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deb48411e12af050d66625a13379fb60af1e3737ca57dcc41fafee210506964a | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
# The idea for this module (but no code) was borrowed from the
# quantities (http://pythonhosted.org/quantities/) package.
"""Helper functions for Quantity.
In particular, this implements the logic that determines scaling and result
units for a given ufunc, given input units.
"""
from fractions import Fraction
import numpy as np
from . import UFUNC_HELPERS, UNSUPPORTED_UFUNCS
from astropy.units.core import (
UnitsError, UnitConversionError, UnitTypeError,
dimensionless_unscaled, get_current_unit_registry)
def _d(unit):
if unit is None:
return dimensionless_unscaled
else:
return unit
def get_converter(from_unit, to_unit):
"""Like Unit._get_converter, except returns None if no scaling is needed,
i.e., if the inferred scale is unity."""
try:
scale = from_unit._to(to_unit)
except UnitsError:
return from_unit._apply_equivalencies(
from_unit, to_unit, get_current_unit_registry().equivalencies)
except AttributeError:
raise UnitTypeError("Unit '{0}' cannot be converted to '{1}'"
.format(from_unit, to_unit))
if scale == 1.:
return None
else:
return lambda val: scale * val
def get_converters_and_unit(f, unit1, unit2):
converters = [None, None]
# By default, we try adjusting unit2 to unit1, so that the result will
# be unit1 as well. But if there is no second unit, we have to try
# adjusting unit1 (to dimensionless, see below).
if unit2 is None:
if unit1 is None:
# No units for any input -- e.g., np.add(a1, a2, out=q)
return converters, dimensionless_unscaled
changeable = 0
# swap units.
unit2 = unit1
unit1 = None
elif unit2 is unit1:
# ensure identical units is fast ("==" is slow, so avoid that).
return converters, unit1
else:
changeable = 1
# Try to get a converter from unit2 to unit1.
if unit1 is None:
try:
converters[changeable] = get_converter(unit2,
dimensionless_unscaled)
except UnitsError:
# special case: would be OK if unitless number is zero, inf, nan
converters[1-changeable] = False
return converters, unit2
else:
return converters, dimensionless_unscaled
else:
try:
converters[changeable] = get_converter(unit2, unit1)
except UnitsError:
raise UnitConversionError(
"Can only apply '{0}' function to quantities "
"with compatible dimensions"
.format(f.__name__))
return converters, unit1
# SINGLE ARGUMENT UFUNC HELPERS
#
# The functions below take a single argument, which is the quantity upon which
# the ufunc is being used. The output of the helper function should be two
# values: a list with a single converter to be used to scale the input before
# it is being passed to the ufunc (or None if no conversion is needed), and
# the unit the output will be in.
def helper_onearg_test(f, unit):
return ([None], None)
def helper_invariant(f, unit):
return ([None], _d(unit))
def helper_square(f, unit):
return ([None], unit ** 2 if unit is not None else dimensionless_unscaled)
def helper_reciprocal(f, unit):
return ([None], unit ** -1 if unit is not None else dimensionless_unscaled)
one_half = 0.5 # faster than Fraction(1, 2)
one_third = Fraction(1, 3)
def helper_sqrt(f, unit):
return ([None], unit ** one_half if unit is not None
else dimensionless_unscaled)
def helper_cbrt(f, unit):
return ([None], (unit ** one_third if unit is not None
else dimensionless_unscaled))
def helper_modf(f, unit):
if unit is None:
return [None], (dimensionless_unscaled, dimensionless_unscaled)
try:
return ([get_converter(unit, dimensionless_unscaled)],
(dimensionless_unscaled, dimensionless_unscaled))
except UnitsError:
raise UnitTypeError("Can only apply '{0}' function to "
"dimensionless quantities"
.format(f.__name__))
def helper__ones_like(f, unit):
return [None], dimensionless_unscaled
def helper_dimensionless_to_dimensionless(f, unit):
if unit is None:
return [None], dimensionless_unscaled
try:
return ([get_converter(unit, dimensionless_unscaled)],
dimensionless_unscaled)
except UnitsError:
raise UnitTypeError("Can only apply '{0}' function to "
"dimensionless quantities"
.format(f.__name__))
def helper_dimensionless_to_radian(f, unit):
from astropy.units.si import radian
if unit is None:
return [None], radian
try:
return [get_converter(unit, dimensionless_unscaled)], radian
except UnitsError:
raise UnitTypeError("Can only apply '{0}' function to "
"dimensionless quantities"
.format(f.__name__))
def helper_degree_to_radian(f, unit):
from astropy.units.si import degree, radian
try:
return [get_converter(unit, degree)], radian
except UnitsError:
raise UnitTypeError("Can only apply '{0}' function to "
"quantities with angle units"
.format(f.__name__))
def helper_radian_to_degree(f, unit):
from astropy.units.si import degree, radian
try:
return [get_converter(unit, radian)], degree
except UnitsError:
raise UnitTypeError("Can only apply '{0}' function to "
"quantities with angle units"
.format(f.__name__))
def helper_radian_to_dimensionless(f, unit):
from astropy.units.si import radian
try:
return [get_converter(unit, radian)], dimensionless_unscaled
except UnitsError:
raise UnitTypeError("Can only apply '{0}' function to "
"quantities with angle units"
.format(f.__name__))
def helper_frexp(f, unit):
if not unit.is_unity():
raise UnitTypeError("Can only apply '{0}' function to "
"unscaled dimensionless quantities"
.format(f.__name__))
return [None], (None, None)
# TWO ARGUMENT UFUNC HELPERS
#
# The functions below take a two arguments. The output of the helper function
# should be two values: a tuple of two converters to be used to scale the
# inputs before being passed to the ufunc (None if no conversion is needed),
# and the unit the output will be in.
def helper_multiplication(f, unit1, unit2):
return [None, None], _d(unit1) * _d(unit2)
def helper_division(f, unit1, unit2):
return [None, None], _d(unit1) / _d(unit2)
def helper_power(f, unit1, unit2):
# TODO: find a better way to do this, currently need to signal that one
# still needs to raise power of unit1 in main code
if unit2 is None:
return [None, None], False
try:
return [None, get_converter(unit2, dimensionless_unscaled)], False
except UnitsError:
raise UnitTypeError("Can only raise something to a "
"dimensionless quantity")
def helper_ldexp(f, unit1, unit2):
if unit2 is not None:
raise TypeError("Cannot use ldexp with a quantity "
"as second argument.")
else:
return [None, None], _d(unit1)
def helper_copysign(f, unit1, unit2):
# if first arg is not a quantity, just return plain array
if unit1 is None:
return [None, None], None
else:
return [None, None], unit1
def helper_heaviside(f, unit1, unit2):
try:
converter2 = (get_converter(unit2, dimensionless_unscaled)
if unit2 is not None else None)
except UnitsError:
raise UnitTypeError("Can only apply 'heaviside' function with a "
"dimensionless second argument.")
return ([None, converter2], dimensionless_unscaled)
def helper_two_arg_dimensionless(f, unit1, unit2):
try:
converter1 = (get_converter(unit1, dimensionless_unscaled)
if unit1 is not None else None)
converter2 = (get_converter(unit2, dimensionless_unscaled)
if unit2 is not None else None)
except UnitsError:
raise UnitTypeError("Can only apply '{0}' function to "
"dimensionless quantities"
.format(f.__name__))
return ([converter1, converter2], dimensionless_unscaled)
# This used to be a separate function that just called get_converters_and_unit.
# Using it directly saves a few us; keeping the clearer name.
helper_twoarg_invariant = get_converters_and_unit
def helper_twoarg_comparison(f, unit1, unit2):
converters, _ = get_converters_and_unit(f, unit1, unit2)
return converters, None
def helper_twoarg_invtrig(f, unit1, unit2):
from astropy.units.si import radian
converters, _ = get_converters_and_unit(f, unit1, unit2)
return converters, radian
def helper_twoarg_floor_divide(f, unit1, unit2):
converters, _ = get_converters_and_unit(f, unit1, unit2)
return converters, dimensionless_unscaled
def helper_divmod(f, unit1, unit2):
converters, result_unit = get_converters_and_unit(f, unit1, unit2)
return converters, (dimensionless_unscaled, result_unit)
# list of ufuncs:
# http://docs.scipy.org/doc/numpy/reference/ufuncs.html#available-ufuncs
UNSUPPORTED_UFUNCS |= {
np.bitwise_and, np.bitwise_or, np.bitwise_xor, np.invert, np.left_shift,
np.right_shift, np.logical_and, np.logical_or, np.logical_xor,
np.logical_not}
for name in 'isnat', 'gcd', 'lcm':
# isnat was introduced in numpy 1.14, gcd+lcm in 1.15
ufunc = getattr(np, name, None)
if isinstance(ufunc, np.ufunc):
UNSUPPORTED_UFUNCS |= {ufunc}
# SINGLE ARGUMENT UFUNCS
# ufuncs that return a boolean and do not care about the unit
onearg_test_ufuncs = (np.isfinite, np.isinf, np.isnan, np.sign, np.signbit)
for ufunc in onearg_test_ufuncs:
UFUNC_HELPERS[ufunc] = helper_onearg_test
# ufuncs that return a value with the same unit as the input
invariant_ufuncs = (np.absolute, np.fabs, np.conj, np.conjugate, np.negative,
np.spacing, np.rint, np.floor, np.ceil, np.trunc,
np.positive)
for ufunc in invariant_ufuncs:
UFUNC_HELPERS[ufunc] = helper_invariant
# ufuncs that require dimensionless input and and give dimensionless output
dimensionless_to_dimensionless_ufuncs = (np.exp, np.expm1, np.exp2, np.log,
np.log10, np.log2, np.log1p)
# As found out in gh-7058, some numpy 1.13 conda installations also provide
# np.erf, even though upstream doesn't have it. We include it if present.
if isinstance(getattr(np.core.umath, 'erf', None), np.ufunc):
dimensionless_to_dimensionless_ufuncs += (np.core.umath.erf,)
for ufunc in dimensionless_to_dimensionless_ufuncs:
UFUNC_HELPERS[ufunc] = helper_dimensionless_to_dimensionless
# ufuncs that require dimensionless input and give output in radians
dimensionless_to_radian_ufuncs = (np.arccos, np.arcsin, np.arctan, np.arccosh,
np.arcsinh, np.arctanh)
for ufunc in dimensionless_to_radian_ufuncs:
UFUNC_HELPERS[ufunc] = helper_dimensionless_to_radian
# ufuncs that require input in degrees and give output in radians
degree_to_radian_ufuncs = (np.radians, np.deg2rad)
for ufunc in degree_to_radian_ufuncs:
UFUNC_HELPERS[ufunc] = helper_degree_to_radian
# ufuncs that require input in radians and give output in degrees
radian_to_degree_ufuncs = (np.degrees, np.rad2deg)
for ufunc in radian_to_degree_ufuncs:
UFUNC_HELPERS[ufunc] = helper_radian_to_degree
# ufuncs that require input in radians and give dimensionless output
radian_to_dimensionless_ufuncs = (np.cos, np.sin, np.tan, np.cosh, np.sinh,
np.tanh)
for ufunc in radian_to_dimensionless_ufuncs:
UFUNC_HELPERS[ufunc] = helper_radian_to_dimensionless
# ufuncs handled as special cases
UFUNC_HELPERS[np.sqrt] = helper_sqrt
UFUNC_HELPERS[np.square] = helper_square
UFUNC_HELPERS[np.reciprocal] = helper_reciprocal
UFUNC_HELPERS[np.cbrt] = helper_cbrt
UFUNC_HELPERS[np.core.umath._ones_like] = helper__ones_like
UFUNC_HELPERS[np.modf] = helper_modf
UFUNC_HELPERS[np.frexp] = helper_frexp
# TWO ARGUMENT UFUNCS
# two argument ufuncs that require dimensionless input and and give
# dimensionless output
two_arg_dimensionless_ufuncs = (np.logaddexp, np.logaddexp2)
for ufunc in two_arg_dimensionless_ufuncs:
UFUNC_HELPERS[ufunc] = helper_two_arg_dimensionless
# two argument ufuncs that return a value with the same unit as the input
twoarg_invariant_ufuncs = (np.add, np.subtract, np.hypot, np.maximum,
np.minimum, np.fmin, np.fmax, np.nextafter,
np.remainder, np.mod, np.fmod)
for ufunc in twoarg_invariant_ufuncs:
UFUNC_HELPERS[ufunc] = helper_twoarg_invariant
# two argument ufuncs that need compatible inputs and return a boolean
twoarg_comparison_ufuncs = (np.greater, np.greater_equal, np.less,
np.less_equal, np.not_equal, np.equal)
for ufunc in twoarg_comparison_ufuncs:
UFUNC_HELPERS[ufunc] = helper_twoarg_comparison
# two argument ufuncs that do inverse trigonometry
twoarg_invtrig_ufuncs = (np.arctan2,)
# another private function in numpy; use getattr in case it disappears
if isinstance(getattr(np.core.umath, '_arg', None), np.ufunc):
twoarg_invtrig_ufuncs += (np.core.umath._arg,)
for ufunc in twoarg_invtrig_ufuncs:
UFUNC_HELPERS[ufunc] = helper_twoarg_invtrig
# ufuncs handled as special cases
UFUNC_HELPERS[np.multiply] = helper_multiplication
if isinstance(getattr(np, 'matmul', None), np.ufunc):
UFUNC_HELPERS[np.matmul] = helper_multiplication
UFUNC_HELPERS[np.divide] = helper_division
UFUNC_HELPERS[np.true_divide] = helper_division
UFUNC_HELPERS[np.power] = helper_power
UFUNC_HELPERS[np.ldexp] = helper_ldexp
UFUNC_HELPERS[np.copysign] = helper_copysign
UFUNC_HELPERS[np.floor_divide] = helper_twoarg_floor_divide
UFUNC_HELPERS[np.heaviside] = helper_heaviside
UFUNC_HELPERS[np.float_power] = helper_power
UFUNC_HELPERS[np.divmod] = helper_divmod
|
e614e891d5169b4e5b13399b520b575c25aa225470975978e531e5ba2c461bf7 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Converters for Quantity."""
import numpy as np
from astropy.units.core import (UnitsError, UnitConversionError, UnitTypeError,
dimensionless_unscaled)
__all__ = ['can_have_arbitrary_unit', 'converters_and_unit',
'check_output', 'UFUNC_HELPERS', 'UNSUPPORTED_UFUNCS']
class UfuncHelpers(dict):
"""Registry of unit conversion functions to help ufunc evaluation.
Based on dict for quick access, but with a missing method to load
helpers for additional modules such as scipy.special and erfa.
Such modules should be registered using ``register_module``.
"""
UNSUPPORTED = set()
def register_module(self, module, names, importer):
"""Register (but do not import) a set of ufunc helpers.
Parameters
----------
module : str
Name of the module with the ufuncs (e.g., 'scipy.special').
names : iterable of str
Names of the module ufuncs for which helpers are available.
importer : callable
Function that imports the ufuncs and returns a dict of helpers
keyed by those ufuncs. If the value is `None`, the ufunc is
explicitly *not* supported.
"""
self.modules[module] = {'names': names,
'importer': importer}
@property
def modules(self):
"""Modules for which helpers are available (but not yet loaded)."""
if not hasattr(self, '_modules'):
self._modules = {}
return self._modules
def import_module(self, module):
"""Import the helpers from the given module using its helper function.
Parameters
----------
module : str
Name of the module. Has to have been registered beforehand.
"""
module_info = self.modules.pop(module)
self.update(module_info['importer']())
def __missing__(self, ufunc):
"""Called if a ufunc is not found.
Check if the ufunc is in any of the available modules, and, if so,
import the helpers for that module.
"""
if ufunc in self.UNSUPPORTED:
raise TypeError("Cannot use ufunc '{0}' with quantities"
.format(ufunc.__name__))
for module, module_info in list(self.modules.items()):
if ufunc.__name__ in module_info['names']:
# A ufunc with the same name is supported by this module.
# Of course, this doesn't necessarily mean it is the
# right module. So, we try let the importer do its work.
# If it fails (e.g., for `scipy.special`), then that's
# fine, just raise the TypeError. If it succeeds, but
# the ufunc is not found, that is also fine: we will
# enter __missing__ again and either find another
# module or get the TypeError there.
try:
self.import_module(module)
except ImportError:
pass
else:
return self[ufunc]
raise TypeError("unknown ufunc {0}. If you believe this ufunc "
"should be supported, please raise an issue on "
"https://github.com/astropy/astropy"
.format(ufunc.__name__))
def __setitem__(self, key, value):
# Implementation note: in principle, we could just let `None`
# mean that something is not implemented, but this means an
# extra if clause for the output, slowing down the common
# path where a ufunc is supported.
if value is None:
self.UNSUPPORTED |= {key}
self.pop(key, None)
else:
super().__setitem__(key, value)
self.UNSUPPORTED -= {key}
UFUNC_HELPERS = UfuncHelpers()
UNSUPPORTED_UFUNCS = UFUNC_HELPERS.UNSUPPORTED
def can_have_arbitrary_unit(value):
"""Test whether the items in value can have arbitrary units
Numbers whose value does not change upon a unit change, i.e.,
zero, infinity, or not-a-number
Parameters
----------
value : number or array
Returns
-------
`True` if each member is either zero or not finite, `False` otherwise
"""
return np.all(np.logical_or(np.equal(value, 0.), ~np.isfinite(value)))
def converters_and_unit(function, method, *args):
"""Determine the required converters and the unit of the ufunc result.
Converters are functions required to convert to a ufunc's expected unit,
e.g., radian for np.sin; or to ensure units of two inputs are consistent,
e.g., for np.add. In these examples, the unit of the result would be
dimensionless_unscaled for np.sin, and the same consistent unit for np.add.
Parameters
----------
function : `~numpy.ufunc`
Numpy universal function
method : str
Method with which the function is evaluated, e.g.,
'__call__', 'reduce', etc.
*args : Quantity or other ndarray subclass
Input arguments to the function
Raises
------
TypeError : when the specified function cannot be used with Quantities
(e.g., np.logical_or), or when the routine does not know how to handle
the specified function (in which case an issue should be raised on
https://github.com/astropy/astropy).
UnitTypeError : when the conversion to the required (or consistent) units
is not possible.
"""
# Check whether we support this ufunc, by getting the helper function
# (defined in helpers) which returns a list of function(s) that convert the
# input(s) to the unit required for the ufunc, as well as the unit the
# result will have (a tuple of units if there are multiple outputs).
ufunc_helper = UFUNC_HELPERS[function]
if method == '__call__' or (method == 'outer' and function.nin == 2):
# Find out the units of the arguments passed to the ufunc; usually,
# at least one is a quantity, but for two-argument ufuncs, the second
# could also be a Numpy array, etc. These are given unit=None.
units = [getattr(arg, 'unit', None) for arg in args]
# Determine possible conversion functions, and the result unit.
converters, result_unit = ufunc_helper(function, *units)
if any(converter is False for converter in converters):
# for two-argument ufuncs with a quantity and a non-quantity,
# the quantity normally needs to be dimensionless, *except*
# if the non-quantity can have arbitrary unit, i.e., when it
# is all zero, infinity or NaN. In that case, the non-quantity
# can just have the unit of the quantity
# (this allows, e.g., `q > 0.` independent of unit)
maybe_arbitrary_arg = args[converters.index(False)]
try:
if can_have_arbitrary_unit(maybe_arbitrary_arg):
converters = [None, None]
else:
raise UnitConversionError(
"Can only apply '{0}' function to "
"dimensionless quantities when other "
"argument is not a quantity (unless the "
"latter is all zero/infinity/nan)"
.format(function.__name__))
except TypeError:
# _can_have_arbitrary_unit failed: arg could not be compared
# with zero or checked to be finite. Then, ufunc will fail too.
raise TypeError("Unsupported operand type(s) for ufunc {0}: "
"'{1}' and '{2}'"
.format(function.__name__,
args[0].__class__.__name__,
args[1].__class__.__name__))
# In the case of np.power and np.float_power, the unit itself needs to
# be modified by an amount that depends on one of the input values,
# so we need to treat this as a special case.
# TODO: find a better way to deal with this.
if result_unit is False:
if units[0] is None or units[0] == dimensionless_unscaled:
result_unit = dimensionless_unscaled
else:
if units[1] is None:
p = args[1]
else:
p = args[1].to(dimensionless_unscaled).value
try:
result_unit = units[0] ** p
except ValueError as exc:
# Changing the unit does not work for, e.g., array-shaped
# power, but this is OK if we're (scaled) dimensionless.
try:
converters[0] = units[0]._get_converter(
dimensionless_unscaled)
except UnitConversionError:
raise exc
else:
result_unit = dimensionless_unscaled
else: # methods for which the unit should stay the same
nin = function.nin
unit = getattr(args[0], 'unit', None)
if method == 'at' and nin <= 2:
if nin == 1:
units = [unit]
else:
units = [unit, getattr(args[2], 'unit', None)]
converters, result_unit = ufunc_helper(function, *units)
# ensure there is no 'converter' for indices (2nd argument)
converters.insert(1, None)
elif method in {'reduce', 'accumulate', 'reduceat'} and nin == 2:
converters, result_unit = ufunc_helper(function, unit, unit)
converters = converters[:1]
if method == 'reduceat':
# add 'scale' for indices (2nd argument)
converters += [None]
else:
if method in {'reduce', 'accumulate',
'reduceat', 'outer'} and nin != 2:
raise ValueError("{0} only supported for binary functions"
.format(method))
raise TypeError("Unexpected ufunc method {0}. If this should "
"work, please raise an issue on"
"https://github.com/astropy/astropy"
.format(method))
# for all but __call__ method, scaling is not allowed
if unit is not None and result_unit is None:
raise TypeError("Cannot use '{1}' method on ufunc {0} with a "
"Quantity instance as the result is not a "
"Quantity.".format(function.__name__, method))
if (converters[0] is not None or
(unit is not None and unit is not result_unit and
(not result_unit.is_equivalent(unit) or
result_unit.to(unit) != 1.))):
# NOTE: this cannot be the more logical UnitTypeError, since
# then things like np.cumprod will not longer fail (they check
# for TypeError).
raise UnitsError("Cannot use '{1}' method on ufunc {0} with a "
"Quantity instance as it would change the unit."
.format(function.__name__, method))
return converters, result_unit
def check_output(output, unit, inputs, function=None):
"""Check that function output can be stored in the output array given.
Parameters
----------
output : array or `~astropy.units.Quantity` or tuple
Array that should hold the function output (or tuple of such arrays).
unit : `~astropy.units.Unit` or None, or tuple
Unit that the output will have, or `None` for pure numbers (should be
tuple of same if output is a tuple of outputs).
inputs : tuple
Any input arguments. These should be castable to the output.
function : callable
The function that will be producing the output. If given, used to
give a more informative error message.
Returns
-------
arrays : `~numpy.ndarray` view of ``output`` (or tuple of such views).
Raises
------
UnitTypeError : If ``unit`` is inconsistent with the class of ``output``
TypeError : If the ``inputs`` cannot be cast safely to ``output``.
"""
if isinstance(output, tuple):
return tuple(check_output(output_, unit_, inputs, function)
for output_, unit_ in zip(output, unit))
# ``None`` indicates no actual array is needed. This can happen, e.g.,
# with np.modf(a, out=(None, b)).
if output is None:
return None
if hasattr(output, '__quantity_subclass__'):
# Check that we're not trying to store a plain Numpy array or a
# Quantity with an inconsistent unit (e.g., not angular for Angle).
if unit is None:
raise TypeError("Cannot store non-quantity output{0} in {1} "
"instance".format(
(" from {0} function".format(function.__name__)
if function is not None else ""),
type(output)))
if output.__quantity_subclass__(unit)[0] is not type(output):
raise UnitTypeError(
"Cannot store output with unit '{0}'{1} "
"in {2} instance. Use {3} instance instead."
.format(unit, (" from {0} function".format(function.__name__)
if function is not None else ""), type(output),
output.__quantity_subclass__(unit)[0]))
# Turn into ndarray, so we do not loop into array_wrap/array_ufunc
# if the output is used to store results of a function.
output = output.view(np.ndarray)
else:
# output is not a Quantity, so cannot obtain a unit.
if not (unit is None or unit is dimensionless_unscaled):
raise UnitTypeError("Cannot store quantity with dimension "
"{0}in a non-Quantity instance."
.format("" if function is None else
"resulting from {0} function "
.format(function.__name__)))
# check we can handle the dtype (e.g., that we are not int
# when float is required).
if not np.can_cast(np.result_type(*inputs), output.dtype,
casting='same_kind'):
raise TypeError("Arguments cannot be cast safely to inplace "
"output with dtype={0}".format(output.dtype))
return output
|
a0a4850efbfdfecac31d9c2d49fb372eb5863c0d2617e3d56bb02460dd8b81e2 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Helper functions for Quantity.
In particular, this implements the logic that determines scaling and result
units for a given ufunc, given input units.
"""
from .converters import *
# By importing helpers, all the unit conversion functions needed for
# numpy ufuncs are defined.
from . import helpers
# For scipy.special and erfa, importing the helper modules ensures
# the definitions are added as modules to UFUNC_HELPERS, to be loaded
# on demand.
from . import scipy_special, erfa
|
8b9401e22dc418f0ec2c65fec5ea3ee16fc4e49f0385b3ba7b99c4bc725006c5 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Quantity helpers for the ERFA ufuncs."""
from astropy.units.core import UnitsError, UnitTypeError, dimensionless_unscaled
from . import UFUNC_HELPERS
from .helpers import get_converter, helper_invariant, helper_multiplication
erfa_ufuncs = ('s2c', 's2p', 'c2s', 'p2s', 'pm', 'pdp', 'pxp', 'rxp')
def helper_s2c(f, unit1, unit2):
from astropy.units.si import radian
try:
return [get_converter(unit1, radian),
get_converter(unit2, radian)], dimensionless_unscaled
except UnitsError:
raise UnitTypeError("Can only apply '{0}' function to "
"quantities with angle units"
.format(f.__name__))
def helper_s2p(f, unit1, unit2, unit3):
from astropy.units.si import radian
try:
return [get_converter(unit1, radian),
get_converter(unit2, radian), None], unit3
except UnitsError:
raise UnitTypeError("Can only apply '{0}' function to "
"quantities with angle units"
.format(f.__name__))
def helper_c2s(f, unit1):
from astropy.units.si import radian
return [None], (radian, radian)
def helper_p2s(f, unit1):
from astropy.units.si import radian
return [None], (radian, radian, unit1)
def get_erfa_helpers():
from astropy._erfa import ufunc as erfa_ufunc
ERFA_HELPERS = {}
ERFA_HELPERS[erfa_ufunc.s2c] = helper_s2c
ERFA_HELPERS[erfa_ufunc.s2p] = helper_s2p
ERFA_HELPERS[erfa_ufunc.c2s] = helper_c2s
ERFA_HELPERS[erfa_ufunc.p2s] = helper_p2s
ERFA_HELPERS[erfa_ufunc.pm] = helper_invariant
ERFA_HELPERS[erfa_ufunc.pdp] = helper_multiplication
ERFA_HELPERS[erfa_ufunc.pxp] = helper_multiplication
ERFA_HELPERS[erfa_ufunc.rxp] = helper_multiplication
return ERFA_HELPERS
UFUNC_HELPERS.register_module('astropy._erfa.ufunc', erfa_ufuncs,
get_erfa_helpers)
|
5210581995ebb4c0cbf166f86115ed744fa73cefdd06523814ab66b4903574d9 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Quantity helpers for the scipy.special ufuncs.
Available ufuncs in this module are at
https://docs.scipy.org/doc/scipy/reference/special.html
"""
from astropy.units.core import UnitsError, UnitTypeError, dimensionless_unscaled
from . import UFUNC_HELPERS
from .helpers import (get_converter,
helper_dimensionless_to_dimensionless,
helper_cbrt,
helper_two_arg_dimensionless)
# ufuncs that require dimensionless input and give dimensionless output.
dimensionless_to_dimensionless_sps_ufuncs = (
'erf', 'gamma', 'gammasgn', 'psi', 'rgamma', 'erfc', 'erfcx', 'erfi',
'wofz', 'dawsn', 'entr', 'exprel', 'expm1', 'log1p', 'exp2', 'exp10',
'j0', 'j1', 'y0', 'y1', 'i0', 'i0e', 'i1', 'i1e',
'k0', 'k0e', 'k1', 'k1e', 'itj0y0', 'it2j0y0', 'iti0k0', 'it2i0k0',
'loggamma')
scipy_special_ufuncs = dimensionless_to_dimensionless_sps_ufuncs
# ufuncs that require input in degrees and give dimensionless output.
degree_to_dimensionless_sps_ufuncs = ('cosdg', 'sindg', 'tandg', 'cotdg')
scipy_special_ufuncs += degree_to_dimensionless_sps_ufuncs
# ufuncs that require 2 dimensionless inputs and give dimensionless output.
# note: 'jv' and 'jn' are aliases in some scipy versions, which will
# cause the same key to be written twice, but since both are handled by the
# same helper there is no harm done.
two_arg_dimensionless_sps_ufuncs = (
'jv', 'jn', 'jve', 'yn', 'yv', 'yve', 'kn', 'kv', 'kve', 'iv', 'ive',
'hankel1', 'hankel1e', 'hankel2', 'hankel2e')
scipy_special_ufuncs += two_arg_dimensionless_sps_ufuncs
# ufuncs handled as special cases
scipy_special_ufuncs += ('cbrt', 'radian')
def helper_degree_to_dimensionless(f, unit):
from astropy.units.si import degree
try:
return [get_converter(unit, degree)], dimensionless_unscaled
except UnitsError:
raise UnitTypeError("Can only apply '{0}' function to "
"quantities with angle units"
.format(f.__name__))
def helper_degree_minute_second_to_radian(f, unit1, unit2, unit3):
from astropy.units.si import degree, arcmin, arcsec, radian
try:
return [get_converter(unit1, degree),
get_converter(unit2, arcmin),
get_converter(unit3, arcsec)], radian
except UnitsError:
raise UnitTypeError("Can only apply '{0}' function to "
"quantities with angle units"
.format(f.__name__))
def get_scipy_special_helpers():
import scipy.special as sps
SCIPY_HELPERS = {}
for name in dimensionless_to_dimensionless_sps_ufuncs:
# TODO: Revert https://github.com/astropy/astropy/pull/7219 when
# astropy requires scipy>=0.18, and loggamma is guaranteed
# to exist.
# See https://github.com/astropy/astropy/issues/7159
ufunc = getattr(sps, name, None)
if ufunc:
SCIPY_HELPERS[ufunc] = helper_dimensionless_to_dimensionless
for ufunc in degree_to_dimensionless_sps_ufuncs:
SCIPY_HELPERS[getattr(sps, ufunc)] = helper_degree_to_dimensionless
for ufunc in two_arg_dimensionless_sps_ufuncs:
SCIPY_HELPERS[getattr(sps, ufunc)] = helper_two_arg_dimensionless
# ufuncs handled as special cases
SCIPY_HELPERS[sps.cbrt] = helper_cbrt
SCIPY_HELPERS[sps.radian] = helper_degree_minute_second_to_radian
return SCIPY_HELPERS
UFUNC_HELPERS.register_module('scipy.special', scipy_special_ufuncs,
get_scipy_special_helpers)
|
a3c54f2d0a97188a826cc8afab5e04e323d9d2378764caaac074a3aa77099560 | # coding: utf-8
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Separate tests specifically for equivalencies."""
# THIRD-PARTY
import warnings
import pytest
import numpy as np
from numpy.testing import assert_allclose
# LOCAL
from astropy import units as u
from astropy.units.equivalencies import Equivalency
from astropy import constants, cosmology
from astropy.tests.helper import assert_quantity_allclose
def test_dimensionless_angles():
# test that the angles_dimensionless option allows one to change
# by any order in radian in the unit (#1161)
rad1 = u.dimensionless_angles()
assert u.radian.to(1, equivalencies=rad1) == 1.
assert u.deg.to(1, equivalencies=rad1) == u.deg.to(u.rad)
assert u.steradian.to(1, equivalencies=rad1) == 1.
assert u.dimensionless_unscaled.to(u.steradian, equivalencies=rad1) == 1.
# now quantities
assert (1.*u.radian).to_value(1, equivalencies=rad1) == 1.
assert (1.*u.deg).to_value(1, equivalencies=rad1) == u.deg.to(u.rad)
assert (1.*u.steradian).to_value(1, equivalencies=rad1) == 1.
# more complicated example
I = 1.e45 * u.g * u.cm**2
Omega = u.cycle / (1.*u.s)
Erot = 0.5 * I * Omega**2
# check that equivalency makes this work
Erot_in_erg1 = Erot.to(u.erg, equivalencies=rad1)
# and check that value is correct
assert_allclose(Erot_in_erg1.value, (Erot/u.radian**2).to_value(u.erg))
# test build-in equivalency in subclass
class MyRad1(u.Quantity):
_equivalencies = rad1
phase = MyRad1(1., u.cycle)
assert phase.to_value(1) == u.cycle.to(u.radian)
@pytest.mark.parametrize('log_unit', (u.mag, u.dex, u.dB))
def test_logarithmic(log_unit):
# check conversion of mag, dB, and dex to dimensionless and vice versa
with pytest.raises(u.UnitsError):
log_unit.to(1, 0.)
with pytest.raises(u.UnitsError):
u.dimensionless_unscaled.to(log_unit)
assert log_unit.to(1, 0., equivalencies=u.logarithmic()) == 1.
assert u.dimensionless_unscaled.to(log_unit,
equivalencies=u.logarithmic()) == 0.
