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"""
Primality testing
"""
from itertools import count
from sympy.core.sympify import sympify
from sympy.external.gmpy import (gmpy as _gmpy, gcd, jacobi,
is_square as gmpy_is_square,
bit_scan1, is_fermat_prp, is_euler_prp,
is_selfridge_prp, is_strong_selfridge_prp,
is_strong_bpsw_prp)
from sympy.external.ntheory import _lucas_sequence
from sympy.utilities.misc import as_int, filldedent
# Note: This list should be updated whenever new Mersenne primes are found.
# Refer: https://www.mersenne.org/
MERSENNE_PRIME_EXPONENTS = (2, 3, 5, 7, 13, 17, 19, 31, 61, 89, 107, 127, 521, 607, 1279, 2203,
2281, 3217, 4253, 4423, 9689, 9941, 11213, 19937, 21701, 23209, 44497, 86243, 110503, 132049,
216091, 756839, 859433, 1257787, 1398269, 2976221, 3021377, 6972593, 13466917, 20996011, 24036583,
25964951, 30402457, 32582657, 37156667, 42643801, 43112609, 57885161, 74207281, 77232917, 82589933)
def is_fermat_pseudoprime(n, a):
r"""Returns True if ``n`` is prime or is an odd composite integer that
is coprime to ``a`` and satisfy the modular arithmetic congruence relation:
.. math ::
a^{n-1} \equiv 1 \pmod{n}
(where mod refers to the modulo operation).
Parameters
==========
n : Integer
``n`` is a positive integer.
a : Integer
``a`` is a positive integer.
``a`` and ``n`` should be relatively prime.
Returns
=======
bool : If ``n`` is prime, it always returns ``True``.
The composite number that returns ``True`` is called an Fermat pseudoprime.
Examples
========
>>> from sympy.ntheory.primetest import is_fermat_pseudoprime
>>> from sympy.ntheory.factor_ import isprime
>>> for n in range(1, 1000):
... if is_fermat_pseudoprime(n, 2) and not isprime(n):
... print(n)
341
561
645
References
==========
.. [1] https://en.wikipedia.org/wiki/Fermat_pseudoprime
"""
n, a = as_int(n), as_int(a)
if a == 1:
return n == 2 or bool(n % 2)
return is_fermat_prp(n, a)
def is_euler_pseudoprime(n, a):
r"""Returns True if ``n`` is prime or is an odd composite integer that
is coprime to ``a`` and satisfy the modular arithmetic congruence relation:
.. math ::
a^{(n-1)/2} \equiv \pm 1 \pmod{n}
(where mod refers to the modulo operation).
Parameters
==========
n : Integer
``n`` is a positive integer.
a : Integer
``a`` is a positive integer.
``a`` and ``n`` should be relatively prime.
Returns
=======
bool : If ``n`` is prime, it always returns ``True``.
The composite number that returns ``True`` is called an Euler pseudoprime.
Examples
========
>>> from sympy.ntheory.primetest import is_euler_pseudoprime
>>> from sympy.ntheory.factor_ import isprime
>>> for n in range(1, 1000):
... if is_euler_pseudoprime(n, 2) and not isprime(n):
... print(n)
341
561
References
==========
.. [1] https://en.wikipedia.org/wiki/Euler_pseudoprime
"""
n, a = as_int(n), as_int(a)
if a < 1:
raise ValueError("a should be an integer greater than 0")
if n < 1:
raise ValueError("n should be an integer greater than 0")
if n == 1:
return False
if a == 1:
return n == 2 or bool(n % 2) # (prime or odd composite)
if n % 2 == 0:
return n == 2
if gcd(n, a) != 1:
raise ValueError("The two numbers should be relatively prime")
return pow(a, (n - 1) // 2, n) in [1, n - 1]
def is_euler_jacobi_pseudoprime(n, a):
r"""Returns True if ``n`` is prime or is an odd composite integer that
is coprime to ``a`` and satisfy the modular arithmetic congruence relation:
.. math ::
a^{(n-1)/2} \equiv \left(\frac{a}{n}\right) \pmod{n}
(where mod refers to the modulo operation).
Parameters
==========
n : Integer
``n`` is a positive integer.
a : Integer
``a`` is a positive integer.
``a`` and ``n`` should be relatively prime.
Returns
=======
bool : If ``n`` is prime, it always returns ``True``.
The composite number that returns ``True`` is called an Euler-Jacobi pseudoprime.
