Bernoulli numbers:
>>> zeta(2)
pi**2/6
>>> zeta(4)
pi**4/90
>>> zeta(-1)
-1/12
The specific formulae are:
.. math:: \zeta(2n) = (-1)^{n+1} \frac{B_{2n} (2\pi)^{2n}}{2(2n)!}
.. math:: \zeta(-n) = -\frac{B_{n+1}}{n+1}
At negative even integers the Riemann zeta function is zero:
>>> zeta(-4)
0
No closed-form expressions are known at positive odd integers, but
numerical evaluation is possible:
>>> zeta(3).n()
1.20205690315959
The derivative of $\zeta(s, a)$ with respect to $a$ can be computed:
>>> from sympy.abc import a
>>> zeta(s, a).diff(a)
-s*zeta(s + 1, a)
However the derivative with respect to $s$ has no useful closed form
expression:
>>> zeta(s, a).diff(s)
Derivative(zeta(s, a), s)
The Hurwitz zeta function can be expressed in terms of the Lerch
transcendent, :class:`~.lerchphi`:
>>> from sympy import lerchphi
>>> zeta(s, a).rewrite(lerchphi)
lerchphi(1, s, a)
See Also
========
dirichlet_eta, lerchphi, polylog
References
==========
.. [1] http://dlmf.nist.gov/25.11
.. [2] https://en.wikipedia.org/wiki/Hurwitz_zeta_function
"""
@classmethod
def eval(cls, z, a_=None):
if a_ is None:
z, a = list(map(sympify, (z, 1)))
else:
z, a = list(map(sympify, (z, a_)))
if a.is_Number:
if a is S.NaN:
return S.NaN
elif a is S.One and a_ is not None:
return cls(z)
# TODO Should a == 0 return S.NaN as well?
if z.is_Number:
if z is S.NaN:
return S.NaN
elif z is S.Infinity:
return S.One
elif z.is_zero:
return S.Half - a
elif z is S.One:
return S.ComplexInfinity
if z.is_integer:
if a.is_Integer:
if z.is_negative:
zeta = S.NegativeOne**z * bernoulli(-z + 1)/(-z + 1)
elif z.is_even and z.is_positive:
B, F = bernoulli(z), factorial(z)
zeta = (S.NegativeOne**(z/2+1) * 2**(z - 1) * B * pi**z) / F
else:
return
if a.is_negative:
return zeta + harmonic(abs(a), z)
else:
return zeta - harmonic(a - 1, z)
if z.is_zero:
return S.Half - a
def _eval_rewrite_as_dirichlet_eta(self, s, a=1, **kwargs):
if a != 1:
return self
s = self.args[0]
return dirichlet_eta(s)/(1 - 2**(1 - s))
def _eval_rewrite_as_lerchphi(self, s, a=1, **kwargs):
return lerchphi(1, s, a)
def _eval_is_finite(self):
arg_is_one = (self.args[0] - 1).is_zero
if arg_is_one is not None:
return not arg_is_one
def fdiff(self, argindex=1):
if len(self.args) == 2:
s, a = self.args
else:
s, a = self.args + (1,)
if argindex == 2:
return -s*zeta(s + 1, a)
else:
raise ArgumentIndexError
class dirichlet_eta(Function):
r"""
Dirichlet eta function.
Explanation
===========
For $\operatorname{Re}(s) > 0$, this function is defined as
.. math:: \eta(s) = \sum_{n=1}^\infty \frac{(-1)^{n-1}}{n^s}.
It admits a unique analytic continuation to all of $\mathbb{C}$.
It is an entire, unbranched function.
Examples
========
The Dirichlet eta function is closely related to the Riemann zeta function:
>>> from sympy import dirichlet_eta, zeta
>>> from sympy.abc import s
>>> dirichlet_eta(s).rewrite(zeta)
(1 - 2**(1 - s))*zeta(s)
See Also
========
zeta
References
==========
.. [1] https://en.wikipedia.org/wiki/Dirichlet_eta_function
"""
@classmethod
def eval(cls, s):
if s == 1:
return log(2)
z = zeta(s)
if not z.has(zeta):
return (1 - 2**(1 - s))*z
def _eval_rewrite_as_zeta(self, s, **kwargs):
return (1 - 2**(1 - s)) * zeta(s)
class riemann_xi(Function):
r"""
Riemann Xi function.
Examples
========
The Riemann Xi function is closely related to the Riemann zeta function.
The zeros of Riemann Xi function are precisely the non-trivial zeros
of the zeta function.
>>> from sympy import riemann_xi, zeta
>>> from sympy.abc import s
>>> riemann_xi(s).rewrite(zeta)
s*(s - 1)*gamma(s/2)*zeta(s)/(2*pi**(s/2))
References
==========
.. [1] https://en.wikipedia.org/wiki/Riemann_Xi_function
"""
@classmethod
def eval(cls, s):
from sympy.functions.special.gamma_functions import gamma
z = zeta(s)
if s in (S.Zero, S.One):
return S.Half
if not isinstance(z, zeta):
return s*(s - 1)*gamma(s/2)*z/(2*pi**(s/2))
def _eval_rewrite_as_zeta(self, s, **kwargs):
from sympy.functions.special.gamma_functions import gamma
return s*(s - 1)*gamma(s/2)*zeta(s)/(2*pi**(s/2))
class stieltjes(Function):
r"""
Represents Stieltjes constants, $\gamma_{k}$ that occur in
Laurent Series expansion of the Riemann zeta function.
Examples
========
>>> from sympy import stieltjes
>>> from sympy.abc import n, m
>>> stieltjes(n)
stieltjes(n)
The zero'th stieltjes constant:
>>> stieltjes(0)
EulerGamma
>>> stieltjes(0, 1)
EulerGamma
For generalized stieltjes constants:
>>> stieltjes(n, m)
stieltjes(n, m)
Constants are only defined for integers >= 0:
>>> stieltjes(-1)
zoo
References
==========
.. [1] https://en.wikipedia.org/wiki/Stieltjes_constants
"""
@classmethod
def eval(cls, n, a=None):
n = sympify(n)
if a is not None:
a = sympify(a)
if a is S.NaN:
return S.NaN
if a.is_Integer and a.is_nonpositive:
return S.ComplexInfinity
if n.is_Number:
if n is S.NaN:
return S.NaN
elif n < 0:
return S.ComplexInfinity
elif not n.is_Integer:
return S.ComplexInfinity
elif n is S.Zero and a in [None, 1]:
return S.EulerGamma
if n.is_extended_negative:
return S.ComplexInfinity
if n.is_zero and a in [None, 1]:
return S.EulerGamma
if n.is_integer == False:
return S.ComplexInfinity
|
4f1ace3cae9275d3af9eeec587139a90d912a2ba5e44a395c353b42196893f6a | from sympy.core import S, sympify, oo, diff
from sympy.core.function import Function, ArgumentIndexError
from sympy.core.logic import fuzzy_not
from sympy.core.relational import Eq
from sympy.functions.elementary.complexes import im
from sympy.functions.elementary.piecewise import Piecewise
from sympy.functions.special.delta_functions import Heaviside
###############################################################################
############################# SINGULARITY FUNCTION ############################
###############################################################################
class SingularityFunction(Function):
r"""
Singularity functions are a class of discontinuous functions.
Explanation
===========
Singularity functions take a variable, an offset, and an exponent as
arguments. These functions are represented using Macaulay brackets as:
SingularityFunction(x, a, n) := <x - a>^n
The singularity function will automatically evaluate to
``Derivative(DiracDelta(x - a), x, -n - 1)`` if ``n < 0``
and ``(x - a)**n*Heaviside(x - a)`` if ``n >= 0``.
Examples
========
>>> from sympy import SingularityFunction, diff, Piecewise, DiracDelta, Heaviside, Symbol
>>> from sympy.abc import x, a, n
>>> SingularityFunction(x, a, n)
SingularityFunction(x, a, n)
>>> y = Symbol('y', positive=True)
>>> n = Symbol('n', nonnegative=True)
>>> SingularityFunction(y, -10, n)
(y + 10)**n
>>> y = Symbol('y', negative=True)
>>> SingularityFunction(y, 10, n)
0
>>> SingularityFunction(x, 4, -1).subs(x, 4)
oo
>>> SingularityFunction(x, 10, -2).subs(x, 10)
oo
>>> SingularityFunction(4, 1, 5)
243
>>> diff(SingularityFunction(x, 1, 5) + SingularityFunction(x, 1, 4), x)
4*SingularityFunction(x, 1, 3) + 5*SingularityFunction(x, 1, 4)
>>> diff(SingularityFunction(x, 4, 0), x, 2)
SingularityFunction(x, 4, -2)
>>> SingularityFunction(x, 4, 5).rewrite(Piecewise)
Piecewise(((x - 4)**5, x > 4), (0, True))
>>> expr = SingularityFunction(x, a, n)
>>> y = Symbol('y', positive=True)
>>> n = Symbol('n', nonnegative=True)
>>> expr.subs({x: y, a: -10, n: n})
(y + 10)**n
The methods ``rewrite(DiracDelta)``, ``rewrite(Heaviside)``, and
``rewrite('HeavisideDiracDelta')`` returns the same output. One can use any
of these methods according to their choice.