# also try with quantities
q_dex = np.array([0., -1., 1., 2.]) * u.dex
q_expected = 10.**q_dex.value * u.dimensionless_unscaled
q_log_unit = q_dex.to(log_unit)
assert np.all(q_log_unit.to(1, equivalencies=u.logarithmic()) ==
q_expected)
assert np.all(q_expected.to(log_unit, equivalencies=u.logarithmic()) ==
q_log_unit)
with u.set_enabled_equivalencies(u.logarithmic()):
assert np.all(np.abs(q_log_unit - q_expected.to(log_unit)) <
1.e-10*log_unit)
doppler_functions = [u.doppler_optical, u.doppler_radio, u.doppler_relativistic]
@pytest.mark.parametrize(('function'), doppler_functions)
def test_doppler_frequency_0(function):
rest = 105.01 * u.GHz
velo0 = rest.to(u.km/u.s, equivalencies=function(rest))
assert velo0.value == 0
@pytest.mark.parametrize(('function'), doppler_functions)
def test_doppler_wavelength_0(function):
rest = 105.01 * u.GHz
q1 = 0.00285489437196 * u.m
velo0 = q1.to(u.km/u.s, equivalencies=function(rest))
np.testing.assert_almost_equal(velo0.value, 0, decimal=6)
@pytest.mark.parametrize(('function'), doppler_functions)
def test_doppler_energy_0(function):
rest = 105.01 * u.GHz
q1 = 0.0004342864612223407 * u.eV
velo0 = q1.to(u.km/u.s, equivalencies=function(rest))
np.testing.assert_almost_equal(velo0.value, 0, decimal=6)
@pytest.mark.parametrize(('function'), doppler_functions)
def test_doppler_frequency_circle(function):
rest = 105.01 * u.GHz
shifted = 105.03 * u.GHz
velo = shifted.to(u.km/u.s, equivalencies=function(rest))
freq = velo.to(u.GHz, equivalencies=function(rest))
np.testing.assert_almost_equal(freq.value, shifted.value, decimal=7)
@pytest.mark.parametrize(('function'), doppler_functions)
def test_doppler_wavelength_circle(function):
rest = 105.01 * u.nm
shifted = 105.03 * u.nm
velo = shifted.to(u.km / u.s, equivalencies=function(rest))
wav = velo.to(u.nm, equivalencies=function(rest))
np.testing.assert_almost_equal(wav.value, shifted.value, decimal=7)
@pytest.mark.parametrize(('function'), doppler_functions)
def test_doppler_energy_circle(function):
rest = 1.0501 * u.eV
shifted = 1.0503 * u.eV
velo = shifted.to(u.km / u.s, equivalencies=function(rest))
en = velo.to(u.eV, equivalencies=function(rest))
np.testing.assert_almost_equal(en.value, shifted.value, decimal=7)
values_ghz = (999.899940784289, 999.8999307714406, 999.8999357778647)
@pytest.mark.parametrize(('function', 'value'),
list(zip(doppler_functions, values_ghz)))
def test_30kms(function, value):
rest = 1000 * u.GHz
velo = 30 * u.km/u.s
shifted = velo.to(u.GHz, equivalencies=function(rest))
np.testing.assert_almost_equal(shifted.value, value, decimal=7)
bad_values = (5, 5*u.Jy, None)
@pytest.mark.parametrize(('function', 'value'),
list(zip(doppler_functions, bad_values)))
def test_bad_restfreqs(function, value):
with pytest.raises(u.UnitsError):
function(value)
def test_massenergy():
# The relative tolerance of these tests is set by the uncertainties
# in the charge of the electron, which is known to about
# 3e-9 (relative tolerance). Therefore, we limit the
# precision of the tests to 1e-7 to be safe. The masses are
# (loosely) known to ~ 5e-8 rel tolerance, so we couldn't test to
# 1e-7 if we used the values from astropy.constants; that is,
# they might change by more than 1e-7 in some future update, so instead
# they are hardwired here.
# Electron, proton, neutron, muon, 1g
mass_eV = u.Quantity([510.998928e3, 938.272046e6, 939.565378e6,
105.6583715e6, 5.60958884539e32], u.eV)
mass_g = u.Quantity([9.10938291e-28, 1.672621777e-24, 1.674927351e-24,
1.88353147e-25, 1], u.g)
# Test both ways
assert np.allclose(mass_eV.to_value(u.g, equivalencies=u.mass_energy()),
mass_g.value, rtol=1e-7)
assert np.allclose(mass_g.to_value(u.eV, equivalencies=u.mass_energy()),
mass_eV.value, rtol=1e-7)
# Basic tests of 'derived' equivalencies
# Surface density
sdens_eV = u.Quantity(5.60958884539e32, u.eV / u.m**2)
sdens_g = u.Quantity(1e-4, u.g / u.cm**2)
assert np.allclose(sdens_eV.to_value(u.g / u.cm**2,
equivalencies=u.mass_energy()),
sdens_g.value, rtol=1e-7)
assert np.allclose(sdens_g.to_value(u.eV / u.m**2,
equivalencies=u.mass_energy()),
sdens_eV.value, rtol=1e-7)
# Density
dens_eV = u.Quantity(5.60958884539e32, u.eV / u.m**3)
dens_g = u.Quantity(1e-6, u.g / u.cm**3)
assert np.allclose(dens_eV.to_value(u.g / u.cm**3,
equivalencies=u.mass_energy()),
dens_g.value, rtol=1e-7)
assert np.allclose(dens_g.to_value(u.eV / u.m**3,
equivalencies=u.mass_energy()),
dens_eV.value, rtol=1e-7)
# Power
pow_eV = u.Quantity(5.60958884539e32, u.eV / u.s)
pow_g = u.Quantity(1, u.g / u.s)
assert np.allclose(pow_eV.to_value(u.g / u.s,
equivalencies=u.mass_energy()),
pow_g.value, rtol=1e-7)
assert np.allclose(pow_g.to_value(u.eV / u.s,
equivalencies=u.mass_energy()),
pow_eV.value, rtol=1e-7)
def test_is_equivalent():
assert u.m.is_equivalent(u.pc)
assert u.cycle.is_equivalent(u.mas)
assert not u.cycle.is_equivalent(u.dimensionless_unscaled)
assert u.cycle.is_equivalent(u.dimensionless_unscaled,
u.dimensionless_angles())
assert not (u.Hz.is_equivalent(u.J))
assert u.Hz.is_equivalent(u.J, u.spectral())
assert u.J.is_equivalent(u.Hz, u.spectral())
assert u.pc.is_equivalent(u.arcsecond, u.parallax())
assert u.arcminute.is_equivalent(u.au, u.parallax())
# Pass a tuple for multiple possibilities
assert u.cm.is_equivalent((u.m, u.s, u.kg))
assert u.ms.is_equivalent((u.m, u.s, u.kg))
assert u.g.is_equivalent((u.m, u.s, u.kg))
assert not u.L.is_equivalent((u.m, u.s, u.kg))
assert not (u.km / u.s).is_equivalent((u.m, u.s, u.kg))
def test_parallax():
a = u.arcsecond.to(u.pc, 10, u.parallax())
assert_allclose(a, 0.10)
b = u.pc.to(u.arcsecond, a, u.parallax())
assert_allclose(b, 10)
a = u.arcminute.to(u.au, 1, u.parallax())
assert_allclose(a, 3437.7467916)
b = u.au.to(u.arcminute, a, u.parallax())
assert_allclose(b, 1)
val = (-1 * u.mas).to(u.pc, u.parallax())
assert np.isnan(val.value)
val = (-1 * u.mas).to_value(u.pc, u.parallax())
assert np.isnan(val)
def test_parallax2():
a = u.arcsecond.to(u.pc, [0.1, 2.5], u.parallax())
assert_allclose(a, [10, 0.4])
def test_spectral():
a = u.AA.to(u.Hz, 1, u.spectral())
assert_allclose(a, 2.9979245799999995e+18)
b = u.Hz.to(u.AA, a, u.spectral())
assert_allclose(b, 1)
a = u.AA.to(u.MHz, 1, u.spectral())
assert_allclose(a, 2.9979245799999995e+12)
b = u.MHz.to(u.AA, a, u.spectral())
assert_allclose(b, 1)
a = u.m.to(u.Hz, 1, u.spectral())
assert_allclose(a, 2.9979245799999995e+8)
b = u.Hz.to(u.m, a, u.spectral())
assert_allclose(b, 1)
def test_spectral2():
a = u.nm.to(u.J, 500, u.spectral())
assert_allclose(a, 3.972891366538605e-19)
b = u.J.to(u.nm, a, u.spectral())
assert_allclose(b, 500)
a = u.AA.to(u.Hz, 1, u.spectral())
b = u.Hz.to(u.J, a, u.spectral())
c = u.AA.to(u.J, 1, u.spectral())
assert_allclose(b, c)
c = u.J.to(u.Hz, b, u.spectral())
assert_allclose(a, c)
def test_spectral3():
a = u.nm.to(u.Hz, [1000, 2000], u.spectral())
assert_allclose(a, [2.99792458e+14, 1.49896229e+14])
@pytest.mark.parametrize(
('in_val', 'in_unit'),
[([0.1, 5000.0, 10000.0], u.AA),
([1e+5, 2.0, 1.0], u.micron ** -1),
([2.99792458e+19, 5.99584916e+14, 2.99792458e+14], u.Hz),
([1.98644568e-14, 3.97289137e-19, 1.98644568e-19], u.J)])
def test_spectral4(in_val, in_unit):
"""Wave number conversion w.r.t. wavelength, freq, and energy."""
# Spectroscopic and angular
out_units = [u.micron ** -1, u.radian / u.micron]
answers = [[1e+5, 2.0, 1.0], [6.28318531e+05, 12.5663706, 6.28318531]]
for out_unit, ans in zip(out_units, answers):
# Forward
a = in_unit.to(out_unit, in_val, u.spectral())
assert_allclose(a, ans)
# Backward
b = out_unit.to(in_unit, ans, u.spectral())
assert_allclose(b, in_val)
def test_spectraldensity2():
# flux density
flambda = u.erg / u.angstrom / u.cm ** 2 / u.s
fnu = u.erg / u.Hz / u.cm ** 2 / u.s
a = flambda.to(fnu, 1, u.spectral_density(u.Quantity(3500, u.AA)))
assert_allclose(a, 4.086160166177361e-12)
# luminosity density
llambda = u.erg / u.angstrom / u.s
lnu = u.erg / u.Hz / u.s
a = llambda.to(lnu, 1, u.spectral_density(u.Quantity(3500, u.AA)))
assert_allclose(a, 4.086160166177361e-12)
a = lnu.to(llambda, 1, u.spectral_density(u.Quantity(3500, u.AA)))
assert_allclose(a, 2.44728537142857e11)
def test_spectraldensity3():
# Define F_nu in Jy
f_nu = u.Jy
# Define F_lambda in ergs / cm^2 / s / micron
f_lambda = u.erg / u.cm ** 2 / u.s / u.micron
# 1 GHz
one_ghz = u.Quantity(1, u.GHz)
# Convert to ergs / cm^2 / s / Hz
assert_allclose(f_nu.to(u.erg / u.cm ** 2 / u.s / u.Hz, 1.), 1.e-23, 10)
# Convert to ergs / cm^2 / s at 10 Ghz
assert_allclose(f_nu.to(u.erg / u.cm ** 2 / u.s, 1.,
equivalencies=u.spectral_density(one_ghz * 10)),
1.e-13, 10)
# Convert to F_lambda at 1 Ghz
assert_allclose(f_nu.to(f_lambda, 1.,
equivalencies=u.spectral_density(one_ghz)),
3.335640951981521e-20, 10)
# Convert to Jy at 1 Ghz
assert_allclose(f_lambda.to(u.Jy, 1.,
equivalencies=u.spectral_density(one_ghz)),
1. / 3.335640951981521e-20, 10)
# Convert to ergs / cm^2 / s at 10 microns
assert_allclose(f_lambda.to(u.erg / u.cm ** 2 / u.s, 1.,
equivalencies=u.spectral_density(u.Quantity(10, u.micron))),
10., 10)
def test_spectraldensity4():
"""PHOTLAM and PHOTNU conversions."""
flam = u.erg / (u.cm ** 2 * u.s * u.AA)
fnu = u.erg / (u.cm ** 2 * u.s * u.Hz)
photlam = u.photon / (u.cm ** 2 * u.s * u.AA)
photnu = u.photon / (u.cm ** 2 * u.s * u.Hz)
wave = u.Quantity([4956.8, 4959.55, 4962.3], u.AA)
flux_photlam = [9.7654e-3, 1.003896e-2, 9.78473e-3]
flux_photnu = [8.00335589e-14, 8.23668949e-14, 8.03700310e-14]
flux_flam = [3.9135e-14, 4.0209e-14, 3.9169e-14]
flux_fnu = [3.20735792e-25, 3.29903646e-25, 3.21727226e-25]
flux_jy = [3.20735792e-2, 3.29903646e-2, 3.21727226e-2]
flux_stmag = [12.41858665, 12.38919182, 12.41764379]
flux_abmag = [12.63463143, 12.60403221, 12.63128047]
# PHOTLAM <--> FLAM
assert_allclose(photlam.to(
flam, flux_photlam, u.spectral_density(wave)), flux_flam, rtol=1e-6)
assert_allclose(flam.to(
photlam, flux_flam, u.spectral_density(wave)), flux_photlam, rtol=1e-6)
# PHOTLAM <--> FNU
assert_allclose(photlam.to(
fnu, flux_photlam, u.spectral_density(wave)), flux_fnu, rtol=1e-6)
assert_allclose(fnu.to(
photlam, flux_fnu, u.spectral_density(wave)), flux_photlam, rtol=1e-6)
# PHOTLAM <--> Jy
assert_allclose(photlam.to(
u.Jy, flux_photlam, u.spectral_density(wave)), flux_jy, rtol=1e-6)
assert_allclose(u.Jy.to(
photlam, flux_jy, u.spectral_density(wave)), flux_photlam, rtol=1e-6)
# PHOTLAM <--> PHOTNU
assert_allclose(photlam.to(
photnu, flux_photlam, u.spectral_density(wave)), flux_photnu, rtol=1e-6)
assert_allclose(photnu.to(
photlam, flux_photnu, u.spectral_density(wave)), flux_photlam, rtol=1e-6)
# PHOTNU <--> FNU
assert_allclose(photnu.to(
fnu, flux_photnu, u.spectral_density(wave)), flux_fnu, rtol=1e-6)
assert_allclose(fnu.to(
photnu, flux_fnu, u.spectral_density(wave)), flux_photnu, rtol=1e-6)
# PHOTNU <--> FLAM
assert_allclose(photnu.to(
flam, flux_photnu, u.spectral_density(wave)), flux_flam, rtol=1e-6)
assert_allclose(flam.to(
photnu, flux_flam, u.spectral_density(wave)), flux_photnu, rtol=1e-6)
# PHOTLAM <--> STMAG
assert_allclose(photlam.to(
u.STmag, flux_photlam, u.spectral_density(wave)), flux_stmag, rtol=1e-6)
assert_allclose(u.STmag.to(
photlam, flux_stmag, u.spectral_density(wave)), flux_photlam, rtol=1e-6)
# PHOTLAM <--> ABMAG
assert_allclose(photlam.to(
u.ABmag, flux_photlam, u.spectral_density(wave)), flux_abmag, rtol=1e-6)
assert_allclose(u.ABmag.to(
photlam, flux_abmag, u.spectral_density(wave)), flux_photlam, rtol=1e-6)
def test_spectraldensity5():
""" Test photon luminosity density conversions. """
L_la = u.erg / (u.s * u.AA)
L_nu = u.erg / (u.s * u.Hz)
phot_L_la = u.photon / (u.s * u.AA)
phot_L_nu = u.photon / (u.s * u.Hz)
wave = u.Quantity([4956.8, 4959.55, 4962.3], u.AA)
flux_phot_L_la = [9.7654e-3, 1.003896e-2, 9.78473e-3]
flux_phot_L_nu = [8.00335589e-14, 8.23668949e-14, 8.03700310e-14]
flux_L_la = [3.9135e-14, 4.0209e-14, 3.9169e-14]
flux_L_nu = [3.20735792e-25, 3.29903646e-25, 3.21727226e-25]
# PHOTLAM <--> FLAM
assert_allclose(phot_L_la.to(
L_la, flux_phot_L_la, u.spectral_density(wave)), flux_L_la, rtol=1e-6)
assert_allclose(L_la.to(
phot_L_la, flux_L_la, u.spectral_density(wave)), flux_phot_L_la, rtol=1e-6)
# PHOTLAM <--> FNU
assert_allclose(phot_L_la.to(
L_nu, flux_phot_L_la, u.spectral_density(wave)), flux_L_nu, rtol=1e-6)
assert_allclose(L_nu.to(
phot_L_la, flux_L_nu, u.spectral_density(wave)), flux_phot_L_la, rtol=1e-6)
# PHOTLAM <--> PHOTNU
assert_allclose(phot_L_la.to(
phot_L_nu, flux_phot_L_la, u.spectral_density(wave)), flux_phot_L_nu, rtol=1e-6)
assert_allclose(phot_L_nu.to(
phot_L_la, flux_phot_L_nu, u.spectral_density(wave)), flux_phot_L_la, rtol=1e-6)
# PHOTNU <--> FNU
assert_allclose(phot_L_nu.to(
L_nu, flux_phot_L_nu, u.spectral_density(wave)), flux_L_nu, rtol=1e-6)
assert_allclose(L_nu.to(
phot_L_nu, flux_L_nu, u.spectral_density(wave)), flux_phot_L_nu, rtol=1e-6)
# PHOTNU <--> FLAM
assert_allclose(phot_L_nu.to(
L_la, flux_phot_L_nu, u.spectral_density(wave)), flux_L_la, rtol=1e-6)
assert_allclose(L_la.to(
phot_L_nu, flux_L_la, u.spectral_density(wave)), flux_phot_L_nu, rtol=1e-6)
def test_equivalent_units():
from astropy.units import imperial
with u.add_enabled_units(imperial):
units = u.g.find_equivalent_units()
units_set = set(units)
match = set(
[u.M_e, u.M_p, u.g, u.kg, u.solMass, u.t, u.u, u.M_earth,
u.M_jup, imperial.oz, imperial.lb, imperial.st, imperial.ton,
imperial.slug])
assert units_set == match
r = repr(units)
assert r.count('\n') == len(units) + 2
def test_equivalent_units2():
units = set(u.Hz.find_equivalent_units(u.spectral()))
match = set(
[u.AU, u.Angstrom, u.Hz, u.J, u.Ry, u.cm, u.eV, u.erg, u.lyr,
u.m, u.micron, u.pc, u.solRad, u.Bq, u.Ci, u.k, u.earthRad,
u.jupiterRad])
assert units == match
from astropy.units import imperial
with u.add_enabled_units(imperial):
units = set(u.Hz.find_equivalent_units(u.spectral()))
match = set(
[u.AU, u.Angstrom, imperial.BTU, u.Hz, u.J, u.Ry,
imperial.cal, u.cm, u.eV, u.erg, imperial.ft, imperial.fur,
imperial.inch, imperial.kcal, u.lyr, u.m, imperial.mi,
imperial.mil, u.micron, u.pc, u.solRad, imperial.yd, u.Bq, u.Ci,
imperial.nmi, u.k, u.earthRad, u.jupiterRad])
assert units == match
units = set(u.Hz.find_equivalent_units(u.spectral()))
match = set(
[u.AU, u.Angstrom, u.Hz, u.J, u.Ry, u.cm, u.eV, u.erg, u.lyr,
u.m, u.micron, u.pc, u.solRad, u.Bq, u.Ci, u.k, u.earthRad,
u.jupiterRad])
assert units == match
def test_trivial_equivalency():
assert u.m.to(u.kg, equivalencies=[(u.m, u.kg)]) == 1.0
def test_invalid_equivalency():
with pytest.raises(ValueError):
u.m.to(u.kg, equivalencies=[(u.m,)])
with pytest.raises(ValueError):
u.m.to(u.kg, equivalencies=[(u.m, 5.0)])
def test_irrelevant_equivalency():
with pytest.raises(u.UnitsError):
u.m.to(u.kg, equivalencies=[(u.m, u.l)])
def test_brightness_temperature():
omega_B = np.pi * (50 * u.arcsec) ** 2
nu = u.GHz * 5
tb = 7.052590289134352 * u.K
np.testing.assert_almost_equal(
tb.value, (1 * u.Jy).to_value(
u.K, equivalencies=u.brightness_temperature(nu, beam_area=omega_B)))
np.testing.assert_almost_equal(
1.0, tb.to_value(
u.Jy, equivalencies=u.brightness_temperature(nu, beam_area=omega_B)))
def test_swapped_args_brightness_temperature():
"""
#5173 changes the order of arguments but accepts the old (deprecated) args
"""
omega_B = np.pi * (50 * u.arcsec) ** 2
nu = u.GHz * 5
tb = 7.052590289134352 * u.K
# https://docs.pytest.org/en/latest/warnings.html#ensuring-function-triggers
with warnings.catch_warnings():
warnings.simplefilter('always')
with pytest.warns(DeprecationWarning) as warning_list:
result = (1*u.Jy).to(u.K,
equivalencies=u.brightness_temperature(omega_B,
nu))
roundtrip = result.to(u.Jy,
equivalencies=u.brightness_temperature(omega_B,
nu))
assert len(warning_list) == 2
np.testing.assert_almost_equal(tb.value, result.value)
np.testing.assert_almost_equal(roundtrip.value, 1)
def test_surfacebrightness():
sb = 50*u.MJy/u.sr
k = sb.to(u.K, u.brightness_temperature(50*u.GHz))
np.testing.assert_almost_equal(k.value, 0.650965, 5)
assert k.unit.is_equivalent(u.K)
def test_beam():
# pick a beam area: 2 pi r^2 = area of a Gaussina with sigma=50 arcsec
omega_B = 2 * np.pi * (50 * u.arcsec) ** 2
new_beam = (5*u.beam).to(u.sr, u.equivalencies.beam_angular_area(omega_B))
np.testing.assert_almost_equal(omega_B.to(u.sr).value * 5, new_beam.value)
assert new_beam.unit.is_equivalent(u.sr)
# make sure that it's still consistent with 5 beams
nbeams = new_beam.to(u.beam, u.equivalencies.beam_angular_area(omega_B))
np.testing.assert_almost_equal(nbeams.value, 5)
# test inverse beam equivalency
# (this is just a sanity check that the equivalency is defined;
# it's not for testing numerical consistency)
new_inverse_beam = (5/u.beam).to(1/u.sr, u.equivalencies.beam_angular_area(omega_B))
# test practical case
# (this is by far the most important one)
flux_density = (5*u.Jy/u.beam).to(u.MJy/u.sr, u.equivalencies.beam_angular_area(omega_B))
np.testing.assert_almost_equal(flux_density.value, 13.5425483146382)
def test_thermodynamic_temperature():
nu = 143 * u.GHz
tb = 0.0026320518775281975 * u.K
np.testing.assert_almost_equal(
tb.value, (1 * u.MJy/u.sr).to_value(
u.K, equivalencies=u.thermodynamic_temperature(nu, T_cmb=2.7255 * u.K)))
np.testing.assert_almost_equal(
1.0, tb.to_value(
u.MJy / u.sr, equivalencies=u.thermodynamic_temperature(nu, T_cmb=2.7255 * u.K)))
def test_equivalency_context():
with u.set_enabled_equivalencies(u.dimensionless_angles()):
phase = u.Quantity(1., u.cycle)
assert_allclose(np.exp(1j*phase), 1.)
Omega = u.cycle / (1.*u.minute)
assert_allclose(np.exp(1j*Omega*60.*u.second), 1.)
# ensure we can turn off equivalencies even within the scope
with pytest.raises(u.UnitsError):
phase.to(1, equivalencies=None)
# test the manager also works in the Quantity constructor.
q1 = u.Quantity(phase, u.dimensionless_unscaled)
assert_allclose(q1.value, u.cycle.to(u.radian))
# and also if we use a class that happens to have a unit attribute.
class MyQuantityLookalike(np.ndarray):
pass
mylookalike = np.array(1.).view(MyQuantityLookalike)
mylookalike.unit = 'cycle'
# test the manager also works in the Quantity constructor.
q2 = u.Quantity(mylookalike, u.dimensionless_unscaled)
assert_allclose(q2.value, u.cycle.to(u.radian))
with u.set_enabled_equivalencies(u.spectral()):
u.GHz.to(u.cm)
eq_on = u.GHz.find_equivalent_units()
with pytest.raises(u.UnitsError):
u.GHz.to(u.cm, equivalencies=None)
# without equivalencies, we should find a smaller (sub)set
eq_off = u.GHz.find_equivalent_units()
assert all(eq in set(eq_on) for eq in eq_off)
assert set(eq_off) < set(eq_on)
# Check the equivalency manager also works in ufunc evaluations,
# not just using (wrong) scaling. [#2496]
l2v = u.doppler_optical(6000 * u.angstrom)
l1 = 6010 * u.angstrom
assert l1.to(u.km/u.s, equivalencies=l2v) > 100. * u.km / u.s
with u.set_enabled_equivalencies(l2v):
assert l1 > 100. * u.km / u.s
assert abs((l1 - 500. * u.km / u.s).to(u.angstrom)) < 1. * u.km/u.s
def test_equivalency_context_manager():
base_registry = u.get_current_unit_registry()
def just_to_from_units(equivalencies):
return [(equiv[0], equiv[1]) for equiv in equivalencies]
tf_dimensionless_angles = just_to_from_units(u.dimensionless_angles())
tf_spectral = just_to_from_units(u.spectral())
assert base_registry.equivalencies == []
with u.set_enabled_equivalencies(u.dimensionless_angles()):
new_registry = u.get_current_unit_registry()
assert (set(just_to_from_units(new_registry.equivalencies)) ==
set(tf_dimensionless_angles))
assert set(new_registry.all_units) == set(base_registry.all_units)
with u.set_enabled_equivalencies(u.spectral()):
newer_registry = u.get_current_unit_registry()
assert (set(just_to_from_units(newer_registry.equivalencies)) ==
set(tf_spectral))
assert (set(newer_registry.all_units) ==
set(base_registry.all_units))
assert (set(just_to_from_units(new_registry.equivalencies)) ==
set(tf_dimensionless_angles))
assert set(new_registry.all_units) == set(base_registry.all_units)
with u.add_enabled_equivalencies(u.spectral()):
newer_registry = u.get_current_unit_registry()
assert (set(just_to_from_units(newer_registry.equivalencies)) ==
set(tf_dimensionless_angles) | set(tf_spectral))
assert (set(newer_registry.all_units) ==
set(base_registry.all_units))
assert base_registry is u.get_current_unit_registry()
def test_temperature():
from astropy.units.imperial import deg_F
t_k = 0 * u.K
assert_allclose(t_k.to_value(u.deg_C, u.temperature()), -273.15)
assert_allclose(t_k.to_value(deg_F, u.temperature()), -459.67)
def test_temperature_energy():
x = 1000 * u.K
y = (x * constants.k_B).to(u.keV)
assert_allclose(x.to_value(u.keV, u.temperature_energy()), y.value)
assert_allclose(y.to_value(u.K, u.temperature_energy()), x.value)
def test_molar_mass_amu():
x = 1 * (u.g/u.mol)
y = 1 * u.u
assert_allclose(x.to_value(u.u, u.molar_mass_amu()), y.value)
assert_allclose(y.to_value(u.g/u.mol, u.molar_mass_amu()), x.value)
with pytest.raises(u.UnitsError):
x.to(u.u)
def test_compose_equivalencies():
x = u.Unit("arcsec").compose(units=(u.pc,), equivalencies=u.parallax())
assert x[0] == u.pc
x = u.Unit("2 arcsec").compose(units=(u.pc,), equivalencies=u.parallax())
assert x[0] == u.Unit(0.5 * u.pc)
x = u.degree.compose(equivalencies=u.dimensionless_angles())
assert u.Unit(u.degree.to(u.radian)) in x
x = (u.nm).compose(units=(u.m, u.s), equivalencies=u.doppler_optical(0.55*u.micron))
for y in x:
if y.bases == [u.m, u.s]:
assert y.powers == [1, -1]
assert_allclose(
y.scale,
u.nm.to(u.m / u.s, equivalencies=u.doppler_optical(0.55 * u.micron)))
break
else:
assert False, "Didn't find speed in compose results"
def test_pixel_scale():
pix = 75*u.pix
asec = 30*u.arcsec
pixscale = 0.4*u.arcsec/u.pix
pixscale2 = 2.5*u.pix/u.arcsec
assert_quantity_allclose(pix.to(u.arcsec, u.pixel_scale(pixscale)), asec)
assert_quantity_allclose(pix.to(u.arcmin, u.pixel_scale(pixscale)), asec)
assert_quantity_allclose(pix.to(u.arcsec, u.pixel_scale(pixscale2)), asec)
assert_quantity_allclose(pix.to(u.arcmin, u.pixel_scale(pixscale2)), asec)
assert_quantity_allclose(asec.to(u.pix, u.pixel_scale(pixscale)), pix)
assert_quantity_allclose(asec.to(u.pix, u.pixel_scale(pixscale2)), pix)
def test_plate_scale():
mm = 1.5*u.mm
asec = 30*u.arcsec
platescale = 20*u.arcsec/u.mm
platescale2 = 0.05*u.mm/u.arcsec
assert_quantity_allclose(mm.to(u.arcsec, u.plate_scale(platescale)), asec)
assert_quantity_allclose(mm.to(u.arcmin, u.plate_scale(platescale)), asec)
assert_quantity_allclose(mm.to(u.arcsec, u.plate_scale(platescale2)), asec)
assert_quantity_allclose(mm.to(u.arcmin, u.plate_scale(platescale2)), asec)
assert_quantity_allclose(asec.to(u.mm, u.plate_scale(platescale)), mm)
assert_quantity_allclose(asec.to(u.mm, u.plate_scale(platescale2)), mm)
def test_littleh():
H0_70 = 70*u.km/u.s/u.Mpc
h70dist = 70 * u.Mpc/u.littleh
assert_quantity_allclose(h70dist.to(u.Mpc, u.with_H0(H0_70)), 100*u.Mpc)
# make sure using the default cosmology works
cosmodist = cosmology.default_cosmology.get().H0.value * u.Mpc/u.littleh
assert_quantity_allclose(cosmodist.to(u.Mpc, u.with_H0()), 100*u.Mpc)
# Now try a luminosity scaling
h1lum = .49 * u.Lsun * u.littleh**-2
assert_quantity_allclose(h1lum.to(u.Lsun, u.with_H0(H0_70)), 1*u.Lsun)
# And the trickiest one: magnitudes. Using H0=10 here for the round numbers
H0_10 = 10*u.km/u.s/u.Mpc
# assume the "true" magnitude M = 12.
# Then M - 5*log_10(h) = M + 5 = 17
withlittlehmag = 17 * (u.mag - u.MagUnit(u.littleh**2))
assert_quantity_allclose(withlittlehmag.to(u.mag, u.with_H0(H0_10)), 12*u.mag)
def test_equivelency():
ps = u.pixel_scale(10*u.arcsec/u.pix)
assert isinstance(ps, Equivalency)
assert isinstance(ps.name, list)
assert len(ps.name) == 1
assert ps.name[0] == "pixel_scale"
assert isinstance(ps.kwargs, list)
assert len(ps.kwargs) == 1
assert ps.kwargs[0] == dict({'pixscale': 10*u.arcsec/u.pix})
def test_add_equivelencies():
e1 = u.pixel_scale(10*u.arcsec/u.pixel) + u.temperature_energy()
assert isinstance(e1, Equivalency)
assert e1.name == ["pixel_scale", "temperature_energy"]
assert isinstance(e1.kwargs, list)
assert e1.kwargs == [dict({'pixscale': 10*u.arcsec/u.pix}), dict()]
e2 = u.pixel_scale(10*u.arcsec/u.pixel) + [1, 2,3]
assert isinstance(e2, list)
|
04e59b63117ea1ac4b831ec7b350f3ce8154bae96ba94b3aa6c46b145637f917 | # coding: utf-8
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Test utilities for `astropy.units`.
"""
import numpy as np
from numpy import finfo
from astropy.units.utils import sanitize_scale
from astropy.units.utils import quantity_asanyarray
from astropy.units.quantity import Quantity
_float_finfo = finfo(float)
def test_quantity_asanyarray():
array_of_quantities = [Quantity(1), Quantity(2), Quantity(3)]
quantity_array = quantity_asanyarray(array_of_quantities)
assert isinstance(quantity_array, Quantity)
array_of_integers = [1, 2, 3]
np_array = quantity_asanyarray(array_of_integers)
assert isinstance(np_array, np.ndarray)
def test_sanitize_scale():
assert sanitize_scale( complex(2, _float_finfo.eps) ) == 2
assert sanitize_scale( complex(_float_finfo.eps, 2) ) == 2j
|
6b8a327aab5af4942457ee7cb3209e26056f33a035ba3aaf93eaaf296b51dd0d | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import pytest
from astropy import units as u # pylint: disable=W0611
@pytest.mark.parametrize("solarx_unit,solary_unit", [
(u.arcsec, u.arcsec),
('angle', 'angle')])
def test_args3(solarx_unit, solary_unit):
@u.quantity_input
def myfunc_args(solarx: solarx_unit, solary: solary_unit):
return solarx, solary
solarx, solary = myfunc_args(1*u.arcsec, 1*u.arcsec)
assert isinstance(solarx, u.Quantity)
assert isinstance(solary, u.Quantity)
assert solarx.unit == u.arcsec
assert solary.unit == u.arcsec
@pytest.mark.parametrize("solarx_unit,solary_unit", [
(u.arcsec, u.arcsec),
('angle', 'angle')])
def test_args_noconvert3(solarx_unit, solary_unit):
@u.quantity_input()
def myfunc_args(solarx: solarx_unit, solary: solary_unit):
return solarx, solary
solarx, solary = myfunc_args(1*u.deg, 1*u.arcmin)
assert isinstance(solarx, u.Quantity)
assert isinstance(solary, u.Quantity)
assert solarx.unit == u.deg
assert solary.unit == u.arcmin
@pytest.mark.parametrize("solarx_unit", [
u.arcsec, 'angle'])
def test_args_nonquantity3(solarx_unit):
@u.quantity_input
def myfunc_args(solarx: solarx_unit, solary):
return solarx, solary
solarx, solary = myfunc_args(1*u.arcsec, 100)
assert isinstance(solarx, u.Quantity)
assert isinstance(solary, int)
assert solarx.unit == u.arcsec
@pytest.mark.parametrize("solarx_unit,solary_unit", [
(u.arcsec, u.eV),
('angle', 'energy')])
def test_arg_equivalencies3(solarx_unit, solary_unit):
@u.quantity_input(equivalencies=u.mass_energy())
def myfunc_args(solarx: solarx_unit, solary: solary_unit):
return solarx, solary+(10*u.J) # Add an energy to check equiv is working
solarx, solary = myfunc_args(1*u.arcsec, 100*u.gram)
assert isinstance(solarx, u.Quantity)
assert isinstance(solary, u.Quantity)
assert solarx.unit == u.arcsec
assert solary.unit == u.gram
@pytest.mark.parametrize("solarx_unit,solary_unit", [
(u.arcsec, u.deg),
('angle', 'angle')])
def test_wrong_unit3(solarx_unit, solary_unit):
@u.quantity_input
def myfunc_args(solarx: solarx_unit, solary: solary_unit):
return solarx, solary
with pytest.raises(u.UnitsError) as e:
solarx, solary = myfunc_args(1*u.arcsec, 100*u.km)
str_to = str(solary_unit)
assert str(e.value) == "Argument 'solary' to function 'myfunc_args' must be in units convertible to '{0}'.".format(str_to)
@pytest.mark.parametrize("solarx_unit,solary_unit", [
(u.arcsec, u.deg),
('angle', 'angle')])
def test_not_quantity3(solarx_unit, solary_unit):
@u.quantity_input
def myfunc_args(solarx: solarx_unit, solary: solary_unit):
return solarx, solary
with pytest.raises(TypeError) as e:
solarx, solary = myfunc_args(1*u.arcsec, 100)
assert str(e.value) == "Argument 'solary' to function 'myfunc_args' has no 'unit' attribute. You may want to pass in an astropy Quantity instead."
def test_decorator_override():
@u.quantity_input(solarx=u.arcsec)
def myfunc_args(solarx: u.km, solary: u.arcsec):
return solarx, solary
solarx, solary = myfunc_args(1*u.arcsec, 1*u.arcsec)
assert isinstance(solarx, u.Quantity)
assert isinstance(solary, u.Quantity)
assert solarx.unit == u.arcsec
assert solary.unit == u.arcsec
@pytest.mark.parametrize("solarx_unit,solary_unit", [
(u.arcsec, u.deg),
('angle', 'angle')])
def test_kwargs3(solarx_unit, solary_unit):
@u.quantity_input
def myfunc_args(solarx: solarx_unit, solary, myk: solary_unit=1*u.arcsec):
return solarx, solary, myk
solarx, solary, myk = myfunc_args(1*u.arcsec, 100, myk=100*u.deg)
assert isinstance(solarx, u.Quantity)
assert isinstance(solary, int)
assert isinstance(myk, u.Quantity)
assert myk.unit == u.deg
@pytest.mark.parametrize("solarx_unit,solary_unit", [
(u.arcsec, u.deg),
('angle', 'angle')])
def test_unused_kwargs3(solarx_unit, solary_unit):
@u.quantity_input
def myfunc_args(solarx: solarx_unit, solary, myk: solary_unit=1*u.arcsec, myk2=1000):
return solarx, solary, myk, myk2
solarx, solary, myk, myk2 = myfunc_args(1*u.arcsec, 100, myk=100*u.deg, myk2=10)
assert isinstance(solarx, u.Quantity)
assert isinstance(solary, int)
assert isinstance(myk, u.Quantity)
assert isinstance(myk2, int)
assert myk.unit == u.deg
assert myk2 == 10
@pytest.mark.parametrize("solarx_unit,energy", [
(u.arcsec, u.eV),
('angle', 'energy')])
def test_kwarg_equivalencies3(solarx_unit, energy):
@u.quantity_input(equivalencies=u.mass_energy())
def myfunc_args(solarx: solarx_unit, energy: energy=10*u.eV):
return solarx, energy+(10*u.J) # Add an energy to check equiv is working
solarx, energy = myfunc_args(1*u.arcsec, 100*u.gram)
assert isinstance(solarx, u.Quantity)
assert isinstance(energy, u.Quantity)
assert solarx.unit == u.arcsec
assert energy.unit == u.gram
@pytest.mark.parametrize("solarx_unit,solary_unit", [
(u.arcsec, u.deg),
('angle', 'angle')])
def test_kwarg_wrong_unit3(solarx_unit, solary_unit):
@u.quantity_input
def myfunc_args(solarx: solarx_unit, solary: solary_unit=10*u.deg):
return solarx, solary
with pytest.raises(u.UnitsError) as e:
solarx, solary = myfunc_args(1*u.arcsec, solary=100*u.km)
str_to = str(solary_unit)
assert str(e.value) == "Argument 'solary' to function 'myfunc_args' must be in units convertible to '{0}'.".format(str_to)
@pytest.mark.parametrize("solarx_unit,solary_unit", [
(u.arcsec, u.deg),
('angle', 'angle')])
def test_kwarg_not_quantity3(solarx_unit, solary_unit):
@u.quantity_input
def myfunc_args(solarx: solarx_unit, solary: solary_unit=10*u.deg):
return solarx, solary
with pytest.raises(TypeError) as e:
solarx, solary = myfunc_args(1*u.arcsec, solary=100)
assert str(e.value) == "Argument 'solary' to function 'myfunc_args' has no 'unit' attribute. You may want to pass in an astropy Quantity instead."