Examples
========
>>> from sympy.ntheory.primetest import is_euler_jacobi_pseudoprime
>>> from sympy.ntheory.factor_ import isprime
>>> for n in range(1, 1000):
... if is_euler_jacobi_pseudoprime(n, 2) and not isprime(n):
... print(n)
561
References
==========
.. [1] https://en.wikipedia.org/wiki/Euler%E2%80%93Jacobi_pseudoprime
"""
n, a = as_int(n), as_int(a)
if a == 1:
return n == 2 or bool(n % 2)
return is_euler_prp(n, a)
def is_square(n, prep=True):
"""Return True if n == a * a for some integer a, else False.
If n is suspected of *not* being a square then this is a
quick method of confirming that it is not.
Examples
========
>>> from sympy.ntheory.primetest import is_square
>>> is_square(25)
True
>>> is_square(2)
False
References
==========
.. [1] https://mersenneforum.org/showpost.php?p=110896
See Also
========
sympy.core.intfunc.isqrt
"""
if prep:
n = as_int(n)
if n < 0:
return False
if n in (0, 1):
return True
return gmpy_is_square(n)
def _test(n, base, s, t):
"""Miller-Rabin strong pseudoprime test for one base.
Return False if n is definitely composite, True if n is
probably prime, with a probability greater than 3/4.
"""
# do the Fermat test
b = pow(base, t, n)
if b == 1 or b == n - 1:
return True
for _ in range(s - 1):
b = pow(b, 2, n)
if b == n - 1:
return True
# see I. Niven et al. "An Introduction to Theory of Numbers", page 78
if b == 1:
return False
return False
def mr(n, bases):
"""Perform a Miller-Rabin strong pseudoprime test on n using a
given list of bases/witnesses.
References
==========
.. [1] Richard Crandall & Carl Pomerance (2005), "Prime Numbers:
A Computational Perspective", Springer, 2nd edition, 135-138
A list of thresholds and the bases they require are here:
https://en.wikipedia.org/wiki/Miller%E2%80%93Rabin_primality_test#Deterministic_variants
Examples
========
>>> from sympy.ntheory.primetest import mr
>>> mr(1373651, [2, 3])
False
>>> mr(479001599, [31, 73])
True
"""
from sympy.polys.domains import ZZ
n = as_int(n)
if n < 2:
return False
# remove powers of 2 from n-1 (= t * 2**s)
s = bit_scan1(n - 1)
t = n >> s
for base in bases:
# Bases >= n are wrapped, bases < 2 are invalid
if base >= n:
base %= n
if base >= 2:
base = ZZ(base)
if not _test(n, base, s, t):
return False
return True
def _lucas_extrastrong_params(n):
"""Calculates the "extra strong" parameters (D, P, Q) for n.
Parameters
==========
n : int
positive odd integer
Returns
=======
D, P, Q: "extra strong" parameters.
``(0, 0, 0)`` if we find a nontrivial divisor of ``n``.
Examples
========
>>> from sympy.ntheory.primetest import _lucas_extrastrong_params
>>> _lucas_extrastrong_params(101)
(12, 4, 1)
>>> _lucas_extrastrong_params(15)
(0, 0, 0)
References
==========
.. [1] OEIS A217719: Extra Strong Lucas Pseudoprimes
https://oeis.org/A217719
.. [2] https://en.wikipedia.org/wiki/Lucas_pseudoprime
"""
for P in count(3):
D = P**2 - 4
j = jacobi(D, n)
if j == -1:
return (D, P, 1)
elif j == 0 and D % n:
return (0, 0, 0)
def is_lucas_prp(n):
"""Standard Lucas compositeness test with Selfridge parameters. Returns
False if n is definitely composite, and True if n is a Lucas probable
prime.
This is typically used in combination with the Miller-Rabin test.
References
==========
.. [1] Robert Baillie, Samuel S. Wagstaff, Lucas Pseudoprimes,
Math. Comp. Vol 35, Number 152 (1980), pp. 1391-1417,
https://doi.org/10.1090%2FS0025-5718-1980-0583518-6
http://mpqs.free.fr/LucasPseudoprimes.pdf
.. [2] OEIS A217120: Lucas Pseudoprimes
https://oeis.org/A217120
.. [3] https://en.wikipedia.org/wiki/Lucas_pseudoprime
Examples
========
>>> from sympy.ntheory.primetest import isprime, is_lucas_prp
>>> for i in range(10000):
... if is_lucas_prp(i) and not isprime(i):
... print(i)
323
377
1159
1829
3827
5459
5777
9071
9179
"""
n = as_int(n)
if n < 2:
return False
return is_selfridge_prp(n)
def is_strong_lucas_prp(n):
"""Strong Lucas compositeness test with Selfridge parameters. Returns
False if n is definitely composite, and True if n is a strong Lucas
probable prime.