>>> expr = SingularityFunction(x, 4, 5) + SingularityFunction(x, -3, -1) - SingularityFunction(x, 0, -2)
>>> expr.rewrite(Heaviside)
(x - 4)**5*Heaviside(x - 4) + DiracDelta(x + 3) - DiracDelta(x, 1)
>>> expr.rewrite(DiracDelta)
(x - 4)**5*Heaviside(x - 4) + DiracDelta(x + 3) - DiracDelta(x, 1)
>>> expr.rewrite('HeavisideDiracDelta')
(x - 4)**5*Heaviside(x - 4) + DiracDelta(x + 3) - DiracDelta(x, 1)
See Also
========
DiracDelta, Heaviside
References
==========
.. [1] https://en.wikipedia.org/wiki/Singularity_function
"""
is_real = True
def fdiff(self, argindex=1):
"""
Returns the first derivative of a DiracDelta Function.
Explanation
===========
The difference between ``diff()`` and ``fdiff()`` is: ``diff()`` is the
user-level function and ``fdiff()`` is an object method. ``fdiff()`` is
a convenience method available in the ``Function`` class. It returns
the derivative of the function without considering the chain rule.
``diff(function, x)`` calls ``Function._eval_derivative`` which in turn
calls ``fdiff()`` internally to compute the derivative of the function.
"""
if argindex == 1:
x = sympify(self.args[0])
a = sympify(self.args[1])
n = sympify(self.args[2])
if n in (S.Zero, S.NegativeOne):
return self.func(x, a, n-1)
elif n.is_positive:
return n*self.func(x, a, n-1)
else:
raise ArgumentIndexError(self, argindex)
@classmethod
def eval(cls, variable, offset, exponent):
"""
Returns a simplified form or a value of Singularity Function depending
on the argument passed by the object.
Explanation
===========
The ``eval()`` method is automatically called when the
``SingularityFunction`` class is about to be instantiated and it
returns either some simplified instance or the unevaluated instance
depending on the argument passed. In other words, ``eval()`` method is
not needed to be called explicitly, it is being called and evaluated
once the object is called.
Examples
========
>>> from sympy import SingularityFunction, Symbol, nan
>>> from sympy.abc import x, a, n
>>> SingularityFunction(x, a, n)
SingularityFunction(x, a, n)
>>> SingularityFunction(5, 3, 2)
4
>>> SingularityFunction(x, a, nan)
nan
>>> SingularityFunction(x, 3, 0).subs(x, 3)
1
>>> SingularityFunction(x, a, n).eval(3, 5, 1)
0
>>> SingularityFunction(x, a, n).eval(4, 1, 5)
243
>>> x = Symbol('x', positive = True)
>>> a = Symbol('a', negative = True)
>>> n = Symbol('n', nonnegative = True)
>>> SingularityFunction(x, a, n)
(-a + x)**n
>>> x = Symbol('x', negative = True)
>>> a = Symbol('a', positive = True)
>>> SingularityFunction(x, a, n)
0
"""
x = sympify(variable)
a = sympify(offset)
n = sympify(exponent)
shift = (x - a)
if fuzzy_not(im(shift).is_zero):
raise ValueError("Singularity Functions are defined only for Real Numbers.")
if fuzzy_not(im(n).is_zero):
raise ValueError("Singularity Functions are not defined for imaginary exponents.")
if shift is S.NaN or n is S.NaN:
return S.NaN
if (n + 2).is_negative:
raise ValueError("Singularity Functions are not defined for exponents less than -2.")
if shift.is_extended_negative:
return S.Zero
if n.is_nonnegative and shift.is_extended_nonnegative:
return (x - a)**n
if n in (S.NegativeOne, -2):
if shift.is_negative or shift.is_extended_positive:
return S.Zero
if shift.is_zero:
return S.Infinity
def _eval_rewrite_as_Piecewise(self, *args, **kwargs):
'''
Converts a Singularity Function expression into its Piecewise form.
'''
x = self.args[0]
a = self.args[1]
n = sympify(self.args[2])
if n in (S.NegativeOne, -2):
return Piecewise((oo, Eq((x - a), 0)), (0, True))
elif n.is_nonnegative:
return Piecewise(((x - a)**n, (x - a) > 0), (0, True))
def _eval_rewrite_as_Heaviside(self, *args, **kwargs):
'''
Rewrites a Singularity Function expression using Heavisides and DiracDeltas.
'''
x = self.args[0]
a = self.args[1]
n = sympify(self.args[2])
if n == -2:
return diff(Heaviside(x - a), x.free_symbols.pop(), 2)
if n == -1:
return diff(Heaviside(x - a), x.free_symbols.pop(), 1)
if n.is_nonnegative:
return (x - a)**n*Heaviside(x - a)
def _eval_as_leading_term(self, x, logx=None, cdir=0):
z, a, n = self.args
shift = (z - a).subs(x, 0)
if n < 0:
return S.Zero
elif n.is_zero and shift.is_zero:
return S.Zero if cdir == -1 else S.One
elif shift.is_positive:
return shift**n
return S.Zero
def _eval_nseries(self, x, n, logx=None, cdir=0):
z, a, n = self.args
shift = (z - a).subs(x, 0)
if n < 0:
return S.Zero
elif n.is_zero and shift.is_zero:
return S.Zero if cdir == -1 else S.One
elif shift.is_positive:
return ((z - a)**n)._eval_nseries(x, n, logx=logx, cdir=cdir)
return S.Zero
_eval_rewrite_as_DiracDelta = _eval_rewrite_as_Heaviside
_eval_rewrite_as_HeavisideDiracDelta = _eval_rewrite_as_Heaviside
|
db78655f3e4146d01f6f582bf0e7caed36fa884cc6077f2097195c3d419d43f2 | from functools import wraps
from sympy.core import S
from sympy.core.add import Add
from sympy.core.cache import cacheit
from sympy.core.expr import Expr
from sympy.core.function import Function, ArgumentIndexError, _mexpand
from sympy.core.logic import fuzzy_or, fuzzy_not
from sympy.core.numbers import Rational, pi, I
from sympy.core.power import Pow
from sympy.core.symbol import Dummy, Wild
from sympy.core.sympify import sympify
from sympy.functions.combinatorial.factorials import factorial
from sympy.functions.elementary.trigonometric import sin, cos, csc, cot
from sympy.functions.elementary.integers import ceiling
from sympy.functions.elementary.complexes import Abs
from sympy.functions.elementary.exponential import exp, log
from sympy.functions.elementary.miscellaneous import sqrt, root
from sympy.functions.elementary.complexes import re, im
from sympy.functions.special.gamma_functions import gamma, digamma, uppergamma
from sympy.functions.special.hyper import hyper
from sympy.polys.orthopolys import spherical_bessel_fn
from mpmath import mp, workprec
# TODO
# o Scorer functions G1 and G2
# o Asymptotic expansions
# These are possible, e.g. for fixed order, but since the bessel type
# functions are oscillatory they are not actually tractable at
# infinity, so this is not particularly useful right now.
# o Nicer series expansions.
# o More rewriting.
# o Add solvers to ode.py (or rather add solvers for the hypergeometric equation).
class BesselBase(Function):
"""
Abstract base class for Bessel-type functions.
This class is meant to reduce code duplication.
All Bessel-type functions can 1) be differentiated, with the derivatives
expressed in terms of similar functions, and 2) be rewritten in terms
of other Bessel-type functions.
Here, Bessel-type functions are assumed to have one complex parameter.
To use this base class, define class attributes ``_a`` and ``_b`` such that
``2*F_n' = -_a*F_{n+1} + b*F_{n-1}``.
"""
@property
def order(self):
""" The order of the Bessel-type function. """
return self.args[0]
@property
def argument(self):
""" The argument of the Bessel-type function. """
return self.args[1]
@classmethod
def eval(cls, nu, z):
return
def fdiff(self, argindex=2):
if argindex != 2:
raise ArgumentIndexError(self, argindex)
return (self._b/2 * self.__class__(self.order - 1, self.argument) -
self._a/2 * self.__class__(self.order + 1, self.argument))
def _eval_conjugate(self):
z = self.argument
if z.is_extended_negative is False:
return self.__class__(self.order.conjugate(), z.conjugate())
def _eval_is_meromorphic(self, x, a):
nu, z = self.order, self.argument
if nu.has(x):
return False
if not z._eval_is_meromorphic(x, a):
return None
z0 = z.subs(x, a)
if nu.is_integer:
if isinstance(self, (besselj, besseli, hn1, hn2, jn, yn)) or not nu.is_zero:
return fuzzy_not(z0.is_infinite)
return fuzzy_not(fuzzy_or([z0.is_zero, z0.is_infinite]))
def _eval_expand_func(self, **hints):
nu, z, f = self.order, self.argument, self.__class__
if nu.is_real:
if (nu - 1).is_positive:
return (-self._a*self._b*f(nu - 2, z)._eval_expand_func() +
2*self._a*(nu - 1)*f(nu - 1, z)._eval_expand_func()/z)
elif (nu + 1).is_negative:
return (2*self._b*(nu + 1)*f(nu + 1, z)._eval_expand_func()/z -
self._a*self._b*f(nu + 2, z)._eval_expand_func())
return self
def _eval_simplify(self, **kwargs):
from sympy.simplify.simplify import besselsimp
return besselsimp(self)
class besselj(BesselBase):
r"""
Bessel function of the first kind.