@pytest.mark.parametrize("solarx_unit,solary_unit", [
(u.arcsec, u.deg),
('angle', 'angle')])
def test_kwarg_default3(solarx_unit, solary_unit):
@u.quantity_input
def myfunc_args(solarx: solarx_unit, solary: solary_unit=10*u.deg):
return solarx, solary
solarx, solary = myfunc_args(1*u.arcsec)
def test_return_annotation():
@u.quantity_input
def myfunc_args(solarx: u.arcsec) -> u.deg:
return solarx
solarx = myfunc_args(1*u.arcsec)
assert solarx.unit is u.deg
def test_return_annotation_none():
@u.quantity_input
def myfunc_args(solarx: u.arcsec) -> None:
pass
solarx = myfunc_args(1*u.arcsec)
assert solarx is None
|
2065d43406e3483a11597bdd48a7cd8c8b8cdfbaf143b0907a5e21bd057b0a2d | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Regression tests for the units.format package
"""
import pytest
from numpy.testing import assert_allclose
from astropy.tests.helper import catch_warnings
from astropy import units as u
from astropy.constants import si
from astropy.units import core
from astropy.units import format as u_format
from astropy.units.utils import is_effectively_unity
@pytest.mark.parametrize('strings, unit', [
(["m s", "m*s", "m.s"], u.m * u.s),
(["m/s", "m*s**-1", "m /s", "m / s", "m/ s"], u.m / u.s),
(["m**2", "m2", "m**(2)", "m**+2", "m+2", "m^(+2)"], u.m ** 2),
(["m**-3", "m-3", "m^(-3)", "/m3"], u.m ** -3),
(["m**(1.5)", "m(3/2)", "m**(3/2)", "m^(3/2)"], u.m ** 1.5),
(["2.54 cm"], u.Unit(u.cm * 2.54)),
(["10+8m"], u.Unit(u.m * 1e8)),
# This is the VOUnits documentation, but doesn't seem to follow the
# unity grammar (["3.45 10**(-4)Jy"], 3.45 * 1e-4 * u.Jy)
(["sqrt(m)"], u.m ** 0.5),
(["dB(mW)", "dB (mW)"], u.DecibelUnit(u.mW)),
(["mag"], u.mag),
(["mag(ct/s)"], u.MagUnit(u.ct / u.s)),
(["dex"], u.dex),
(["dex(cm s**-2)", "dex(cm/s2)"], u.DexUnit(u.cm / u.s**2))])
def test_unit_grammar(strings, unit):
for s in strings:
print(s)
unit2 = u_format.Generic.parse(s)
assert unit2 == unit
@pytest.mark.parametrize('string', ['sin( /pixel /s)', 'mag(mag)',
'dB(dB(mW))', 'dex()'])
def test_unit_grammar_fail(string):
with pytest.raises(ValueError):
print(string)
u_format.Generic.parse(string)
@pytest.mark.parametrize('strings, unit', [
(["0.1nm"], u.AA),
(["mW/m2"], u.Unit(u.erg / u.cm ** 2 / u.s)),
(["mW/(m2)"], u.Unit(u.erg / u.cm ** 2 / u.s)),
(["km/s", "km.s-1"], u.km / u.s),
(["10pix/nm"], u.Unit(10 * u.pix / u.nm)),
(["1.5x10+11m"], u.Unit(1.5e11 * u.m)),
(["1.5×10+11m"], u.Unit(1.5e11 * u.m)),
(["m2"], u.m ** 2),
(["10+21m"], u.Unit(u.m * 1e21)),
(["2.54cm"], u.Unit(u.cm * 2.54)),
(["20%"], 0.20 * u.dimensionless_unscaled),
(["10+9"], 1.e9 * u.dimensionless_unscaled),
(["2x10-9"], 2.e-9 * u.dimensionless_unscaled),
(["---"], u.dimensionless_unscaled),
(["ma"], u.ma),
(["mAU"], u.mAU),
(["uarcmin"], u.uarcmin),
(["uarcsec"], u.uarcsec),
(["kbarn"], u.kbarn),
(["Gbit"], u.Gbit),
(["Gibit"], 2 ** 30 * u.bit),
(["kbyte"], u.kbyte),
(["mRy"], 0.001 * u.Ry),
(["mmag"], u.mmag),
(["Mpc"], u.Mpc),
(["Gyr"], u.Gyr),
(["°"], u.degree),
(["°/s"], u.degree / u.s),
(["Å"], u.AA),
(["Å/s"], u.AA / u.s),
(["\\h"], si.h)])
def test_cds_grammar(strings, unit):
for s in strings:
print(s)
unit2 = u_format.CDS.parse(s)
assert unit2 == unit
@pytest.mark.parametrize('string', [
'0.1 nm',
'solMass(3/2)',
'km / s',
'km s-1',
'pix0.1nm',
'pix/(0.1nm)',
'km*s',
'km**2',
'5x8+3m',
'0.1---',
'---m',
'm---',
'mag(s-1)',
'dB(mW)',
'dex(cm s-2)'])
def test_cds_grammar_fail(string):
with pytest.raises(ValueError):
print(string)
u_format.CDS.parse(string)
# These examples are taken from the EXAMPLES section of
# https://heasarc.gsfc.nasa.gov/docs/heasarc/ofwg/docs/general/ogip_93_001/
@pytest.mark.parametrize('strings, unit', [
(["count /s", "count/s", "count s**(-1)", "count / s", "count /s "],
u.count / u.s),
(["/pixel /s", "/(pixel * s)"], (u.pixel * u.s) ** -1),
(["count /m**2 /s /eV", "count m**(-2) * s**(-1) * eV**(-1)",
"count /(m**2 * s * eV)"],
u.count * u.m ** -2 * u.s ** -1 * u.eV ** -1),
(["erg /pixel /s /GHz", "erg /s /GHz /pixel", "erg /pixel /(s * GHz)"],
u.erg / (u.s * u.GHz * u.pixel)),
(["keV**2 /yr /angstrom", "10**(10) keV**2 /yr /m"],
# Though this is given as an example, it seems to violate the rules
# of not raising scales to powers, so I'm just excluding it
# "(10**2 MeV)**2 /yr /m"
u.keV**2 / (u.yr * u.angstrom)),
(["10**(46) erg /s", "10**46 erg /s", "10**(39) J /s", "10**(39) W",
"10**(15) YW", "YJ /fs"],
10**46 * u.erg / u.s),
(["10**(-7) J /cm**2 /MeV", "10**(-9) J m**(-2) eV**(-1)",
"nJ m**(-2) eV**(-1)", "nJ /m**2 /eV"],
10 ** -7 * u.J * u.cm ** -2 * u.MeV ** -1),
(["sqrt(erg /pixel /s /GHz)", "(erg /pixel /s /GHz)**(0.5)",
"(erg /pixel /s /GHz)**(1/2)",
"erg**(0.5) pixel**(-0.5) s**(-0.5) GHz**(-0.5)"],
(u.erg * u.pixel ** -1 * u.s ** -1 * u.GHz ** -1) ** 0.5),
(["(count /s) (/pixel /s)", "(count /s) * (/pixel /s)",
"count /pixel /s**2"],
(u.count / u.s) * (1.0 / (u.pixel * u.s)))])
def test_ogip_grammar(strings, unit):
for s in strings:
print(s)
unit2 = u_format.OGIP.parse(s)
assert unit2 == unit
@pytest.mark.parametrize('string', [
'log(photon /m**2 /s /Hz)',
'sin( /pixel /s)',
'log(photon /cm**2 /s /Hz) /(sin( /pixel /s))',
'log(photon /cm**2 /s /Hz) (sin( /pixel /s))**(-1)',
'dB(mW)', 'dex(cm/s**2)'])
def test_ogip_grammar_fail(string):
with pytest.raises(ValueError):
print(string)
u_format.OGIP.parse(string)
@pytest.mark.parametrize('unit', [val for key, val in u.__dict__.items()
if (isinstance(val, core.UnitBase) and
not isinstance(val, core.PrefixUnit))])
def test_roundtrip(unit):
a = core.Unit(unit.to_string('generic'), format='generic')
b = core.Unit(unit.decompose().to_string('generic'), format='generic')
assert_allclose(a.decompose().scale, unit.decompose().scale, rtol=1e-2)
assert_allclose(b.decompose().scale, unit.decompose().scale, rtol=1e-2)
@pytest.mark.parametrize('unit', [
val for key, val in u_format.VOUnit._units.items()
if (isinstance(val, core.UnitBase) and
not isinstance(val, core.PrefixUnit))])
def test_roundtrip_vo_unit(unit):
a = core.Unit(unit.to_string('vounit'), format='vounit')
assert_allclose(a.decompose().scale, unit.decompose().scale, rtol=1e-2)
if unit not in (u.mag, u.dB):
ud = unit.decompose().to_string('vounit')
assert ' ' not in ud
b = core.Unit(ud, format='vounit')
assert_allclose(b.decompose().scale, unit.decompose().scale, rtol=1e-2)
@pytest.mark.parametrize('unit', [
val for key, val in u_format.Fits._units.items()
if (isinstance(val, core.UnitBase) and
not isinstance(val, core.PrefixUnit))])
def test_roundtrip_fits(unit):
s = unit.to_string('fits')
a = core.Unit(s, format='fits')
assert_allclose(a.decompose().scale, unit.decompose().scale, rtol=1e-2)
@pytest.mark.parametrize('unit', [
val for key, val in u_format.CDS._units.items()
if (isinstance(val, core.UnitBase) and
not isinstance(val, core.PrefixUnit))])
def test_roundtrip_cds(unit):
a = core.Unit(unit.to_string('cds'), format='cds')
assert_allclose(a.decompose().scale, unit.decompose().scale, rtol=1e-2)
try:
b = core.Unit(unit.decompose().to_string('cds'), format='cds')
except ValueError: # skip mag: decomposes into dex, unknown to OGIP
return
assert_allclose(b.decompose().scale, unit.decompose().scale, rtol=1e-2)
@pytest.mark.parametrize('unit', [
val for key, val in u_format.OGIP._units.items()
if (isinstance(val, core.UnitBase) and
not isinstance(val, core.PrefixUnit))])
def test_roundtrip_ogip(unit):
a = core.Unit(unit.to_string('ogip'), format='ogip')
assert_allclose(a.decompose().scale, unit.decompose().scale, rtol=1e-2)
try:
b = core.Unit(unit.decompose().to_string('ogip'), format='ogip')
except ValueError: # skip mag: decomposes into dex, unknown to OGIP
return
assert_allclose(b.decompose().scale, unit.decompose().scale, rtol=1e-2)
def test_fits_units_available():
u_format.Fits._units
def test_vo_units_available():
u_format.VOUnit._units
def test_cds_units_available():
u_format.CDS._units
def test_cds_non_ascii_unit():
"""Regression test for #5350. This failed with a decoding error as
μas could not be represented in ascii."""
from astropy.units import cds
with cds.enable():
u.radian.find_equivalent_units(include_prefix_units=True)
def test_latex():
fluxunit = u.erg / (u.cm ** 2 * u.s)
assert fluxunit.to_string('latex') == r'$\mathrm{\frac{erg}{s\,cm^{2}}}$'
def test_new_style_latex():
fluxunit = u.erg / (u.cm ** 2 * u.s)
assert "{0:latex}".format(fluxunit) == r'$\mathrm{\frac{erg}{s\,cm^{2}}}$'
def test_latex_scale():
fluxunit = u.Unit(1.e-24 * u.erg / (u.cm ** 2 * u.s * u.Hz))
latex = r'$\mathrm{1 \times 10^{-24}\,\frac{erg}{Hz\,s\,cm^{2}}}$'
assert fluxunit.to_string('latex') == latex
def test_latex_inline_scale():
fluxunit = u.Unit(1.e-24 * u.erg / (u.cm ** 2 * u.s * u.Hz))
latex_inline = (r'$\mathrm{1 \times 10^{-24}\,erg'
r'\,Hz^{-1}\,s^{-1}\,cm^{-2}}$')
assert fluxunit.to_string('latex_inline') == latex_inline
@pytest.mark.parametrize('format_spec, string', [
('generic', 'erg / (cm2 s)'),
('s', 'erg / (cm2 s)'),
('console', ' erg \n ------\n s cm^2'),
('latex', '$\\mathrm{\\frac{erg}{s\\,cm^{2}}}$'),
('latex_inline', '$\\mathrm{erg\\,s^{-1}\\,cm^{-2}}$'),
('>20s', ' erg / (cm2 s)')])
def test_format_styles(format_spec, string):
fluxunit = u.erg / (u.cm ** 2 * u.s)
assert format(fluxunit, format_spec) == string
def test_flatten_to_known():
myunit = u.def_unit("FOOBAR_One", u.erg / u.Hz)
assert myunit.to_string('fits') == 'erg Hz-1'
myunit2 = myunit * u.bit ** 3
assert myunit2.to_string('fits') == 'bit3 erg Hz-1'
def test_flatten_impossible():
myunit = u.def_unit("FOOBAR_Two")
with u.add_enabled_units(myunit), pytest.raises(ValueError):
myunit.to_string('fits')
def test_console_out():
"""
Issue #436.
"""
u.Jy.decompose().to_string('console')
def test_flexible_float():
assert u.min._represents.to_string('latex') == r'$\mathrm{60\,s}$'
def test_fraction_repr():
area = u.cm ** 2.0
assert '.' not in area.to_string('latex')
fractional = u.cm ** 2.5
assert '5/2' in fractional.to_string('latex')
assert fractional.to_string('unicode') == 'cm⁵⸍²'
def test_scale_effectively_unity():
"""Scale just off unity at machine precision level is OK.
Ensures #748 does not recur
"""
a = (3. * u.N).cgs
assert is_effectively_unity(a.unit.scale)
assert len(a.__repr__().split()) == 3
def test_percent():
"""Test that the % unit is properly recognized. Since % is a special
symbol, this goes slightly beyond the round-tripping tested above."""
assert u.Unit('%') == u.percent == u.Unit(0.01)
assert u.Unit('%', format='cds') == u.Unit(0.01)
assert u.Unit(0.01).to_string('cds') == '%'
with pytest.raises(ValueError):
u.Unit('%', format='fits')
with pytest.raises(ValueError):
u.Unit('%', format='vounit')
def test_scaled_dimensionless():
"""Test that scaled dimensionless units are properly recognized in generic
and CDS, but not in fits and vounit."""
assert u.Unit('0.1') == u.Unit(0.1) == 0.1 * u.dimensionless_unscaled
assert u.Unit('1.e-4') == u.Unit(1.e-4)
assert u.Unit('10-4', format='cds') == u.Unit(1.e-4)
assert u.Unit('10+8').to_string('cds') == '10+8'
with pytest.raises(ValueError):
u.Unit(0.15).to_string('fits')
assert u.Unit(0.1).to_string('fits') == '10**-1'
with pytest.raises(ValueError):
u.Unit(0.1).to_string('vounit')
def test_deprecated_did_you_mean_units():
try:
u.Unit('ANGSTROM', format='fits')
except ValueError as e:
assert 'Did you mean Angstrom or angstrom?' in str(e)
try:
u.Unit('crab', format='ogip')
except ValueError as e:
assert 'Crab (deprecated)' in str(e)
assert 'mCrab (deprecated)' in str(e)
try:
u.Unit('ANGSTROM', format='vounit')
except ValueError as e:
assert 'angstrom (deprecated)' in str(e)
assert '0.1nm' in str(e)
assert str(e).count('0.1nm') == 1
with catch_warnings() as w:
u.Unit('angstrom', format='vounit')
assert len(w) == 1
assert '0.1nm' in str(w[0].message)
@pytest.mark.parametrize('string', ['mag(ct/s)', 'dB(mW)', 'dex(cm s**-2)'])
def test_fits_function(string):
# Function units cannot be written, so ensure they're not parsed either.
with pytest.raises(ValueError):
print(string)
u_format.Fits().parse(string)
@pytest.mark.parametrize('string', ['mag(ct/s)', 'dB(mW)', 'dex(cm s**-2)'])
def test_vounit_function(string):
# Function units cannot be written, so ensure they're not parsed either.
with pytest.raises(ValueError):
print(string)
u_format.VOUnit().parse(string)
def test_vounit_binary_prefix():
u.Unit('KiB', format='vounit') == u.Unit('1024 B')
u.Unit('Kibyte', format='vounit') == u.Unit('1024 B')
u.Unit('Kibit', format='vounit') == u.Unit('1024 B')
with catch_warnings() as w:
u.Unit('kibibyte', format='vounit')
assert len(w) == 1
def test_vounit_unknown():
assert u.Unit('unknown', format='vounit') is None
assert u.Unit('UNKNOWN', format='vounit') is None
assert u.Unit('', format='vounit') is u.dimensionless_unscaled
def test_vounit_details():
assert u.Unit('Pa', format='vounit') is u.Pascal
# The da- prefix is not allowed, and the d- prefix is discouraged
assert u.dam.to_string('vounit') == '10m'
assert u.Unit('dam dag').to_string('vounit') == '100g m'
def test_vounit_custom():
x = u.Unit("'foo' m", format='vounit')
x_vounit = x.to_string('vounit')
assert x_vounit == "'foo' m"
x_string = x.to_string()
assert x_string == "foo m"
x = u.Unit("m'foo' m", format='vounit')
assert x.bases[1]._represents.scale == 0.001
x_vounit = x.to_string('vounit')
assert x_vounit == "m m'foo'"
x_string = x.to_string()
assert x_string == 'm mfoo'
def test_vounit_implicit_custom():
x = u.Unit("furlong/week", format="vounit")
assert x.bases[0]._represents.scale == 1e-15
assert x.bases[0]._represents.bases[0].name == 'urlong'
@pytest.mark.parametrize('scale, number, string',
[('10+2', 100, '10**2'),
('10(+2)', 100, '10**2'),
('10**+2', 100, '10**2'),
('10**(+2)', 100, '10**2'),
('10^+2', 100, '10**2'),
('10^(+2)', 100, '10**2'),
('10**2', 100, '10**2'),
('10**(2)', 100, '10**2'),
('10^2', 100, '10**2'),
('10^(2)', 100, '10**2'),
('10-20', 10**(-20), '10**-20'),
('10(-20)', 10**(-20), '10**-20'),
('10**-20', 10**(-20), '10**-20'),
('10**(-20)', 10**(-20), '10**-20'),
('10^-20', 10**(-20), '10**-20'),
('10^(-20)', 10**(-20), '10**-20'),
])
def test_fits_scale_factor(scale, number, string):
x = u.Unit(scale + ' erg/s/cm**2/Angstrom', format='fits')
assert x == number * (u.erg / u.s / u.cm ** 2 / u.Angstrom)
assert x.to_string(format='fits') == string + ' Angstrom-1 cm-2 erg s-1'
x = u.Unit(scale + '*erg/s/cm**2/Angstrom', format='fits')
assert x == number * (u.erg / u.s / u.cm ** 2 / u.Angstrom)
assert x.to_string(format='fits') == string + ' Angstrom-1 cm-2 erg s-1'
def test_fits_scale_factor_errors():
with pytest.raises(ValueError):
x = u.Unit('1000 erg/s/cm**2/Angstrom', format='fits')
with pytest.raises(ValueError):
x = u.Unit('12 erg/s/cm**2/Angstrom', format='fits')
x = u.Unit(1.2 * u.erg)
with pytest.raises(ValueError):
x.to_string(format='fits')
x = u.Unit(100.0 * u.erg)
assert x.to_string(format='fits') == '10**2 erg'
|
30fb6b2eb898cc7fcc601b7ae1d8f3c44f3945a9f1d204a40628862424a121d1 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Regression tests for the units package
"""
import pickle
from fractions import Fraction
import pytest
import numpy as np
from numpy.testing import assert_allclose
from astropy.tests.helper import raises, catch_warnings
from astropy import units as u
from astropy import constants as c
from astropy.units import utils
def test_getting_started():
"""
Corresponds to "Getting Started" section in the docs.
"""
from astropy.units import imperial
with imperial.enable():
speed_unit = u.cm / u.s
x = speed_unit.to(imperial.mile / u.hour, 1)
assert_allclose(x, 0.02236936292054402)
speed_converter = speed_unit._get_converter("mile hour^-1")
x = speed_converter([1., 1000., 5000.])
assert_allclose(x, [2.23693629e-02, 2.23693629e+01, 1.11846815e+02])
def test_initialisation():
assert u.Unit(u.m) is u.m
ten_meter = u.Unit(10.*u.m)
assert ten_meter == u.CompositeUnit(10., [u.m], [1])
assert u.Unit(ten_meter) is ten_meter
assert u.Unit(10.*ten_meter) == u.CompositeUnit(100., [u.m], [1])
foo = u.Unit('foo', (10. * ten_meter)**2, namespace=locals())
assert foo == u.CompositeUnit(10000., [u.m], [2])
assert u.Unit('m') == u.m
assert u.Unit('') == u.dimensionless_unscaled
assert u.one == u.dimensionless_unscaled
assert u.Unit('10 m') == ten_meter
assert u.Unit(10.) == u.CompositeUnit(10., [], [])
def test_invalid_power():
x = u.m ** Fraction(1, 3)
assert isinstance(x.powers[0], Fraction)
x = u.m ** Fraction(1, 2)
assert isinstance(x.powers[0], float)
# Test the automatic conversion to a fraction
x = u.m ** (1. / 3.)
assert isinstance(x.powers[0], Fraction)
def test_invalid_compare():
assert not (u.m == u.s)
def test_convert():
assert u.h._get_converter(u.s)(1) == 3600
def test_convert_fail():
with pytest.raises(u.UnitsError):
u.cm.to(u.s, 1)
with pytest.raises(u.UnitsError):
(u.cm / u.s).to(u.m, 1)
def test_composite():
assert (u.cm / u.s * u.h)._get_converter(u.m)(1) == 36
assert u.cm * u.cm == u.cm ** 2
assert u.cm * u.cm * u.cm == u.cm ** 3
assert u.Hz.to(1000 * u.Hz, 1) == 0.001
def test_str():
assert str(u.cm) == "cm"
def test_repr():
assert repr(u.cm) == 'Unit("cm")'
def test_represents():
assert u.m.represents is u.m
assert u.km.represents.scale == 1000.
assert u.km.represents.bases == [u.m]
assert u.Ry.scale == 1.0 and u.Ry.bases == [u.Ry]
assert_allclose(u.Ry.represents.scale, 13.605692518464949)
assert u.Ry.represents.bases == [u.eV]
bla = u.def_unit('bla', namespace=locals())
assert bla.represents is bla
blabla = u.def_unit('blabla', 10 * u.hr, namespace=locals())
assert blabla.represents.scale == 10.
assert blabla.represents.bases == [u.hr]
assert blabla.decompose().scale == 10 * 3600
assert blabla.decompose().bases == [u.s]
def test_units_conversion():
assert_allclose(u.kpc.to(u.Mpc), 0.001)
assert_allclose(u.Mpc.to(u.kpc), 1000)
assert_allclose(u.yr.to(u.Myr), 1.e-6)
assert_allclose(u.AU.to(u.pc), 4.84813681e-6)
assert_allclose(u.cycle.to(u.rad), 6.283185307179586)
def test_units_manipulation():
# Just do some manipulation and check it's happy
(u.kpc * u.yr) ** Fraction(1, 3) / u.Myr
(u.AA * u.erg) ** 9
def test_decompose():
assert u.Ry == u.Ry.decompose()
def test_dimensionless_to_si():
"""
Issue #1150: Test for conversion of dimensionless quantities
to the SI system
"""
testunit = ((1.0 * u.kpc) / (1.0 * u.Mpc))
assert testunit.unit.physical_type == 'dimensionless'
assert_allclose(testunit.si, 0.001)
def test_dimensionless_to_cgs():
"""
Issue #1150: Test for conversion of dimensionless quantities
to the CGS system
"""
testunit = ((1.0 * u.m) / (1.0 * u.km))
assert testunit.unit.physical_type == 'dimensionless'
assert_allclose(testunit.cgs, 0.001)
def test_unknown_unit():
with catch_warnings(u.UnitsWarning) as warning_lines:
u.Unit("FOO", parse_strict='warn')
assert 'FOO' in str(warning_lines[0].message)
def test_multiple_solidus():
assert u.Unit("m/s/kg").to_string() == u.m / u.s / u.kg
with catch_warnings(u.UnitsWarning) as warning_lines:
assert u.Unit("m/s/kg").to_string() == u.m / (u.s * u.kg)
assert 'm/s/kg' in str(warning_lines[0].message)
assert 'discouraged' in str(warning_lines[0].message)
with pytest.raises(ValueError):
u.Unit("m/s/kg", format="vounit")
def test_unknown_unit3():
unit = u.Unit("FOO", parse_strict='silent')
assert isinstance(unit, u.UnrecognizedUnit)
assert unit.name == "FOO"
unit2 = u.Unit("FOO", parse_strict='silent')
assert unit == unit2
assert unit.is_equivalent(unit2)
unit3 = u.Unit("BAR", parse_strict='silent')
assert unit != unit3
assert not unit.is_equivalent(unit3)
# Also test basic (in)equalities.
assert unit == "FOO"
assert unit != u.m
# next two from gh-7603.
assert unit != None # noqa
assert unit not in (None, u.m)
with pytest.raises(ValueError):
unit._get_converter(unit3)
x = unit.to_string('latex')
y = unit2.to_string('cgs')
with pytest.raises(ValueError):
unit4 = u.Unit("BAR", parse_strict='strict')
with pytest.raises(TypeError):
unit5 = u.Unit(None)
@raises(TypeError)
def test_invalid_scale():
x = ['a', 'b', 'c'] * u.m
def test_cds_power():
unit = u.Unit("10+22/cm2", format="cds", parse_strict='silent')
assert unit.scale == 1e22
def test_register():
foo = u.def_unit("foo", u.m ** 3, namespace=locals())
assert 'foo' in locals()
with u.add_enabled_units(foo):
assert 'foo' in u.get_current_unit_registry().registry
assert 'foo' not in u.get_current_unit_registry().registry
def test_in_units():
speed_unit = u.cm / u.s
x = speed_unit.in_units(u.pc / u.hour, 1)
def test_null_unit():
assert (u.m / u.m) == u.Unit(1)
def test_unrecognized_equivalency():
assert u.m.is_equivalent('foo') is False
assert u.m.is_equivalent('pc') is True
@raises(TypeError)
def test_unit_noarg():
u.Unit()
def test_convertible_exception():
try:
u.AA.to(u.h * u.s ** 2)
except u.UnitsError as e:
assert "length" in str(e)
def test_convertible_exception2():
try:
u.m.to(u.s)
except u.UnitsError as e:
assert "length" in str(e)
@raises(TypeError)
def test_invalid_type():
class A:
pass
u.Unit(A())
def test_steradian():
"""
Issue #599
"""
assert u.sr.is_equivalent(u.rad * u.rad)
results = u.sr.compose(units=u.cgs.bases)
assert results[0].bases[0] is u.rad
results = u.sr.compose(units=u.cgs.__dict__)
assert results[0].bases[0] is u.sr
def test_decompose_bases():
"""
From issue #576
"""
from astropy.units import cgs
from astropy.constants import e
d = e.esu.unit.decompose(bases=cgs.bases)
assert d._bases == [u.cm, u.g, u.s]
assert d._powers == [Fraction(3, 2), 0.5, -1]
assert d._scale == 1.0
def test_complex_compose():
complex = u.cd * u.sr * u.Wb
composed = complex.compose()
assert set(composed[0]._bases) == set([u.lm, u.Wb])
def test_equiv_compose():
composed = u.m.compose(equivalencies=u.spectral())
assert any([u.Hz] == x.bases for x in composed)
def test_empty_compose():
with pytest.raises(u.UnitsError):
composed = u.m.compose(units=[])
def _unit_as_str(unit):
# This function serves two purposes - it is used to sort the units to
# test alphabetically, and it is also use to allow pytest to show the unit
# in the [] when running the parametrized tests.
return str(unit)
# We use a set to make sure we don't have any duplicates.
COMPOSE_ROUNDTRIP = set()
for val in u.__dict__.values():
if (isinstance(val, u.UnitBase) and
not isinstance(val, u.PrefixUnit)):
COMPOSE_ROUNDTRIP.add(val)
@pytest.mark.parametrize('unit', sorted(COMPOSE_ROUNDTRIP, key=_unit_as_str), ids=_unit_as_str)
def test_compose_roundtrip(unit):
composed_list = unit.decompose().compose()
found = False
for composed in composed_list:
if len(composed.bases):
if composed.bases[0] is unit:
found = True
break
elif len(unit.bases) == 0:
found = True
break
assert found
# We use a set to make sure we don't have any duplicates.
COMPOSE_CGS_TO_SI = set()
for val in u.cgs.__dict__.values():
# Can't decompose Celsius
if (isinstance(val, u.UnitBase) and
not isinstance(val, u.PrefixUnit) and
val != u.cgs.deg_C):
COMPOSE_CGS_TO_SI.add(val)
@pytest.mark.parametrize('unit', sorted(COMPOSE_CGS_TO_SI, key=_unit_as_str),
ids=_unit_as_str)
def test_compose_cgs_to_si(unit):
si = unit.to_system(u.si)
assert [x.is_equivalent(unit) for x in si]
assert si[0] == unit.si
# We use a set to make sure we don't have any duplicates.
COMPOSE_SI_TO_CGS = set()
for val in u.si.__dict__.values():
# Can't decompose Celsius
if (isinstance(val, u.UnitBase) and
not isinstance(val, u.PrefixUnit) and
val != u.si.deg_C):
COMPOSE_SI_TO_CGS.add(val)
@pytest.mark.parametrize('unit', sorted(COMPOSE_SI_TO_CGS, key=_unit_as_str), ids=_unit_as_str)
def test_compose_si_to_cgs(unit):
# Can't convert things with Ampere to CGS without more context
try:
cgs = unit.to_system(u.cgs)
except u.UnitsError:
if u.A in unit.decompose().bases:
pass
else:
raise
else:
assert [x.is_equivalent(unit) for x in cgs]
assert cgs[0] == unit.cgs
def test_to_cgs():
assert u.Pa.to_system(u.cgs)[1]._bases[0] is u.Ba
assert u.Pa.to_system(u.cgs)[1]._scale == 10.0
def test_decompose_to_cgs():
from astropy.units import cgs
assert u.m.decompose(bases=cgs.bases)._bases[0] is cgs.cm
def test_compose_issue_579():
unit = u.kg * u.s ** 2 / u.m
result = unit.compose(units=[u.N, u.s, u.m])
assert len(result) == 1
assert result[0]._bases == [u.s, u.N, u.m]
assert result[0]._powers == [4, 1, -2]
def test_compose_prefix_unit():
x = u.m.compose(units=(u.m,))
assert x[0].bases[0] is u.m
assert x[0].scale == 1.0
x = u.m.compose(units=[u.km], include_prefix_units=True)
assert x[0].bases[0] is u.km
assert x[0].scale == 0.001
x = u.m.compose(units=[u.km])
assert x[0].bases[0] is u.km
assert x[0].scale == 0.001
x = (u.km/u.s).compose(units=(u.pc, u.Myr))
assert x[0].bases == [u.pc, u.Myr]
assert_allclose(x[0].scale, 1.0227121650537077)
with raises(u.UnitsError):
(u.km/u.s).compose(units=(u.pc, u.Myr), include_prefix_units=False)
def test_self_compose():
unit = u.kg * u.s
assert len(unit.compose(units=[u.g, u.s])) == 1
@raises(u.UnitsError)
def test_compose_failed():
unit = u.kg
result = unit.compose(units=[u.N])
def test_compose_fractional_powers():
# Warning: with a complicated unit, this test becomes very slow;
# e.g., x = (u.kg / u.s ** 3 * u.au ** 2.5 / u.yr ** 0.5 / u.sr ** 2)
# takes 3 s
x = u.m ** 0.5 / u.yr ** 1.5
factored = x.compose()
for unit in factored:
assert x.decompose() == unit.decompose()
factored = x.compose(units=u.cgs)
for unit in factored:
assert x.decompose() == unit.decompose()
factored = x.compose(units=u.si)
for unit in factored:
assert x.decompose() == unit.decompose()
def test_compose_best_unit_first():
results = u.l.compose()
assert len(results[0].bases) == 1
assert results[0].bases[0] is u.l
results = (u.s ** -1).compose()
assert results[0].bases[0] in (u.Hz, u.Bq)
results = (u.Ry.decompose()).compose()
assert results[0].bases[0] is u.Ry
def test_compose_no_duplicates():
new = u.kg / u.s ** 3 * u.au ** 2.5 / u.yr ** 0.5 / u.sr ** 2
composed = new.compose(units=u.cgs.bases)
assert len(composed) == 1
def test_long_int():
"""
Issue #672
"""
sigma = 10 ** 21 * u.M_p / u.cm ** 2
sigma.to(u.M_sun / u.pc ** 2)
def test_endian_independence():
"""
Regression test for #744
A logic issue in the units code meant that big endian arrays could not be
converted because the dtype is '>f4', not 'float32', and the code was
looking for the strings 'float' or 'int'.