This is often used in combination with the Miller-Rabin test, and
in particular, when combined with M-R base 2 creates the strong BPSW test.
References
==========
.. [1] Robert Baillie, Samuel S. Wagstaff, Lucas Pseudoprimes,
Math. Comp. Vol 35, Number 152 (1980), pp. 1391-1417,
https://doi.org/10.1090%2FS0025-5718-1980-0583518-6
http://mpqs.free.fr/LucasPseudoprimes.pdf
.. [2] OEIS A217255: Strong Lucas Pseudoprimes
https://oeis.org/A217255
.. [3] https://en.wikipedia.org/wiki/Lucas_pseudoprime
.. [4] https://en.wikipedia.org/wiki/Baillie-PSW_primality_test
Examples
========
>>> from sympy.ntheory.primetest import isprime, is_strong_lucas_prp
>>> for i in range(20000):
... if is_strong_lucas_prp(i) and not isprime(i):
... print(i)
5459
5777
10877
16109
18971
"""
n = as_int(n)
if n < 2:
return False
return is_strong_selfridge_prp(n)
def is_extra_strong_lucas_prp(n):
"""Extra Strong Lucas compositeness test. Returns False if n is
definitely composite, and True if n is an "extra strong" Lucas probable
prime.
The parameters are selected using P = 3, Q = 1, then incrementing P until
(D|n) == -1. The test itself is as defined in [1]_, from the
Mo and Jones preprint. The parameter selection and test are the same as
used in OEIS A217719, Perl's Math::Prime::Util, and the Lucas pseudoprime
page on Wikipedia.
It is 20-50% faster than the strong test.
Because of the different parameters selected, there is no relationship
between the strong Lucas pseudoprimes and extra strong Lucas pseudoprimes.
In particular, one is not a subset of the other.
References
==========
.. [1] Jon Grantham, Frobenius Pseudoprimes,
Math. Comp. Vol 70, Number 234 (2001), pp. 873-891,
https://doi.org/10.1090%2FS0025-5718-00-01197-2
.. [2] OEIS A217719: Extra Strong Lucas Pseudoprimes
https://oeis.org/A217719
.. [3] https://en.wikipedia.org/wiki/Lucas_pseudoprime
Examples
========
>>> from sympy.ntheory.primetest import isprime, is_extra_strong_lucas_prp
>>> for i in range(20000):
... if is_extra_strong_lucas_prp(i) and not isprime(i):
... print(i)
989
3239
5777
10877
"""
# Implementation notes:
# 1) the parameters differ from Thomas R. Nicely's. His parameter
# selection leads to pseudoprimes that overlap M-R tests, and
# contradict Baillie and Wagstaff's suggestion of (D|n) = -1.
# 2) The MathWorld page as of June 2013 specifies Q=-1. The Lucas
# sequence must have Q=1. See Grantham theorem 2.3, any of the
# references on the MathWorld page, or run it and see Q=-1 is wrong.
n = as_int(n)
if n == 2:
return True
if n < 2 or (n % 2) == 0:
return False
if gmpy_is_square(n):
return False
D, P, Q = _lucas_extrastrong_params(n)
if D == 0:
return False
# remove powers of 2 from n+1 (= k * 2**s)
s = bit_scan1(n + 1)
k = (n + 1) >> s
U, V, _ = _lucas_sequence(n, P, Q, k)
if U == 0 and (V == 2 or V == n - 2):
return True
for _ in range(1, s):
if V == 0:
return True
V = (V*V - 2) % n
return False
def proth_test(n):
r""" Test if the Proth number `n = k2^m + 1` is prime. where k is a positive odd number and `2^m > k`.
Parameters
==========
n : Integer
``n`` is Proth number
Returns
=======
bool : If ``True``, then ``n`` is the Proth prime
Raises
======
ValueError
If ``n`` is not Proth number.
Examples
========
>>> from sympy.ntheory.primetest import proth_test
>>> proth_test(41)
True
>>> proth_test(57)
False
References
==========
.. [1] https://en.wikipedia.org/wiki/Proth_prime
"""
n = as_int(n)
if n < 3:
raise ValueError("n is not Proth number")
m = bit_scan1(n - 1)
k = n >> m
if m < k.bit_length():
raise ValueError("n is not Proth number")
if n % 3 == 0:
return n == 3
if k % 3: # n % 12 == 5
return pow(3, n >> 1, n) == n - 1
# If `n` is a square number, then `jacobi(a, n) = 1` for any `a`
if gmpy_is_square(n):
return False
# `a` may be chosen at random.
# In any case, we want to find `a` such that `jacobi(a, n) = -1`.
for a in range(5, n):
j = jacobi(a, n)
if j == -1:
return pow(a, n >> 1, n) == n - 1
if j == 0:
return False
def _lucas_lehmer_primality_test(p):
r""" Test if the Mersenne number `M_p = 2^p-1` is prime.