Explanation
===========
The Bessel $J$ function of order $\nu$ is defined to be the function
satisfying Bessel's differential equation
.. math ::
z^2 \frac{\mathrm{d}^2 w}{\mathrm{d}z^2}
+ z \frac{\mathrm{d}w}{\mathrm{d}z} + (z^2 - \nu^2) w = 0,
with Laurent expansion
.. math ::
J_\nu(z) = z^\nu \left(\frac{1}{\Gamma(\nu + 1) 2^\nu} + O(z^2) \right),
if $\nu$ is not a negative integer. If $\nu=-n \in \mathbb{Z}_{<0}$
*is* a negative integer, then the definition is
.. math ::
J_{-n}(z) = (-1)^n J_n(z).
Examples
========
Create a Bessel function object:
>>> from sympy import besselj, jn
>>> from sympy.abc import z, n
>>> b = besselj(n, z)
Differentiate it:
>>> b.diff(z)
besselj(n - 1, z)/2 - besselj(n + 1, z)/2
Rewrite in terms of spherical Bessel functions:
>>> b.rewrite(jn)
sqrt(2)*sqrt(z)*jn(n - 1/2, z)/sqrt(pi)
Access the parameter and argument:
>>> b.order
n
>>> b.argument
z
See Also
========
bessely, besseli, besselk
References
==========
.. [1] Abramowitz, Milton; Stegun, Irene A., eds. (1965), "Chapter 9",
Handbook of Mathematical Functions with Formulas, Graphs, and
Mathematical Tables
.. [2] Luke, Y. L. (1969), The Special Functions and Their
Approximations, Volume 1
.. [3] https://en.wikipedia.org/wiki/Bessel_function
.. [4] http://functions.wolfram.com/Bessel-TypeFunctions/BesselJ/
"""
_a = S.One
_b = S.One
@classmethod
def eval(cls, nu, z):
if z.is_zero:
if nu.is_zero:
return S.One
elif (nu.is_integer and nu.is_zero is False) or re(nu).is_positive:
return S.Zero
elif re(nu).is_negative and not (nu.is_integer is True):
return S.ComplexInfinity
elif nu.is_imaginary:
return S.NaN
if z in (S.Infinity, S.NegativeInfinity):
return S.Zero
if z.could_extract_minus_sign():
return (z)**nu*(-z)**(-nu)*besselj(nu, -z)
if nu.is_integer:
if nu.could_extract_minus_sign():
return S.NegativeOne**(-nu)*besselj(-nu, z)
newz = z.extract_multiplicatively(I)
if newz: # NOTE we don't want to change the function if z==0
return I**(nu)*besseli(nu, newz)
# branch handling:
from sympy.functions.elementary.complexes import unpolarify
if nu.is_integer:
newz = unpolarify(z)
if newz != z:
return besselj(nu, newz)
else:
newz, n = z.extract_branch_factor()
if n != 0:
return exp(2*n*pi*nu*I)*besselj(nu, newz)
nnu = unpolarify(nu)
if nu != nnu:
return besselj(nnu, z)
def _eval_rewrite_as_besseli(self, nu, z, **kwargs):
from sympy.functions.elementary.complexes import polar_lift
return exp(I*pi*nu/2)*besseli(nu, polar_lift(-I)*z)
def _eval_rewrite_as_bessely(self, nu, z, **kwargs):
if nu.is_integer is False:
return csc(pi*nu)*bessely(-nu, z) - cot(pi*nu)*bessely(nu, z)
def _eval_rewrite_as_jn(self, nu, z, **kwargs):
return sqrt(2*z/pi)*jn(nu - S.Half, self.argument)
def _eval_as_leading_term(self, x, logx=None, cdir=0):
nu, z = self.args
arg = z.as_leading_term(x)
if x in arg.free_symbols:
return arg**nu/(2**nu*gamma(nu + 1))
else:
return self.func(nu, z.subs(x, 0))
def _eval_is_extended_real(self):
nu, z = self.args
if nu.is_integer and z.is_extended_real:
return True
def _eval_nseries(self, x, n, logx, cdir=0):
from sympy.series.order import Order
nu, z = self.args
# In case of powers less than 1, number of terms need to be computed
# separately to avoid repeated callings of _eval_nseries with wrong n
try:
_, exp = z.leadterm(x)
except (ValueError, NotImplementedError):
return self
if exp.is_positive:
newn = ceiling(n/exp)
o = Order(x**n, x)
r = (z/2)._eval_nseries(x, n, logx, cdir).removeO()
if r is S.Zero:
return o
t = (_mexpand(r**2) + o).removeO()
term = r**nu/gamma(nu + 1)
s = [term]
for k in range(1, (newn + 1)//2):
term *= -t/(k*(nu + k))
term = (_mexpand(term) + o).removeO()
s.append(term)
return Add(*s) + o
return super(besselj, self)._eval_nseries(x, n, logx, cdir)
class bessely(BesselBase):
r"""
Bessel function of the second kind.
Explanation
===========
The Bessel $Y$ function of order $\nu$ is defined as
.. math ::
Y_\nu(z) = \lim_{\mu \to \nu} \frac{J_\mu(z) \cos(\pi \mu)
- J_{-\mu}(z)}{\sin(\pi \mu)},
where $J_\mu(z)$ is the Bessel function of the first kind.
It is a solution to Bessel's equation, and linearly independent from
$J_\nu$.
Examples
========
>>> from sympy import bessely, yn
>>> from sympy.abc import z, n
>>> b = bessely(n, z)
>>> b.diff(z)
bessely(n - 1, z)/2 - bessely(n + 1, z)/2
>>> b.rewrite(yn)
sqrt(2)*sqrt(z)*yn(n - 1/2, z)/sqrt(pi)
See Also
========
besselj, besseli, besselk
References
==========
.. [1] http://functions.wolfram.com/Bessel-TypeFunctions/BesselY/
"""
_a = S.One
_b = S.One
@classmethod
def eval(cls, nu, z):
if z.is_zero:
if nu.is_zero:
return S.NegativeInfinity
elif re(nu).is_zero is False:
return S.ComplexInfinity
elif re(nu).is_zero:
return S.NaN
if z in (S.Infinity, S.NegativeInfinity):
return S.Zero
if nu.is_integer:
if nu.could_extract_minus_sign():
return S.NegativeOne**(-nu)*bessely(-nu, z)
def _eval_rewrite_as_besselj(self, nu, z, **kwargs):
if nu.is_integer is False:
return csc(pi*nu)*(cos(pi*nu)*besselj(nu, z) - besselj(-nu, z))
def _eval_rewrite_as_besseli(self, nu, z, **kwargs):
aj = self._eval_rewrite_as_besselj(*self.args)
if aj:
return aj.rewrite(besseli)
def _eval_rewrite_as_yn(self, nu, z, **kwargs):
return sqrt(2*z/pi) * yn(nu - S.Half, self.argument)
def _eval_as_leading_term(self, x, logx=None, cdir=0):
nu, z = self.args
term_one = ((2/pi)*log(z/2)*besselj(nu, z))
term_two = (z/2)**(-nu)*factorial(nu - 1)/pi if (nu - 1).is_positive else S.Zero
term_three = (z/2)**nu/(pi*factorial(nu))*(digamma(nu + 1) - S.EulerGamma)
arg = Add(*[term_one, term_two, term_three]).as_leading_term(x)
if x in arg.free_symbols:
return arg
else:
return self.func(nu, z.subs(x, 0).cancel())
def _eval_is_extended_real(self):
nu, z = self.args
if nu.is_integer and z.is_positive:
return True
def _eval_nseries(self, x, n, logx, cdir=0):
from sympy.series.order import Order
nu, z = self.args
# In case of powers less than 1, number of terms need to be computed
# separately to avoid repeated callings of _eval_nseries with wrong n
try:
_, exp = z.leadterm(x)
except (ValueError, NotImplementedError):
return self
if exp.is_positive and nu.is_integer:
newn = ceiling(n/exp)
bn = besselj(nu, z)
a = ((2/pi)*log(z/2)*bn)._eval_nseries(x, n, logx, cdir)
b, c = [], []
o = Order(x**n, x)
r = (z/2)._eval_nseries(x, n, logx, cdir).removeO()
if r is S.Zero:
return o
t = (_mexpand(r**2) + o).removeO()
if nu > S.One:
term = r**(-nu)*factorial(nu - 1)/pi
b.append(term)
for k in range(1, nu - 1):
term *= t*(nu - k - 1)/k
term = (_mexpand(term) + o).removeO()
b.append(term)
p = r**nu/(pi*factorial(nu))
term = p*(digamma(nu + 1) - S.EulerGamma)
c.append(term)
for k in range(1, (newn + 1)//2):
p *= -t/(k*(k + nu))
p = (_mexpand(p) + o).removeO()
term = p*(digamma(k + nu + 1) + digamma(k + 1))
c.append(term)
return a - Add(*b) - Add(*c) # Order term comes from a
return super(bessely, self)._eval_nseries(x, n, logx, cdir)
class besseli(BesselBase):
r"""
Modified Bessel function of the first kind.
Explanation
===========
The Bessel $I$ function is a solution to the modified Bessel equation
.. math ::
z^2 \frac{\mathrm{d}^2 w}{\mathrm{d}z^2}
+ z \frac{\mathrm{d}w}{\mathrm{d}z} + (z^2 + \nu^2)^2 w = 0.
It can be defined as
.. math ::
I_\nu(z) = i^{-\nu} J_\nu(iz),
where $J_\nu(z)$ is the Bessel function of the first kind.