"""
for endian in ['<', '>']:
for ntype in ['i', 'f']:
for byte in ['4', '8']:
x = np.array([1, 2, 3], dtype=(endian + ntype + byte))
u.m.to(u.cm, x)
def test_radian_base():
"""
Issue #863
"""
assert (1 * u.degree).si.unit == u.rad
def test_no_as():
# We don't define 'as', since it is a keyword, but we
# do want to define the long form (`attosecond`).
assert not hasattr(u, 'as')
assert hasattr(u, 'attosecond')
def test_no_duplicates_in_names():
# Regression test for #5036
assert u.ct.names == ['ct', 'count']
assert u.ct.short_names == ['ct', 'count']
assert u.ct.long_names == ['count']
assert set(u.ph.names) == set(u.ph.short_names) | set(u.ph.long_names)
def test_pickling():
p = pickle.dumps(u.m)
other = pickle.loads(p)
assert other is u.m
new_unit = u.IrreducibleUnit(['foo'], format={'baz': 'bar'})
# This is local, so the unit should not be registered.
assert 'foo' not in u.get_current_unit_registry().registry
# Test pickling of this unregistered unit.
p = pickle.dumps(new_unit)
new_unit_copy = pickle.loads(p)
assert new_unit_copy.names == ['foo']
assert new_unit_copy.get_format_name('baz') == 'bar'
# It should still not be registered.
assert 'foo' not in u.get_current_unit_registry().registry
# Now try the same with a registered unit.
with u.add_enabled_units([new_unit]):
p = pickle.dumps(new_unit)
assert 'foo' in u.get_current_unit_registry().registry
# Check that a registered unit can be loaded and that it gets re-enabled.
with u.add_enabled_units([]):
assert 'foo' not in u.get_current_unit_registry().registry
new_unit_copy = pickle.loads(p)
assert new_unit_copy.names == ['foo']
assert new_unit_copy.get_format_name('baz') == 'bar'
assert 'foo' in u.get_current_unit_registry().registry
# And just to be sure, that it gets removed outside of the context.
assert 'foo' not in u.get_current_unit_registry().registry
def test_pickle_unrecognized_unit():
"""
Issue #2047
"""
a = u.Unit('asdf', parse_strict='silent')
pickle.loads(pickle.dumps(a))
@raises(ValueError)
def test_duplicate_define():
u.def_unit('m', namespace=u.__dict__)
def test_all_units():
from astropy.units.core import get_current_unit_registry
registry = get_current_unit_registry()
assert len(registry.all_units) > len(registry.non_prefix_units)
def test_repr_latex():
assert u.m._repr_latex_() == u.m.to_string('latex')
def test_operations_with_strings():
assert u.m / '5s' == (u.m / (5.0 * u.s))
assert u.m * '5s' == (5.0 * u.m * u.s)
def test_comparison():
assert u.m > u.cm
assert u.m >= u.cm
assert u.cm < u.m
assert u.cm <= u.m
with pytest.raises(u.UnitsError):
u.m > u.kg
def test_compose_into_arbitrary_units():
# Issue #1438
from astropy.constants import G
G.decompose([u.kg, u.km, u.Unit("15 s")])
def test_unit_multiplication_with_string():
"""Check that multiplication with strings produces the correct unit."""
u1 = u.cm
us = 'kg'
assert us * u1 == u.Unit(us) * u1
assert u1 * us == u1 * u.Unit(us)
def test_unit_division_by_string():
"""Check that multiplication with strings produces the correct unit."""
u1 = u.cm
us = 'kg'
assert us / u1 == u.Unit(us) / u1
assert u1 / us == u1 / u.Unit(us)
def test_sorted_bases():
"""See #1616."""
assert (u.m * u.Jy).bases == (u.Jy * u.m).bases
def test_megabit():
"""See #1543"""
assert u.Mbit is u.Mb
assert u.megabit is u.Mb
assert u.Mbyte is u.MB
assert u.megabyte is u.MB
def test_composite_unit_get_format_name():
"""See #1576"""
unit1 = u.Unit('nrad/s')
unit2 = u.Unit('Hz(1/2)')
assert (str(u.CompositeUnit(1, [unit1, unit2], [1, -1])) ==
'nrad / (Hz(1/2) s)')
def test_unicode_policy():
from astropy.tests.helper import assert_follows_unicode_guidelines
assert_follows_unicode_guidelines(
u.degree, roundtrip=u.__dict__)
def test_suggestions():
for search, matches in [
('microns', 'micron'),
('s/microns', 'micron'),
('M', 'm'),
('metre', 'meter'),
('angstroms', 'Angstrom or angstrom'),
('milimeter', 'millimeter'),
('ångström', 'Angstrom or angstrom'),
('kev', 'EV, eV, kV or keV')]:
try:
u.Unit(search)
except ValueError as e:
assert 'Did you mean {0}?'.format(matches) in str(e)
else:
assert False, 'Expected ValueError'
def test_fits_hst_unit():
"""See #1911."""
x = u.Unit("erg /s /cm**2 /angstrom")
assert x == u.erg * u.s ** -1 * u.cm ** -2 * u.angstrom ** -1
def test_barn_prefixes():
"""Regression test for https://github.com/astropy/astropy/issues/3753"""
assert u.fbarn is u.femtobarn
assert u.pbarn is u.picobarn
def test_fractional_powers():
"""See #2069"""
m = 1e9 * u.Msun
tH = 1. / (70. * u.km / u.s / u.Mpc)
vc = 200 * u.km/u.s
x = (c.G ** 2 * m ** 2 * tH.cgs) ** Fraction(1, 3) / vc
v1 = x.to('pc')
x = (c.G ** 2 * m ** 2 * tH) ** Fraction(1, 3) / vc
v2 = x.to('pc')
x = (c.G ** 2 * m ** 2 * tH.cgs) ** (1.0 / 3.0) / vc
v3 = x.to('pc')
x = (c.G ** 2 * m ** 2 * tH) ** (1.0 / 3.0) / vc
v4 = x.to('pc')
assert_allclose(v1, v2)
assert_allclose(v2, v3)
assert_allclose(v3, v4)
x = u.m ** (1.0 / 11.0)
assert isinstance(x.powers[0], float)
x = u.m ** (3.0 / 7.0)
assert isinstance(x.powers[0], Fraction)
assert x.powers[0].numerator == 3
assert x.powers[0].denominator == 7
x = u.cm ** Fraction(1, 2) * u.cm ** Fraction(2, 3)
assert isinstance(x.powers[0], Fraction)
assert x.powers[0] == Fraction(7, 6)
def test_inherit_docstrings():
assert u.UnrecognizedUnit.is_unity.__doc__ == u.UnitBase.is_unity.__doc__
def test_sqrt_mag():
sqrt_mag = u.mag ** 0.5
assert hasattr(sqrt_mag.decompose().scale, 'imag')
assert (sqrt_mag.decompose())**2 == u.mag
def test_composite_compose():
# Issue #2382
composite_unit = u.s.compose(units=[u.Unit("s")])[0]
u.s.compose(units=[composite_unit])
def test_data_quantities():
assert u.byte.is_equivalent(u.bit)
def test_compare_with_none():
# Ensure that equality comparisons with `None` work, and don't
# raise exceptions. We are deliberately not using `is None` here
# because that doesn't trigger the bug. See #3108.
assert not (u.m == None) # nopep8
assert u.m != None # nopep8
def test_validate_power_detect_fraction():
frac = utils.validate_power(1.1666666666666665)
assert isinstance(frac, Fraction)
assert frac.numerator == 7
assert frac.denominator == 6
def test_complex_fractional_rounding_errors():
# See #3788
kappa = 0.34 * u.cm**2 / u.g
r_0 = 886221439924.7849 * u.cm
q = 1.75
rho_0 = 5e-10 * u.solMass / u.solRad**3
y = 0.5
beta = 0.19047619047619049
a = 0.47619047619047628
m_h = 1e6*u.solMass
t1 = 2 * c.c / (kappa * np.sqrt(np.pi))
t2 = (r_0**-q) / (rho_0 * y * beta * (a * c.G * m_h)**0.5)
result = ((t1 * t2)**-0.8)
assert result.unit.physical_type == 'length'
result.to(u.solRad)
def test_fractional_rounding_errors_simple():
x = (u.m ** 1.5) ** Fraction(4, 5)
assert isinstance(x.powers[0], Fraction)
assert x.powers[0].numerator == 6
assert x.powers[0].denominator == 5
def test_enable_unit_groupings():
from astropy.units import cds
with cds.enable():
assert cds.geoMass in u.kg.find_equivalent_units()
from astropy.units import imperial
with imperial.enable():
assert imperial.inch in u.m.find_equivalent_units()
def test_unit_summary_prefixes():
"""
Test for a few units that the unit summary table correctly reports
whether or not that unit supports prefixes.
Regression test for https://github.com/astropy/astropy/issues/3835
"""
from astropy.units import astrophys
for summary in utils._iter_unit_summary(astrophys.__dict__):
unit, _, _, _, prefixes = summary
if unit.name == 'lyr':
assert prefixes
elif unit.name == 'pc':
assert prefixes
elif unit.name == 'barn':
assert prefixes
elif unit.name == 'cycle':
assert prefixes == 'No'
elif unit.name == 'vox':
assert prefixes == 'Yes'
def test_raise_to_negative_power():
"""Test that order of bases is changed when raising to negative power.
Regression test for https://github.com/astropy/astropy/issues/8260
"""
m2s2 = u.m ** 2 / u.s **2
spm = m2s2 ** (-1 / 2)
assert spm.bases == [u.s, u.m]
assert spm.powers == [1, -1]
assert spm == u.s / u.m
|
f812b25b297b6530226d9347035032779c8bf7cf99b1cc9d4af2355d77e69838 | # The purpose of these tests are to ensure that calling quantities using
# array methods returns quantities with the right units, or raises exceptions.
import pytest
import numpy as np
from astropy import units as u
class TestQuantityArrayCopy:
"""
Test whether arrays are properly copied/used in place
"""
def test_copy_on_creation(self):
v = np.arange(1000.)
q_nocopy = u.Quantity(v, "km/s", copy=False)
q_copy = u.Quantity(v, "km/s", copy=True)
v[0] = -1.
assert q_nocopy[0].value == v[0]
assert q_copy[0].value != v[0]
def test_to_copies(self):
q = u.Quantity(np.arange(1., 100.), "km/s")
q2 = q.to(u.m/u.s)
assert np.all(q.value != q2.value)
q3 = q.to(u.km/u.s)
assert np.all(q.value == q3.value)
q[0] = -1.*u.km/u.s
assert q[0].value != q3[0].value
def test_si_copies(self):
q = u.Quantity(np.arange(100.), "m/s")
q2 = q.si
assert np.all(q.value == q2.value)
q[0] = -1.*u.m/u.s
assert q[0].value != q2[0].value
def test_getitem_is_view(self):
"""Check that [keys] work, and that, like ndarray, it returns
a view, so that changing one changes the other.
Also test that one can add axes (closes #1422)
"""
q = u.Quantity(np.arange(100.), "m/s")
q_sel = q[10:20]
q_sel[0] = -1.*u.m/u.s
assert q_sel[0] == q[10]
# also check that getitem can do new axes
q2 = q[:, np.newaxis]
q2[10, 0] = -9*u.m/u.s
assert np.all(q2.flatten() == q)
def test_flat(self):
q = u.Quantity(np.arange(9.).reshape(3, 3), "m/s")
q_flat = q.flat
# check that a single item is a quantity (with the right value)
assert q_flat[8] == 8. * u.m / u.s
# and that getting a range works as well
assert np.all(q_flat[0:2] == np.arange(2.) * u.m / u.s)
# as well as getting items via iteration
q_flat_list = [_q for _q in q.flat]
assert np.all(u.Quantity(q_flat_list) ==
u.Quantity([_a for _a in q.value.flat], q.unit))
# check that flat works like a view of the real array
q_flat[8] = -1. * u.km / u.s
assert q_flat[8] == -1. * u.km / u.s
assert q[2, 2] == -1. * u.km / u.s
# while if one goes by an iterated item, a copy is made
q_flat_list[8] = -2 * u.km / u.s
assert q_flat_list[8] == -2. * u.km / u.s
assert q_flat[8] == -1. * u.km / u.s
assert q[2, 2] == -1. * u.km / u.s
class TestQuantityReshapeFuncs:
"""Test different ndarray methods that alter the array shape
tests: reshape, squeeze, ravel, flatten, transpose, swapaxes
"""
def test_reshape(self):
q = np.arange(6.) * u.m
q_reshape = q.reshape(3, 2)
assert isinstance(q_reshape, u.Quantity)
assert q_reshape.unit == q.unit
assert np.all(q_reshape.value == q.value.reshape(3, 2))
def test_squeeze(self):
q = np.arange(6.).reshape(6, 1) * u.m
q_squeeze = q.squeeze()
assert isinstance(q_squeeze, u.Quantity)
assert q_squeeze.unit == q.unit
assert np.all(q_squeeze.value == q.value.squeeze())
def test_ravel(self):
q = np.arange(6.).reshape(3, 2) * u.m
q_ravel = q.ravel()
assert isinstance(q_ravel, u.Quantity)
assert q_ravel.unit == q.unit
assert np.all(q_ravel.value == q.value.ravel())
def test_flatten(self):
q = np.arange(6.).reshape(3, 2) * u.m
q_flatten = q.flatten()
assert isinstance(q_flatten, u.Quantity)
assert q_flatten.unit == q.unit
assert np.all(q_flatten.value == q.value.flatten())
def test_transpose(self):
q = np.arange(6.).reshape(3, 2) * u.m
q_transpose = q.transpose()
assert isinstance(q_transpose, u.Quantity)
assert q_transpose.unit == q.unit
assert np.all(q_transpose.value == q.value.transpose())
def test_swapaxes(self):
q = np.arange(6.).reshape(3, 1, 2) * u.m
q_swapaxes = q.swapaxes(0, 2)
assert isinstance(q_swapaxes, u.Quantity)
assert q_swapaxes.unit == q.unit
assert np.all(q_swapaxes.value == q.value.swapaxes(0, 2))
class TestQuantityStatsFuncs:
"""
Test statistical functions
"""
def test_mean(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
assert np.mean(q1) == 3.6 * u.m
def test_mean_inplace(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
qi = 1.5 * u.s
qi2 = np.mean(q1, out=qi)
assert qi2 is qi
assert qi == 3.6 * u.m
def test_std(self):
q1 = np.array([1., 2.]) * u.m
assert np.std(q1) == 0.5 * u.m
def test_std_inplace(self):
q1 = np.array([1., 2.]) * u.m
qi = 1.5 * u.s
np.std(q1, out=qi)
assert qi == 0.5 * u.m
def test_var(self):
q1 = np.array([1., 2.]) * u.m
assert np.var(q1) == 0.25 * u.m ** 2
def test_var_inplace(self):
q1 = np.array([1., 2.]) * u.m
qi = 1.5 * u.s
np.var(q1, out=qi)
assert qi == 0.25 * u.m ** 2
def test_median(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
assert np.median(q1) == 4. * u.m
def test_median_inplace(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
qi = 1.5 * u.s
np.median(q1, out=qi)
assert qi == 4 * u.m
def test_min(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
assert np.min(q1) == 1. * u.m
def test_min_inplace(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
qi = 1.5 * u.s
np.min(q1, out=qi)
assert qi == 1. * u.m
def test_argmin(self):
q1 = np.array([6., 2., 4., 5., 6.]) * u.m
assert np.argmin(q1) == 1
def test_max(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
assert np.max(q1) == 6. * u.m
def test_max_inplace(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
qi = 1.5 * u.s
np.max(q1, out=qi)
assert qi == 6. * u.m
def test_argmax(self):
q1 = np.array([5., 2., 4., 5., 6.]) * u.m
assert np.argmax(q1) == 4
def test_clip(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.km / u.m
c1 = q1.clip(1500, 5.5 * u.Mm / u.km)
assert np.all(c1 == np.array([1.5, 2., 4., 5., 5.5]) * u.km / u.m)
def test_clip_inplace(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.km / u.m
c1 = q1.clip(1500, 5.5 * u.Mm / u.km, out=q1)
assert np.all(q1 == np.array([1.5, 2., 4., 5., 5.5]) * u.km / u.m)
c1[0] = 10 * u.Mm/u.mm
assert np.all(c1.value == q1.value)
def test_conj(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.km / u.m
assert np.all(q1.conj() == q1)
def test_ptp(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
assert np.ptp(q1) == 5. * u.m
def test_ptp_inplace(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
qi = 1.5 * u.s
np.ptp(q1, out=qi)
assert qi == 5. * u.m
def test_round(self):
q1 = np.array([1.253, 2.253, 3.253]) * u.kg
assert np.all(np.round(q1) == np.array([1, 2, 3]) * u.kg)
assert np.all(np.round(q1, decimals=2) ==
np.round(q1.value, decimals=2) * u.kg)
assert np.all(q1.round(decimals=2) ==
q1.value.round(decimals=2) * u.kg)
def test_round_inplace(self):
q1 = np.array([1.253, 2.253, 3.253]) * u.kg
qi = np.zeros(3) * u.s
a = q1.round(decimals=2, out=qi)
assert a is qi
assert np.all(q1.round(decimals=2) == qi)
def test_sum(self):
q1 = np.array([1., 2., 6.]) * u.m
assert np.all(q1.sum() == 9. * u.m)
assert np.all(np.sum(q1) == 9. * u.m)
q2 = np.array([[4., 5., 9.], [1., 1., 1.]]) * u.s
assert np.all(q2.sum(0) == np.array([5., 6., 10.]) * u.s)
assert np.all(np.sum(q2, 0) == np.array([5., 6., 10.]) * u.s)
def test_sum_inplace(self):
q1 = np.array([1., 2., 6.]) * u.m
qi = 1.5 * u.s
np.sum(q1, out=qi)
assert qi == 9. * u.m
def test_cumsum(self):
q1 = np.array([1, 2, 6]) * u.m
assert np.all(q1.cumsum() == np.array([1, 3, 9]) * u.m)
assert np.all(np.cumsum(q1) == np.array([1, 3, 9]) * u.m)
q2 = np.array([4, 5, 9]) * u.s
assert np.all(q2.cumsum() == np.array([4, 9, 18]) * u.s)
assert np.all(np.cumsum(q2) == np.array([4, 9, 18]) * u.s)
def test_cumsum_inplace(self):
q1 = np.array([1, 2, 6]) * u.m
qi = np.ones(3) * u.s
np.cumsum(q1, out=qi)
assert np.all(qi == np.array([1, 3, 9]) * u.m)
q2 = q1
q1.cumsum(out=q1)
assert np.all(q2 == qi)
def test_nansum(self):
q1 = np.array([1., 2., np.nan]) * u.m
assert np.all(q1.nansum() == 3. * u.m)
assert np.all(np.nansum(q1) == 3. * u.m)
q2 = np.array([[np.nan, 5., 9.], [1., np.nan, 1.]]) * u.s
assert np.all(q2.nansum(0) == np.array([1., 5., 10.]) * u.s)
assert np.all(np.nansum(q2, 0) == np.array([1., 5., 10.]) * u.s)
def test_nansum_inplace(self):
q1 = np.array([1., 2., np.nan]) * u.m
qi = 1.5 * u.s
qout = q1.nansum(out=qi)
assert qout is qi
assert qi == np.nansum(q1.value) * q1.unit
qi2 = 1.5 * u.s
qout2 = np.nansum(q1, out=qi2)
assert qout2 is qi2
assert qi2 == np.nansum(q1.value) * q1.unit
def test_prod(self):
q1 = np.array([1, 2, 6]) * u.m
with pytest.raises(u.UnitsError) as exc:
q1.prod()
with pytest.raises(u.UnitsError) as exc:
np.prod(q1)
q2 = np.array([3., 4., 5.]) * u.Unit(1)
assert q2.prod() == 60. * u.Unit(1)
assert np.prod(q2) == 60. * u.Unit(1)
def test_cumprod(self):
q1 = np.array([1, 2, 6]) * u.m
with pytest.raises(u.UnitsError) as exc:
q1.cumprod()
with pytest.raises(u.UnitsError) as exc:
np.cumprod(q1)
q2 = np.array([3, 4, 5]) * u.Unit(1)
assert np.all(q2.cumprod() == np.array([3, 12, 60]) * u.Unit(1))
assert np.all(np.cumprod(q2) == np.array([3, 12, 60]) * u.Unit(1))
def test_diff(self):
q1 = np.array([1., 2., 4., 10.]) * u.m
assert np.all(q1.diff() == np.array([1., 2., 6.]) * u.m)
assert np.all(np.diff(q1) == np.array([1., 2., 6.]) * u.m)
def test_ediff1d(self):
q1 = np.array([1., 2., 4., 10.]) * u.m
assert np.all(q1.ediff1d() == np.array([1., 2., 6.]) * u.m)
assert np.all(np.ediff1d(q1) == np.array([1., 2., 6.]) * u.m)
@pytest.mark.xfail
def test_dot_func(self):
q1 = np.array([1., 2., 4., 10.]) * u.m
q2 = np.array([3., 4., 5., 6.]) * u.s
q3 = np.dot(q1, q2)
assert q3.value == np.dot(q1.value, q2.value)
assert q3.unit == u.m * u.s
def test_dot_meth(self):
q1 = np.array([1., 2., 4., 10.]) * u.m
q2 = np.array([3., 4., 5., 6.]) * u.s
q3 = q1.dot(q2)
assert q3.value == np.dot(q1.value, q2.value)
assert q3.unit == u.m * u.s
def test_trace_func(self):
q = np.array([[1., 2.], [3., 4.]]) * u.m
assert np.trace(q) == 5. * u.m
def test_trace_meth(self):
q1 = np.array([[1., 2.], [3., 4.]]) * u.m
assert q1.trace() == 5. * u.m
cont = u.Quantity(4., u.s)
q2 = np.array([[3., 4.], [5., 6.]]) * u.m
q2.trace(out=cont)
assert cont == 9. * u.m
def test_clip_func(self):
q = np.arange(10) * u.m
assert np.all(np.clip(q, 3 * u.m, 6 * u.m) == np.array([3., 3., 3., 3., 4., 5., 6., 6., 6., 6.]) * u.m)
def test_clip_meth(self):
expected = np.array([3., 3., 3., 3., 4., 5., 6., 6., 6., 6.]) * u.m
q1 = np.arange(10) * u.m
q3 = q1.clip(3 * u.m, 6 * u.m)
assert np.all(q1.clip(3 * u.m, 6 * u.m) == expected)
cont = np.zeros(10) * u.s
q1.clip(3 * u.m, 6 * u.m, out=cont)
assert np.all(cont == expected)
class TestArrayConversion:
"""
Test array conversion methods
"""
def test_item(self):
q1 = u.Quantity(np.array([1, 2, 3]), u.m / u.km, dtype=int)
assert q1.item(1) == 2 * q1.unit
q1.itemset(1, 1)
assert q1.item(1) == 1000 * u.m / u.km
q1.itemset(1, 100 * u.cm / u.km)
assert q1.item(1) == 1 * u.m / u.km
with pytest.raises(TypeError):
q1.itemset(1, 1.5 * u.m / u.km)
with pytest.raises(ValueError):
q1.itemset()
q1[1] = 1
assert q1[1] == 1000 * u.m / u.km
q1[1] = 100 * u.cm / u.km
assert q1[1] == 1 * u.m / u.km
with pytest.raises(TypeError):
q1[1] = 1.5 * u.m / u.km
def test_take_put(self):
q1 = np.array([1, 2, 3]) * u.m / u.km
assert q1.take(1) == 2 * u.m / u.km
assert all(q1.take((0, 2)) == np.array([1, 3]) * u.m / u.km)
q1.put((1, 2), (3, 4))
assert np.all(q1.take((1, 2)) == np.array([3000, 4000]) * q1.unit)
q1.put(0, 500 * u.cm / u.km)
assert q1.item(0) == 5 * u.m / u.km
def test_slice(self):
"""Test that setitem changes the unit if needed (or ignores it for
values where that is allowed; viz., #2695)"""
q2 = np.array([[1., 2., 3.], [4., 5., 6.]]) * u.km / u.m
q1 = q2.copy()
q2[0, 0] = 10000.
assert q2.unit == q1.unit
assert q2[0, 0].value == 10.
q2[0] = 9. * u.Mm / u.km
assert all(q2.flatten()[:3].value == np.array([9., 9., 9.]))
q2[0, :-1] = 8000.
assert all(q2.flatten()[:3].value == np.array([8., 8., 9.]))
with pytest.raises(u.UnitsError):
q2[1, 1] = 10 * u.s
# just to be sure, repeat with a dimensionfull unit
q3 = u.Quantity(np.arange(10.), "m/s")
q3[5] = 100. * u.cm / u.s
assert q3[5].value == 1.
# and check unit is ignored for 0, inf, nan, where that is reasonable
q3[5] = 0.
assert q3[5] == 0.
q3[5] = np.inf
assert np.isinf(q3[5])
q3[5] = np.nan
assert np.isnan(q3[5])
def test_fill(self):
q1 = np.array([1, 2, 3]) * u.m / u.km
q1.fill(2)
assert np.all(q1 == 2000 * u.m / u.km)
def test_repeat_compress_diagonal(self):
q1 = np.array([1, 2, 3]) * u.m / u.km
q2 = q1.repeat(2)
assert q2.unit == q1.unit
assert all(q2.value == q1.value.repeat(2))
q2.sort()
assert q2.unit == q1.unit
q2 = q1.compress(np.array([True, True, False, False]))
assert q2.unit == q1.unit
assert all(q2.value == q1.value.compress(np.array([True, True,
False, False])))
q1 = np.array([[1, 2], [3, 4]]) * u.m / u.km
q2 = q1.diagonal()
assert q2.unit == q1.unit
assert all(q2.value == q1.value.diagonal())
def test_view(self):
q1 = np.array([1, 2, 3], dtype=np.int64) * u.m / u.km
q2 = q1.view(np.ndarray)
assert not hasattr(q2, 'unit')
q3 = q2.view(u.Quantity)
assert q3._unit is None
# MaskedArray copies and properties assigned in __dict__
q4 = np.ma.MaskedArray(q1)
assert q4._unit is q1._unit
q5 = q4.view(u.Quantity)
assert q5.unit is q1.unit
def test_slice_to_quantity(self):
"""
Regression test for https://github.com/astropy/astropy/issues/2003
"""
a = np.random.uniform(size=(10, 8))
x, y, z = a[:, 1:4].T * u.km/u.s
total = np.sum(a[:, 1] * u.km / u.s - x)
assert isinstance(total, u.Quantity)
assert total == (0.0 * u.km / u.s)
def test_byte_type_view_field_changes(self):
q1 = np.array([1, 2, 3], dtype=np.int64) * u.m / u.km
q2 = q1.byteswap()
assert q2.unit == q1.unit
assert all(q2.value == q1.value.byteswap())
q2 = q1.astype(np.float64)
assert all(q2 == q1)
assert q2.dtype == np.float64
q2a = q1.getfield(np.int32, offset=0)
q2b = q1.byteswap().getfield(np.int32, offset=4)
assert q2a.unit == q1.unit
assert all(q2b.byteswap() == q2a)
def test_sort(self):
q1 = np.array([1., 5., 2., 4.]) * u.km / u.m
i = q1.argsort()
assert not hasattr(i, 'unit')
q1.sort()
i = q1.searchsorted([1500, 2500])
assert not hasattr(i, 'unit')
assert all(i == q1.to(
u.dimensionless_unscaled).value.searchsorted([1500, 2500]))
def test_not_implemented(self):
q1 = np.array([1, 2, 3]) * u.m / u.km
with pytest.raises(NotImplementedError):
q1.choose([0, 0, 1])
with pytest.raises(NotImplementedError):
q1.tolist()
with pytest.raises(NotImplementedError):
q1.tostring()
with pytest.raises(NotImplementedError):
q1.tofile(0)
with pytest.raises(NotImplementedError):
q1.dump('a.a')
with pytest.raises(NotImplementedError):
q1.dumps()
class TestRecArray:
"""Record arrays are not specifically supported, but we should not
prevent their use unnecessarily"""
def setup(self):
self.ra = (np.array(np.arange(12.).reshape(4, 3))
.view(dtype=('f8,f8,f8')).squeeze())
def test_creation(self):
qra = u.Quantity(self.ra, u.m)
assert np.all(qra[:2].value == self.ra[:2])
def test_equality(self):
qra = u.Quantity(self.ra, u.m)
qra[1] = qra[2]
assert qra[1] == qra[2]
|
344ddaee761ef9579cc1cd14d7d22070820bb2fddbce82113e29ee0a0b022025 | # coding: utf-8
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Test the Logarithmic Units and Quantities
"""
import pickle
import itertools
import pytest
import numpy as np
from numpy.testing import assert_allclose
from astropy.tests.helper import assert_quantity_allclose
from astropy import units as u, constants as c
lu_units = [u.dex, u.mag, u.decibel]
lu_subclasses = [u.DexUnit, u.MagUnit, u.DecibelUnit]
lq_subclasses = [u.Dex, u.Magnitude, u.Decibel]
pu_sample = (u.dimensionless_unscaled, u.m, u.g/u.s**2, u.Jy)
class TestLogUnitCreation:
def test_logarithmic_units(self):
"""Check logarithmic units are set up correctly."""
assert u.dB.to(u.dex) == 0.1
assert u.dex.to(u.mag) == -2.5
assert u.mag.to(u.dB) == -4
@pytest.mark.parametrize('lu_unit, lu_cls', zip(lu_units, lu_subclasses))
def test_callable_units(self, lu_unit, lu_cls):
assert isinstance(lu_unit, u.UnitBase)
assert callable(lu_unit)
assert lu_unit._function_unit_class is lu_cls
@pytest.mark.parametrize('lu_unit', lu_units)
def test_equality_to_normal_unit_for_dimensionless(self, lu_unit):
lu = lu_unit()
assert lu == lu._default_function_unit # eg, MagUnit() == u.mag
assert lu._default_function_unit == lu # and u.mag == MagUnit()
@pytest.mark.parametrize('lu_unit, physical_unit',
itertools.product(lu_units, pu_sample))
def test_call_units(self, lu_unit, physical_unit):
"""Create a LogUnit subclass using the callable unit and physical unit,
and do basic check that output is right."""
lu1 = lu_unit(physical_unit)
assert lu1.physical_unit == physical_unit
assert lu1.function_unit == lu1._default_function_unit
def test_call_invalid_unit(self):
with pytest.raises(TypeError):
u.mag([])
with pytest.raises(ValueError):
u.mag(u.mag())
@pytest.mark.parametrize('lu_cls, physical_unit', itertools.product(
lu_subclasses + [u.LogUnit], pu_sample))
def test_subclass_creation(self, lu_cls, physical_unit):
"""Create a LogUnit subclass object for given physical unit,
and do basic check that output is right."""
lu1 = lu_cls(physical_unit)
assert lu1.physical_unit == physical_unit
assert lu1.function_unit == lu1._default_function_unit
lu2 = lu_cls(physical_unit,
function_unit=2*lu1._default_function_unit)
assert lu2.physical_unit == physical_unit
assert lu2.function_unit == u.Unit(2*lu2._default_function_unit)
with pytest.raises(ValueError):
lu_cls(physical_unit, u.m)
def test_lshift_magnitude(self):
mag = 1. << u.ABmag
assert isinstance(mag, u.Magnitude)
assert mag.unit == u.ABmag
assert mag.value == 1.
# same test for an array, which should produce a view
a2 = np.arange(10.)
q2 = a2 << u.ABmag
assert isinstance(q2, u.Magnitude)
assert q2.unit == u.ABmag
assert np.all(q2.value == a2)
a2[9] = 0.
assert np.all(q2.value == a2)
# a different magnitude unit
mag = 10. << u.STmag
assert isinstance(mag, u.Magnitude)
assert mag.unit == u.STmag
assert mag.value == 10.
def test_ilshift_magnitude(self):
# test in-place operation and conversion
mag_fnu_cgs = u.mag(u.erg/u.s/u.cm**2/u.Hz)
m = np.arange(10.0) * u.mag(u.Jy)
jy = m.physical
m2 = m << mag_fnu_cgs
assert np.all(m2 == m.to(mag_fnu_cgs))
m2 = m
m <<= mag_fnu_cgs
assert m is m2 # Check it was done in-place!
assert np.all(m.value == m2.value)
assert m.unit == mag_fnu_cgs
# Check it works if equivalencies are in-place.
with u.add_enabled_equivalencies(u.spectral_density(5500*u.AA)):
st = jy.to(u.ST)
m <<= u.STmag
assert m is m2
assert_quantity_allclose(m.physical, st)
assert m.unit == u.STmag
def test_lshift_errors(self):
m = np.arange(10.0) * u.mag(u.Jy)
with pytest.raises(u.UnitsError):
m << u.STmag
with pytest.raises(u.UnitsError):
m << u.Jy
with pytest.raises(u.UnitsError):
m <<= u.STmag
with pytest.raises(u.UnitsError):
m <<= u.Jy
def test_predefined_magnitudes():
assert_quantity_allclose((-21.1*u.STmag).physical,
1.*u.erg/u.cm**2/u.s/u.AA)
assert_quantity_allclose((-48.6*u.ABmag).physical,
1.*u.erg/u.cm**2/u.s/u.Hz)
assert_quantity_allclose((0*u.M_bol).physical, c.L_bol0)
assert_quantity_allclose((0*u.m_bol).physical,
c.L_bol0/(4.*np.pi*(10.*c.pc)**2))
def test_predefined_reinitialisation():
assert u.mag('STflux') == u.STmag
assert u.mag('ABflux') == u.ABmag
assert u.mag('Bol') == u.M_bol
assert u.mag('bol') == u.m_bol
# required for backwards-compatibility, at least unless deprecated
assert u.mag('ST') == u.STmag
assert u.mag('AB') == u.ABmag
def test_predefined_string_roundtrip():
"""Ensure round-tripping; see #5015"""
with u.magnitude_zero_points.enable():
assert u.Unit(u.STmag.to_string()) == u.STmag
assert u.Unit(u.ABmag.to_string()) == u.ABmag
assert u.Unit(u.M_bol.to_string()) == u.M_bol
assert u.Unit(u.m_bol.to_string()) == u.m_bol
def test_inequality():
"""Check __ne__ works (regresssion for #5342)."""
lu1 = u.mag(u.Jy)
lu2 = u.dex(u.Jy)
lu3 = u.mag(u.Jy**2)
lu4 = lu3 - lu1
assert lu1 != lu2
assert lu1 != lu3
assert lu1 == lu4
class TestLogUnitStrings:
def test_str(self):
"""Do some spot checks that str, repr, etc. work as expected."""
lu1 = u.mag(u.Jy)
assert str(lu1) == 'mag(Jy)'
assert repr(lu1) == 'Unit("mag(Jy)")'
assert lu1.to_string('generic') == 'mag(Jy)'
with pytest.raises(ValueError):
lu1.to_string('fits')
lu2 = u.dex()
assert str(lu2) == 'dex'
assert repr(lu2) == 'Unit("dex(1)")'
assert lu2.to_string() == 'dex(1)'
lu3 = u.MagUnit(u.Jy, function_unit=2*u.mag)
assert str(lu3) == '2 mag(Jy)'
assert repr(lu3) == 'MagUnit("Jy", unit="2 mag")'
assert lu3.to_string() == '2 mag(Jy)'
lu4 = u.mag(u.ct)
assert lu4.to_string('generic') == 'mag(ct)'
assert lu4.to_string('latex') == ('$\\mathrm{mag}$$\\mathrm{\\left( '
'\\mathrm{ct} \\right)}$')
assert lu4._repr_latex_() == lu4.to_string('latex')
class TestLogUnitConversion:
@pytest.mark.parametrize('lu_unit, physical_unit',
itertools.product(lu_units, pu_sample))
def test_physical_unit_conversion(self, lu_unit, physical_unit):
"""Check various LogUnit subclasses are equivalent and convertible
to their non-log counterparts."""
lu1 = lu_unit(physical_unit)
assert lu1.is_equivalent(physical_unit)
assert lu1.to(physical_unit, 0.) == 1.
assert physical_unit.is_equivalent(lu1)
assert physical_unit.to(lu1, 1.) == 0.
pu = u.Unit(8.*physical_unit)
assert lu1.is_equivalent(physical_unit)
assert lu1.to(pu, 0.) == 0.125
assert pu.is_equivalent(lu1)
assert_allclose(pu.to(lu1, 0.125), 0., atol=1.e-15)
# Check we round-trip.
value = np.linspace(0., 10., 6)
assert_allclose(pu.to(lu1, lu1.to(pu, value)), value, atol=1.e-15)
# And that we're not just returning True all the time.
pu2 = u.g
assert not lu1.is_equivalent(pu2)
with pytest.raises(u.UnitsError):
lu1.to(pu2)
assert not pu2.is_equivalent(lu1)
with pytest.raises(u.UnitsError):
pu2.to(lu1)
@pytest.mark.parametrize('lu_unit', lu_units)
def test_container_unit_conversion(self, lu_unit):
"""Check that conversion to logarithmic units (u.mag, u.dB, u.dex)
is only possible when the physical unit is dimensionless."""
values = np.linspace(0., 10., 6)
lu1 = lu_unit(u.dimensionless_unscaled)
assert lu1.is_equivalent(lu1.function_unit)
assert_allclose(lu1.to(lu1.function_unit, values), values)
lu2 = lu_unit(u.Jy)
assert not lu2.is_equivalent(lu2.function_unit)
with pytest.raises(u.UnitsError):
lu2.to(lu2.function_unit, values)
@pytest.mark.parametrize(
'flu_unit, tlu_unit, physical_unit',
itertools.product(lu_units, lu_units, pu_sample))
def test_subclass_conversion(self, flu_unit, tlu_unit, physical_unit):
"""Check various LogUnit subclasses are equivalent and convertible
to each other if they correspond to equivalent physical units."""
values = np.linspace(0., 10., 6)
flu = flu_unit(physical_unit)
tlu = tlu_unit(physical_unit)
assert flu.is_equivalent(tlu)
assert_allclose(flu.to(tlu), flu.function_unit.to(tlu.function_unit))
assert_allclose(flu.to(tlu, values),
values * flu.function_unit.to(tlu.function_unit))
tlu2 = tlu_unit(u.Unit(100.*physical_unit))
assert flu.is_equivalent(tlu2)
# Check that we round-trip.
assert_allclose(flu.to(tlu2, tlu2.to(flu, values)), values, atol=1.e-15)
tlu3 = tlu_unit(physical_unit.to_system(u.si)[0])
assert flu.is_equivalent(tlu3)
assert_allclose(flu.to(tlu3, tlu3.to(flu, values)), values, atol=1.e-15)
tlu4 = tlu_unit(u.g)
assert not flu.is_equivalent(tlu4)
with pytest.raises(u.UnitsError):
flu.to(tlu4, values)
def test_unit_decomposition(self):
lu = u.mag(u.Jy)
assert lu.decompose() == u.mag(u.Jy.decompose())
assert lu.decompose().physical_unit.bases == [u.kg, u.s]
assert lu.si == u.mag(u.Jy.si)
assert lu.si.physical_unit.bases == [u.kg, u.s]
assert lu.cgs == u.mag(u.Jy.cgs)
assert lu.cgs.physical_unit.bases == [u.g, u.s]
def test_unit_multiple_possible_equivalencies(self):
lu = u.mag(u.Jy)
assert lu.is_equivalent(pu_sample)
def test_magnitude_conversion_fails_message(self):
"""Check that "dimensionless" magnitude units include a message in their
exception text suggesting a possible cause of the problem.