Parameters
==========
p : int
``p`` is an odd prime number
Returns
=======
bool : If ``True``, then `M_p` is the Mersenne prime
Examples
========
>>> from sympy.ntheory.primetest import _lucas_lehmer_primality_test
>>> _lucas_lehmer_primality_test(5) # 2**5 - 1 = 31 is prime
True
>>> _lucas_lehmer_primality_test(11) # 2**11 - 1 = 2047 is not prime
False
See Also
========
is_mersenne_prime
References
==========
.. [1] https://en.wikipedia.org/wiki/Lucas%E2%80%93Lehmer_primality_test
"""
v = 4
m = 2**p - 1
for _ in range(p - 2):
v = pow(v, 2, m) - 2
return v == 0
def is_mersenne_prime(n):
"""Returns True if ``n`` is a Mersenne prime, else False.
A Mersenne prime is a prime number having the form `2^i - 1`.
Examples
========
>>> from sympy.ntheory.factor_ import is_mersenne_prime
>>> is_mersenne_prime(6)
False
>>> is_mersenne_prime(127)
True
References
==========
.. [1] https://mathworld.wolfram.com/MersennePrime.html
"""
n = as_int(n)
if n < 1:
return False
if n & (n + 1):
# n is not Mersenne number
return False
p = n.bit_length()
if p in MERSENNE_PRIME_EXPONENTS:
return True
if p < 65_000_000 or not isprime(p):
# According to GIMPS, verification was completed on September 19, 2023 for p less than 65 million.
# https://www.mersenne.org/report_milestones/
# If p is composite number, then n=2**p-1 is composite number.
return False
result = _lucas_lehmer_primality_test(p)
if result:
raise ValueError(filldedent('''
This Mersenne Prime, 2^%s - 1, should
be added to SymPy's known values.''' % p))
return result
def isprime(n):
"""
Test if n is a prime number (True) or not (False). For n < 2^64 the
answer is definitive; larger n values have a small probability of actually
being pseudoprimes.
Negative numbers (e.g. -2) are not considered prime.
The first step is looking for trivial factors, which if found enables
a quick return. Next, if the sieve is large enough, use bisection search
on the sieve. For small numbers, a set of deterministic Miller-Rabin
tests are performed with bases that are known to have no counterexamples
in their range. Finally if the number is larger than 2^64, a strong
BPSW test is performed. While this is a probable prime test and we
believe counterexamples exist, there are no known counterexamples.
Examples
========
>>> from sympy.ntheory import isprime
>>> isprime(13)
True
>>> isprime(15)
False
Notes
=====
This routine is intended only for integer input, not numerical
expressions which may represent numbers. Floats are also
rejected as input because they represent numbers of limited
precision. While it is tempting to permit 7.0 to represent an
integer there are errors that may "pass silently" if this is
allowed:
>>> from sympy import Float, S
>>> int(1e3) == 1e3 == 10**3
True
>>> int(1e23) == 1e23
True
>>> int(1e23) == 10**23
False
>>> near_int = 1 + S(1)/10**19
>>> near_int == int(near_int)
False
>>> n = Float(near_int, 10) # truncated by precision
>>> n % 1 == 0
True
>>> n = Float(near_int, 20)
>>> n % 1 == 0
False
See Also
========
sympy.ntheory.generate.primerange : Generates all primes in a given range
sympy.functions.combinatorial.numbers.primepi : Return the number of primes less than or equal to n
sympy.ntheory.generate.prime : Return the nth prime
References
==========
.. [1] https://en.wikipedia.org/wiki/Strong_pseudoprime
.. [2] Robert Baillie, Samuel S. Wagstaff, Lucas Pseudoprimes,
Math. Comp. Vol 35, Number 152 (1980), pp. 1391-1417,
https://doi.org/10.1090%2FS0025-5718-1980-0583518-6
http://mpqs.free.fr/LucasPseudoprimes.pdf
.. [3] https://en.wikipedia.org/wiki/Baillie-PSW_primality_test
"""
n = as_int(n)