Examples
========
>>> from sympy import besseli
>>> from sympy.abc import z, n
>>> besseli(n, z).diff(z)
besseli(n - 1, z)/2 + besseli(n + 1, z)/2
See Also
========
besselj, bessely, besselk
References
==========
.. [1] http://functions.wolfram.com/Bessel-TypeFunctions/BesselI/
"""
_a = -S.One
_b = S.One
@classmethod
def eval(cls, nu, z):
if z.is_zero:
if nu.is_zero:
return S.One
elif (nu.is_integer and nu.is_zero is False) or re(nu).is_positive:
return S.Zero
elif re(nu).is_negative and not (nu.is_integer is True):
return S.ComplexInfinity
elif nu.is_imaginary:
return S.NaN
if im(z) in (S.Infinity, S.NegativeInfinity):
return S.Zero
if z.could_extract_minus_sign():
return (z)**nu*(-z)**(-nu)*besseli(nu, -z)
if nu.is_integer:
if nu.could_extract_minus_sign():
return besseli(-nu, z)
newz = z.extract_multiplicatively(I)
if newz: # NOTE we don't want to change the function if z==0
return I**(-nu)*besselj(nu, -newz)
# branch handling:
from sympy.functions.elementary.complexes import unpolarify
if nu.is_integer:
newz = unpolarify(z)
if newz != z:
return besseli(nu, newz)
else:
newz, n = z.extract_branch_factor()
if n != 0:
return exp(2*n*pi*nu*I)*besseli(nu, newz)
nnu = unpolarify(nu)
if nu != nnu:
return besseli(nnu, z)
def _eval_rewrite_as_besselj(self, nu, z, **kwargs):
from sympy.functions.elementary.complexes import polar_lift
return exp(-I*pi*nu/2)*besselj(nu, polar_lift(I)*z)
def _eval_rewrite_as_bessely(self, nu, z, **kwargs):
aj = self._eval_rewrite_as_besselj(*self.args)
if aj:
return aj.rewrite(bessely)
def _eval_rewrite_as_jn(self, nu, z, **kwargs):
return self._eval_rewrite_as_besselj(*self.args).rewrite(jn)
def _eval_is_extended_real(self):
nu, z = self.args
if nu.is_integer and z.is_extended_real:
return True
class besselk(BesselBase):
r"""
Modified Bessel function of the second kind.
Explanation
===========
The Bessel $K$ function of order $\nu$ is defined as
.. math ::
K_\nu(z) = \lim_{\mu \to \nu} \frac{\pi}{2}
\frac{I_{-\mu}(z) -I_\mu(z)}{\sin(\pi \mu)},
where $I_\mu(z)$ is the modified Bessel function of the first kind.
It is a solution of the modified Bessel equation, and linearly independent
from $Y_\nu$.
Examples
========
>>> from sympy import besselk
>>> from sympy.abc import z, n
>>> besselk(n, z).diff(z)
-besselk(n - 1, z)/2 - besselk(n + 1, z)/2
See Also
========
besselj, besseli, bessely
References
==========
.. [1] http://functions.wolfram.com/Bessel-TypeFunctions/BesselK/
"""
_a = S.One
_b = -S.One
@classmethod
def eval(cls, nu, z):
if z.is_zero:
if nu.is_zero:
return S.Infinity
elif re(nu).is_zero is False:
return S.ComplexInfinity
elif re(nu).is_zero:
return S.NaN
if z in (S.Infinity, I*S.Infinity, I*S.NegativeInfinity):
return S.Zero
if nu.is_integer:
if nu.could_extract_minus_sign():
return besselk(-nu, z)
def _eval_rewrite_as_besseli(self, nu, z, **kwargs):
if nu.is_integer is False:
return pi*csc(pi*nu)*(besseli(-nu, z) - besseli(nu, z))/2
def _eval_rewrite_as_besselj(self, nu, z, **kwargs):
ai = self._eval_rewrite_as_besseli(*self.args)
if ai:
return ai.rewrite(besselj)
def _eval_rewrite_as_bessely(self, nu, z, **kwargs):
aj = self._eval_rewrite_as_besselj(*self.args)
if aj:
return aj.rewrite(bessely)
def _eval_rewrite_as_yn(self, nu, z, **kwargs):
ay = self._eval_rewrite_as_bessely(*self.args)
if ay:
return ay.rewrite(yn)
def _eval_is_extended_real(self):
nu, z = self.args
if nu.is_integer and z.is_positive:
return True
class hankel1(BesselBase):
r"""
Hankel function of the first kind.
Explanation
===========
This function is defined as
.. math ::
H_\nu^{(1)} = J_\nu(z) + iY_\nu(z),
where $J_\nu(z)$ is the Bessel function of the first kind, and
$Y_\nu(z)$ is the Bessel function of the second kind.
It is a solution to Bessel's equation.
Examples
========
>>> from sympy import hankel1
>>> from sympy.abc import z, n
>>> hankel1(n, z).diff(z)
hankel1(n - 1, z)/2 - hankel1(n + 1, z)/2
See Also
========
hankel2, besselj, bessely
References
==========
.. [1] http://functions.wolfram.com/Bessel-TypeFunctions/HankelH1/
"""
_a = S.One
_b = S.One
def _eval_conjugate(self):
z = self.argument
if z.is_extended_negative is False:
return hankel2(self.order.conjugate(), z.conjugate())
class hankel2(BesselBase):
r"""
Hankel function of the second kind.
Explanation
===========
This function is defined as
.. math ::
H_\nu^{(2)} = J_\nu(z) - iY_\nu(z),
where $J_\nu(z)$ is the Bessel function of the first kind, and
$Y_\nu(z)$ is the Bessel function of the second kind.
It is a solution to Bessel's equation, and linearly independent from
$H_\nu^{(1)}$.
Examples
========
>>> from sympy import hankel2
>>> from sympy.abc import z, n
>>> hankel2(n, z).diff(z)
hankel2(n - 1, z)/2 - hankel2(n + 1, z)/2
See Also
========
hankel1, besselj, bessely
References
==========
.. [1] http://functions.wolfram.com/Bessel-TypeFunctions/HankelH2/
"""
_a = S.One
_b = S.One
def _eval_conjugate(self):
z = self.argument
if z.is_extended_negative is False:
return hankel1(self.order.conjugate(), z.conjugate())
def assume_integer_order(fn):
@wraps(fn)
def g(self, nu, z):
if nu.is_integer:
return fn(self, nu, z)
return g
class SphericalBesselBase(BesselBase):
"""
Base class for spherical Bessel functions.
These are thin wrappers around ordinary Bessel functions,
since spherical Bessel functions differ from the ordinary
ones just by a slight change in order.
To use this class, define the ``_eval_evalf()`` and ``_expand()`` methods.
"""
def _expand(self, **hints):
""" Expand self into a polynomial. Nu is guaranteed to be Integer. """
raise NotImplementedError('expansion')
def _eval_expand_func(self, **hints):
if self.order.is_Integer:
return self._expand(**hints)
return self
def fdiff(self, argindex=2):
if argindex != 2:
raise ArgumentIndexError(self, argindex)
return self.__class__(self.order - 1, self.argument) - \
self * (self.order + 1)/self.argument
def _jn(n, z):
return (spherical_bessel_fn(n, z)*sin(z) +
S.NegativeOne**(n + 1)*spherical_bessel_fn(-n - 1, z)*cos(z))
def _yn(n, z):
# (-1)**(n + 1) * _jn(-n - 1, z)
return (S.NegativeOne**(n + 1) * spherical_bessel_fn(-n - 1, z)*sin(z) -
spherical_bessel_fn(n, z)*cos(z))
class jn(SphericalBesselBase):
r"""
Spherical Bessel function of the first kind.
Explanation
===========
This function is a solution to the spherical Bessel equation
.. math ::
z^2 \frac{\mathrm{d}^2 w}{\mathrm{d}z^2}
+ 2z \frac{\mathrm{d}w}{\mathrm{d}z} + (z^2 - \nu(\nu + 1)) w = 0.
It can be defined as
.. math ::
j_\nu(z) = \sqrt{\frac{\pi}{2z}} J_{\nu + \frac{1}{2}}(z),
where $J_\nu(z)$ is the Bessel function of the first kind.
The spherical Bessel functions of integral order are
calculated using the formula:
.. math:: j_n(z) = f_n(z) \sin{z} + (-1)^{n+1} f_{-n-1}(z) \cos{z},
where the coefficients $f_n(z)$ are available as
:func:`sympy.polys.orthopolys.spherical_bessel_fn`.