"""
with pytest.raises(u.UnitConversionError) as excinfo:
(10*u.ABmag - 2*u.ABmag).to(u.nJy)
assert "Did you perhaps subtract magnitudes so the unit got lost?" in str(excinfo.value)
class TestLogUnitArithmetic:
def test_multiplication_division(self):
"""Check that multiplication/division with other units is only
possible when the physical unit is dimensionless, and that this
turns the unit into a normal one."""
lu1 = u.mag(u.Jy)
with pytest.raises(u.UnitsError):
lu1 * u.m
with pytest.raises(u.UnitsError):
u.m * lu1
with pytest.raises(u.UnitsError):
lu1 / lu1
for unit in (u.dimensionless_unscaled, u.m, u.mag, u.dex):
with pytest.raises(u.UnitsError):
lu1 / unit
lu2 = u.mag(u.dimensionless_unscaled)
with pytest.raises(u.UnitsError):
lu2 * lu1
with pytest.raises(u.UnitsError):
lu2 / lu1
# But dimensionless_unscaled can be cancelled.
assert lu2 / lu2 == u.dimensionless_unscaled
# With dimensionless, normal units are OK, but we return a plain unit.
tf = lu2 * u.m
tr = u.m * lu2
for t in (tf, tr):
assert not isinstance(t, type(lu2))
assert t == lu2.function_unit * u.m
with u.set_enabled_equivalencies(u.logarithmic()):
with pytest.raises(u.UnitsError):
t.to(lu2.physical_unit)
# Now we essentially have a LogUnit with a prefactor of 100,
# so should be equivalent again.
t = tf / u.cm
with u.set_enabled_equivalencies(u.logarithmic()):
assert t.is_equivalent(lu2.function_unit)
assert_allclose(t.to(u.dimensionless_unscaled, np.arange(3.)/100.),
lu2.to(lu2.physical_unit, np.arange(3.)))
# If we effectively remove lu1, a normal unit should be returned.
t2 = tf / lu2
assert not isinstance(t2, type(lu2))
assert t2 == u.m
t3 = tf / lu2.function_unit
assert not isinstance(t3, type(lu2))
assert t3 == u.m
# For completeness, also ensure non-sensical operations fail
with pytest.raises(TypeError):
lu1 * object()
with pytest.raises(TypeError):
slice(None) * lu1
with pytest.raises(TypeError):
lu1 / []
with pytest.raises(TypeError):
1 / lu1
@pytest.mark.parametrize('power', (2, 0.5, 1, 0))
def test_raise_to_power(self, power):
"""Check that raising LogUnits to some power is only possible when the
physical unit is dimensionless, and that conversion is turned off when
the resulting logarithmic unit (such as mag**2) is incompatible."""
lu1 = u.mag(u.Jy)
if power == 0:
assert lu1 ** power == u.dimensionless_unscaled
elif power == 1:
assert lu1 ** power == lu1
else:
with pytest.raises(u.UnitsError):
lu1 ** power
# With dimensionless, though, it works, but returns a normal unit.
lu2 = u.mag(u.dimensionless_unscaled)
t = lu2**power
if power == 0:
assert t == u.dimensionless_unscaled
elif power == 1:
assert t == lu2
else:
assert not isinstance(t, type(lu2))
assert t == lu2.function_unit**power
# also check we roundtrip
t2 = t**(1./power)
assert t2 == lu2.function_unit
with u.set_enabled_equivalencies(u.logarithmic()):
assert_allclose(t2.to(u.dimensionless_unscaled, np.arange(3.)),
lu2.to(lu2.physical_unit, np.arange(3.)))
@pytest.mark.parametrize('other', pu_sample)
def test_addition_subtraction_to_normal_units_fails(self, other):
lu1 = u.mag(u.Jy)
with pytest.raises(u.UnitsError):
lu1 + other
with pytest.raises(u.UnitsError):
lu1 - other
with pytest.raises(u.UnitsError):
other - lu1
def test_addition_subtraction_to_non_units_fails(self):
lu1 = u.mag(u.Jy)
with pytest.raises(TypeError):
lu1 + 1.
with pytest.raises(TypeError):
lu1 - [1., 2., 3.]
@pytest.mark.parametrize(
'other', (u.mag, u.mag(), u.mag(u.Jy), u.mag(u.m),
u.Unit(2*u.mag), u.MagUnit('', 2.*u.mag)))
def test_addition_subtraction(self, other):
"""Check physical units are changed appropriately"""
lu1 = u.mag(u.Jy)
other_pu = getattr(other, 'physical_unit', u.dimensionless_unscaled)
lu_sf = lu1 + other
assert lu_sf.is_equivalent(lu1.physical_unit * other_pu)
lu_sr = other + lu1
assert lu_sr.is_equivalent(lu1.physical_unit * other_pu)
lu_df = lu1 - other
assert lu_df.is_equivalent(lu1.physical_unit / other_pu)
lu_dr = other - lu1
assert lu_dr.is_equivalent(other_pu / lu1.physical_unit)
def test_complicated_addition_subtraction(self):
"""for fun, a more complicated example of addition and subtraction"""
dm0 = u.Unit('DM', 1./(4.*np.pi*(10.*u.pc)**2))
lu_dm = u.mag(dm0)
lu_absST = u.STmag - lu_dm
assert lu_absST.is_equivalent(u.erg/u.s/u.AA)
def test_neg_pos(self):
lu1 = u.mag(u.Jy)
neg_lu = -lu1
assert neg_lu != lu1
assert neg_lu.physical_unit == u.Jy**-1
assert -neg_lu == lu1
pos_lu = +lu1
assert pos_lu is not lu1
assert pos_lu == lu1
def test_pickle():
lu1 = u.dex(u.cm/u.s**2)
s = pickle.dumps(lu1)
lu2 = pickle.loads(s)
assert lu1 == lu2
def test_hashable():
lu1 = u.dB(u.mW)
lu2 = u.dB(u.m)
lu3 = u.dB(u.mW)
assert hash(lu1) != hash(lu2)
assert hash(lu1) == hash(lu3)
luset = {lu1, lu2, lu3}
assert len(luset) == 2
class TestLogQuantityCreation:
@pytest.mark.parametrize('lq, lu', zip(lq_subclasses + [u.LogQuantity],
lu_subclasses + [u.LogUnit]))
def test_logarithmic_quantities(self, lq, lu):
"""Check logarithmic quantities are all set up correctly"""
assert lq._unit_class == lu
assert type(lu()._quantity_class(1.)) is lq
@pytest.mark.parametrize('lq_cls, physical_unit',
itertools.product(lq_subclasses, pu_sample))
def test_subclass_creation(self, lq_cls, physical_unit):
"""Create LogQuantity subclass objects for some physical units,
and basic check on transformations"""
value = np.arange(1., 10.)
log_q = lq_cls(value * physical_unit)
assert log_q.unit.physical_unit == physical_unit
assert log_q.unit.function_unit == log_q.unit._default_function_unit
assert_allclose(log_q.physical.value, value)
with pytest.raises(ValueError):
lq_cls(value, physical_unit)
@pytest.mark.parametrize(
'unit', (u.mag, u.mag(), u.mag(u.Jy), u.mag(u.m),
u.Unit(2*u.mag), u.MagUnit('', 2.*u.mag),
u.MagUnit(u.Jy, -1*u.mag), u.MagUnit(u.m, -2.*u.mag)))
def test_different_units(self, unit):
q = u.Magnitude(1.23, unit)
assert q.unit.function_unit == getattr(unit, 'function_unit', unit)
assert q.unit.physical_unit is getattr(unit, 'physical_unit',
u.dimensionless_unscaled)
@pytest.mark.parametrize('value, unit', (
(1.*u.mag(u.Jy), None),
(1.*u.dex(u.Jy), None),
(1.*u.mag(u.W/u.m**2/u.Hz), u.mag(u.Jy)),
(1.*u.dex(u.W/u.m**2/u.Hz), u.mag(u.Jy))))
def test_function_values(self, value, unit):
lq = u.Magnitude(value, unit)
assert lq == value
assert lq.unit.function_unit == u.mag
assert lq.unit.physical_unit == getattr(unit, 'physical_unit',
value.unit.physical_unit)
@pytest.mark.parametrize(
'unit', (u.mag(), u.mag(u.Jy), u.mag(u.m), u.MagUnit('', 2.*u.mag),
u.MagUnit(u.Jy, -1*u.mag), u.MagUnit(u.m, -2.*u.mag)))
def test_indirect_creation(self, unit):
q1 = 2.5 * unit
assert isinstance(q1, u.Magnitude)
assert q1.value == 2.5
assert q1.unit == unit
pv = 100. * unit.physical_unit
q2 = unit * pv
assert q2.unit == unit
assert q2.unit.physical_unit == pv.unit
assert q2.to_value(unit.physical_unit) == 100.
assert (q2._function_view / u.mag).to_value(1) == -5.
q3 = unit / 0.4
assert q3 == q1
def test_from_view(self):
# Cannot view a physical quantity as a function quantity, since the
# values would change.
q = [100., 1000.] * u.cm/u.s**2
with pytest.raises(TypeError):
q.view(u.Dex)
# But fine if we have the right magnitude.
q = [2., 3.] * u.dex
lq = q.view(u.Dex)
assert isinstance(lq, u.Dex)
assert lq.unit.physical_unit == u.dimensionless_unscaled
assert np.all(q == lq)
def test_using_quantity_class(self):
"""Check that we can use Quantity if we have subok=True"""
# following issue #5851
lu = u.dex(u.AA)
with pytest.raises(u.UnitTypeError):
u.Quantity(1., lu)
q = u.Quantity(1., lu, subok=True)
assert type(q) is lu._quantity_class
def test_conversion_to_and_from_physical_quantities():
"""Ensures we can convert from regular quantities."""
mst = [10., 12., 14.] * u.STmag
flux_lambda = mst.physical
mst_roundtrip = flux_lambda.to(u.STmag)
# check we return a logquantity; see #5178.
assert isinstance(mst_roundtrip, u.Magnitude)
assert mst_roundtrip.unit == mst.unit
assert_allclose(mst_roundtrip.value, mst.value)
wave = [4956.8, 4959.55, 4962.3] * u.AA
flux_nu = mst.to(u.Jy, equivalencies=u.spectral_density(wave))
mst_roundtrip2 = flux_nu.to(u.STmag, u.spectral_density(wave))
assert isinstance(mst_roundtrip2, u.Magnitude)
assert mst_roundtrip2.unit == mst.unit
assert_allclose(mst_roundtrip2.value, mst.value)
def test_quantity_decomposition():
lq = 10.*u.mag(u.Jy)
assert lq.decompose() == lq
assert lq.decompose().unit.physical_unit.bases == [u.kg, u.s]
assert lq.si == lq
assert lq.si.unit.physical_unit.bases == [u.kg, u.s]
assert lq.cgs == lq
assert lq.cgs.unit.physical_unit.bases == [u.g, u.s]
class TestLogQuantityViews:
def setup(self):
self.lq = u.Magnitude(np.arange(10.) * u.Jy)
self.lq2 = u.Magnitude(np.arange(5.))
def test_value_view(self):
lq_value = self.lq.value
assert type(lq_value) is np.ndarray
lq_value[2] = -1.
assert np.all(self.lq.value == lq_value)
def test_function_view(self):
lq_fv = self.lq._function_view
assert type(lq_fv) is u.Quantity
assert lq_fv.unit is self.lq.unit.function_unit
lq_fv[3] = -2. * lq_fv.unit
assert np.all(self.lq.value == lq_fv.value)
def test_quantity_view(self):
# Cannot view as Quantity, since the unit cannot be represented.
with pytest.raises(TypeError):
self.lq.view(u.Quantity)
# But a dimensionless one is fine.
q2 = self.lq2.view(u.Quantity)
assert q2.unit is u.mag
assert np.all(q2.value == self.lq2.value)
lq3 = q2.view(u.Magnitude)
assert type(lq3.unit) is u.MagUnit
assert lq3.unit.physical_unit == u.dimensionless_unscaled
assert np.all(lq3 == self.lq2)
class TestLogQuantitySlicing:
def test_item_get_and_set(self):
lq1 = u.Magnitude(np.arange(1., 11.)*u.Jy)
assert lq1[9] == u.Magnitude(10.*u.Jy)
lq1[2] = 100.*u.Jy
assert lq1[2] == u.Magnitude(100.*u.Jy)
with pytest.raises(u.UnitsError):
lq1[2] = 100.*u.m
with pytest.raises(u.UnitsError):
lq1[2] = 100.*u.mag
with pytest.raises(u.UnitsError):
lq1[2] = u.Magnitude(100.*u.m)
assert lq1[2] == u.Magnitude(100.*u.Jy)
def test_slice_get_and_set(self):
lq1 = u.Magnitude(np.arange(1., 10.)*u.Jy)
lq1[2:4] = 100.*u.Jy
assert np.all(lq1[2:4] == u.Magnitude(100.*u.Jy))
with pytest.raises(u.UnitsError):
lq1[2:4] = 100.*u.m
with pytest.raises(u.UnitsError):
lq1[2:4] = 100.*u.mag
with pytest.raises(u.UnitsError):
lq1[2:4] = u.Magnitude(100.*u.m)
assert np.all(lq1[2] == u.Magnitude(100.*u.Jy))
class TestLogQuantityArithmetic:
def test_multiplication_division(self):
"""Check that multiplication/division with other quantities is only
possible when the physical unit is dimensionless, and that this turns
the result into a normal quantity."""
lq = u.Magnitude(np.arange(1., 11.)*u.Jy)
with pytest.raises(u.UnitsError):
lq * (1.*u.m)
with pytest.raises(u.UnitsError):
(1.*u.m) * lq
with pytest.raises(u.UnitsError):
lq / lq
for unit in (u.m, u.mag, u.dex):
with pytest.raises(u.UnitsError):
lq / unit
lq2 = u.Magnitude(np.arange(1, 11.))
with pytest.raises(u.UnitsError):
lq2 * lq
with pytest.raises(u.UnitsError):
lq2 / lq
with pytest.raises(u.UnitsError):
lq / lq2
# but dimensionless_unscaled can be cancelled
r = lq2 / u.Magnitude(2.)
assert r.unit == u.dimensionless_unscaled
assert np.all(r.value == lq2.value/2.)
# with dimensionless, normal units OK, but return normal quantities
tf = lq2 * u.m
tr = u.m * lq2
for t in (tf, tr):
assert not isinstance(t, type(lq2))
assert t.unit == lq2.unit.function_unit * u.m
with u.set_enabled_equivalencies(u.logarithmic()):
with pytest.raises(u.UnitsError):
t.to(lq2.unit.physical_unit)
t = tf / (50.*u.cm)
# now we essentially have the same quantity but with a prefactor of 2
assert t.unit.is_equivalent(lq2.unit.function_unit)
assert_allclose(t.to(lq2.unit.function_unit), lq2._function_view*2)
@pytest.mark.parametrize('power', (2, 0.5, 1, 0))
def test_raise_to_power(self, power):
"""Check that raising LogQuantities to some power is only possible when
the physical unit is dimensionless, and that conversion is turned off
when the resulting logarithmic unit (say, mag**2) is incompatible."""
lq = u.Magnitude(np.arange(1., 4.)*u.Jy)
if power == 0:
assert np.all(lq ** power == 1.)
elif power == 1:
assert np.all(lq ** power == lq)
else:
with pytest.raises(u.UnitsError):
lq ** power
# with dimensionless, it works, but falls back to normal quantity
# (except for power=1)
lq2 = u.Magnitude(np.arange(10.))
t = lq2**power
if power == 0:
assert t.unit is u.dimensionless_unscaled
assert np.all(t.value == 1.)
elif power == 1:
assert np.all(t == lq2)
else:
assert not isinstance(t, type(lq2))
assert t.unit == lq2.unit.function_unit ** power
with u.set_enabled_equivalencies(u.logarithmic()):
with pytest.raises(u.UnitsError):
t.to(u.dimensionless_unscaled)
def test_error_on_lq_as_power(self):
lq = u.Magnitude(np.arange(1., 4.)*u.Jy)
with pytest.raises(TypeError):
lq ** lq
@pytest.mark.parametrize('other', pu_sample)
def test_addition_subtraction_to_normal_units_fails(self, other):
lq = u.Magnitude(np.arange(1., 10.)*u.Jy)
q = 1.23 * other
with pytest.raises(u.UnitsError):
lq + q
with pytest.raises(u.UnitsError):
lq - q
with pytest.raises(u.UnitsError):
q - lq
@pytest.mark.parametrize(
'other', (1.23 * u.mag, 2.34 * u.mag(),
u.Magnitude(3.45 * u.Jy), u.Magnitude(4.56 * u.m),
5.67 * u.Unit(2*u.mag), u.Magnitude(6.78, 2.*u.mag)))
def test_addition_subtraction(self, other):
"""Check that addition/subtraction with quantities with magnitude or
MagUnit units works, and that it changes the physical units
appropriately."""
lq = u.Magnitude(np.arange(1., 10.)*u.Jy)
other_physical = other.to(getattr(other.unit, 'physical_unit',
u.dimensionless_unscaled),
equivalencies=u.logarithmic())
lq_sf = lq + other
assert_allclose(lq_sf.physical, lq.physical * other_physical)
lq_sr = other + lq
assert_allclose(lq_sr.physical, lq.physical * other_physical)
lq_df = lq - other
assert_allclose(lq_df.physical, lq.physical / other_physical)
lq_dr = other - lq
assert_allclose(lq_dr.physical, other_physical / lq.physical)
@pytest.mark.parametrize('other', pu_sample)
def test_inplace_addition_subtraction_unit_checks(self, other):
lu1 = u.mag(u.Jy)
lq1 = u.Magnitude(np.arange(1., 10.), lu1)
with pytest.raises(u.UnitsError):
lq1 += other
assert np.all(lq1.value == np.arange(1., 10.))
assert lq1.unit == lu1
with pytest.raises(u.UnitsError):
lq1 -= other
assert np.all(lq1.value == np.arange(1., 10.))
assert lq1.unit == lu1
@pytest.mark.parametrize(
'other', (1.23 * u.mag, 2.34 * u.mag(),
u.Magnitude(3.45 * u.Jy), u.Magnitude(4.56 * u.m),
5.67 * u.Unit(2*u.mag), u.Magnitude(6.78, 2.*u.mag)))
def test_inplace_addition_subtraction(self, other):
"""Check that inplace addition/subtraction with quantities with
magnitude or MagUnit units works, and that it changes the physical
units appropriately."""
lq = u.Magnitude(np.arange(1., 10.)*u.Jy)
other_physical = other.to(getattr(other.unit, 'physical_unit',
u.dimensionless_unscaled),
equivalencies=u.logarithmic())
lq_sf = lq.copy()
lq_sf += other
assert_allclose(lq_sf.physical, lq.physical * other_physical)
lq_df = lq.copy()
lq_df -= other
assert_allclose(lq_df.physical, lq.physical / other_physical)
def test_complicated_addition_subtraction(self):
"""For fun, a more complicated example of addition and subtraction."""
dm0 = u.Unit('DM', 1./(4.*np.pi*(10.*u.pc)**2))
DMmag = u.mag(dm0)
m_st = 10. * u.STmag
dm = 5. * DMmag
M_st = m_st - dm
assert M_st.unit.is_equivalent(u.erg/u.s/u.AA)
assert np.abs(M_st.physical /
(m_st.physical*4.*np.pi*(100.*u.pc)**2) - 1.) < 1.e-15
class TestLogQuantityComparisons:
def test_comparison_to_non_quantities_fails(self):
lq = u.Magnitude(np.arange(1., 10.)*u.Jy)
with pytest.raises(TypeError):
lq > 'a'
assert not (lq == 'a')
assert lq != 'a'
def test_comparison(self):
lq1 = u.Magnitude(np.arange(1., 4.)*u.Jy)
lq2 = u.Magnitude(2.*u.Jy)
assert np.all((lq1 > lq2) == np.array([True, False, False]))
assert np.all((lq1 == lq2) == np.array([False, True, False]))
lq3 = u.Dex(2.*u.Jy)
assert np.all((lq1 > lq3) == np.array([True, False, False]))
assert np.all((lq1 == lq3) == np.array([False, True, False]))
lq4 = u.Magnitude(2.*u.m)
assert not (lq1 == lq4)
assert lq1 != lq4
with pytest.raises(u.UnitsError):
lq1 < lq4
q5 = 1.5 * u.Jy
assert np.all((lq1 > q5) == np.array([True, False, False]))
assert np.all((q5 < lq1) == np.array([True, False, False]))
with pytest.raises(u.UnitsError):
lq1 >= 2.*u.m
with pytest.raises(u.UnitsError):
lq1 <= lq1.value * u.mag
# For physically dimensionless, we can compare with the function unit.
lq6 = u.Magnitude(np.arange(1., 4.))
fv6 = lq6.value * u.mag
assert np.all(lq6 == fv6)
# but not some arbitrary unit, of course.
with pytest.raises(u.UnitsError):
lq6 < 2.*u.m
class TestLogQuantityMethods:
def setup(self):
self.mJy = np.arange(1., 5.).reshape(2, 2) * u.mag(u.Jy)
self.m1 = np.arange(1., 5.5, 0.5).reshape(3, 3) * u.mag()
self.mags = (self.mJy, self.m1)
@pytest.mark.parametrize('method', ('mean', 'min', 'max', 'round', 'trace',
'std', 'var', 'ptp', 'diff', 'ediff1d'))
def test_always_ok(self, method):
for mag in self.mags:
res = getattr(mag, method)()
assert np.all(res.value ==
getattr(mag._function_view, method)().value)
if method in ('std', 'ptp', 'diff', 'ediff1d'):
assert res.unit == u.mag()
elif method == 'var':
assert res.unit == u.mag**2
else:
assert res.unit == mag.unit
def test_clip(self):
for mag in self.mags:
assert np.all(mag.clip(2. * mag.unit, 4. * mag.unit).value ==
mag.value.clip(2., 4.))
@pytest.mark.parametrize('method', ('sum', 'cumsum', 'nansum'))
def test_only_ok_if_dimensionless(self, method):
res = getattr(self.m1, method)()
assert np.all(res.value ==
getattr(self.m1._function_view, method)().value)
assert res.unit == self.m1.unit
with pytest.raises(TypeError):
getattr(self.mJy, method)()
def test_dot(self):
assert np.all(self.m1.dot(self.m1).value ==
self.m1.value.dot(self.m1.value))
@pytest.mark.parametrize('method', ('prod', 'cumprod'))
def test_never_ok(self, method):
with pytest.raises(TypeError):
getattr(self.mJy, method)()
with pytest.raises(TypeError):
getattr(self.m1, method)()
|
d7db36018d388aa14ecb5447678c59eaf785f419576627d1c2ee262958bf3eb0 | # coding: utf-8
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Test the Quantity class and related.
"""
import copy
import pickle
import decimal
from fractions import Fraction
import pytest
import numpy as np
from numpy.testing import (assert_allclose, assert_array_equal,
assert_array_almost_equal)
from astropy.tests.helper import catch_warnings, raises
from astropy.utils import isiterable, minversion
from astropy.utils.compat import NUMPY_LT_1_14
from astropy.utils.exceptions import AstropyDeprecationWarning, AstropyWarning
from astropy import units as u
from astropy.units.quantity import _UNIT_NOT_INITIALISED
try:
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from distutils.version import LooseVersion
MATPLOTLIB_LT_15 = LooseVersion(matplotlib.__version__) < LooseVersion("1.5")
HAS_MATPLOTLIB = True
except ImportError:
HAS_MATPLOTLIB = False
""" The Quantity class will represent a number + unit + uncertainty """
class TestQuantityCreation:
def test_1(self):
# create objects through operations with Unit objects:
quantity = 11.42 * u.meter # returns a Quantity object
assert isinstance(quantity, u.Quantity)
quantity = u.meter * 11.42 # returns a Quantity object
assert isinstance(quantity, u.Quantity)
quantity = 11.42 / u.meter
assert isinstance(quantity, u.Quantity)
quantity = u.meter / 11.42
assert isinstance(quantity, u.Quantity)
quantity = 11.42 * u.meter / u.second
assert isinstance(quantity, u.Quantity)
with pytest.raises(TypeError):
quantity = 182.234 + u.meter
with pytest.raises(TypeError):
quantity = 182.234 - u.meter
with pytest.raises(TypeError):
quantity = 182.234 % u.meter
def test_2(self):
# create objects using the Quantity constructor:
q1 = u.Quantity(11.412, unit=u.meter)
q2 = u.Quantity(21.52, "cm")
q3 = u.Quantity(11.412)
# By default quantities that don't specify a unit are unscaled
# dimensionless
assert q3.unit == u.Unit(1)
with pytest.raises(TypeError):
q4 = u.Quantity(object(), unit=u.m)
def test_3(self):
# with pytest.raises(u.UnitsError):
with pytest.raises(ValueError): # Until @mdboom fixes the errors in units
q1 = u.Quantity(11.412, unit="testingggg")
def test_nan_inf(self):
# Not-a-number
q = u.Quantity('nan', unit='cm')
assert np.isnan(q.value)
q = u.Quantity('NaN', unit='cm')
assert np.isnan(q.value)
q = u.Quantity('-nan', unit='cm') # float() allows this
assert np.isnan(q.value)
q = u.Quantity('nan cm')
assert np.isnan(q.value)
assert q.unit == u.cm
# Infinity
q = u.Quantity('inf', unit='cm')
assert np.isinf(q.value)
q = u.Quantity('-inf', unit='cm')
assert np.isinf(q.value)
q = u.Quantity('inf cm')
assert np.isinf(q.value)
assert q.unit == u.cm
q = u.Quantity('Infinity', unit='cm') # float() allows this
assert np.isinf(q.value)
# make sure these strings don't parse...
with pytest.raises(TypeError):
q = u.Quantity('', unit='cm')
with pytest.raises(TypeError):
q = u.Quantity('spam', unit='cm')
def test_unit_property(self):
# test getting and setting 'unit' attribute
q1 = u.Quantity(11.4, unit=u.meter)
with pytest.raises(AttributeError):
q1.unit = u.cm
def test_preserve_dtype(self):
"""Test that if an explicit dtype is given, it is used, while if not,
numbers are converted to float (including decimal.Decimal, which
numpy converts to an object; closes #1419)
"""
# If dtype is specified, use it, but if not, convert int, bool to float
q1 = u.Quantity(12, unit=u.m / u.s, dtype=int)
assert q1.dtype == int
q2 = u.Quantity(q1)
assert q2.dtype == float
assert q2.value == float(q1.value)
assert q2.unit == q1.unit
# but we should preserve float32
a3 = np.array([1., 2.], dtype=np.float32)
q3 = u.Quantity(a3, u.yr)
assert q3.dtype == a3.dtype
# items stored as objects by numpy should be converted to float
# by default
q4 = u.Quantity(decimal.Decimal('10.25'), u.m)
assert q4.dtype == float
q5 = u.Quantity(decimal.Decimal('10.25'), u.m, dtype=object)
assert q5.dtype == object
def test_copy(self):
# By default, a new quantity is constructed, but not if copy=False
a = np.arange(10.)
q0 = u.Quantity(a, unit=u.m / u.s)
assert q0.base is not a
q1 = u.Quantity(a, unit=u.m / u.s, copy=False)
assert q1.base is a
q2 = u.Quantity(q0)
assert q2 is not q0
assert q2.base is not q0.base
q2 = u.Quantity(q0, copy=False)
assert q2 is q0
assert q2.base is q0.base
q3 = u.Quantity(q0, q0.unit, copy=False)
assert q3 is q0
assert q3.base is q0.base
q4 = u.Quantity(q0, u.cm / u.s, copy=False)
assert q4 is not q0
assert q4.base is not q0.base
def test_subok(self):
"""Test subok can be used to keep class, or to insist on Quantity"""
class MyQuantitySubclass(u.Quantity):
pass
myq = MyQuantitySubclass(np.arange(10.), u.m)
# try both with and without changing the unit
assert type(u.Quantity(myq)) is u.Quantity
assert type(u.Quantity(myq, subok=True)) is MyQuantitySubclass
assert type(u.Quantity(myq, u.km)) is u.Quantity
assert type(u.Quantity(myq, u.km, subok=True)) is MyQuantitySubclass
def test_order(self):
"""Test that order is correctly propagated to np.array"""
ac = np.array(np.arange(10.), order='C')
qcc = u.Quantity(ac, u.m, order='C')
assert qcc.flags['C_CONTIGUOUS']
qcf = u.Quantity(ac, u.m, order='F')
assert qcf.flags['F_CONTIGUOUS']
qca = u.Quantity(ac, u.m, order='A')
assert qca.flags['C_CONTIGUOUS']
# check it works also when passing in a quantity
assert u.Quantity(qcc, order='C').flags['C_CONTIGUOUS']
assert u.Quantity(qcc, order='A').flags['C_CONTIGUOUS']
assert u.Quantity(qcc, order='F').flags['F_CONTIGUOUS']
af = np.array(np.arange(10.), order='F')
qfc = u.Quantity(af, u.m, order='C')
assert qfc.flags['C_CONTIGUOUS']
qff = u.Quantity(ac, u.m, order='F')
assert qff.flags['F_CONTIGUOUS']
qfa = u.Quantity(af, u.m, order='A')
assert qfa.flags['F_CONTIGUOUS']
assert u.Quantity(qff, order='C').flags['C_CONTIGUOUS']
assert u.Quantity(qff, order='A').flags['F_CONTIGUOUS']
assert u.Quantity(qff, order='F').flags['F_CONTIGUOUS']
def test_ndmin(self):
"""Test that ndmin is correctly propagated to np.array"""
a = np.arange(10.)
q1 = u.Quantity(a, u.m, ndmin=1)
assert q1.ndim == 1 and q1.shape == (10,)
q2 = u.Quantity(a, u.m, ndmin=2)
assert q2.ndim == 2 and q2.shape == (1, 10)
# check it works also when passing in a quantity
q3 = u.Quantity(q1, u.m, ndmin=3)
assert q3.ndim == 3 and q3.shape == (1, 1, 10)
def test_non_quantity_with_unit(self):
"""Test that unit attributes in objects get recognized."""
class MyQuantityLookalike(np.ndarray):
pass
a = np.arange(3.)
mylookalike = a.copy().view(MyQuantityLookalike)
mylookalike.unit = 'm'
q1 = u.Quantity(mylookalike)
assert isinstance(q1, u.Quantity)
assert q1.unit is u.m
assert np.all(q1.value == a)
q2 = u.Quantity(mylookalike, u.mm)
assert q2.unit is u.mm
assert np.all(q2.value == 1000.*a)
q3 = u.Quantity(mylookalike, copy=False)
assert np.all(q3.value == mylookalike)
q3[2] = 0
assert q3[2] == 0.
assert mylookalike[2] == 0.
mylookalike = a.copy().view(MyQuantityLookalike)
mylookalike.unit = u.m
q4 = u.Quantity(mylookalike, u.mm, copy=False)
q4[2] = 0
assert q4[2] == 0.
assert mylookalike[2] == 2.
mylookalike.unit = 'nonsense'
with pytest.raises(TypeError):
u.Quantity(mylookalike)
def test_creation_via_view(self):
# This works but is no better than 1. * u.m
q1 = 1. << u.m
assert isinstance(q1, u.Quantity)
assert q1.unit == u.m
assert q1.value == 1.
# With an array, we get an actual view.
a2 = np.arange(10.)
q2 = a2 << u.m / u.s
assert isinstance(q2, u.Quantity)
assert q2.unit == u.m / u.s
assert np.all(q2.value == a2)
a2[9] = 0.
assert np.all(q2.value == a2)
# But with a unit change we get a copy.
q3 = q2 << u.mm / u.s
assert isinstance(q3, u.Quantity)
assert q3.unit == u.mm / u.s
assert np.all(q3.value == a2 * 1000.)
a2[8] = 0.
assert q3[8].value == 8000.
# Without a unit change, we do get a view.
q4 = q2 << q2.unit
a2[7] = 0.
assert np.all(q4.value == a2)
with pytest.raises(u.UnitsError):
q2 << u.s
# But one can do an in-place unit change.
a2_copy = a2.copy()
q2 <<= u.mm / u.s
assert q2.unit == u.mm / u.s
# Of course, this changes a2 as well.
assert np.all(q2.value == a2)
# Sanity check on the values.
assert np.all(q2.value == a2_copy * 1000.)
a2[8] = -1.