# Step 1, do quick composite testing via trial division. The individual
# modulo tests benchmark faster than one or two primorial igcds for me.
# The point here is just to speedily handle small numbers and many
# composites. Step 2 only requires that n <= 2 get handled here.
if n in [2, 3, 5]:
return True
if n < 2 or (n % 2) == 0 or (n % 3) == 0 or (n % 5) == 0:
return False
if n < 49:
return True
if (n % 7) == 0 or (n % 11) == 0 or (n % 13) == 0 or (n % 17) == 0 or \
(n % 19) == 0 or (n % 23) == 0 or (n % 29) == 0 or (n % 31) == 0 or \
(n % 37) == 0 or (n % 41) == 0 or (n % 43) == 0 or (n % 47) == 0:
return False
if n < 2809:
return True
if n < 65077:
# There are only five Euler pseudoprimes with a least prime factor greater than 47
return pow(2, n >> 1, n) in [1, n - 1] and n not in [8321, 31621, 42799, 49141, 49981]
# bisection search on the sieve if the sieve is large enough
from sympy.ntheory.generate import sieve as s
if n <= s._list[-1]:
l, u = s.search(n)
return l == u
# If we have GMPY2, skip straight to step 3 and do a strong BPSW test.
# This should be a bit faster than our step 2, and for large values will
# be a lot faster than our step 3 (C+GMP vs. Python).
if _gmpy is not None:
return is_strong_bpsw_prp(n)
# Step 2: deterministic Miller-Rabin testing for numbers < 2^64. See:
# https://miller-rabin.appspot.com/
# for lists. We have made sure the M-R routine will successfully handle
# bases larger than n, so we can use the minimal set.
# In September 2015 deterministic numbers were extended to over 2^81.
# https://arxiv.org/pdf/1509.00864.pdf
# https://oeis.org/A014233
if n < 341531:
return mr(n, [9345883071009581737])
if n < 885594169:
return mr(n, [725270293939359937, 3569819667048198375])
if n < 350269456337:
return mr(n, [4230279247111683200, 14694767155120705706, 16641139526367750375])
if n < 55245642489451:
return mr(n, [2, 141889084524735, 1199124725622454117, 11096072698276303650])
if n < 7999252175582851:
return mr(n, [2, 4130806001517, 149795463772692060, 186635894390467037, 3967304179347715805])
if n < 585226005592931977:
return mr(n, [2, 123635709730000, 9233062284813009, 43835965440333360, 761179012939631437, 1263739024124850375])
if n < 18446744073709551616:
return mr(n, [2, 325, 9375, 28178, 450775, 9780504, 1795265022])
if n < 318665857834031151167461:
return mr(n, [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37])
if n < 3317044064679887385961981:
return mr(n, [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41])
# We could do this instead at any point:
#if n < 18446744073709551616:
# return mr(n, [2]) and is_extra_strong_lucas_prp(n)
# Here are tests that are safe for MR routines that don't understand
# large bases.
#if n < 9080191:
# return mr(n, [31, 73])
#if n < 19471033:
# return mr(n, [2, 299417])
#if n < 38010307:
# return mr(n, [2, 9332593])
#if n < 316349281:
# return mr(n, [11000544, 31481107])
#if n < 4759123141:
# return mr(n, [2, 7, 61])
#if n < 105936894253:
# return mr(n, [2, 1005905886, 1340600841])
#if n < 31858317218647:
# return mr(n, [2, 642735, 553174392, 3046413974])
#if n < 3071837692357849:
# return mr(n, [2, 75088, 642735, 203659041, 3613982119])
#if n < 18446744073709551616:
# return mr(n, [2, 325, 9375, 28178, 450775, 9780504, 1795265022])
# Step 3: BPSW.
#
# Time for isprime(10**2000 + 4561), no gmpy or gmpy2 installed
# 44.0s old isprime using 46 bases
# 5.3s strong BPSW + one random base
# 4.3s extra strong BPSW + one random base
# 4.1s strong BPSW
# 3.2s extra strong BPSW
# Classic BPSW from page 1401 of the paper. See alternate ideas below.
return is_strong_bpsw_prp(n)
# Using extra strong test, which is somewhat faster
#return mr(n, [2]) and is_extra_strong_lucas_prp(n)
# Add a random M-R base
#import random
#return mr(n, [2, random.randint(3, n-1)]) and is_strong_lucas_prp(n)
def is_gaussian_prime(num):
r"""Test if num is a Gaussian prime number.
References
==========
.. [1] https://oeis.org/wiki/Gaussian_primes
"""
num = sympify(num)
a, b = num.as_real_imag()
a = as_int(a, strict=False)
b = as_int(b, strict=False)
if a == 0:
b = abs(b)
return isprime(b) and b % 4 == 3
elif b == 0:
a = abs(a)
return isprime(a) and a % 4 == 3
return isprime(a**2 + b**2)