Examples
========
>>> from sympy import Symbol, jn, sin, cos, expand_func, besselj, bessely
>>> z = Symbol("z")
>>> nu = Symbol("nu", integer=True)
>>> print(expand_func(jn(0, z)))
sin(z)/z
>>> expand_func(jn(1, z)) == sin(z)/z**2 - cos(z)/z
True
>>> expand_func(jn(3, z))
(-6/z**2 + 15/z**4)*sin(z) + (1/z - 15/z**3)*cos(z)
>>> jn(nu, z).rewrite(besselj)
sqrt(2)*sqrt(pi)*sqrt(1/z)*besselj(nu + 1/2, z)/2
>>> jn(nu, z).rewrite(bessely)
(-1)**nu*sqrt(2)*sqrt(pi)*sqrt(1/z)*bessely(-nu - 1/2, z)/2
>>> jn(2, 5.2+0.3j).evalf(20)
0.099419756723640344491 - 0.054525080242173562897*I
See Also
========
besselj, bessely, besselk, yn
References
==========
.. [1] http://dlmf.nist.gov/10.47
"""
@classmethod
def eval(cls, nu, z):
if z.is_zero:
if nu.is_zero:
return S.One
elif nu.is_integer:
if nu.is_positive:
return S.Zero
else:
return S.ComplexInfinity
if z in (S.NegativeInfinity, S.Infinity):
return S.Zero
def _eval_rewrite_as_besselj(self, nu, z, **kwargs):
return sqrt(pi/(2*z)) * besselj(nu + S.Half, z)
def _eval_rewrite_as_bessely(self, nu, z, **kwargs):
return S.NegativeOne**nu * sqrt(pi/(2*z)) * bessely(-nu - S.Half, z)
def _eval_rewrite_as_yn(self, nu, z, **kwargs):
return S.NegativeOne**(nu) * yn(-nu - 1, z)
def _expand(self, **hints):
return _jn(self.order, self.argument)
def _eval_evalf(self, prec):
if self.order.is_Integer:
return self.rewrite(besselj)._eval_evalf(prec)
class yn(SphericalBesselBase):
r"""
Spherical Bessel function of the second kind.
Explanation
===========
This function is another solution to the spherical Bessel equation, and
linearly independent from $j_n$. It can be defined as
.. math ::
y_\nu(z) = \sqrt{\frac{\pi}{2z}} Y_{\nu + \frac{1}{2}}(z),
where $Y_\nu(z)$ is the Bessel function of the second kind.
For integral orders $n$, $y_n$ is calculated using the formula:
.. math:: y_n(z) = (-1)^{n+1} j_{-n-1}(z)
Examples
========
>>> from sympy import Symbol, yn, sin, cos, expand_func, besselj, bessely
>>> z = Symbol("z")
>>> nu = Symbol("nu", integer=True)
>>> print(expand_func(yn(0, z)))
-cos(z)/z
>>> expand_func(yn(1, z)) == -cos(z)/z**2-sin(z)/z
True
>>> yn(nu, z).rewrite(besselj)
(-1)**(nu + 1)*sqrt(2)*sqrt(pi)*sqrt(1/z)*besselj(-nu - 1/2, z)/2
>>> yn(nu, z).rewrite(bessely)
sqrt(2)*sqrt(pi)*sqrt(1/z)*bessely(nu + 1/2, z)/2
>>> yn(2, 5.2+0.3j).evalf(20)
0.18525034196069722536 + 0.014895573969924817587*I
See Also
========
besselj, bessely, besselk, jn
References
==========
.. [1] http://dlmf.nist.gov/10.47
"""
@assume_integer_order
def _eval_rewrite_as_besselj(self, nu, z, **kwargs):
return S.NegativeOne**(nu+1) * sqrt(pi/(2*z)) * besselj(-nu - S.Half, z)
@assume_integer_order
def _eval_rewrite_as_bessely(self, nu, z, **kwargs):
return sqrt(pi/(2*z)) * bessely(nu + S.Half, z)
def _eval_rewrite_as_jn(self, nu, z, **kwargs):
return S.NegativeOne**(nu + 1) * jn(-nu - 1, z)
def _expand(self, **hints):
return _yn(self.order, self.argument)
def _eval_evalf(self, prec):
if self.order.is_Integer:
return self.rewrite(bessely)._eval_evalf(prec)
class SphericalHankelBase(SphericalBesselBase):
@assume_integer_order
def _eval_rewrite_as_besselj(self, nu, z, **kwargs):
# jn +- I*yn
# jn as beeselj: sqrt(pi/(2*z)) * besselj(nu + S.Half, z)
# yn as besselj: (-1)**(nu+1) * sqrt(pi/(2*z)) * besselj(-nu - S.Half, z)
hks = self._hankel_kind_sign
return sqrt(pi/(2*z))*(besselj(nu + S.Half, z) +
hks*I*S.NegativeOne**(nu+1)*besselj(-nu - S.Half, z))
@assume_integer_order
def _eval_rewrite_as_bessely(self, nu, z, **kwargs):
# jn +- I*yn
# jn as bessely: (-1)**nu * sqrt(pi/(2*z)) * bessely(-nu - S.Half, z)
# yn as bessely: sqrt(pi/(2*z)) * bessely(nu + S.Half, z)
hks = self._hankel_kind_sign
return sqrt(pi/(2*z))*(S.NegativeOne**nu*bessely(-nu - S.Half, z) +
hks*I*bessely(nu + S.Half, z))
def _eval_rewrite_as_yn(self, nu, z, **kwargs):
hks = self._hankel_kind_sign
return jn(nu, z).rewrite(yn) + hks*I*yn(nu, z)
def _eval_rewrite_as_jn(self, nu, z, **kwargs):
hks = self._hankel_kind_sign
return jn(nu, z) + hks*I*yn(nu, z).rewrite(jn)
def _eval_expand_func(self, **hints):
if self.order.is_Integer:
return self._expand(**hints)
else:
nu = self.order
z = self.argument
hks = self._hankel_kind_sign
return jn(nu, z) + hks*I*yn(nu, z)
def _expand(self, **hints):
n = self.order
z = self.argument
hks = self._hankel_kind_sign
# fully expanded version
# return ((fn(n, z) * sin(z) +
# (-1)**(n + 1) * fn(-n - 1, z) * cos(z)) + # jn
# (hks * I * (-1)**(n + 1) *
# (fn(-n - 1, z) * hk * I * sin(z) +
# (-1)**(-n) * fn(n, z) * I * cos(z))) # +-I*yn
# )
return (_jn(n, z) + hks*I*_yn(n, z)).expand()
def _eval_evalf(self, prec):
if self.order.is_Integer:
return self.rewrite(besselj)._eval_evalf(prec)
class hn1(SphericalHankelBase):
r"""
Spherical Hankel function of the first kind.
Explanation
===========
This function is defined as
.. math:: h_\nu^(1)(z) = j_\nu(z) + i y_\nu(z),
where $j_\nu(z)$ and $y_\nu(z)$ are the spherical
Bessel function of the first and second kinds.
For integral orders $n$, $h_n^(1)$ is calculated using the formula:
.. math:: h_n^(1)(z) = j_{n}(z) + i (-1)^{n+1} j_{-n-1}(z)
Examples
========
>>> from sympy import Symbol, hn1, hankel1, expand_func, yn, jn
>>> z = Symbol("z")
>>> nu = Symbol("nu", integer=True)
>>> print(expand_func(hn1(nu, z)))
jn(nu, z) + I*yn(nu, z)
>>> print(expand_func(hn1(0, z)))
sin(z)/z - I*cos(z)/z
>>> print(expand_func(hn1(1, z)))
-I*sin(z)/z - cos(z)/z + sin(z)/z**2 - I*cos(z)/z**2
>>> hn1(nu, z).rewrite(jn)
(-1)**(nu + 1)*I*jn(-nu - 1, z) + jn(nu, z)
>>> hn1(nu, z).rewrite(yn)
(-1)**nu*yn(-nu - 1, z) + I*yn(nu, z)
>>> hn1(nu, z).rewrite(hankel1)
sqrt(2)*sqrt(pi)*sqrt(1/z)*hankel1(nu, z)/2
See Also
========
hn2, jn, yn, hankel1, hankel2
References
==========
.. [1] http://dlmf.nist.gov/10.47
"""
_hankel_kind_sign = S.One
@assume_integer_order
def _eval_rewrite_as_hankel1(self, nu, z, **kwargs):
return sqrt(pi/(2*z))*hankel1(nu, z)
class hn2(SphericalHankelBase):
r"""
Spherical Hankel function of the second kind.
Explanation
===========
This function is defined as
.. math:: h_\nu^(2)(z) = j_\nu(z) - i y_\nu(z),
where $j_\nu(z)$ and $y_\nu(z)$ are the spherical
Bessel function of the first and second kinds.
For integral orders $n$, $h_n^(2)$ is calculated using the formula:
.. math:: h_n^(2)(z) = j_{n} - i (-1)^{n+1} j_{-n-1}(z)
Examples
========
>>> from sympy import Symbol, hn2, hankel2, expand_func, jn, yn
>>> z = Symbol("z")
>>> nu = Symbol("nu", integer=True)
>>> print(expand_func(hn2(nu, z)))
jn(nu, z) - I*yn(nu, z)
>>> print(expand_func(hn2(0, z)))
sin(z)/z + I*cos(z)/z
>>> print(expand_func(hn2(1, z)))
I*sin(z)/z - cos(z)/z + sin(z)/z**2 + I*cos(z)/z**2
>>> hn2(nu, z).rewrite(hankel2)
sqrt(2)*sqrt(pi)*sqrt(1/z)*hankel2(nu, z)/2
>>> hn2(nu, z).rewrite(jn)
-(-1)**(nu + 1)*I*jn(-nu - 1, z) + jn(nu, z)
>>> hn2(nu, z).rewrite(yn)
(-1)**nu*yn(-nu - 1, z) - I*yn(nu, z)
See Also
========
hn1, jn, yn, hankel1, hankel2
References
==========
.. [1] http://dlmf.nist.gov/10.47
"""
_hankel_kind_sign = -S.One
@assume_integer_order
def _eval_rewrite_as_hankel2(self, nu, z, **kwargs):
return sqrt(pi/(2*z))*hankel2(nu, z)
def jn_zeros(n, k, method="sympy", dps=15):
"""
Zeros of the spherical Bessel function of the first kind.