# Using quantities, one can also work with strings.
q5 = q2 << 'km/hr'
assert q5.unit == u.km / u.hr
assert np.all(q5 == q2)
# Finally, we can use scalar quantities as units.
not_quite_a_foot = 30. * u.cm
a6 = np.arange(5.)
q6 = a6 << not_quite_a_foot
assert q6.unit == u.Unit(not_quite_a_foot)
assert np.all(q6.to_value(u.cm) == 30. * a6)
def test_rshift_warns(self):
with pytest.raises(TypeError), \
catch_warnings() as warning_lines:
1 >> u.m
assert len(warning_lines) == 1
assert warning_lines[0].category == AstropyWarning
assert 'is not implemented' in str(warning_lines[0].message)
q = 1. * u.km
with pytest.raises(TypeError), \
catch_warnings() as warning_lines:
q >> u.m
assert len(warning_lines) == 1
assert warning_lines[0].category == AstropyWarning
assert 'is not implemented' in str(warning_lines[0].message)
with pytest.raises(TypeError), \
catch_warnings() as warning_lines:
q >>= u.m
assert len(warning_lines) == 1
assert warning_lines[0].category == AstropyWarning
assert 'is not implemented' in str(warning_lines[0].message)
with pytest.raises(TypeError), \
catch_warnings() as warning_lines:
1. >> q
assert len(warning_lines) == 1
assert warning_lines[0].category == AstropyWarning
assert 'is not implemented' in str(warning_lines[0].message)
class TestQuantityOperations:
q1 = u.Quantity(11.42, u.meter)
q2 = u.Quantity(8.0, u.centimeter)
def test_addition(self):
# Take units from left object, q1
new_quantity = self.q1 + self.q2
assert new_quantity.value == 11.5
assert new_quantity.unit == u.meter
# Take units from left object, q2
new_quantity = self.q2 + self.q1
assert new_quantity.value == 1150.0
assert new_quantity.unit == u.centimeter
new_q = u.Quantity(1500.1, u.m) + u.Quantity(13.5, u.km)
assert new_q.unit == u.m
assert new_q.value == 15000.1
def test_subtraction(self):
# Take units from left object, q1
new_quantity = self.q1 - self.q2
assert new_quantity.value == 11.34
assert new_quantity.unit == u.meter
# Take units from left object, q2
new_quantity = self.q2 - self.q1
assert new_quantity.value == -1134.0
assert new_quantity.unit == u.centimeter
def test_multiplication(self):
# Take units from left object, q1
new_quantity = self.q1 * self.q2
assert new_quantity.value == 91.36
assert new_quantity.unit == (u.meter * u.centimeter)
# Take units from left object, q2
new_quantity = self.q2 * self.q1
assert new_quantity.value == 91.36
assert new_quantity.unit == (u.centimeter * u.meter)
# Multiply with a number
new_quantity = 15. * self.q1
assert new_quantity.value == 171.3
assert new_quantity.unit == u.meter
# Multiply with a number
new_quantity = self.q1 * 15.
assert new_quantity.value == 171.3
assert new_quantity.unit == u.meter
def test_division(self):
# Take units from left object, q1
new_quantity = self.q1 / self.q2
assert_array_almost_equal(new_quantity.value, 1.4275, decimal=5)
assert new_quantity.unit == (u.meter / u.centimeter)
# Take units from left object, q2
new_quantity = self.q2 / self.q1
assert_array_almost_equal(new_quantity.value, 0.70052539404553416,
decimal=16)
assert new_quantity.unit == (u.centimeter / u.meter)
q1 = u.Quantity(11.4, unit=u.meter)
q2 = u.Quantity(10.0, unit=u.second)
new_quantity = q1 / q2
assert_array_almost_equal(new_quantity.value, 1.14, decimal=10)
assert new_quantity.unit == (u.meter / u.second)
# divide with a number
new_quantity = self.q1 / 10.
assert new_quantity.value == 1.142
assert new_quantity.unit == u.meter
# divide with a number
new_quantity = 11.42 / self.q1
assert new_quantity.value == 1.
assert new_quantity.unit == u.Unit("1/m")
def test_commutativity(self):
"""Regression test for issue #587."""
new_q = u.Quantity(11.42, 'm*s')
assert self.q1 * u.s == u.s * self.q1 == new_q
assert self.q1 / u.s == u.Quantity(11.42, 'm/s')
assert u.s / self.q1 == u.Quantity(1 / 11.42, 's/m')
def test_power(self):
# raise quantity to a power
new_quantity = self.q1 ** 2
assert_array_almost_equal(new_quantity.value, 130.4164, decimal=5)
assert new_quantity.unit == u.Unit("m^2")
new_quantity = self.q1 ** 3
assert_array_almost_equal(new_quantity.value, 1489.355288, decimal=7)
assert new_quantity.unit == u.Unit("m^3")
def test_matrix_multiplication(self):
a = np.eye(3)
q = a * u.m
result1 = q @ a
assert np.all(result1 == q)
result2 = a @ q
assert np.all(result2 == q)
result3 = q @ q
assert np.all(result3 == a * u.m ** 2)
# less trivial case.
q2 = np.array([[[1., 0., 0.],
[0., 1., 0.],
[0., 0., 1.]],
[[0., 1., 0.],
[0., 0., 1.],
[1., 0., 0.]],
[[0., 0., 1.],
[1., 0., 0.],
[0., 1., 0.]]]) / u.s
result4 = q @ q2
assert np.all(result4 == np.matmul(a, q2.value) * q.unit * q2.unit)
def test_unary(self):
# Test the minus unary operator
new_quantity = -self.q1
assert new_quantity.value == -self.q1.value
assert new_quantity.unit == self.q1.unit
new_quantity = -(-self.q1)
assert new_quantity.value == self.q1.value
assert new_quantity.unit == self.q1.unit
# Test the plus unary operator
new_quantity = +self.q1
assert new_quantity.value == self.q1.value
assert new_quantity.unit == self.q1.unit
def test_abs(self):
q = 1. * u.m / u.s
new_quantity = abs(q)
assert new_quantity.value == q.value
assert new_quantity.unit == q.unit
q = -1. * u.m / u.s
new_quantity = abs(q)
assert new_quantity.value == -q.value
assert new_quantity.unit == q.unit
def test_incompatible_units(self):
""" When trying to add or subtract units that aren't compatible, throw an error """
q1 = u.Quantity(11.412, unit=u.meter)
q2 = u.Quantity(21.52, unit=u.second)
with pytest.raises(u.UnitsError):
new_q = q1 + q2
def test_non_number_type(self):
q1 = u.Quantity(11.412, unit=u.meter)
type_err_msg = ("Unsupported operand type(s) for ufunc add: "
"'Quantity' and 'dict'")
with pytest.raises(TypeError) as exc:
q1 + {'a': 1}
assert exc.value.args[0] == type_err_msg
with pytest.raises(TypeError):
q1 + u.meter
def test_dimensionless_operations(self):
# test conversion to dimensionless
dq = 3. * u.m / u.km
dq1 = dq + 1. * u.mm / u.km
assert dq1.value == 3.001
assert dq1.unit == dq.unit
dq2 = dq + 1.
assert dq2.value == 1.003
assert dq2.unit == u.dimensionless_unscaled
# this test will check that operations with dimensionless Quantities
# don't work
with pytest.raises(u.UnitsError):
self.q1 + u.Quantity(0.1, unit=u.Unit(""))
with pytest.raises(u.UnitsError):
self.q1 - u.Quantity(0.1, unit=u.Unit(""))
# and test that scaling of integers works
q = u.Quantity(np.array([1, 2, 3]), u.m / u.km, dtype=int)
q2 = q + np.array([4, 5, 6])
assert q2.unit == u.dimensionless_unscaled
assert_allclose(q2.value, np.array([4.001, 5.002, 6.003]))
# but not if doing it inplace
with pytest.raises(TypeError):
q += np.array([1, 2, 3])
# except if it is actually possible
q = np.array([1, 2, 3]) * u.km / u.m
q += np.array([4, 5, 6])
assert q.unit == u.dimensionless_unscaled
assert np.all(q.value == np.array([1004, 2005, 3006]))
def test_complicated_operation(self):
""" Perform a more complicated test """
from astropy.units import imperial
# Multiple units
distance = u.Quantity(15., u.meter)
time = u.Quantity(11., u.second)
velocity = (distance / time).to(imperial.mile / u.hour)
assert_array_almost_equal(
velocity.value, 3.05037, decimal=5)
G = u.Quantity(6.673E-11, u.m ** 3 / u.kg / u.s ** 2)
new_q = ((1. / (4. * np.pi * G)).to(u.pc ** -3 / u.s ** -2 * u.kg))
# Area
side1 = u.Quantity(11., u.centimeter)
side2 = u.Quantity(7., u.centimeter)
area = side1 * side2
assert_array_almost_equal(area.value, 77., decimal=15)
assert area.unit == u.cm * u.cm
def test_comparison(self):
# equality/ non-equality is straightforward for quantity objects
assert (1 / (u.cm * u.cm)) == 1 * u.cm ** -2
assert 1 * u.m == 100 * u.cm
assert 1 * u.m != 1 * u.cm
# when one is a unit, Quantity does not know what to do,
# but unit is fine with it, so it still works
unit = u.cm**3
q = 1. * unit
assert q.__eq__(unit) is NotImplemented
assert unit.__eq__(q) is True
assert q == unit
q = 1000. * u.mm**3
assert q == unit
# mismatched types should never work
assert not 1. * u.cm == 1.
assert 1. * u.cm != 1.
# comparison with zero should raise a deprecation warning
for quantity in (1. * u.cm, 1. * u.dimensionless_unscaled):
with catch_warnings(AstropyDeprecationWarning) as warning_lines:
bool(quantity)
assert warning_lines[0].category == AstropyDeprecationWarning
assert (str(warning_lines[0].message) == 'The truth value of '
'a Quantity is ambiguous. In the future this will '
'raise a ValueError.')
def test_numeric_converters(self):
# float, int, long, and __index__ should only work for single
# quantities, of appropriate type, and only if they are dimensionless.
# for index, this should be unscaled as well
# (Check on __index__ is also a regression test for #1557)
# quantities with units should never convert, or be usable as an index
q1 = u.Quantity(1, u.m)
converter_err_msg = ("only dimensionless scalar quantities "
"can be converted to Python scalars")
index_err_msg = ("only integer dimensionless scalar quantities "
"can be converted to a Python index")
with pytest.raises(TypeError) as exc:
float(q1)
assert exc.value.args[0] == converter_err_msg
with pytest.raises(TypeError) as exc:
int(q1)
assert exc.value.args[0] == converter_err_msg
# We used to test `q1 * ['a', 'b', 'c'] here, but that that worked
# at all was a really odd confluence of bugs. Since it doesn't work
# in numpy >=1.10 any more, just go directly for `__index__` (which
# makes the test more similar to the `int`, `long`, etc., tests).
with pytest.raises(TypeError) as exc:
q1.__index__()
assert exc.value.args[0] == index_err_msg
# dimensionless but scaled is OK, however
q2 = u.Quantity(1.23, u.m / u.km)
assert float(q2) == float(q2.to_value(u.dimensionless_unscaled))
assert int(q2) == int(q2.to_value(u.dimensionless_unscaled))
with pytest.raises(TypeError) as exc:
q2.__index__()
assert exc.value.args[0] == index_err_msg
# dimensionless unscaled is OK, though for index needs to be int
q3 = u.Quantity(1.23, u.dimensionless_unscaled)
assert float(q3) == 1.23
assert int(q3) == 1
with pytest.raises(TypeError) as exc:
q3.__index__()
assert exc.value.args[0] == index_err_msg
# integer dimensionless unscaled is good for all
q4 = u.Quantity(2, u.dimensionless_unscaled, dtype=int)
assert float(q4) == 2.
assert int(q4) == 2
assert q4.__index__() == 2
# but arrays are not OK
q5 = u.Quantity([1, 2], u.m)
with pytest.raises(TypeError) as exc:
float(q5)
assert exc.value.args[0] == converter_err_msg
with pytest.raises(TypeError) as exc:
int(q5)
assert exc.value.args[0] == converter_err_msg
with pytest.raises(TypeError) as exc:
q5.__index__()
assert exc.value.args[0] == index_err_msg
# See https://github.com/numpy/numpy/issues/5074
# It seems unlikely this will be resolved, so xfail'ing it.
@pytest.mark.xfail(reason="list multiplication only works for numpy <=1.10")
def test_numeric_converter_to_index_in_practice(self):
"""Test that use of __index__ actually works."""
q4 = u.Quantity(2, u.dimensionless_unscaled, dtype=int)
assert q4 * ['a', 'b', 'c'] == ['a', 'b', 'c', 'a', 'b', 'c']
def test_array_converters(self):
# Scalar quantity
q = u.Quantity(1.23, u.m)
assert np.all(np.array(q) == np.array([1.23]))
# Array quantity
q = u.Quantity([1., 2., 3.], u.m)
assert np.all(np.array(q) == np.array([1., 2., 3.]))
def test_quantity_conversion():
q1 = u.Quantity(0.1, unit=u.meter)
value = q1.value
assert value == 0.1
value_in_km = q1.to_value(u.kilometer)
assert value_in_km == 0.0001
new_quantity = q1.to(u.kilometer)
assert new_quantity.value == 0.0001
with pytest.raises(u.UnitsError):
q1.to(u.zettastokes)
with pytest.raises(u.UnitsError):
q1.to_value(u.zettastokes)
def test_quantity_value_views():
q1 = u.Quantity([1., 2.], unit=u.meter)
# views if the unit is the same.
v1 = q1.value
v1[0] = 0.
assert np.all(q1 == [0., 2.] * u.meter)
v2 = q1.to_value()
v2[1] = 3.
assert np.all(q1 == [0., 3.] * u.meter)
v3 = q1.to_value('m')
v3[0] = 1.
assert np.all(q1 == [1., 3.] * u.meter)
v4 = q1.to_value('cm')
v4[0] = 0.
# copy if different unit.
assert np.all(q1 == [1., 3.] * u.meter)
def test_quantity_conversion_with_equiv():
q1 = u.Quantity(0.1, unit=u.meter)
v2 = q1.to_value(u.Hz, equivalencies=u.spectral())
assert_allclose(v2, 2997924580.0)
q2 = q1.to(u.Hz, equivalencies=u.spectral())
assert_allclose(q2.value, v2)
q1 = u.Quantity(0.4, unit=u.arcsecond)
v2 = q1.to_value(u.au, equivalencies=u.parallax())
q2 = q1.to(u.au, equivalencies=u.parallax())
v3 = q2.to_value(u.arcminute, equivalencies=u.parallax())
q3 = q2.to(u.arcminute, equivalencies=u.parallax())
assert_allclose(v2, 515662.015)
assert_allclose(q2.value, v2)
assert q2.unit == u.au
assert_allclose(v3, 0.0066666667)
assert_allclose(q3.value, v3)
assert q3.unit == u.arcminute
def test_quantity_conversion_equivalency_passed_on():
class MySpectral(u.Quantity):
_equivalencies = u.spectral()
def __quantity_view__(self, obj, unit):
return obj.view(MySpectral)
def __quantity_instance__(self, *args, **kwargs):
return MySpectral(*args, **kwargs)
q1 = MySpectral([1000, 2000], unit=u.Hz)
q2 = q1.to(u.nm)
assert q2.unit == u.nm
q3 = q2.to(u.Hz)
assert q3.unit == u.Hz
assert_allclose(q3.value, q1.value)
q4 = MySpectral([1000, 2000], unit=u.nm)
q5 = q4.to(u.Hz).to(u.nm)
assert q5.unit == u.nm
assert_allclose(q4.value, q5.value)
# Regression test for issue #2315, divide-by-zero error when examining 0*unit
def test_self_equivalency():
assert u.deg.is_equivalent(0*u.radian)
assert u.deg.is_equivalent(1*u.radian)
def test_si():
q1 = 10. * u.m * u.s ** 2 / (200. * u.ms) ** 2 # 250 meters
assert q1.si.value == 250
assert q1.si.unit == u.m
q = 10. * u.m # 10 meters
assert q.si.value == 10
assert q.si.unit == u.m
q = 10. / u.m # 10 1 / meters
assert q.si.value == 10
assert q.si.unit == (1 / u.m)
def test_cgs():
q1 = 10. * u.cm * u.s ** 2 / (200. * u.ms) ** 2 # 250 centimeters
assert q1.cgs.value == 250
assert q1.cgs.unit == u.cm
q = 10. * u.m # 10 centimeters
assert q.cgs.value == 1000
assert q.cgs.unit == u.cm
q = 10. / u.cm # 10 1 / centimeters
assert q.cgs.value == 10
assert q.cgs.unit == (1 / u.cm)
q = 10. * u.Pa # 10 pascals
assert q.cgs.value == 100
assert q.cgs.unit == u.barye
class TestQuantityComparison:
def test_quantity_equality(self):
assert u.Quantity(1000, unit='m') == u.Quantity(1, unit='km')
assert not (u.Quantity(1, unit='m') == u.Quantity(1, unit='km'))
# for ==, !=, return False, True if units do not match
assert (u.Quantity(1100, unit=u.m) != u.Quantity(1, unit=u.s)) is True
assert (u.Quantity(1100, unit=u.m) == u.Quantity(1, unit=u.s)) is False
def test_quantity_comparison(self):
assert u.Quantity(1100, unit=u.meter) > u.Quantity(1, unit=u.kilometer)
assert u.Quantity(900, unit=u.meter) < u.Quantity(1, unit=u.kilometer)
with pytest.raises(u.UnitsError):
assert u.Quantity(1100, unit=u.meter) > u.Quantity(1, unit=u.second)
with pytest.raises(u.UnitsError):
assert u.Quantity(1100, unit=u.meter) < u.Quantity(1, unit=u.second)
assert u.Quantity(1100, unit=u.meter) >= u.Quantity(1, unit=u.kilometer)
assert u.Quantity(1000, unit=u.meter) >= u.Quantity(1, unit=u.kilometer)
assert u.Quantity(900, unit=u.meter) <= u.Quantity(1, unit=u.kilometer)
assert u.Quantity(1000, unit=u.meter) <= u.Quantity(1, unit=u.kilometer)
with pytest.raises(u.UnitsError):
assert u.Quantity(
1100, unit=u.meter) >= u.Quantity(1, unit=u.second)
with pytest.raises(u.UnitsError):
assert u.Quantity(1100, unit=u.meter) <= u.Quantity(1, unit=u.second)
assert u.Quantity(1200, unit=u.meter) != u.Quantity(1, unit=u.kilometer)
class TestQuantityDisplay:
scalarintq = u.Quantity(1, unit='m', dtype=int)
scalarfloatq = u.Quantity(1.3, unit='m')
arrq = u.Quantity([1, 2.3, 8.9], unit='m')
scalar_complex_q = u.Quantity(complex(1.0, 2.0))
scalar_big_complex_q = u.Quantity(complex(1.0, 2.0e27) * 1e25)
scalar_big_neg_complex_q = u.Quantity(complex(-1.0, -2.0e27) * 1e36)
arr_complex_q = u.Quantity(np.arange(3) * (complex(-1.0, -2.0e27) * 1e36))
big_arr_complex_q = u.Quantity(np.arange(125) * (complex(-1.0, -2.0e27) * 1e36))
def test_dimensionless_quantity_repr(self):
q2 = u.Quantity(1., unit='m-1')
q3 = u.Quantity(1, unit='m-1', dtype=int)
if NUMPY_LT_1_14:
assert repr(self.scalarintq * q2) == "<Quantity 1.0>"
assert repr(self.arrq * q2) == "<Quantity [ 1. , 2.3, 8.9]>"
else:
assert repr(self.scalarintq * q2) == "<Quantity 1.>"
assert repr(self.arrq * q2) == "<Quantity [1. , 2.3, 8.9]>"
assert repr(self.scalarintq * q3) == "<Quantity 1>"
def test_dimensionless_quantity_str(self):
q2 = u.Quantity(1., unit='m-1')
q3 = u.Quantity(1, unit='m-1', dtype=int)
assert str(self.scalarintq * q2) == "1.0"
assert str(self.scalarintq * q3) == "1"
if NUMPY_LT_1_14:
assert str(self.arrq * q2) == "[ 1. 2.3 8.9]"
else:
assert str(self.arrq * q2) == "[1. 2.3 8.9]"
def test_dimensionless_quantity_format(self):
q1 = u.Quantity(3.14)
assert format(q1, '.2f') == '3.14'
def test_scalar_quantity_str(self):
assert str(self.scalarintq) == "1 m"
assert str(self.scalarfloatq) == "1.3 m"
def test_scalar_quantity_repr(self):
assert repr(self.scalarintq) == "<Quantity 1 m>"
assert repr(self.scalarfloatq) == "<Quantity 1.3 m>"
def test_array_quantity_str(self):
if NUMPY_LT_1_14:
assert str(self.arrq) == "[ 1. 2.3 8.9] m"
else:
assert str(self.arrq) == "[1. 2.3 8.9] m"
def test_array_quantity_repr(self):
if NUMPY_LT_1_14:
assert repr(self.arrq) == "<Quantity [ 1. , 2.3, 8.9] m>"
else:
assert repr(self.arrq) == "<Quantity [1. , 2.3, 8.9] m>"
def test_scalar_quantity_format(self):
assert format(self.scalarintq, '02d') == "01 m"
assert format(self.scalarfloatq, '.1f') == "1.3 m"
assert format(self.scalarfloatq, '.0f') == "1 m"
def test_uninitialized_unit_format(self):
bad_quantity = np.arange(10.).view(u.Quantity)
assert str(bad_quantity).endswith(_UNIT_NOT_INITIALISED)
assert repr(bad_quantity).endswith(_UNIT_NOT_INITIALISED + '>')
def test_to_string(self):
qscalar = u.Quantity(1.5e14, 'm/s')
# __str__ is the default `format`
assert str(qscalar) == qscalar.to_string()
res = 'Quantity as KMS: 150000000000.0 km / s'
assert "Quantity as KMS: {0}".format(qscalar.to_string(unit=u.km / u.s)) == res
res = r'$1.5 \times 10^{14} \; \mathrm{\frac{m}{s}}$'
assert qscalar.to_string(format="latex") == res
res = r'$1.5 \times 10^{14} \; \mathrm{\frac{m}{s}}$'
assert qscalar.to_string(format="latex", subfmt="inline") == res
res = r'$\displaystyle 1.5 \times 10^{14} \; \mathrm{\frac{m}{s}}$'
assert qscalar.to_string(format="latex", subfmt="display") == res
def test_repr_latex(self):
from astropy.units.quantity import conf
q2scalar = u.Quantity(1.5e14, 'm/s')
assert self.scalarintq._repr_latex_() == r'$1 \; \mathrm{m}$'
assert self.scalarfloatq._repr_latex_() == r'$1.3 \; \mathrm{m}$'
assert (q2scalar._repr_latex_() ==
r'$1.5 \times 10^{14} \; \mathrm{\frac{m}{s}}$')
assert self.arrq._repr_latex_() == r'$[1,~2.3,~8.9] \; \mathrm{m}$'
# Complex quantities
assert self.scalar_complex_q._repr_latex_() == r'$(1+2i) \; \mathrm{}$'
assert (self.scalar_big_complex_q._repr_latex_() ==
r'$(1 \times 10^{25}+2 \times 10^{52}i) \; \mathrm{}$')
assert (self.scalar_big_neg_complex_q._repr_latex_() ==
r'$(-1 \times 10^{36}-2 \times 10^{63}i) \; \mathrm{}$')
assert (self.arr_complex_q._repr_latex_() ==
(r'$[(0-0i),~(-1 \times 10^{36}-2 \times 10^{63}i),'
r'~(-2 \times 10^{36}-4 \times 10^{63}i)] \; \mathrm{}$'))
assert r'\dots' in self.big_arr_complex_q._repr_latex_()
qmed = np.arange(100)*u.m
qbig = np.arange(1000)*u.m
qvbig = np.arange(10000)*1e9*u.m
pops = np.get_printoptions()
oldlat = conf.latex_array_threshold
try:
# check precision behavior
q = u.Quantity(987654321.123456789, 'm/s')
qa = np.array([7.89123, 123456789.987654321, 0]) * u.cm
np.set_printoptions(precision=8)
assert q._repr_latex_() == r'$9.8765432 \times 10^{8} \; \mathrm{\frac{m}{s}}$'
assert qa._repr_latex_() == r'$[7.89123,~1.2345679 \times 10^{8},~0] \; \mathrm{cm}$'
np.set_printoptions(precision=2)
assert q._repr_latex_() == r'$9.9 \times 10^{8} \; \mathrm{\frac{m}{s}}$'
assert qa._repr_latex_() == r'$[7.9,~1.2 \times 10^{8},~0] \; \mathrm{cm}$'
# check thresholding behavior
conf.latex_array_threshold = 100 # should be default
lsmed = qmed._repr_latex_()
assert r'\dots' not in lsmed
lsbig = qbig._repr_latex_()
assert r'\dots' in lsbig
lsvbig = qvbig._repr_latex_()
assert r'\dots' in lsvbig
conf.latex_array_threshold = 1001
lsmed = qmed._repr_latex_()
assert r'\dots' not in lsmed
lsbig = qbig._repr_latex_()
assert r'\dots' not in lsbig
lsvbig = qvbig._repr_latex_()
assert r'\dots' in lsvbig
conf.latex_array_threshold = -1 # means use the numpy threshold
np.set_printoptions(threshold=99)
lsmed = qmed._repr_latex_()
assert r'\dots' in lsmed
lsbig = qbig._repr_latex_()
assert r'\dots' in lsbig
lsvbig = qvbig._repr_latex_()
assert r'\dots' in lsvbig
finally:
# prevent side-effects from influencing other tests
np.set_printoptions(**pops)
conf.latex_array_threshold = oldlat
qinfnan = [np.inf, -np.inf, np.nan] * u.m
assert qinfnan._repr_latex_() == r'$[\infty,~-\infty,~{\rm NaN}] \; \mathrm{m}$'
def test_decompose():
q1 = 5 * u.N
assert q1.decompose() == (5 * u.kg * u.m * u.s ** -2)
def test_decompose_regression():
"""
Regression test for bug #1163
If decompose was called multiple times on a Quantity with an array and a
scale != 1, the result changed every time. This is because the value was
being referenced not copied, then modified, which changed the original
value.
"""
q = np.array([1, 2, 3]) * u.m / (2. * u.km)
assert np.all(q.decompose().value == np.array([0.0005, 0.001, 0.0015]))
assert np.all(q == np.array([1, 2, 3]) * u.m / (2. * u.km))
assert np.all(q.decompose().value == np.array([0.0005, 0.001, 0.0015]))
def test_arrays():
"""
Test using quantites with array values
"""
qsec = u.Quantity(np.arange(10), u.second)
assert isinstance(qsec.value, np.ndarray)
assert not qsec.isscalar
# len and indexing should work for arrays
assert len(qsec) == len(qsec.value)
qsecsub25 = qsec[2:5]
assert qsecsub25.unit == qsec.unit
assert isinstance(qsecsub25, u.Quantity)
assert len(qsecsub25) == 3
# make sure isscalar, len, and indexing behave correcly for non-arrays.
qsecnotarray = u.Quantity(10., u.second)
assert qsecnotarray.isscalar
with pytest.raises(TypeError):
len(qsecnotarray)
with pytest.raises(TypeError):
qsecnotarray[0]
qseclen0array = u.Quantity(np.array(10), u.second, dtype=int)
# 0d numpy array should act basically like a scalar
assert qseclen0array.isscalar
with pytest.raises(TypeError):
len(qseclen0array)
with pytest.raises(TypeError):
qseclen0array[0]
assert isinstance(qseclen0array.value, int)
a = np.array([(1., 2., 3.), (4., 5., 6.), (7., 8., 9.)],
dtype=[('x', float),
('y', float),
('z', float)])
qkpc = u.Quantity(a, u.kpc)
assert not qkpc.isscalar
qkpc0 = qkpc[0]
assert qkpc0.value == a[0]
assert qkpc0.unit == qkpc.unit
assert isinstance(qkpc0, u.Quantity)
assert qkpc0.isscalar
qkpcx = qkpc['x']
assert np.all(qkpcx.value == a['x'])
assert qkpcx.unit == qkpc.unit
assert isinstance(qkpcx, u.Quantity)
assert not qkpcx.isscalar
qkpcx1 = qkpc['x'][1]
assert qkpcx1.unit == qkpc.unit
assert isinstance(qkpcx1, u.Quantity)
assert qkpcx1.isscalar
qkpc1x = qkpc[1]['x']
assert qkpc1x.isscalar
assert qkpc1x == qkpcx1
# can also create from lists, will auto-convert to arrays
qsec = u.Quantity(list(range(10)), u.second)
assert isinstance(qsec.value, np.ndarray)
# quantity math should work with arrays
assert_array_equal((qsec * 2).value, (np.arange(10) * 2))
assert_array_equal((qsec / 2).value, (np.arange(10) / 2))
# quantity addition/subtraction should *not* work with arrays b/c unit
# ambiguous
with pytest.raises(u.UnitsError):
assert_array_equal((qsec + 2).value, (np.arange(10) + 2))
with pytest.raises(u.UnitsError):
assert_array_equal((qsec - 2).value, (np.arange(10) + 2))
# should create by unit multiplication, too
qsec2 = np.arange(10) * u.second
qsec3 = u.second * np.arange(10)
assert np.all(qsec == qsec2)
assert np.all(qsec2 == qsec3)
# make sure numerical-converters fail when arrays are present
with pytest.raises(TypeError):
float(qsec)
with pytest.raises(TypeError):
int(qsec)
def test_array_indexing_slicing():
q = np.array([1., 2., 3.]) * u.m
assert q[0] == 1. * u.m
assert np.all(q[0:2] == u.Quantity([1., 2.], u.m))
def test_array_setslice():
q = np.array([1., 2., 3.]) * u.m
q[1:2] = np.array([400.]) * u.cm
assert np.all(q == np.array([1., 4., 3.]) * u.m)
def test_inverse_quantity():
"""
Regression test from issue #679
"""
q = u.Quantity(4., u.meter / u.second)
qot = q / 2
toq = 2 / q
npqot = q / np.array(2)
assert npqot.value == 2.0
assert npqot.unit == (u.meter / u.second)
assert qot.value == 2.0
assert qot.unit == (u.meter / u.second)
assert toq.value == 0.5
assert toq.unit == (u.second / u.meter)
def test_quantity_mutability():
q = u.Quantity(9.8, u.meter / u.second / u.second)
with pytest.raises(AttributeError):
q.value = 3
with pytest.raises(AttributeError):
q.unit = u.kg
def test_quantity_initialized_with_quantity():
q1 = u.Quantity(60, u.second)
q2 = u.Quantity(q1, u.minute)
assert q2.value == 1
q3 = u.Quantity([q1, q2], u.second)
assert q3[0].value == 60
assert q3[1].value == 60
q4 = u.Quantity([q2, q1])
assert q4.unit == q2.unit
assert q4[0].value == 1
assert q4[1].value == 1
def test_quantity_string_unit():
q1 = 1. * u.m / 's'
assert q1.value == 1
assert q1.unit == (u.m / u.s)
q2 = q1 * "m"
assert q2.unit == ((u.m * u.m) / u.s)
@raises(ValueError)
def test_quantity_invalid_unit_string():
"foo" * u.m
def test_implicit_conversion():
q = u.Quantity(1.0, u.meter)
# Manually turn this on to simulate what might happen in a subclass
q._include_easy_conversion_members = True
assert_allclose(q.centimeter, 100)
assert_allclose(q.cm, 100)
assert_allclose(q.parsec, 3.240779289469756e-17)
def test_implicit_conversion_autocomplete():
q = u.Quantity(1.0, u.meter)
# Manually turn this on to simulate what might happen in a subclass
q._include_easy_conversion_members = True
q.foo = 42
attrs = dir(q)
assert 'centimeter' in attrs
assert 'cm' in attrs
assert 'parsec' in attrs
assert 'foo' in attrs
assert 'to' in attrs
assert 'value' in attrs
# Something from the base class, object
assert '__setattr__' in attrs
with pytest.raises(AttributeError):
q.l
def test_quantity_iterability():
"""Regressiont est for issue #878.
Scalar quantities should not be iterable and should raise a type error on
iteration.
"""
q1 = [15.0, 17.0] * u.m
assert isiterable(q1)
q2 = next(iter(q1))
assert q2 == 15.0 * u.m
assert not isiterable(q2)
pytest.raises(TypeError, iter, q2)
def test_copy():
q1 = u.Quantity(np.array([[1., 2., 3.], [4., 5., 6.]]), unit=u.m)
q2 = q1.copy()
assert np.all(q1.value == q2.value)
assert q1.unit == q2.unit
assert q1.dtype == q2.dtype
assert q1.value is not q2.value
q3 = q1.copy(order='F')
assert q3.flags['F_CONTIGUOUS']
assert np.all(q1.value == q3.value)
assert q1.unit == q3.unit
assert q1.dtype == q3.dtype
assert q1.value is not q3.value
q4 = q1.copy(order='C')
assert q4.flags['C_CONTIGUOUS']
assert np.all(q1.value == q4.value)
assert q1.unit == q4.unit
assert q1.dtype == q4.dtype
assert q1.value is not q4.value
def test_deepcopy():
q1 = u.Quantity(np.array([1., 2., 3.]), unit=u.m)
q2 = copy.deepcopy(q1)
assert isinstance(q2, u.Quantity)
assert np.all(q1.value == q2.value)
assert q1.unit == q2.unit
assert q1.dtype == q2.dtype
assert q1.value is not q2.value
def test_equality_numpy_scalar():
"""
A regression test to ensure that numpy scalars are correctly compared
(which originally failed due to the lack of ``__array_priority__``).
"""
assert 10 != 10. * u.m
assert np.int64(10) != 10 * u.m
assert 10 * u.m != np.int64(10)
def test_quantity_pickelability():
"""
Testing pickleability of quantity
"""
q1 = np.arange(10) * u.m
q2 = pickle.loads(pickle.dumps(q1))
assert np.all(q1.value == q2.value)
assert q1.unit.is_equivalent(q2.unit)
assert q1.unit == q2.unit
def test_quantity_initialisation_from_string():
q = u.Quantity('1')
assert q.unit == u.dimensionless_unscaled
assert q.value == 1.
q = u.Quantity('1.5 m/s')
assert q.unit == u.m/u.s
assert q.value == 1.5
assert u.Unit(q) == u.Unit('1.5 m/s')
q = u.Quantity('.5 m')
assert q == u.Quantity(0.5, u.m)
q = u.Quantity('-1e1km')
assert q == u.Quantity(-10, u.km)
q = u.Quantity('-1e+1km')
assert q == u.Quantity(-10, u.km)
q = u.Quantity('+.5km')
assert q == u.Quantity(.5, u.km)
q = u.Quantity('+5e-1km')
assert q == u.Quantity(.5, u.km)
q = u.Quantity('5', u.m)
assert q == u.Quantity(5., u.m)
q = u.Quantity('5 km', u.m)
assert q.value == 5000.
assert q.unit == u.m
q = u.Quantity('5Em')
assert q == u.Quantity(5., u.Em)
with pytest.raises(TypeError):
u.Quantity('')
with pytest.raises(TypeError):
u.Quantity('m')
with pytest.raises(TypeError):
u.Quantity('1.2.3 deg')
with pytest.raises(TypeError):
u.Quantity('1+deg')
with pytest.raises(TypeError):
u.Quantity('1-2deg')
with pytest.raises(TypeError):
u.Quantity('1.2e-13.3m')
with pytest.raises(TypeError):
u.Quantity(['5'])
with pytest.raises(TypeError):
u.Quantity(np.array(['5']))
with pytest.raises(ValueError):
u.Quantity('5E')
with pytest.raises(ValueError):
u.Quantity('5 foo')
def test_unsupported():
q1 = np.arange(10) * u.m
with pytest.raises(TypeError):
q2 = np.bitwise_and(q1, q1)
def test_unit_identity():
q = 1.0 * u.hour
assert q.unit is u.hour
def test_quantity_to_view():
q1 = np.array([1000, 2000]) * u.m
q2 = q1.to(u.km)
assert q1.value[0] == 1000
assert q2.value[0] == 1
@raises(ValueError)
def test_quantity_tuple_power():
(5.0 * u.m) ** (1, 2)
def test_quantity_fraction_power():
q = (25.0 * u.m**2) ** Fraction(1, 2)
assert q.value == 5.
assert q.unit == u.m
# Regression check to ensure we didn't create an object type by raising
# the value of the quantity to a Fraction. [#3922]
assert q.dtype.kind == 'f'
def test_inherit_docstrings():
assert u.Quantity.argmax.__doc__ == np.ndarray.argmax.__doc__
def test_quantity_from_table():
"""
Checks that units from tables are respected when converted to a Quantity.
This also generically checks the use of *anything* with a `unit` attribute
passed into Quantity
"""
from... table import Table
t = Table(data=[np.arange(5), np.arange(5)], names=['a', 'b'])
t['a'].unit = u.kpc
qa = u.Quantity(t['a'])
assert qa.unit == u.kpc
assert_array_equal(qa.value, t['a'])
qb = u.Quantity(t['b'])
assert qb.unit == u.dimensionless_unscaled
assert_array_equal(qb.value, t['b'])
# This does *not* auto-convert, because it's not necessarily obvious that's
# desired. Instead we revert to standard `Quantity` behavior
qap = u.Quantity(t['a'], u.pc)
assert qap.unit == u.pc
assert_array_equal(qap.value, t['a'] * 1000)
qbp = u.Quantity(t['b'], u.pc)
assert qbp.unit == u.pc
assert_array_equal(qbp.value, t['b'])
def test_assign_slice_with_quantity_like():
# Regression tests for gh-5961
from astropy.table import Table, Column
# first check directly that we can use a Column to assign to a slice.
c = Column(np.arange(10.), unit=u.mm)
q = u.Quantity(c)
q[:2] = c[:2]
# next check that we do not fail the original problem.
t = Table()
t['x'] = np.arange(10) * u.mm
t['y'] = np.ones(10) * u.mm
assert type(t['x']) is Column
xy = np.vstack([t['x'], t['y']]).T * u.mm
ii = [0, 2, 4]
assert xy[ii, 0].unit == t['x'][ii].unit
# should not raise anything
xy[ii, 0] = t['x'][ii]
def test_insert():
"""
Test Quantity.insert method. This does not test the full capabilities
of the underlying np.insert, but hits the key functionality for
Quantity.
"""
q = [1, 2] * u.m
# Insert a compatible float with different units
q2 = q.insert(0, 1 * u.km)
assert np.all(q2.value == [1000, 1, 2])
assert q2.unit is u.m
assert q2.dtype.kind == 'f'
if minversion(np, '1.8.0'):
q2 = q.insert(1, [1, 2] * u.km)
assert np.all(q2.value == [1, 1000, 2000, 2])
assert q2.unit is u.m
# Cannot convert 1.5 * u.s to m
with pytest.raises(u.UnitsError):
q.insert(1, 1.5 * u.s)
# Tests with multi-dim quantity
q = [[1, 2], [3, 4]] * u.m
q2 = q.insert(1, [10, 20] * u.m, axis=0)
assert np.all(q2.value == [[1, 2],
[10, 20],
[3, 4]])
q2 = q.insert(1, [10, 20] * u.m, axis=1)
assert np.all(q2.value == [[1, 10, 2],
[3, 20, 4]])
q2 = q.insert(1, 10 * u.m, axis=1)
assert np.all(q2.value == [[1, 10, 2],
[3, 10, 4]])
def test_repr_array_of_quantity():
"""
Test print/repr of object arrays of Quantity objects with different
units.
Regression test for the issue first reported in
https://github.com/astropy/astropy/issues/3777
"""
a = np.array([1 * u.m, 2 * u.s], dtype=object)
if NUMPY_LT_1_14:
assert repr(a) == 'array([<Quantity 1.0 m>, <Quantity 2.0 s>], dtype=object)'
assert str(a) == '[<Quantity 1.0 m> <Quantity 2.0 s>]'
else:
assert repr(a) == 'array([<Quantity 1. m>, <Quantity 2. s>], dtype=object)'
assert str(a) == '[<Quantity 1. m> <Quantity 2. s>]'
class TestSpecificTypeQuantity:
def setup(self):
class Length(u.SpecificTypeQuantity):
_equivalent_unit = u.m
class Length2(Length):
_default_unit = u.m
class Length3(Length):
_unit = u.m
self.Length = Length
self.Length2 = Length2
self.Length3 = Length3
def test_creation(self):
l = self.Length(np.arange(10.)*u.km)
assert type(l) is self.Length
with pytest.raises(u.UnitTypeError):
self.Length(np.arange(10.) * u.hour)
with pytest.raises(u.UnitTypeError):
self.Length(np.arange(10.))
l2 = self.Length2(np.arange(5.))
assert type(l2) is self.Length2
assert l2._default_unit is self.Length2._default_unit
with pytest.raises(u.UnitTypeError):
self.Length3(np.arange(10.))
def test_view(self):
l = (np.arange(5.) * u.km).view(self.Length)
assert type(l) is self.Length
with pytest.raises(u.UnitTypeError):
(np.arange(5.) * u.s).view(self.Length)
v = np.arange(5.).view(self.Length)
assert type(v) is self.Length
assert v._unit is None
l3 = np.ones((2, 2)).view(self.Length3)
assert type(l3) is self.Length3
assert l3.unit is self.Length3._unit
def test_operation_precedence_and_fallback(self):
l = self.Length(np.arange(5.)*u.cm)
sum1 = l + 1.*u.m
assert type(sum1) is self.Length
sum2 = 1.*u.km + l
assert type(sum2) is self.Length
sum3 = l + l
assert type(sum3) is self.Length
res1 = l * (1.*u.m)
assert type(res1) is u.Quantity
res2 = l * l
assert type(res2) is u.Quantity
@pytest.mark.skipif('not HAS_MATPLOTLIB')
@pytest.mark.xfail('MATPLOTLIB_LT_15')
class TestQuantityMatplotlib:
"""Test if passing matplotlib quantities works.
TODO: create PNG output and check against reference image
once `astropy.wcsaxes` is merged, which provides
the machinery for this.
See https://github.com/astropy/astropy/issues/1881
See https://github.com/astropy/astropy/pull/2139
"""
def test_plot(self):
data = u.Quantity([4, 5, 6], 's')
plt.plot(data)
def test_scatter(self):
x = u.Quantity([4, 5, 6], 'second')
y = [1, 3, 4] * u.m
plt.scatter(x, y)
def test_unit_class_override():
class MyQuantity(u.Quantity):
pass
my_unit = u.Unit("my_deg", u.deg)
my_unit._quantity_class = MyQuantity
q1 = u.Quantity(1., my_unit)
assert type(q1) is u.Quantity
q2 = u.Quantity(1., my_unit, subok=True)
assert type(q2) is MyQuantity
class QuantityMimic:
def __init__(self, value, unit):
self.value = value
self.unit = unit
def __array__(self):
return np.array(self.value)
class QuantityMimic2(QuantityMimic):
def to(self, unit):
return u.Quantity(self.value, self.unit).to(unit)
def to_value(self, unit):
return u.Quantity(self.value, self.unit).to_value(unit)
class TestQuantityMimics:
"""Test Quantity Mimics that are not ndarray subclasses."""
@pytest.mark.parametrize('Mimic', (QuantityMimic, QuantityMimic2))
def test_mimic_input(self, Mimic):
value = np.arange(10.)
mimic = Mimic(value, u.m)
q = u.Quantity(mimic)
assert q.unit == u.m
assert np.all(q.value == value)
q2 = u.Quantity(mimic, u.cm)
assert q2.unit == u.cm
assert np.all(q2.value == 100 * value)
@pytest.mark.parametrize('Mimic', (QuantityMimic, QuantityMimic2))
def test_mimic_setting(self, Mimic):
mimic = Mimic([1., 2.], u.m)
q = u.Quantity(np.arange(10.), u.cm)
q[8:] = mimic
assert np.all(q[:8].value == np.arange(8.))
assert np.all(q[8:].value == [100., 200.])
|
8e96dbe9a96c356f52de21fcc21905ff4da561c7b516caaa1d4c126d9447d74f | import numpy as np
import pytest
from astropy import units as u
class TestQuantityLinAlgFuncs:
"""
Test linear algebra functions
"""
@pytest.mark.xfail
def test_outer(self):
q1 = np.array([1, 2, 3]) * u.m
q2 = np.array([1, 2]) / u.s
o = np.outer(q1, q2)
assert np.all(o == np.array([[1, 2], [2, 4], [3, 6]]) * u.m / u.s)
@pytest.mark.xfail
def test_inner(self):
q1 = np.array([1, 2, 3]) * u.m
q2 = np.array([4, 5, 6]) / u.s
o = np.inner(q1, q2)
assert o == 32 * u.m / u.s
@pytest.mark.xfail
def test_dot(self):
q1 = np.array([1., 2., 3.]) * u.m
q2 = np.array([4., 5., 6.]) / u.s
o = np.dot(q1, q2)
assert o == 32. * u.m / u.s
@pytest.mark.xfail
def test_matmul(self):
q1 = np.eye(3) * u.m
q2 = np.array([4., 5., 6.]) / u.s
o = np.matmul(q1, q2)
assert o == q2 / u.s
|
a7cf0fe785ab23d2f0fe95709e652b7e5612830f583a7e9c1c626ed9304ee11b | # Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Regression tests for the physical_type support in the units package
"""
from astropy import units as u
from astropy.units import physical
from astropy.constants import hbar
from astropy.tests.helper import raises
def test_simple():
assert u.m.physical_type == 'length'
def test_power():
assert (u.cm ** 3).physical_type == 'volume'
def test_speed():
assert (u.km / u.h).physical_type == 'speed'
def test_unknown():
assert (u.m * u.s).physical_type == 'unknown'
def test_dimensionless():
assert (u.m / u.m).physical_type == 'dimensionless'
def test_angular_momentum():
assert hbar.unit.physical_type == 'angular momentum'
def test_flam():
flam = u.erg / (u.cm**2 * u.s * u.AA)
assert flam.physical_type == 'spectral flux density wav'
def test_photlam():
photlam = u.photon / (u.cm ** 2 * u.s * u.AA)
assert photlam.physical_type == 'photon flux density wav'
def test_photnu():
photnu = u.photon / (u.cm ** 2 * u.s * u.Hz)
assert photnu.physical_type == 'photon flux density'
@raises(ValueError)
def test_redundant_physical_type():
physical.def_physical_type(u.m, 'utter craziness')
def test_data_quantity():
assert u.byte.physical_type == 'data quantity'
assert u.bit.physical_type == 'data quantity'
|
9a4a8030c753f4f5dffe99fb6f180ccc03a8d4b036be41931f4aaba5cd2eede6 | # The purpose of these tests are to ensure that calling ufuncs with quantities
# returns quantities with the right units, or raises exceptions.
import warnings
from collections import namedtuple
import pytest
import numpy as np
from numpy.testing import assert_allclose
from astropy import units as u
from astropy.units import quantity_helper as qh
from astropy._erfa import ufunc as erfa_ufunc
from astropy.tests.helper import raises
try:
import scipy # pylint: disable=W0611
except ImportError:
HAS_SCIPY = False
else:
HAS_SCIPY = True
testcase = namedtuple('testcase', ['f', 'q_in', 'q_out'])
testexc = namedtuple('testexc', ['f', 'q_in', 'exc', 'msg'])
testwarn = namedtuple('testwarn', ['f', 'q_in', 'wfilter'])
@pytest.mark.skip
def test_testcase(tc):
results = tc.f(*tc.q_in)
# careful of the following line, would break on a function returning
# a single tuple (as opposed to tuple of return values)
results = (results, ) if type(results) != tuple else results
for result, expected in zip(results, tc.q_out):
assert result.unit == expected.unit
assert_allclose(result.value, expected.value, atol=1.E-15)
@pytest.mark.skip
def test_testexc(te):
with pytest.raises(te.exc) as exc:
te.f(*te.q_in)
if te.msg is not None:
assert te.msg in exc.value.args[0]
@pytest.mark.skip
def test_testwarn(tw):
with warnings.catch_warnings():
warnings.filterwarnings(tw.wfilter)
tw.f(*tw.q_in)
class TestUfuncHelpers:
# Note that this test should work even if scipy is present, since
# the scipy.special ufuncs are only loaded on demand.
# The test passes independently of whether erfa is already loaded
# (which will be the case for a full test, since coordinates uses it).
def test_coverage(self):
"""Test that we cover all ufunc's"""
all_np_ufuncs = set([ufunc for ufunc in np.core.umath.__dict__.values()
if isinstance(ufunc, np.ufunc)])
all_q_ufuncs = (qh.UNSUPPORTED_UFUNCS |
set(qh.UFUNC_HELPERS.keys()))
# Check that every numpy ufunc is covered.
assert all_np_ufuncs - all_q_ufuncs == set()
# Check that all ufuncs we cover come from numpy or erfa.
# (Since coverage for erfa is incomplete, we do not check
# this the other way).
all_erfa_ufuncs = set([ufunc for ufunc in erfa_ufunc.__dict__.values()
if isinstance(ufunc, np.ufunc)])
assert (all_q_ufuncs - all_np_ufuncs - all_erfa_ufuncs == set())
def test_scipy_registered(self):
# Should be registered as existing even if scipy is not available.
assert 'scipy.special' in qh.UFUNC_HELPERS.modules
def test_removal_addition(self):
assert np.add in qh.UFUNC_HELPERS
assert np.add not in qh.UNSUPPORTED_UFUNCS
qh.UFUNC_HELPERS[np.add] = None
assert np.add not in qh.UFUNC_HELPERS
assert np.add in qh.UNSUPPORTED_UFUNCS
qh.UFUNC_HELPERS[np.add] = qh.UFUNC_HELPERS[np.subtract]
assert np.add in qh.UFUNC_HELPERS
assert np.add not in qh.UNSUPPORTED_UFUNCS
class TestQuantityTrigonometricFuncs:
"""
Test trigonometric functions
"""
@pytest.mark.parametrize('tc', (
testcase(
f=np.sin,
q_in=(30. * u.degree, ),
q_out=(0.5*u.dimensionless_unscaled, )
),
testcase(
f=np.sin,
q_in=(np.array([0., np.pi / 4., np.pi / 2.]) * u.radian, ),
q_out=(np.array([0., 1. / np.sqrt(2.), 1.]) * u.one, )
),
testcase(
f=np.arcsin,
q_in=(np.sin(30. * u.degree), ),
q_out=(np.radians(30.) * u.radian, )
),
testcase(
f=np.arcsin,
q_in=(np.sin(np.array([0., np.pi / 4., np.pi / 2.]) * u.radian), ),
q_out=(np.array([0., np.pi / 4., np.pi / 2.]) * u.radian, )
),
testcase(
f=np.cos,
q_in=(np.pi / 3. * u.radian, ),
q_out=(0.5 * u.dimensionless_unscaled, )
),
testcase(
f=np.cos,
q_in=(np.array([0., np.pi / 4., np.pi / 2.]) * u.radian, ),
q_out=(np.array([1., 1. / np.sqrt(2.), 0.]) * u.one, )
),
testcase(
f=np.arccos,
q_in=(np.cos(np.pi / 3. * u.radian), ),
q_out=(np.pi / 3. * u.radian, )
),
testcase(
f=np.arccos,
q_in=(np.cos(np.array([0., np.pi / 4., np.pi / 2.]) * u.radian), ),
q_out=(np.array([0., np.pi / 4., np.pi / 2.]) * u.radian, ),
),
testcase(
f=np.tan,
q_in=(np.pi / 3. * u.radian, ),
q_out=(np.sqrt(3.) * u.dimensionless_unscaled, )
),
testcase(
f=np.tan,
q_in=(np.array([0., 45., 135., 180.]) * u.degree, ),
q_out=(np.array([0., 1., -1., 0.]) * u.dimensionless_unscaled, )
),
testcase(
f=np.arctan,
q_in=(np.tan(np.pi / 3. * u.radian), ),
q_out=(np.pi / 3. * u.radian, )
),
testcase(
f=np.arctan,
q_in=(np.tan(np.array([10., 30., 70., 80.]) * u.degree), ),
q_out=(np.radians(np.array([10., 30., 70., 80.]) * u.degree), )
),
testcase(
f=np.arctan2,
q_in=(np.array([10., 30., 70., 80.]) * u.m, 2.0 * u.km),
q_out=(np.arctan2(np.array([10., 30., 70., 80.]),
2000.) * u.radian, )
),
testcase(
f=np.arctan2,
q_in=((np.array([10., 80.]) * u.m / (2.0 * u.km)).to(u.one), 1.),
q_out=(np.arctan2(np.array([10., 80.]) / 2000., 1.) * u.radian, )
),
testcase(
f=np.deg2rad,
q_in=(180. * u.degree, ),
q_out=(np.pi * u.radian, )
),
testcase(
f=np.radians,
q_in=(180. * u.degree, ),
q_out=(np.pi * u.radian, )
),
testcase(
f=np.deg2rad,
q_in=(3. * u.radian, ),
q_out=(3. * u.radian, )
),
testcase(
f=np.radians,
q_in=(3. * u.radian, ),
q_out=(3. * u.radian, )
),
testcase(
f=np.rad2deg,
q_in=(60. * u.degree, ),
q_out=(60. * u.degree, )
),
testcase(
f=np.degrees,
q_in=(60. * u.degree, ),
q_out=(60. * u.degree, )
),
testcase(
f=np.rad2deg,
q_in=(np.pi * u.radian, ),
q_out=(180. * u.degree, )
),
testcase(
f=np.degrees,
q_in=(np.pi * u.radian, ),
q_out=(180. * u.degree, )
)
))
def test_testcases(self, tc):
return test_testcase(tc)
@pytest.mark.parametrize('te', (
testexc(
f=np.deg2rad,
q_in=(3. * u.m, ),
exc=TypeError,
msg=None
),
testexc(
f=np.radians,
q_in=(3. * u.m, ),
exc=TypeError,
msg=None
),
testexc(
f=np.rad2deg,
q_in=(3. * u.m),
exc=TypeError,
msg=None
),
testexc(
f=np.degrees,
q_in=(3. * u.m),
exc=TypeError,
msg=None
),
testexc(
f=np.sin,
q_in=(3. * u.m, ),
exc=TypeError,
msg="Can only apply 'sin' function to quantities with angle units"
),
testexc(
f=np.arcsin,
q_in=(3. * u.m, ),
exc=TypeError,
msg="Can only apply 'arcsin' function to dimensionless quantities"
),
testexc(
f=np.cos,
q_in=(3. * u.s, ),
exc=TypeError,
msg="Can only apply 'cos' function to quantities with angle units"
),
testexc(
f=np.arccos,
q_in=(3. * u.s, ),
exc=TypeError,
msg="Can only apply 'arccos' function to dimensionless quantities"
),
testexc(
f=np.tan,
q_in=(np.array([1, 2, 3]) * u.N, ),
exc=TypeError,
msg="Can only apply 'tan' function to quantities with angle units"
),
testexc(
f=np.arctan,
q_in=(np.array([1, 2, 3]) * u.N, ),
exc=TypeError,
msg="Can only apply 'arctan' function to dimensionless quantities"
),
testexc(
f=np.arctan2,
q_in=(np.array([1, 2, 3]) * u.N, 1. * u.s),
exc=u.UnitsError,
msg="compatible dimensions"
),
testexc(
f=np.arctan2,
q_in=(np.array([1, 2, 3]) * u.N, 1.),
exc=u.UnitsError,
msg="dimensionless quantities when other arg"
)
))
def test_testexcs(self, te):
return test_testexc(te)
@pytest.mark.parametrize('tw', (
testwarn(
f=np.arcsin,
q_in=(27. * u.pc / (15 * u.kpc), ),
wfilter='error'
),
))
def test_testwarns(self, tw):
return test_testwarn(tw)
class TestQuantityMathFuncs:
"""
Test other mathematical functions
"""
def test_multiply_scalar(self):
assert np.multiply(4. * u.m, 2. / u.s) == 8. * u.m / u.s
assert np.multiply(4. * u.m, 2.) == 8. * u.m
assert np.multiply(4., 2. / u.s) == 8. / u.s
def test_multiply_array(self):
assert np.all(np.multiply(np.arange(3.) * u.m, 2. / u.s) ==
np.arange(0, 6., 2.) * u.m / u.s)
@pytest.mark.skipif(not isinstance(getattr(np, 'matmul', None), np.ufunc),
reason="np.matmul is not yet a gufunc")
def test_matmul(self):
q = np.arange(3.) * u.m
r = np.matmul(q, q)
assert r == 5. * u.m ** 2
# less trivial case.
q1 = np.eye(3) * u.m
q2 = np.array([[[1., 0., 0.],
[0., 1., 0.],
[0., 0., 1.]],
[[0., 1., 0.],
[0., 0., 1.],
[1., 0., 0.]],
[[0., 0., 1.],
[1., 0., 0.],
[0., 1., 0.]]]) / u.s
r2 = np.matmul(q1, q2)
assert np.all(r2 == np.matmul(q1.value, q2.value) * q1.unit * q2.unit)
@pytest.mark.parametrize('function', (np.divide, np.true_divide))
def test_divide_scalar(self, function):
assert function(4. * u.m, 2. * u.s) == function(4., 2.) * u.m / u.s
assert function(4. * u.m, 2.) == function(4., 2.) * u.m
assert function(4., 2. * u.s) == function(4., 2.) / u.s
@pytest.mark.parametrize('function', (np.divide, np.true_divide))
def test_divide_array(self, function):
assert np.all(function(np.arange(3.) * u.m, 2. * u.s) ==
function(np.arange(3.), 2.) * u.m / u.s)
def test_floor_divide_remainder_and_divmod(self):
inch = u.Unit(0.0254 * u.m)
dividend = np.array([1., 2., 3.]) * u.m
divisor = np.array([3., 4., 5.]) * inch
quotient = dividend // divisor
remainder = dividend % divisor
assert_allclose(quotient.value, [13., 19., 23.])
assert quotient.unit == u.dimensionless_unscaled
assert_allclose(remainder.value, [0.0094, 0.0696, 0.079])
assert remainder.unit == dividend.unit
quotient2 = np.floor_divide(dividend, divisor)
remainder2 = np.remainder(dividend, divisor)
assert np.all(quotient2 == quotient)
assert np.all(remainder2 == remainder)
quotient3, remainder3 = divmod(dividend, divisor)
assert np.all(quotient3 == quotient)
assert np.all(remainder3 == remainder)
with pytest.raises(TypeError):
divmod(dividend, u.km)
with pytest.raises(TypeError):
dividend // u.km
with pytest.raises(TypeError):
dividend % u.km
quotient4, remainder4 = np.divmod(dividend, divisor)
assert np.all(quotient4 == quotient)
assert np.all(remainder4 == remainder)
with pytest.raises(TypeError):
np.divmod(dividend, u.km)
def test_sqrt_scalar(self):
assert np.sqrt(4. * u.m) == 2. * u.m ** 0.5
def test_sqrt_array(self):
assert np.all(np.sqrt(np.array([1., 4., 9.]) * u.m)
== np.array([1., 2., 3.]) * u.m ** 0.5)
def test_square_scalar(self):
assert np.square(4. * u.m) == 16. * u.m ** 2
def test_square_array(self):
assert np.all(np.square(np.array([1., 2., 3.]) * u.m)
== np.array([1., 4., 9.]) * u.m ** 2)
def test_reciprocal_scalar(self):
assert np.reciprocal(4. * u.m) == 0.25 / u.m
def test_reciprocal_array(self):
assert np.all(np.reciprocal(np.array([1., 2., 4.]) * u.m)
== np.array([1., 0.5, 0.25]) / u.m)
def test_heaviside_scalar(self):
assert np.heaviside(0. * u.m, 0.5) == 0.5 * u.dimensionless_unscaled
assert np.heaviside(0. * u.s,
25 * u.percent) == 0.25 * u.dimensionless_unscaled
assert np.heaviside(2. * u.J, 0.25) == 1. * u.dimensionless_unscaled
def test_heaviside_array(self):
values = np.array([-1., 0., 0., +1.])
halfway = np.array([0.75, 0.25, 0.75, 0.25]) * u.dimensionless_unscaled
assert np.all(np.heaviside(values * u.m,
halfway * u.dimensionless_unscaled) ==
[0, 0.25, 0.75, +1.] * u.dimensionless_unscaled)
@pytest.mark.parametrize('function', (np.cbrt, ))
def test_cbrt_scalar(self, function):
assert function(8. * u.m**3) == 2. * u.m
@pytest.mark.parametrize('function', (np.cbrt, ))
def test_cbrt_array(self, function):
# Calculate cbrt on both sides since on Windows the cube root of 64
# does not exactly equal 4. See 4388.
values = np.array([1., 8., 64.])
assert np.all(function(values * u.m**3) ==
function(values) * u.m)
def test_power_scalar(self):
assert np.power(4. * u.m, 2.) == 16. * u.m ** 2
assert np.power(4., 200. * u.cm / u.m) == \
u.Quantity(16., u.dimensionless_unscaled)
# regression check on #1696
assert np.power(4. * u.m, 0.) == 1. * u.dimensionless_unscaled
def test_power_array(self):
assert np.all(np.power(np.array([1., 2., 3.]) * u.m, 3.)
== np.array([1., 8., 27.]) * u.m ** 3)
# regression check on #1696
assert np.all(np.power(np.arange(4.) * u.m, 0.) ==
1. * u.dimensionless_unscaled)
# float_power only introduced in numpy 1.12
@pytest.mark.skipif("not hasattr(np, 'float_power')")
def test_float_power_array(self):
assert np.all(np.float_power(np.array([1., 2., 3.]) * u.m, 3.)
== np.array([1., 8., 27.]) * u.m ** 3)
# regression check on #1696
assert np.all(np.float_power(np.arange(4.) * u.m, 0.) ==
1. * u.dimensionless_unscaled)
@raises(ValueError)
def test_power_array_array(self):
np.power(4. * u.m, [2., 4.])
@raises(ValueError)
def test_power_array_array2(self):
np.power([2., 4.] * u.m, [2., 4.])
def test_power_array_array3(self):
# Identical unit fractions are converted automatically to dimensionless
# and should be allowed as base for np.power: #4764
q = [2., 4.] * u.m / u.m
powers = [2., 4.]
res = np.power(q, powers)
assert np.all(res.value == q.value ** powers)
assert res.unit == u.dimensionless_unscaled
# The same holds for unit fractions that are scaled dimensionless.
q2 = [2., 4.] * u.m / u.cm
# Test also against different types of exponent
for cls in (list, tuple, np.array, np.ma.array, u.Quantity):
res2 = np.power(q2, cls(powers))
assert np.all(res2.value == q2.to_value(1) ** powers)
assert res2.unit == u.dimensionless_unscaled
# Though for single powers, we keep the composite unit.
res3 = q2 ** 2
assert np.all(res3.value == q2.value ** 2)
assert res3.unit == q2.unit ** 2
assert np.all(res3 == q2 ** [2, 2])
def test_power_invalid(self):
with pytest.raises(TypeError) as exc:
np.power(3., 4. * u.m)
assert "raise something to a dimensionless" in exc.value.args[0]
def test_copysign_scalar(self):
assert np.copysign(3 * u.m, 1.) == 3. * u.m
assert np.copysign(3 * u.m, 1. * u.s) == 3. * u.m
assert np.copysign(3 * u.m, -1.) == -3. * u.m
assert np.copysign(3 * u.m, -1. * u.s) == -3. * u.m
def test_copysign_array(self):
assert np.all(np.copysign(np.array([1., 2., 3.]) * u.s, -1.) ==
-np.array([1., 2., 3.]) * u.s)
assert np.all(np.copysign(np.array([1., 2., 3.]) * u.s, -1. * u.m) ==
-np.array([1., 2., 3.]) * u.s)
assert np.all(np.copysign(np.array([1., 2., 3.]) * u.s,
np.array([-2., 2., -4.]) * u.m) ==
np.array([-1., 2., -3.]) * u.s)
q = np.copysign(np.array([1., 2., 3.]), -3 * u.m)
assert np.all(q == np.array([-1., -2., -3.]))
assert not isinstance(q, u.Quantity)
def test_ldexp_scalar(self):
assert np.ldexp(4. * u.m, 2) == 16. * u.m
def test_ldexp_array(self):
assert np.all(np.ldexp(np.array([1., 2., 3.]) * u.m, [3, 2, 1])
== np.array([8., 8., 6.]) * u.m)
def test_ldexp_invalid(self):
with pytest.raises(TypeError):
np.ldexp(3. * u.m, 4.)
with pytest.raises(TypeError):
np.ldexp(3., u.Quantity(4, u.m, dtype=int))
@pytest.mark.parametrize('function', (np.exp, np.expm1, np.exp2,
np.log, np.log2, np.log10, np.log1p))
def test_exp_scalar(self, function):
q = function(3. * u.m / (6. * u.m))
assert q.unit == u.dimensionless_unscaled
assert q.value == function(0.5)
@pytest.mark.parametrize('function', (np.exp, np.expm1, np.exp2,
np.log, np.log2, np.log10, np.log1p))
def test_exp_array(self, function):
q = function(np.array([2., 3., 6.]) * u.m / (6. * u.m))
assert q.unit == u.dimensionless_unscaled
assert np.all(q.value
== function(np.array([1. / 3., 1. / 2., 1.])))
# should also work on quantities that can be made dimensionless
q2 = function(np.array([2., 3., 6.]) * u.m / (6. * u.cm))
assert q2.unit == u.dimensionless_unscaled
assert_allclose(q2.value,
function(np.array([100. / 3., 100. / 2., 100.])))
@pytest.mark.parametrize('function', (np.exp, np.expm1, np.exp2,
np.log, np.log2, np.log10, np.log1p))
def test_exp_invalid_units(self, function):
# Can't use exp() with non-dimensionless quantities
with pytest.raises(TypeError) as exc:
function(3. * u.m / u.s)
assert exc.value.args[0] == ("Can only apply '{0}' function to "
"dimensionless quantities"
.format(function.__name__))
def test_modf_scalar(self):
q = np.modf(9. * u.m / (600. * u.cm))
assert q == (0.5 * u.dimensionless_unscaled,
1. * u.dimensionless_unscaled)
def test_modf_array(self):
v = np.arange(10.) * u.m / (500. * u.cm)
q = np.modf(v)
n = np.modf(v.to_value(u.dimensionless_unscaled))
assert q[0].unit == u.dimensionless_unscaled
assert q[1].unit == u.dimensionless_unscaled
assert all(q[0].value == n[0])
assert all(q[1].value == n[1])
def test_frexp_scalar(self):
q = np.frexp(3. * u.m / (6. * u.m))
assert q == (np.array(0.5), np.array(0.0))
def test_frexp_array(self):
q = np.frexp(np.array([2., 3., 6.]) * u.m / (6. * u.m))
assert all((_q0, _q1) == np.frexp(_d) for _q0, _q1, _d
in zip(q[0], q[1], [1. / 3., 1. / 2., 1.]))
def test_frexp_invalid_units(self):
# Can't use prod() with non-dimensionless quantities
with pytest.raises(TypeError) as exc:
np.frexp(3. * u.m / u.s)
assert exc.value.args[0] == ("Can only apply 'frexp' function to "
"unscaled dimensionless quantities")
# also does not work on quantities that can be made dimensionless
with pytest.raises(TypeError) as exc:
np.frexp(np.array([2., 3., 6.]) * u.m / (6. * u.cm))
assert exc.value.args[0] == ("Can only apply 'frexp' function to "
"unscaled dimensionless quantities")
@pytest.mark.parametrize('function', (np.logaddexp, np.logaddexp2))
def test_dimensionless_twoarg_array(self, function):
q = function(np.array([2., 3., 6.]) * u.m / (6. * u.cm), 1.)
assert q.unit == u.dimensionless_unscaled
assert_allclose(q.value,
function(np.array([100. / 3., 100. / 2., 100.]), 1.))
@pytest.mark.parametrize('function', (np.logaddexp, np.logaddexp2))
def test_dimensionless_twoarg_invalid_units(self, function):
with pytest.raises(TypeError) as exc:
function(1. * u.km / u.s, 3. * u.m / u.s)
assert exc.value.args[0] == ("Can only apply '{0}' function to "
"dimensionless quantities"
.format(function.__name__))
class TestInvariantUfuncs:
@pytest.mark.parametrize(('ufunc'), [np.absolute, np.fabs,
np.conj, np.conjugate,
np.negative, np.spacing, np.rint,
np.floor, np.ceil, np.positive])
def test_invariant_scalar(self, ufunc):
q_i = 4.7 * u.m
q_o = ufunc(q_i)
assert isinstance(q_o, u.Quantity)
assert q_o.unit == q_i.unit
assert q_o.value == ufunc(q_i.value)
@pytest.mark.parametrize(('ufunc'), [np.absolute, np.conjugate,
np.negative, np.rint,
np.floor, np.ceil])
def test_invariant_array(self, ufunc):
q_i = np.array([-3.3, 2.1, 10.2]) * u.kg / u.s
q_o = ufunc(q_i)
assert isinstance(q_o, u.Quantity)
assert q_o.unit == q_i.unit
assert np.all(q_o.value == ufunc(q_i.value))
@pytest.mark.parametrize(('ufunc'), [np.add, np.subtract, np.hypot,
np.maximum, np.minimum, np.nextafter,
np.remainder, np.mod, np.fmod])
def test_invariant_twoarg_scalar(self, ufunc):
q_i1 = 4.7 * u.m
q_i2 = 9.4 * u.km
q_o = ufunc(q_i1, q_i2)
assert isinstance(q_o, u.Quantity)
assert q_o.unit == q_i1.unit
assert_allclose(q_o.value, ufunc(q_i1.value, q_i2.to_value(q_i1.unit)))
@pytest.mark.parametrize(('ufunc'), [np.add, np.subtract, np.hypot,
np.maximum, np.minimum, np.nextafter,
np.remainder, np.mod, np.fmod])
def test_invariant_twoarg_array(self, ufunc):
q_i1 = np.array([-3.3, 2.1, 10.2]) * u.kg / u.s
q_i2 = np.array([10., -5., 1.e6]) * u.g / u.us
q_o = ufunc(q_i1, q_i2)
assert isinstance(q_o, u.Quantity)
assert q_o.unit == q_i1.unit
assert_allclose(q_o.value, ufunc(q_i1.value, q_i2.to_value(q_i1.unit)))
@pytest.mark.parametrize(('ufunc'), [np.add, np.subtract, np.hypot,
np.maximum, np.minimum, np.nextafter,
np.remainder, np.mod, np.fmod])
def test_invariant_twoarg_one_arbitrary(self, ufunc):
q_i1 = np.array([-3.3, 2.1, 10.2]) * u.kg / u.s
arbitrary_unit_value = np.array([0.])
q_o = ufunc(q_i1, arbitrary_unit_value)
assert isinstance(q_o, u.Quantity)
assert q_o.unit == q_i1.unit
assert_allclose(q_o.value, ufunc(q_i1.value, arbitrary_unit_value))
@pytest.mark.parametrize(('ufunc'), [np.add, np.subtract, np.hypot,
np.maximum, np.minimum, np.nextafter,
np.remainder, np.mod, np.fmod])
def test_invariant_twoarg_invalid_units(self, ufunc):
q_i1 = 4.7 * u.m
q_i2 = 9.4 * u.s
with pytest.raises(u.UnitsError) as exc:
ufunc(q_i1, q_i2)
assert "compatible dimensions" in exc.value.args[0]
class TestComparisonUfuncs:
@pytest.mark.parametrize(('ufunc'), [np.greater, np.greater_equal,
np.less, np.less_equal,
np.not_equal, np.equal])
def test_comparison_valid_units(self, ufunc):
q_i1 = np.array([-3.3, 2.1, 10.2]) * u.kg / u.s
q_i2 = np.array([10., -5., 1.e6]) * u.g / u.Ms
q_o = ufunc(q_i1, q_i2)
assert not isinstance(q_o, u.Quantity)
assert q_o.dtype == bool
assert np.all(q_o == ufunc(q_i1.value, q_i2.to_value(q_i1.unit)))
q_o2 = ufunc(q_i1 / q_i2, 2.)
assert not isinstance(q_o2, u.Quantity)
assert q_o2.dtype == bool
assert np.all(q_o2 == ufunc((q_i1 / q_i2)
.to_value(u.dimensionless_unscaled), 2.))