Explanation
===========
This returns an array of zeros of $jn$ up to the $k$-th zero.
* method = "sympy": uses `mpmath.besseljzero
<http://mpmath.org/doc/current/functions/bessel.html#mpmath.besseljzero>`_
* method = "scipy": uses the
`SciPy's sph_jn <http://docs.scipy.org/doc/scipy/reference/generated/scipy.special.jn_zeros.html>`_
and
`newton <http://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.newton.html>`_
to find all
roots, which is faster than computing the zeros using a general
numerical solver, but it requires SciPy and only works with low
precision floating point numbers. (The function used with
method="sympy" is a recent addition to mpmath; before that a general
solver was used.)
Examples
========
>>> from sympy import jn_zeros
>>> jn_zeros(2, 4, dps=5)
[5.7635, 9.095, 12.323, 15.515]
See Also
========
jn, yn, besselj, besselk, bessely
Parameters
==========
n : integer
order of Bessel function
k : integer
number of zeros to return
"""
from math import pi as math_pi
if method == "sympy":
from mpmath import besseljzero
from mpmath.libmp.libmpf import dps_to_prec
prec = dps_to_prec(dps)
return [Expr._from_mpmath(besseljzero(S(n + 0.5)._to_mpmath(prec),
int(l)), prec)
for l in range(1, k + 1)]
elif method == "scipy":
from scipy.optimize import newton
try:
from scipy.special import spherical_jn
f = lambda x: spherical_jn(n, x)
except ImportError:
from scipy.special import sph_jn
f = lambda x: sph_jn(n, x)[0][-1]
else:
raise NotImplementedError("Unknown method.")
def solver(f, x):
if method == "scipy":
root = newton(f, x)
else:
raise NotImplementedError("Unknown method.")
return root
# we need to approximate the position of the first root:
root = n + math_pi
# determine the first root exactly:
root = solver(f, root)
roots = [root]
for i in range(k - 1):
# estimate the position of the next root using the last root + pi:
root = solver(f, root + math_pi)
roots.append(root)
return roots
class AiryBase(Function):
"""
Abstract base class for Airy functions.
This class is meant to reduce code duplication.
"""
def _eval_conjugate(self):
return self.func(self.args[0].conjugate())
def _eval_is_extended_real(self):
return self.args[0].is_extended_real
def as_real_imag(self, deep=True, **hints):
z = self.args[0]
zc = z.conjugate()
f = self.func
u = (f(z)+f(zc))/2
v = I*(f(zc)-f(z))/2
return u, v
def _eval_expand_complex(self, deep=True, **hints):
re_part, im_part = self.as_real_imag(deep=deep, **hints)
return re_part + im_part*S.ImaginaryUnit
class airyai(AiryBase):
r"""
The Airy function $\operatorname{Ai}$ of the first kind.
Explanation
===========
The Airy function $\operatorname{Ai}(z)$ is defined to be the function
satisfying Airy's differential equation
.. math::
\frac{\mathrm{d}^2 w(z)}{\mathrm{d}z^2} - z w(z) = 0.
Equivalently, for real $z$
.. math::
\operatorname{Ai}(z) := \frac{1}{\pi}
\int_0^\infty \cos\left(\frac{t^3}{3} + z t\right) \mathrm{d}t.
Examples
========
Create an Airy function object:
>>> from sympy import airyai
>>> from sympy.abc import z
>>> airyai(z)
airyai(z)
Several special values are known:
>>> airyai(0)
3**(1/3)/(3*gamma(2/3))
>>> from sympy import oo
>>> airyai(oo)
0
>>> airyai(-oo)
0
The Airy function obeys the mirror symmetry:
>>> from sympy import conjugate
>>> conjugate(airyai(z))
airyai(conjugate(z))
Differentiation with respect to $z$ is supported:
>>> from sympy import diff
>>> diff(airyai(z), z)
airyaiprime(z)
>>> diff(airyai(z), z, 2)
z*airyai(z)
Series expansion is also supported:
>>> from sympy import series
>>> series(airyai(z), z, 0, 3)
3**(5/6)*gamma(1/3)/(6*pi) - 3**(1/6)*z*gamma(2/3)/(2*pi) + O(z**3)
We can numerically evaluate the Airy function to arbitrary precision
on the whole complex plane:
>>> airyai(-2).evalf(50)
0.22740742820168557599192443603787379946077222541710
Rewrite $\operatorname{Ai}(z)$ in terms of hypergeometric functions:
>>> from sympy import hyper
>>> airyai(z).rewrite(hyper)
-3**(2/3)*z*hyper((), (4/3,), z**3/9)/(3*gamma(1/3)) + 3**(1/3)*hyper((), (2/3,), z**3/9)/(3*gamma(2/3))
See Also
========
airybi: Airy function of the second kind.
airyaiprime: Derivative of the Airy function of the first kind.
airybiprime: Derivative of the Airy function of the second kind.
References
==========
.. [1] https://en.wikipedia.org/wiki/Airy_function
.. [2] http://dlmf.nist.gov/9
.. [3] http://www.encyclopediaofmath.org/index.php/Airy_functions
.. [4] http://mathworld.wolfram.com/AiryFunctions.html
"""
nargs = 1
unbranched = True
@classmethod
def eval(cls, arg):
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.Zero
elif arg is S.NegativeInfinity:
return S.Zero
elif arg.is_zero:
return S.One / (3**Rational(2, 3) * gamma(Rational(2, 3)))
if arg.is_zero:
return S.One / (3**Rational(2, 3) * gamma(Rational(2, 3)))
def fdiff(self, argindex=1):
if argindex == 1:
return airyaiprime(self.args[0])
else:
raise ArgumentIndexError(self, argindex)
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
if n < 0:
return S.Zero
else:
x = sympify(x)
if len(previous_terms) > 1:
p = previous_terms[-1]
return ((3**Rational(1, 3)*x)**(-n)*(3**Rational(1, 3)*x)**(n + 1)*sin(pi*(n*Rational(2, 3) + Rational(4, 3)))*factorial(n) *
gamma(n/3 + Rational(2, 3))/(sin(pi*(n*Rational(2, 3) + Rational(2, 3)))*factorial(n + 1)*gamma(n/3 + Rational(1, 3))) * p)
else:
return (S.One/(3**Rational(2, 3)*pi) * gamma((n+S.One)/S(3)) * sin(2*pi*(n+S.One)/S(3)) /
factorial(n) * (root(3, 3)*x)**n)
def _eval_rewrite_as_besselj(self, z, **kwargs):
ot = Rational(1, 3)
tt = Rational(2, 3)
a = Pow(-z, Rational(3, 2))
if re(z).is_negative:
return ot*sqrt(-z) * (besselj(-ot, tt*a) + besselj(ot, tt*a))
def _eval_rewrite_as_besseli(self, z, **kwargs):
ot = Rational(1, 3)
tt = Rational(2, 3)
a = Pow(z, Rational(3, 2))
if re(z).is_positive:
return ot*sqrt(z) * (besseli(-ot, tt*a) - besseli(ot, tt*a))
else:
return ot*(Pow(a, ot)*besseli(-ot, tt*a) - z*Pow(a, -ot)*besseli(ot, tt*a))
def _eval_rewrite_as_hyper(self, z, **kwargs):
pf1 = S.One / (3**Rational(2, 3)*gamma(Rational(2, 3)))
pf2 = z / (root(3, 3)*gamma(Rational(1, 3)))
return pf1 * hyper([], [Rational(2, 3)], z**3/9) - pf2 * hyper([], [Rational(4, 3)], z**3/9)
def _eval_expand_func(self, **hints):
arg = self.args[0]
symbs = arg.free_symbols
if len(symbs) == 1:
z = symbs.pop()
c = Wild("c", exclude=[z])
d = Wild("d", exclude=[z])
m = Wild("m", exclude=[z])
n = Wild("n", exclude=[z])
M = arg.match(c*(d*z**n)**m)
if M is not None:
m = M[m]
# The transformation is given by 03.05.16.0001.01
# http://functions.wolfram.com/Bessel-TypeFunctions/AiryAi/16/01/01/0001/
if (3*m).is_integer:
c = M[c]
d = M[d]
n = M[n]
pf = (d * z**n)**m / (d**m * z**(m*n))
newarg = c * d**m * z**(m*n)
return S.Half * ((pf + S.One)*airyai(newarg) - (pf - S.One)/sqrt(3)*airybi(newarg))
class airybi(AiryBase):
r"""
The Airy function $\operatorname{Bi}$ of the second kind.
Explanation
===========
The Airy function $\operatorname{Bi}(z)$ is defined to be the function
satisfying Airy's differential equation
.. math::
\frac{\mathrm{d}^2 w(z)}{\mathrm{d}z^2} - z w(z) = 0.
Equivalently, for real $z$
.. math::
\operatorname{Bi}(z) := \frac{1}{\pi}
\int_0^\infty
\exp\left(-\frac{t^3}{3} + z t\right)
+ \sin\left(\frac{t^3}{3} + z t\right) \mathrm{d}t.
Examples
========
Create an Airy function object:
>>> from sympy import airybi
>>> from sympy.abc import z
>>> airybi(z)
airybi(z)
Several special values are known:
>>> airybi(0)
3**(5/6)/(3*gamma(2/3))
>>> from sympy import oo
>>> airybi(oo)
oo
>>> airybi(-oo)
0
The Airy function obeys the mirror symmetry:
>>> from sympy import conjugate
>>> conjugate(airybi(z))
airybi(conjugate(z))
Differentiation with respect to $z$ is supported:
>>> from sympy import diff
>>> diff(airybi(z), z)
airybiprime(z)
>>> diff(airybi(z), z, 2)
z*airybi(z)
Series expansion is also supported:
>>> from sympy import series
>>> series(airybi(z), z, 0, 3)
3**(1/3)*gamma(1/3)/(2*pi) + 3**(2/3)*z*gamma(2/3)/(2*pi) + O(z**3)
We can numerically evaluate the Airy function to arbitrary precision
on the whole complex plane:
>>> airybi(-2).evalf(50)
-0.41230258795639848808323405461146104203453483447240
Rewrite $\operatorname{Bi}(z)$ in terms of hypergeometric functions:
>>> from sympy import hyper
>>> airybi(z).rewrite(hyper)
3**(1/6)*z*hyper((), (4/3,), z**3/9)/gamma(1/3) + 3**(5/6)*hyper((), (2/3,), z**3/9)/(3*gamma(2/3))
See Also
========
airyai: Airy function of the first kind.
airyaiprime: Derivative of the Airy function of the first kind.
airybiprime: Derivative of the Airy function of the second kind.
References
==========
.. [1] https://en.wikipedia.org/wiki/Airy_function
.. [2] http://dlmf.nist.gov/9
.. [3] http://www.encyclopediaofmath.org/index.php/Airy_functions
.. [4] http://mathworld.wolfram.com/AiryFunctions.html
"""
nargs = 1
unbranched = True
@classmethod
def eval(cls, arg):
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.Infinity
elif arg is S.NegativeInfinity:
return S.Zero
elif arg.is_zero:
return S.One / (3**Rational(1, 6) * gamma(Rational(2, 3)))
if arg.is_zero:
return S.One / (3**Rational(1, 6) * gamma(Rational(2, 3)))
def fdiff(self, argindex=1):
if argindex == 1:
return airybiprime(self.args[0])
else:
raise ArgumentIndexError(self, argindex)
@staticmethod
@cacheit
def taylor_term(n, x, *previous_terms):
if n < 0:
return S.Zero
else:
x = sympify(x)
if len(previous_terms) > 1:
p = previous_terms[-1]
return (3**Rational(1, 3)*x * Abs(sin(2*pi*(n + S.One)/S(3))) * factorial((n - S.One)/S(3)) /
((n + S.One) * Abs(cos(2*pi*(n + S.Half)/S(3))) * factorial((n - 2)/S(3))) * p)
else:
return (S.One/(root(3, 6)*pi) * gamma((n + S.One)/S(3)) * Abs(sin(2*pi*(n + S.One)/S(3))) /
factorial(n) * (root(3, 3)*x)**n)
def _eval_rewrite_as_besselj(self, z, **kwargs):
ot = Rational(1, 3)
tt = Rational(2, 3)
a = Pow(-z, Rational(3, 2))
if re(z).is_negative:
return sqrt(-z/3) * (besselj(-ot, tt*a) - besselj(ot, tt*a))
def _eval_rewrite_as_besseli(self, z, **kwargs):
ot = Rational(1, 3)
tt = Rational(2, 3)
a = Pow(z, Rational(3, 2))
if re(z).is_positive:
return sqrt(z)/sqrt(3) * (besseli(-ot, tt*a) + besseli(ot, tt*a))
else:
b = Pow(a, ot)
c = Pow(a, -ot)
return sqrt(ot)*(b*besseli(-ot, tt*a) + z*c*besseli(ot, tt*a))
def _eval_rewrite_as_hyper(self, z, **kwargs):
pf1 = S.One / (root(3, 6)*gamma(Rational(2, 3)))
pf2 = z*root(3, 6) / gamma(Rational(1, 3))
return pf1 * hyper([], [Rational(2, 3)], z**3/9) + pf2 * hyper([], [Rational(4, 3)], z**3/9)
def _eval_expand_func(self, **hints):
arg = self.args[0]
symbs = arg.free_symbols
if len(symbs) == 1:
z = symbs.pop()
c = Wild("c", exclude=[z])
d = Wild("d", exclude=[z])
m = Wild("m", exclude=[z])
n = Wild("n", exclude=[z])
M = arg.match(c*(d*z**n)**m)
if M is not None:
m = M[m]
# The transformation is given by 03.06.16.0001.01
# http://functions.wolfram.com/Bessel-TypeFunctions/AiryBi/16/01/01/0001/
if (3*m).is_integer:
c = M[c]
d = M[d]
n = M[n]
pf = (d * z**n)**m / (d**m * z**(m*n))
newarg = c * d**m * z**(m*n)
return S.Half * (sqrt(3)*(S.One - pf)*airyai(newarg) + (S.One + pf)*airybi(newarg))
class airyaiprime(AiryBase):
r"""
The derivative $\operatorname{Ai}^\prime$ of the Airy function of the first
kind.
Explanation
===========
The Airy function $\operatorname{Ai}^\prime(z)$ is defined to be the
function
.. math::
\operatorname{Ai}^\prime(z) := \frac{\mathrm{d} \operatorname{Ai}(z)}{\mathrm{d} z}.
Examples
========
Create an Airy function object:
>>> from sympy import airyaiprime
>>> from sympy.abc import z
>>> airyaiprime(z)
airyaiprime(z)
Several special values are known:
>>> airyaiprime(0)
-3**(2/3)/(3*gamma(1/3))
>>> from sympy import oo
>>> airyaiprime(oo)
0
The Airy function obeys the mirror symmetry:
>>> from sympy import conjugate
>>> conjugate(airyaiprime(z))
airyaiprime(conjugate(z))
Differentiation with respect to $z$ is supported:
>>> from sympy import diff
>>> diff(airyaiprime(z), z)
z*airyai(z)
>>> diff(airyaiprime(z), z, 2)
z*airyaiprime(z) + airyai(z)
Series expansion is also supported:
>>> from sympy import series
>>> series(airyaiprime(z), z, 0, 3)
-3**(2/3)/(3*gamma(1/3)) + 3**(1/3)*z**2/(6*gamma(2/3)) + O(z**3)
We can numerically evaluate the Airy function to arbitrary precision
on the whole complex plane:
>>> airyaiprime(-2).evalf(50)
0.61825902074169104140626429133247528291577794512415
Rewrite $\operatorname{Ai}^\prime(z)$ in terms of hypergeometric functions:
>>> from sympy import hyper
>>> airyaiprime(z).rewrite(hyper)
3**(1/3)*z**2*hyper((), (5/3,), z**3/9)/(6*gamma(2/3)) - 3**(2/3)*hyper((), (1/3,), z**3/9)/(3*gamma(1/3))
See Also
========
airyai: Airy function of the first kind.
airybi: Airy function of the second kind.
airybiprime: Derivative of the Airy function of the second kind.
References
==========
.. [1] https://en.wikipedia.org/wiki/Airy_function
.. [2] http://dlmf.nist.gov/9
.. [3] http://www.encyclopediaofmath.org/index.php/Airy_functions
.. [4] http://mathworld.wolfram.com/AiryFunctions.html
"""
nargs = 1
unbranched = True
@classmethod
def eval(cls, arg):
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.Zero
if arg.is_zero:
return S.NegativeOne / (3**Rational(1, 3) * gamma(Rational(1, 3)))
def fdiff(self, argindex=1):
if argindex == 1:
return self.args[0]*airyai(self.args[0])
else:
raise ArgumentIndexError(self, argindex)
def _eval_evalf(self, prec):
z = self.args[0]._to_mpmath(prec)
with workprec(prec):
res = mp.airyai(z, derivative=1)
return Expr._from_mpmath(res, prec)
def _eval_rewrite_as_besselj(self, z, **kwargs):
tt = Rational(2, 3)
a = Pow(-z, Rational(3, 2))
if re(z).is_negative:
return z/3 * (besselj(-tt, tt*a) - besselj(tt, tt*a))
def _eval_rewrite_as_besseli(self, z, **kwargs):
ot = Rational(1, 3)
tt = Rational(2, 3)
a = tt * Pow(z, Rational(3, 2))
if re(z).is_positive:
return z/3 * (besseli(tt, a) - besseli(-tt, a))
else:
a = Pow(z, Rational(3, 2))
b = Pow(a, tt)
c = Pow(a, -tt)
return ot * (z**2*c*besseli(tt, tt*a) - b*besseli(-ot, tt*a))
def _eval_rewrite_as_hyper(self, z, **kwargs):
pf1 = z**2 / (2*3**Rational(2, 3)*gamma(Rational(2, 3)))
pf2 = 1 / (root(3, 3)*gamma(Rational(1, 3)))
return pf1 * hyper([], [Rational(5, 3)], z**3/9) - pf2 * hyper([], [Rational(1, 3)], z**3/9)
def _eval_expand_func(self, **hints):
arg = self.args[0]
symbs = arg.free_symbols
if len(symbs) == 1:
z = symbs.pop()
c = Wild("c", exclude=[z])
d = Wild("d", exclude=[z])
m = Wild("m", exclude=[z])
n = Wild("n", exclude=[z])
M = arg.match(c*(d*z**n)**m)
if M is not None:
m = M[m]
# The transformation is in principle
# given by 03.07.16.0001.01 but note
# that there is an error in this formula.
# http://functions.wolfram.com/Bessel-TypeFunctions/AiryAiPrime/16/01/01/0001/
if (3*m).is_integer:
c = M[c]
d = M[d]
n = M[n]
pf = (d**m * z**(n*m)) / (d * z**n)**m
newarg = c * d**m * z**(n*m)
return S.Half * ((pf + S.One)*airyaiprime(newarg) + (pf - S.One)/sqrt(3)*airybiprime(newarg))
class airybiprime(AiryBase):
r"""
The derivative $\operatorname{Bi}^\prime$ of the Airy function of the first
kind.
Explanation
===========
The Airy function $\operatorname{Bi}^\prime(z)$ is defined to be the
function
.. math::
\operatorname{Bi}^\prime(z) := \frac{\mathrm{d} \operatorname{Bi}(z)}{\mathrm{d} z}.
Examples
========
Create an Airy function object:
>>> from sympy import airybiprime
>>> from sympy.abc import z
>>> airybiprime(z)
airybiprime(z)
Several special values are known:
>>> airybiprime(0)
3**(1/6)/gamma(1/3)
>>> from sympy import oo
>>> airybiprime(oo)
oo
>>> airybiprime(-oo)
0
The Airy function obeys the mirror symmetry:
>>> from sympy import conjugate
>>> conjugate(airybiprime(z))
airybiprime(conjugate(z))
Differentiation with respect to $z$ is supported:
>>> from sympy import diff
>>> diff(airybiprime(z), z)
z*airybi(z)
>>> diff(airybiprime(z), z, 2)
z*airybiprime(z) + airybi(z)
Series expansion is also supported:
>>> from sympy import series
>>> series(airybiprime(z), z, 0, 3)
3**(1/6)/gamma(1/3) + 3**(5/6)*z**2/(6*gamma(2/3)) + O(z**3)
We can numerically evaluate the Airy function to arbitrary precision
on the whole complex plane:
>>> airybiprime(-2).evalf(50)
0.27879516692116952268509756941098324140300059345163
Rewrite $\operatorname{Bi}^\prime(z)$ in terms of hypergeometric functions:
>>> from sympy import hyper
>>> airybiprime(z).rewrite(hyper)
3**(5/6)*z**2*hyper((), (5/3,), z**3/9)/(6*gamma(2/3)) + 3**(1/6)*hyper((), (1/3,), z**3/9)/gamma(1/3)
See Also
========
airyai: Airy function of the first kind.
airybi: Airy function of the second kind.
airyaiprime: Derivative of the Airy function of the first kind.
References
==========
.. [1] https://en.wikipedia.org/wiki/Airy_function
.. [2] http://dlmf.nist.gov/9
.. [3] http://www.encyclopediaofmath.org/index.php/Airy_functions
.. [4] http://mathworld.wolfram.com/AiryFunctions.html
"""
nargs = 1
unbranched = True
@classmethod
def eval(cls, arg):
if arg.is_Number:
if arg is S.NaN:
return S.NaN
elif arg is S.Infinity:
return S.Infinity
elif arg is S.NegativeInfinity:
return S.Zero
elif arg.is_zero:
return 3**Rational(1, 6) / gamma(Rational(1, 3))
if arg.is_zero:
return 3**Rational(1, 6) / gamma(Rational(1, 3))
def fdiff(self, argindex=1):
if argindex == 1:
return self.args[0]*airybi(self.args[0])
else:
raise ArgumentIndexError(self, argindex)
def _eval_evalf(self, prec):
z = self.args[0]._to_mpmath(prec)
with workprec(prec):
res = mp.airybi(z, derivative=1)
return Expr._from_mpmath(res, prec)
def _eval_rewrite_as_besselj(self, z, **kwargs):
tt = Rational(2, 3)
a = tt * Pow(-z, Rational(3, 2))
if re(z).is_negative:
return -z/sqrt(3) * (besselj(-tt, a) + besselj(tt, a))
def _eval_rewrite_as_besseli(self, z, **kwargs):
ot = Rational(1, 3)
tt = Rational(2, 3)
a = tt * Pow(z, Rational(3, 2))
if re(z).is_positive:
return z/sqrt(3) * (besseli(-tt, a) + besseli(tt, a))
else:
a = Pow(z, Rational(3, 2))
b = Pow(a, tt)
c = Pow(a, -tt)
return sqrt(ot) * (b*besseli(-tt, tt*a) + z**2*c*besseli(tt, tt*a))
def _eval_rewrite_as_hyper(self, z, **kwargs):
pf1 = z**2 / (2*root(3, 6)*gamma(Rational(2, 3)))
pf2 = root(3, 6) / gamma(Rational(1, 3))
return pf1 * hyper([], [Rational(5, 3)], z**3/9) + pf2 * hyper([], [Rational(1, 3)], z**3/9)
def _eval_expand_func(self, **hints):
arg = self.args[0]
symbs = arg.free_symbols
if len(symbs) == 1:
z = symbs.pop()
c = Wild("c", exclude=[z])
d = Wild("d", exclude=[z])
m = Wild("m", exclude=[z])
n = Wild("n", exclude=[z])
M = arg.match(c*(d*z**n)**m)
if M is not None:
m = M[m]
# The transformation is in principle
# given by 03.08.16.0001.01 but note
# that there is an error in this formula.
# http://functions.wolfram.com/Bessel-TypeFunctions/AiryBiPrime/16/01/01/0001/
if (3*m).is_integer:
c = M[c]
d = M[d]
n = M[n]
pf = (d**m * z**(n*m)) / (d * z**n)**m
newarg = c * d**m * z**(n*m)
return S.Half * (sqrt(3)*(pf - S.One)*airyaiprime(newarg) + (pf + S.One)*airybiprime(newarg))
class marcumq(Function):
r"""
The Marcum Q-function.
Explanation
===========
The Marcum Q-function is defined by the meromorphic continuation of
.. math::
Q_m(a, b) = a^{- m + 1} \int_{b}^{\infty} x^{m} e^{- \frac{a^{2}}{2} - \frac{x^{2}}{2}} I_{m - 1}\left(a x\right)\, dx
Examples
========
>>> from sympy import marcumq
>>> from sympy.abc import m, a, b
>>> marcumq(m, a, b)
marcumq(m, a, b)
Special values:
>>> marcumq(m, 0, b)
uppergamma(m, b**2/2)/gamma(m)
>>> marcumq(0, 0, 0)
0
>>> marcumq(0, a, 0)
1 - exp(-a**2/2)
>>> marcumq(1, a, a)
1/2 + exp(-a**2)*besseli(0, a**2)/2
>>> marcumq(2, a, a)
1/2 + exp(-a**2)*besseli(0, a**2)/2 + exp(-a**2)*besseli(1, a**2)
Differentiation with respect to $a$ and $b$ is supported:
>>> from sympy import diff
>>> diff(marcumq(m, a, b), a)
a*(-marcumq(m, a, b) + marcumq(m + 1, a, b))
>>> diff(marcumq(m, a, b), b)
-a**(1 - m)*b**m*exp(-a**2/2 - b**2/2)*besseli(m - 1, a*b)
References
==========
.. [1] https://en.wikipedia.org/wiki/Marcum_Q-function
.. [2] http://mathworld.wolfram.com/MarcumQ-Function.html
"""
@classmethod
def eval(cls, m, a, b):
if a is S.Zero:
if m is S.Zero and b is S.Zero:
return S.Zero
return uppergamma(m, b**2 * S.Half) / gamma(m)
if m is S.Zero and b is S.Zero:
return 1 - 1 / exp(a**2 * S.Half)
if a == b:
if m is S.One:
return (1 + exp(-a**2) * besseli(0, a**2))*S.Half
if m == 2:
return S.Half + S.Half * exp(-a**2) * besseli(0, a**2) + exp(-a**2) * besseli(1, a**2)
if a.is_zero:
if m.is_zero and b.is_zero:
return S.Zero
return uppergamma(m, b**2*S.Half) / gamma(m)
if m.is_zero and b.is_zero:
return 1 - 1 / exp(a**2*S.Half)
def fdiff(self, argindex=2):
m, a, b = self.args
if argindex == 2:
return a * (-marcumq(m, a, b) + marcumq(1+m, a, b))
elif argindex == 3:
return (-b**m / a**(m-1)) * exp(-(a**2 + b**2)/2) * besseli(m-1, a*b)
else:
raise ArgumentIndexError(self, argindex)
def _eval_rewrite_as_Integral(self, m, a, b, **kwargs):
from sympy.integrals.integrals import Integral
x = kwargs.get('x', Dummy('x'))
return a ** (1 - m) * \
Integral(x**m * exp(-(x**2 + a**2)/2) * besseli(m-1, a*x), [x, b, S.Infinity])
def _eval_rewrite_as_Sum(self, m, a, b, **kwargs):
from sympy.concrete.summations import Sum
k = kwargs.get('k', Dummy('k'))
return exp(-(a**2 + b**2) / 2) * Sum((a/b)**k * besseli(k, a*b), [k, 1-m, S.Infinity])
def _eval_rewrite_as_besseli(self, m, a, b, **kwargs):
if a == b:
if m == 1:
return (1 + exp(-a**2) * besseli(0, a**2)) / 2
if m.is_Integer and m >= 2:
s = sum([besseli(i, a**2) for i in range(1, m)])
return S.Half + exp(-a**2) * besseli(0, a**2) / 2 + exp(-a**2) * s
def _eval_is_zero(self):
if all(arg.is_zero for arg in self.args):
return True
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