# comparison with 0., inf, nan is OK even for dimensional quantities
for arbitrary_unit_value in (0., np.inf, np.nan):
ufunc(q_i1, arbitrary_unit_value)
ufunc(q_i1, arbitrary_unit_value*np.ones(len(q_i1)))
# and just for completeness
ufunc(q_i1, np.array([0., np.inf, np.nan]))
@pytest.mark.parametrize(('ufunc'), [np.greater, np.greater_equal,
np.less, np.less_equal,
np.not_equal, np.equal])
def test_comparison_invalid_units(self, ufunc):
q_i1 = 4.7 * u.m
q_i2 = 9.4 * u.s
with pytest.raises(u.UnitsError) as exc:
ufunc(q_i1, q_i2)
assert "compatible dimensions" in exc.value.args[0]
class TestInplaceUfuncs:
@pytest.mark.parametrize(('value'), [1., np.arange(10.)])
def test_one_argument_ufunc_inplace(self, value):
# without scaling
s = value * u.rad
check = s
np.sin(s, out=s)
assert check is s
assert check.unit == u.dimensionless_unscaled
# with scaling
s2 = (value * u.rad).to(u.deg)
check2 = s2
np.sin(s2, out=s2)
assert check2 is s2
assert check2.unit == u.dimensionless_unscaled
assert_allclose(s.value, s2.value)
@pytest.mark.parametrize(('value'), [1., np.arange(10.)])
def test_one_argument_ufunc_inplace_2(self, value):
"""Check inplace works with non-quantity input and quantity output"""
s = value * u.m
check = s
np.absolute(value, out=s)
assert check is s
assert np.all(check.value == np.absolute(value))
assert check.unit is u.dimensionless_unscaled
np.sqrt(value, out=s)
assert check is s
assert np.all(check.value == np.sqrt(value))
assert check.unit is u.dimensionless_unscaled
np.exp(value, out=s)
assert check is s
assert np.all(check.value == np.exp(value))
assert check.unit is u.dimensionless_unscaled
np.arcsin(value/10., out=s)
assert check is s
assert np.all(check.value == np.arcsin(value/10.))
assert check.unit is u.radian
@pytest.mark.parametrize(('value'), [1., np.arange(10.)])
def test_one_argument_two_output_ufunc_inplace(self, value):
v = 100. * value * u.cm / u.m
v_copy = v.copy()
tmp = v.copy()
check = v
np.modf(v, tmp, v)
assert check is v
assert check.unit == u.dimensionless_unscaled
v2 = v_copy.to(u.dimensionless_unscaled)
check2 = v2
np.modf(v2, tmp, v2)
assert check2 is v2
assert check2.unit == u.dimensionless_unscaled
# can also replace in last position if no scaling is needed
v3 = v_copy.to(u.dimensionless_unscaled)
check3 = v3
np.modf(v3, v3, tmp)
assert check3 is v3
assert check3.unit == u.dimensionless_unscaled
# And now, with numpy >= 1.13, one can also replace input with
# first output when scaling
v4 = v_copy.copy()
check4 = v4
np.modf(v4, v4, tmp)
assert check4 is v4
assert check4.unit == u.dimensionless_unscaled
@pytest.mark.parametrize(('value'), [1., np.arange(10.)])
def test_two_argument_ufunc_inplace_1(self, value):
s = value * u.cycle
check = s
s /= 2.
assert check is s
assert np.all(check.value == value / 2.)
s /= u.s
assert check is s
assert check.unit == u.cycle / u.s
s *= 2. * u.s
assert check is s
assert np.all(check == value * u.cycle)
@pytest.mark.parametrize(('value'), [1., np.arange(10.)])
def test_two_argument_ufunc_inplace_2(self, value):
s = value * u.cycle
check = s
np.arctan2(s, s, out=s)
assert check is s
assert check.unit == u.radian
with pytest.raises(u.UnitsError):
s += 1. * u.m
assert check is s
assert check.unit == u.radian
np.arctan2(1. * u.deg, s, out=s)
assert check is s
assert check.unit == u.radian
np.add(1. * u.deg, s, out=s)
assert check is s
assert check.unit == u.deg
np.multiply(2. / u.s, s, out=s)
assert check is s
assert check.unit == u.deg / u.s
def test_two_argument_ufunc_inplace_3(self):
s = np.array([1., 2., 3.]) * u.dimensionless_unscaled
np.add(np.array([1., 2., 3.]), np.array([1., 2., 3.]) * 2., out=s)
assert np.all(s.value == np.array([3., 6., 9.]))
assert s.unit is u.dimensionless_unscaled
np.arctan2(np.array([1., 2., 3.]), np.array([1., 2., 3.]) * 2., out=s)
assert_allclose(s.value, np.arctan2(1., 2.))
assert s.unit is u.radian
@pytest.mark.parametrize(('value'), [1., np.arange(10.)])
def test_two_argument_two_output_ufunc_inplace(self, value):
v = value * u.m
divisor = 70.*u.cm
v1 = v.copy()
tmp = v.copy()
check = np.divmod(v1, divisor, out=(tmp, v1))
assert check[0] is tmp and check[1] is v1
assert tmp.unit == u.dimensionless_unscaled
assert v1.unit == v.unit
v2 = v.copy()
check2 = np.divmod(v2, divisor, out=(v2, tmp))
assert check2[0] is v2 and check2[1] is tmp
assert v2.unit == u.dimensionless_unscaled
assert tmp.unit == v.unit
v3a = v.copy()
v3b = v.copy()
check3 = np.divmod(v3a, divisor, out=(v3a, v3b))
assert check3[0] is v3a and check3[1] is v3b
assert v3a.unit == u.dimensionless_unscaled
assert v3b.unit == v.unit
def test_ufunc_inplace_non_contiguous_data(self):
# ensure inplace works also for non-contiguous data (closes #1834)
s = np.arange(10.) * u.m
s_copy = s.copy()
s2 = s[::2]
s2 += 1. * u.cm
assert np.all(s[::2] > s_copy[::2])
assert np.all(s[1::2] == s_copy[1::2])
def test_ufunc_inplace_non_standard_dtype(self):
"""Check that inplace operations check properly for casting.
First two tests that check that float32 is kept close #3976.
"""
a1 = u.Quantity([1, 2, 3, 4], u.m, dtype=np.float32)
a1 *= np.float32(10)
assert a1.unit is u.m
assert a1.dtype == np.float32
a2 = u.Quantity([1, 2, 3, 4], u.m, dtype=np.float32)
a2 += (20.*u.km)
assert a2.unit is u.m
assert a2.dtype == np.float32
# For integer, in-place only works if no conversion is done.
a3 = u.Quantity([1, 2, 3, 4], u.m, dtype=np.int32)
a3 += u.Quantity(10, u.m, dtype=np.int64)
assert a3.unit is u.m
assert a3.dtype == np.int32
a4 = u.Quantity([1, 2, 3, 4], u.m, dtype=np.int32)
with pytest.raises(TypeError):
a4 += u.Quantity(10, u.mm, dtype=np.int64)
class TestUfuncAt:
"""Test that 'at' method for ufuncs (calculates in-place at given indices)
For Quantities, since calculations are in-place, it makes sense only
if the result is still a quantity, and if the unit does not have to change
"""
def test_one_argument_ufunc_at(self):
q = np.arange(10.) * u.m
i = np.array([1, 2])
qv = q.value.copy()
np.negative.at(q, i)
np.negative.at(qv, i)
assert np.all(q.value == qv)
assert q.unit is u.m
# cannot change from quantity to bool array
with pytest.raises(TypeError):
np.isfinite.at(q, i)
# for selective in-place, cannot change the unit
with pytest.raises(u.UnitsError):
np.square.at(q, i)
# except if the unit does not change (i.e., dimensionless)
d = np.arange(10.) * u.dimensionless_unscaled
dv = d.value.copy()
np.square.at(d, i)
np.square.at(dv, i)
assert np.all(d.value == dv)
assert d.unit is u.dimensionless_unscaled
d = np.arange(10.) * u.dimensionless_unscaled
dv = d.value.copy()
np.log.at(d, i)
np.log.at(dv, i)
assert np.all(d.value == dv)
assert d.unit is u.dimensionless_unscaled
# also for sine it doesn't work, even if given an angle
a = np.arange(10.) * u.radian
with pytest.raises(u.UnitsError):
np.sin.at(a, i)
# except, for consistency, if we have made radian equivalent to
# dimensionless (though hopefully it will never be needed)
av = a.value.copy()
with u.add_enabled_equivalencies(u.dimensionless_angles()):
np.sin.at(a, i)
np.sin.at(av, i)
assert_allclose(a.value, av)
# but we won't do double conversion
ad = np.arange(10.) * u.degree
with pytest.raises(u.UnitsError):
np.sin.at(ad, i)
def test_two_argument_ufunc_at(self):
s = np.arange(10.) * u.m
i = np.array([1, 2])
check = s.value.copy()
np.add.at(s, i, 1.*u.km)
np.add.at(check, i, 1000.)
assert np.all(s.value == check)
assert s.unit is u.m
with pytest.raises(u.UnitsError):
np.add.at(s, i, 1.*u.s)
# also raise UnitsError if unit would have to be changed
with pytest.raises(u.UnitsError):
np.multiply.at(s, i, 1*u.s)
# but be fine if it does not
s = np.arange(10.) * u.m
check = s.value.copy()
np.multiply.at(s, i, 2.*u.dimensionless_unscaled)
np.multiply.at(check, i, 2)
assert np.all(s.value == check)
s = np.arange(10.) * u.m
np.multiply.at(s, i, 2.)
assert np.all(s.value == check)
# of course cannot change class of data either
with pytest.raises(TypeError):
np.greater.at(s, i, 1.*u.km)
class TestUfuncReduceReduceatAccumulate:
"""Test 'reduce', 'reduceat' and 'accumulate' methods for ufuncs
For Quantities, it makes sense only if the unit does not have to change
"""
def test_one_argument_ufunc_reduce_accumulate(self):
# one argument cannot be used
s = np.arange(10.) * u.radian
i = np.array([0, 5, 1, 6])
with pytest.raises(ValueError):
np.sin.reduce(s)
with pytest.raises(ValueError):
np.sin.accumulate(s)
with pytest.raises(ValueError):
np.sin.reduceat(s, i)
def test_two_argument_ufunc_reduce_accumulate(self):
s = np.arange(10.) * u.m
i = np.array([0, 5, 1, 6])
check = s.value.copy()
s_add_reduce = np.add.reduce(s)
check_add_reduce = np.add.reduce(check)
assert s_add_reduce.value == check_add_reduce
assert s_add_reduce.unit is u.m
s_add_accumulate = np.add.accumulate(s)
check_add_accumulate = np.add.accumulate(check)
assert np.all(s_add_accumulate.value == check_add_accumulate)
assert s_add_accumulate.unit is u.m
s_add_reduceat = np.add.reduceat(s, i)
check_add_reduceat = np.add.reduceat(check, i)
assert np.all(s_add_reduceat.value == check_add_reduceat)
assert s_add_reduceat.unit is u.m
# reduce(at) or accumulate on comparisons makes no sense,
# as intermediate result is not even a Quantity
with pytest.raises(TypeError):
np.greater.reduce(s)
with pytest.raises(TypeError):
np.greater.accumulate(s)
with pytest.raises(TypeError):
np.greater.reduceat(s, i)
# raise UnitsError if unit would have to be changed
with pytest.raises(u.UnitsError):
np.multiply.reduce(s)
with pytest.raises(u.UnitsError):
np.multiply.accumulate(s)
with pytest.raises(u.UnitsError):
np.multiply.reduceat(s, i)
# but be fine if it does not
s = np.arange(10.) * u.dimensionless_unscaled
check = s.value.copy()
s_multiply_reduce = np.multiply.reduce(s)
check_multiply_reduce = np.multiply.reduce(check)
assert s_multiply_reduce.value == check_multiply_reduce
assert s_multiply_reduce.unit is u.dimensionless_unscaled
s_multiply_accumulate = np.multiply.accumulate(s)
check_multiply_accumulate = np.multiply.accumulate(check)
assert np.all(s_multiply_accumulate.value == check_multiply_accumulate)
assert s_multiply_accumulate.unit is u.dimensionless_unscaled
s_multiply_reduceat = np.multiply.reduceat(s, i)
check_multiply_reduceat = np.multiply.reduceat(check, i)
assert np.all(s_multiply_reduceat.value == check_multiply_reduceat)
assert s_multiply_reduceat.unit is u.dimensionless_unscaled
class TestUfuncOuter:
"""Test 'outer' methods for ufuncs
Just a few spot checks, since it uses the same code as the regular
ufunc call
"""
def test_one_argument_ufunc_outer(self):
# one argument cannot be used
s = np.arange(10.) * u.radian
with pytest.raises(ValueError):
np.sin.outer(s)
def test_two_argument_ufunc_outer(self):
s1 = np.arange(10.) * u.m
s2 = np.arange(2.) * u.s
check1 = s1.value
check2 = s2.value
s12_multiply_outer = np.multiply.outer(s1, s2)
check12_multiply_outer = np.multiply.outer(check1, check2)
assert np.all(s12_multiply_outer.value == check12_multiply_outer)
assert s12_multiply_outer.unit == s1.unit * s2.unit
# raise UnitsError if appropriate
with pytest.raises(u.UnitsError):
np.add.outer(s1, s2)
# but be fine if it does not
s3 = np.arange(2.) * s1.unit
check3 = s3.value
s13_add_outer = np.add.outer(s1, s3)
check13_add_outer = np.add.outer(check1, check3)
assert np.all(s13_add_outer.value == check13_add_outer)
assert s13_add_outer.unit is s1.unit
s13_greater_outer = np.greater.outer(s1, s3)
check13_greater_outer = np.greater.outer(check1, check3)
assert type(s13_greater_outer) is np.ndarray
assert np.all(s13_greater_outer == check13_greater_outer)
if HAS_SCIPY:
from scipy import special as sps
def test_scipy_registration():
"""Check that scipy gets loaded upon first use."""
assert sps.erf not in qh.UFUNC_HELPERS
sps.erf(1. * u.percent)
assert sps.erf in qh.UFUNC_HELPERS
class TestScipySpecialUfuncs:
erf_like_ufuncs = (
sps.erf, sps.gamma, sps.loggamma, sps.gammasgn, sps.psi,
sps.rgamma, sps.erfc, sps.erfcx, sps.erfi, sps.wofz, sps.dawsn,
sps.entr, sps.exprel, sps.expm1, sps.log1p, sps.exp2, sps.exp10)
@pytest.mark.parametrize('function', erf_like_ufuncs)
def test_erf_scalar(self, function):
TestQuantityMathFuncs.test_exp_scalar(None, function)
@pytest.mark.parametrize('function', erf_like_ufuncs)
def test_erf_array(self, function):
TestQuantityMathFuncs.test_exp_array(None, function)
@pytest.mark.parametrize('function', erf_like_ufuncs)
def test_erf_invalid_units(self, function):
TestQuantityMathFuncs.test_exp_invalid_units(None, function)
@pytest.mark.parametrize('function', (sps.cbrt, ))
def test_cbrt_scalar(self, function):
TestQuantityMathFuncs.test_cbrt_scalar(None, function)
@pytest.mark.parametrize('function', (sps.cbrt, ))
def test_cbrt_array(self, function):
TestQuantityMathFuncs.test_cbrt_array(None, function)
@pytest.mark.parametrize('function', (sps.radian, ))
def test_radian(self, function):
q1 = function(180. * u.degree, 0. * u.arcmin, 0. * u.arcsec)
assert_allclose(q1.value, np.pi)
assert q1.unit == u.radian
q2 = function(0. * u.degree, 30. * u.arcmin, 0. * u.arcsec)
assert_allclose(q2.value, (30. * u.arcmin).to(u.radian).value)
assert q2.unit == u.radian
q3 = function(0. * u.degree, 0. * u.arcmin, 30. * u.arcsec)
assert_allclose(q3.value, (30. * u.arcsec).to(u.radian).value)
# the following doesn't make much sense in terms of the name of the
# routine, but we check it gives the correct result.
q4 = function(3. * u.radian, 0. * u.arcmin, 0. * u.arcsec)
assert_allclose(q4.value, 3.)
assert q4.unit == u.radian
with pytest.raises(TypeError):
function(3. * u.m, 2. * u.s, 1. * u.kg)
jv_like_ufuncs = (
sps.jv, sps.jn, sps.jve, sps.yn, sps.yv, sps.yve, sps.kn, sps.kv,
sps.kve, sps.iv, sps.ive, sps.hankel1, sps.hankel1e, sps.hankel2,
sps.hankel2e)
@pytest.mark.parametrize('function', jv_like_ufuncs)
def test_jv_scalar(self, function):
q = function(2. * u.m / (2. * u.m), 3. * u.m / (6. * u.m))
assert q.unit == u.dimensionless_unscaled
assert q.value == function(1.0, 0.5)
@pytest.mark.parametrize('function', jv_like_ufuncs)
def test_jv_array(self, function):
q = function(np.ones(3) * u.m / (1. * u.m),
np.array([2., 3., 6.]) * u.m / (6. * u.m))
assert q.unit == u.dimensionless_unscaled
assert np.all(q.value == function(
np.ones(3),
np.array([1. / 3., 1. / 2., 1.]))
)
# should also work on quantities that can be made dimensionless
q2 = function(np.ones(3) * u.m / (1. * u.m),
np.array([2., 3., 6.]) * u.m / (6. * u.cm))
assert q2.unit == u.dimensionless_unscaled
assert_allclose(q2.value,
function(np.ones(3),
np.array([100. / 3., 100. / 2., 100.])))
@pytest.mark.parametrize('function', jv_like_ufuncs)
def test_jv_invalid_units(self, function):
# Can't use jv() with non-dimensionless quantities
with pytest.raises(TypeError) as exc:
function(1. * u.kg, 3. * u.m / u.s)
assert exc.value.args[0] == ("Can only apply '{0}' function to "
"dimensionless quantities"
.format(function.__name__))
|
5a7946e68481b9dc481bde5247e3c677debf3cb917f431e5c75591c0c1c8c32d | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import pytest
from astropy import units as u
# list of pairs (target unit/physical type, input unit)
x_inputs = [(u.arcsec, u.deg), ('angle', u.deg),
(u.kpc/u.Myr, u.km/u.s), ('speed', u.km/u.s),
([u.arcsec, u.km], u.deg), ([u.arcsec, u.km], u.km), # multiple allowed
(['angle', 'length'], u.deg), (['angle', 'length'], u.km)]
y_inputs = [(u.arcsec, u.deg), ('angle', u.deg),
(u.kpc/u.Myr, u.km/u.s), ('speed', u.km/u.s)]
@pytest.fixture(scope="module",
params=list(range(len(x_inputs))))
def x_input(request):
return x_inputs[request.param]
@pytest.fixture(scope="module",
params=list(range(len(y_inputs))))
def y_input(request):
return y_inputs[request.param]
# ---- Tests that use the fixtures defined above ----
def test_args(x_input, y_input):
x_target, x_unit = x_input
y_target, y_unit = y_input
@u.quantity_input(x=x_target, y=y_target)
def myfunc_args(x, y):
return x, y
x, y = myfunc_args(1*x_unit, 1*y_unit)
assert isinstance(x, u.Quantity)
assert isinstance(y, u.Quantity)
assert x.unit == x_unit
assert y.unit == y_unit
def test_args_nonquantity(x_input):
x_target, x_unit = x_input
@u.quantity_input(x=x_target)
def myfunc_args(x, y):
return x, y
x, y = myfunc_args(1*x_unit, 100)
assert isinstance(x, u.Quantity)
assert isinstance(y, int)
assert x.unit == x_unit
def test_wrong_unit(x_input, y_input):
x_target, x_unit = x_input
y_target, y_unit = y_input
@u.quantity_input(x=x_target, y=y_target)
def myfunc_args(x, y):
return x, y
with pytest.raises(u.UnitsError) as e:
x, y = myfunc_args(1*x_unit, 100*u.Joule) # has to be an unspecified unit
str_to = str(y_target)
assert str(e.value) == "Argument 'y' to function 'myfunc_args' must be in units convertible to '{0}'.".format(str_to)
def test_not_quantity(x_input, y_input):
x_target, x_unit = x_input
y_target, y_unit = y_input
@u.quantity_input(x=x_target, y=y_target)
def myfunc_args(x, y):
return x, y
with pytest.raises(TypeError) as e:
x, y = myfunc_args(1*x_unit, 100)
assert str(e.value) == "Argument 'y' to function 'myfunc_args' has no 'unit' attribute. You may want to pass in an astropy Quantity instead."
def test_kwargs(x_input, y_input):
x_target, x_unit = x_input
y_target, y_unit = y_input
@u.quantity_input(x=x_target, y=y_target)
def myfunc_args(x, my_arg, y=1*y_unit):
return x, my_arg, y
x, my_arg, y = myfunc_args(1*x_unit, 100, y=100*y_unit)
assert isinstance(x, u.Quantity)
assert isinstance(my_arg, int)
assert isinstance(y, u.Quantity)
assert y.unit == y_unit
def test_unused_kwargs(x_input, y_input):
x_target, x_unit = x_input
y_target, y_unit = y_input
@u.quantity_input(x=x_target, y=y_target)
def myfunc_args(x, my_arg1, y=y_unit, my_arg2=1000):
return x, my_arg1, y, my_arg2
x, my_arg1, y, my_arg2 = myfunc_args(1*x_unit, 100,
y=100*y_unit, my_arg2=10)
assert isinstance(x, u.Quantity)
assert isinstance(my_arg1, int)
assert isinstance(y, u.Quantity)
assert isinstance(my_arg2, int)
assert y.unit == y_unit
assert my_arg2 == 10
def test_kwarg_wrong_unit(x_input, y_input):
x_target, x_unit = x_input
y_target, y_unit = y_input
@u.quantity_input(x=x_target, y=y_target)
def myfunc_args(x, y=10*y_unit):
return x, y
with pytest.raises(u.UnitsError) as e:
x, y = myfunc_args(1*x_unit, y=100*u.Joule)
str_to = str(y_target)
assert str(e.value) == "Argument 'y' to function 'myfunc_args' must be in units convertible to '{0}'.".format(str_to)
def test_kwarg_not_quantity(x_input, y_input):
x_target, x_unit = x_input
y_target, y_unit = y_input
@u.quantity_input(x=x_target, y=y_target)
def myfunc_args(x, y=10*y_unit):
return x, y
with pytest.raises(TypeError) as e:
x, y = myfunc_args(1*x_unit, y=100)
assert str(e.value) == "Argument 'y' to function 'myfunc_args' has no 'unit' attribute. You may want to pass in an astropy Quantity instead."
def test_kwarg_default(x_input, y_input):
x_target, x_unit = x_input
y_target, y_unit = y_input
@u.quantity_input(x=x_target, y=y_target)
def myfunc_args(x, y=10*y_unit):
return x, y
x, y = myfunc_args(1*x_unit)
assert isinstance(x, u.Quantity)
assert isinstance(y, u.Quantity)
assert x.unit == x_unit
assert y.unit == y_unit
def test_kwargs_input(x_input, y_input):
x_target, x_unit = x_input
y_target, y_unit = y_input
@u.quantity_input(x=x_target, y=y_target)
def myfunc_args(x=1*x_unit, y=1*y_unit):
return x, y
kwargs = {'x': 10*x_unit, 'y': 10*y_unit}
x, y = myfunc_args(**kwargs)
assert isinstance(x, u.Quantity)
assert isinstance(y, u.Quantity)
assert x.unit == x_unit
assert y.unit == y_unit
def test_kwargs_extra(x_input):
x_target, x_unit = x_input
@u.quantity_input(x=x_target)
def myfunc_args(x, **kwargs):
return x
x = myfunc_args(1*x_unit)
assert isinstance(x, u.Quantity)
assert x.unit == x_unit
# ---- Tests that don't used the fixtures ----
@pytest.mark.parametrize("x_unit,y_unit", [
(u.arcsec, u.eV),
('angle', 'energy')])
def test_arg_equivalencies(x_unit, y_unit):
@u.quantity_input(x=x_unit, y=y_unit,
equivalencies=u.mass_energy())
def myfunc_args(x, y):
return x, y+(10*u.J) # Add an energy to check equiv is working
x, y = myfunc_args(1*u.arcsec, 100*u.gram)
assert isinstance(x, u.Quantity)
assert isinstance(y, u.Quantity)
assert x.unit == u.arcsec
assert y.unit == u.gram
@pytest.mark.parametrize("x_unit,energy_unit", [
(u.arcsec, u.eV),
('angle', 'energy')])
def test_kwarg_equivalencies(x_unit, energy_unit):
@u.quantity_input(x=x_unit, energy=energy_unit, equivalencies=u.mass_energy())
def myfunc_args(x, energy=10*u.eV):
return x, energy+(10*u.J) # Add an energy to check equiv is working
x, energy = myfunc_args(1*u.arcsec, 100*u.gram)
assert isinstance(x, u.Quantity)
assert isinstance(energy, u.Quantity)
assert x.unit == u.arcsec
assert energy.unit == u.gram
def test_no_equivalent():
class test_unit:
pass
class test_quantity:
unit = test_unit()
@u.quantity_input(x=u.arcsec)
def myfunc_args(x):
return x
with pytest.raises(TypeError) as e:
x, y = myfunc_args(test_quantity())
assert str(e.value) == "Argument 'x' to function 'myfunc_args' has a 'unit' attribute without an 'is_equivalent' method. You may want to pass in an astropy Quantity instead."
def test_kwarg_invalid_physical_type():
@u.quantity_input(x='angle', y='africanswallow')
def myfunc_args(x, y=10*u.deg):
return x, y
with pytest.raises(ValueError) as e:
x, y = myfunc_args(1*u.arcsec, y=100*u.deg)
assert str(e.value) == "Invalid unit or physical type 'africanswallow'."
def test_default_value_check():
x_target = u.deg
x_unit = u.arcsec
with pytest.raises(TypeError):
@u.quantity_input(x=x_target)
def myfunc_args(x=1.):
return x
x = myfunc_args()
x = myfunc_args(1*x_unit)
assert isinstance(x, u.Quantity)
assert x.unit == x_unit
def test_args_None():
x_target = u.deg
x_unit = u.arcsec
y_target = u.km
y_unit = u.kpc
@u.quantity_input(x=[x_target, None], y=[None, y_target])
def myfunc_args(x, y):
return x, y
x, y = myfunc_args(1*x_unit, None)
assert isinstance(x, u.Quantity)
assert x.unit == x_unit
assert y is None
x, y = myfunc_args(None, 1*y_unit)
assert isinstance(y, u.Quantity)
assert y.unit == y_unit
assert x is None
def test_args_None_kwarg():
x_target = u.deg
x_unit = u.arcsec
y_target = u.km
@u.quantity_input(x=x_target, y=y_target)
def myfunc_args(x, y=None):
return x, y
x, y = myfunc_args(1*x_unit)
assert isinstance(x, u.Quantity)
assert x.unit == x_unit
assert y is None
x, y = myfunc_args(1*x_unit, None)
assert isinstance(x, u.Quantity)
assert x.unit == x_unit
assert y is None
with pytest.raises(TypeError):
x, y = myfunc_args(None, None)
|
93fae62e10819cf7ed8b897591aeae6a0c662b4d1eb0ce8552fb51615bacb33a | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import numpy as np
from astropy.units import (dimensionless_unscaled, photometric, Unit,
CompositeUnit, UnitsError, UnitTypeError,
UnitConversionError)
from .core import FunctionUnitBase, FunctionQuantity
from .units import dex, dB, mag
__all__ = ['LogUnit', 'MagUnit', 'DexUnit', 'DecibelUnit',
'LogQuantity', 'Magnitude', 'Decibel', 'Dex',
'STmag', 'ABmag', 'M_bol', 'm_bol']
class LogUnit(FunctionUnitBase):
"""Logarithmic unit containing a physical one
Usually, logarithmic units are instantiated via specific subclasses
such `MagUnit`, `DecibelUnit`, and `DexUnit`.
Parameters
----------
physical_unit : `~astropy.units.Unit` or `string`
Unit that is encapsulated within the logarithmic function unit.
If not given, dimensionless.
function_unit : `~astropy.units.Unit` or `string`
By default, the same as the logarithmic unit set by the subclass.
"""
# the four essential overrides of FunctionUnitBase
@property
def _default_function_unit(self):
return dex
@property
def _quantity_class(self):
return LogQuantity
def from_physical(self, x):
"""Transformation from value in physical to value in logarithmic units.
Used in equivalency."""
return dex.to(self._function_unit, np.log10(x))
def to_physical(self, x):
"""Transformation from value in logarithmic to value in physical units.
Used in equivalency."""
return 10 ** self._function_unit.to(dex, x)
# ^^^^ the four essential overrides of FunctionUnitBase
# add addition and subtraction, which imply multiplication/division of
# the underlying physical units
def _add_and_adjust_physical_unit(self, other, sign_self, sign_other):
"""Add/subtract LogUnit to/from another unit, and adjust physical unit.
self and other are multiplied by sign_self and sign_other, resp.
We wish to do: ±lu_1 + ±lu_2 -> lu_f (lu=logarithmic unit)
and pu_1^(±1) * pu_2^(±1) -> pu_f (pu=physical unit)
Raises
------
UnitsError
If function units are not equivalent.
"""
# First, insist on compatible logarithmic type. Here, plain u.mag,
# u.dex, and u.dB are OK, i.e., other does not have to be LogUnit
# (this will indirectly test whether other is a unit at all).
try:
getattr(other, 'function_unit', other)._to(self._function_unit)
except AttributeError:
# if other is not a unit (i.e., does not have _to).
return NotImplemented
except UnitsError:
raise UnitsError("Can only add/subtract logarithmic units of"
"of compatible type.")
other_physical_unit = getattr(other, 'physical_unit',
dimensionless_unscaled)
physical_unit = CompositeUnit(
1, [self._physical_unit, other_physical_unit],
[sign_self, sign_other])
return self._copy(physical_unit)
def __neg__(self):
return self._copy(self.physical_unit**(-1))
def __add__(self, other):
# Only know how to add to a logarithmic unit with compatible type,
# be it a plain one (u.mag, etc.,) or another LogUnit
return self._add_and_adjust_physical_unit(other, +1, +1)
def __radd__(self, other):
return self._add_and_adjust_physical_unit(other, +1, +1)
def __sub__(self, other):
return self._add_and_adjust_physical_unit(other, +1, -1)
def __rsub__(self, other):
# here, in normal usage other cannot be LogUnit; only equivalent one
# would be u.mag,u.dB,u.dex. But might as well use common routine.
return self._add_and_adjust_physical_unit(other, -1, +1)
class MagUnit(LogUnit):
"""Logarithmic physical units expressed in magnitudes
Parameters
----------
physical_unit : `~astropy.units.Unit` or `string`
Unit that is encapsulated within the magnitude function unit.
If not given, dimensionless.
function_unit : `~astropy.units.Unit` or `string`
By default, this is ``mag``, but this allows one to use an equivalent
unit such as ``2 mag``.
"""
@property
def _default_function_unit(self):
return mag
@property
def _quantity_class(self):
return Magnitude
class DexUnit(LogUnit):
"""Logarithmic physical units expressed in magnitudes
Parameters
----------
physical_unit : `~astropy.units.Unit` or `string`
Unit that is encapsulated within the magnitude function unit.
If not given, dimensionless.
function_unit : `~astropy.units.Unit` or `string`
By default, this is ``dex`, but this allows one to use an equivalent
unit such as ``0.5 dex``.
"""
@property
def _default_function_unit(self):
return dex
@property
def _quantity_class(self):
return Dex
class DecibelUnit(LogUnit):
"""Logarithmic physical units expressed in dB
Parameters
----------
physical_unit : `~astropy.units.Unit` or `string`
Unit that is encapsulated within the decibel function unit.
If not given, dimensionless.
function_unit : `~astropy.units.Unit` or `string`
By default, this is ``dB``, but this allows one to use an equivalent
unit such as ``2 dB``.
"""
@property
def _default_function_unit(self):
return dB
@property
def _quantity_class(self):
return Decibel
class LogQuantity(FunctionQuantity):
"""A representation of a (scaled) logarithm of a number with a unit
Parameters
----------
value : number, `~astropy.units.Quantity`, `~astropy.units.function.logarithmic.LogQuantity`, or sequence of convertible items.
The numerical value of the logarithmic quantity. If a number or
a `~astropy.units.Quantity` with a logarithmic unit, it will be
converted to ``unit`` and the physical unit will be inferred from
``unit``. If a `~astropy.units.Quantity` with just a physical unit,
it will converted to the logarithmic unit, after, if necessary,
converting it to the physical unit inferred from ``unit``.
unit : string, `~astropy.units.UnitBase` or `~astropy.units.function.FunctionUnitBase` instance, optional
For an `~astropy.units.function.FunctionUnitBase` instance, the
physical unit will be taken from it; for other input, it will be
inferred from ``value``. By default, ``unit`` is set by the subclass.
dtype : `~numpy.dtype`, optional
The ``dtype`` of the resulting Numpy array or scalar that will
hold the value. If not provided, is is determined automatically
from the input value.
copy : bool, optional
If `True` (default), then the value is copied. Otherwise, a copy will
only be made if ``__array__`` returns a copy, if value is a nested
sequence, or if a copy is needed to satisfy an explicitly given
``dtype``. (The `False` option is intended mostly for internal use,
to speed up initialization where a copy is known to have been made.
Use with care.)
Examples
--------
Typically, use is made of an `~astropy.units.function.FunctionQuantity`
subclass, as in::
>>> import astropy.units as u
>>> u.Magnitude(-2.5)
<Magnitude -2.5 mag>
>>> u.Magnitude(10.*u.count/u.second)
<Magnitude -2.5 mag(ct / s)>
>>> u.Decibel(1.*u.W, u.DecibelUnit(u.mW)) # doctest: +FLOAT_CMP
<Decibel 30. dB(mW)>
"""
# only override of FunctionQuantity
_unit_class = LogUnit
# additions that work just for logarithmic units
def __add__(self, other):
# Add function units, thus multiplying physical units. If no unit is
# given, assume dimensionless_unscaled; this will give the appropriate
# exception in LogUnit.__add__.
new_unit = self.unit + getattr(other, 'unit', dimensionless_unscaled)
# Add actual logarithmic values, rescaling, e.g., dB -> dex.
result = self._function_view + getattr(other, '_function_view', other)
return self._new_view(result, new_unit)
def __radd__(self, other):
return self.__add__(other)
def __iadd__(self, other):
new_unit = self.unit + getattr(other, 'unit', dimensionless_unscaled)
# Do calculation in-place using _function_view of array.
function_view = self._function_view
function_view += getattr(other, '_function_view', other)
self._set_unit(new_unit)
return self
def __sub__(self, other):
# Subtract function units, thus dividing physical units.
new_unit = self.unit - getattr(other, 'unit', dimensionless_unscaled)
# Subtract actual logarithmic values, rescaling, e.g., dB -> dex.
result = self._function_view - getattr(other, '_function_view', other)
return self._new_view(result, new_unit)
def __rsub__(self, other):
new_unit = self.unit.__rsub__(
getattr(other, 'unit', dimensionless_unscaled))
result = self._function_view.__rsub__(
getattr(other, '_function_view', other))
# Ensure the result is in right function unit scale
# (with rsub, this does not have to be one's own).
result = result.to(new_unit.function_unit)
return self._new_view(result, new_unit)
def __isub__(self, other):
new_unit = self.unit - getattr(other, 'unit', dimensionless_unscaled)
# Do calculation in-place using _function_view of array.
function_view = self._function_view
function_view -= getattr(other, '_function_view', other)
self._set_unit(new_unit)
return self
def __pow__(self, other):
# We check if this power is OK by applying it first to the unit.
try:
other = float(other)
except TypeError:
return NotImplemented
new_unit = self.unit ** other
new_value = self.view(np.ndarray) ** other
return self._new_view(new_value, new_unit)
def __ilshift__(self, other):
try:
other = Unit(other)
except UnitTypeError:
return NotImplemented
if not isinstance(other, self._unit_class):
return NotImplemented
try:
factor = self.unit.physical_unit._to(other.physical_unit)
except UnitConversionError:
# Maybe via equivalencies? Now we do make a temporary copy.
try:
value = self._to_value(other)
except UnitConversionError:
return NotImplemented
self.view(np.ndarray)[...] = value
else:
self.view(np.ndarray)[...] += self.unit.from_physical(factor)
self._set_unit(other)
return self
# Could add __mul__ and __div__ and try interpreting other as a power,
# but this seems just too error-prone.
# Methods that do not work for function units generally but are OK for
# logarithmic units as they imply differences and independence of
# physical unit.
def var(self, axis=None, dtype=None, out=None, ddof=0):
return self._wrap_function(np.var, axis, dtype, out=out, ddof=ddof,
unit=self.unit.function_unit**2)
def std(self, axis=None, dtype=None, out=None, ddof=0):
return self._wrap_function(np.std, axis, dtype, out=out, ddof=ddof,
unit=self.unit._copy(dimensionless_unscaled))
def ptp(self, axis=None, out=None):
return self._wrap_function(np.ptp, axis, out=out,
unit=self.unit._copy(dimensionless_unscaled))
def diff(self, n=1, axis=-1):
return self._wrap_function(np.diff, n, axis,
unit=self.unit._copy(dimensionless_unscaled))
def ediff1d(self, to_end=None, to_begin=None):
return self._wrap_function(np.ediff1d, to_end, to_begin,
unit=self.unit._copy(dimensionless_unscaled))
_supported_functions = (FunctionQuantity._supported_functions |
set(getattr(np, function) for function in
('var', 'std', 'ptp', 'diff', 'ediff1d')))
class Dex(LogQuantity):
_unit_class = DexUnit
class Decibel(LogQuantity):
_unit_class = DecibelUnit
class Magnitude(LogQuantity):
_unit_class = MagUnit
dex._function_unit_class = DexUnit
dB._function_unit_class = DecibelUnit
mag._function_unit_class = MagUnit
STmag = MagUnit(photometric.STflux)
STmag.__doc__ = "ST magnitude: STmag=-21.1 corresponds to 1 erg/s/cm2/A"
ABmag = MagUnit(photometric.ABflux)
ABmag.__doc__ = "AB magnitude: ABmag=-48.6 corresponds to 1 erg/s/cm2/Hz"
M_bol = MagUnit(photometric.Bol)
M_bol.__doc__ = ("Absolute bolometric magnitude: M_bol=0 corresponds to "
"L_bol0={0}".format(photometric.Bol.si))
m_bol = MagUnit(photometric.bol)
m_bol.__doc__ = ("Apparent bolometric magnitude: m_bol=0 corresponds to "
"f_bol0={0}".format(photometric.bol.si))
|
c832903d61481ae45b9abcac932faaf5d65223dcbe835aec7064f19f21346201 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Function Units and Quantities."""
from abc import ABCMeta, abstractmethod
import numpy as np
from astropy.units import (Unit, UnitBase, UnitsError, UnitTypeError, UnitConversionError,
dimensionless_unscaled, Quantity)
__all__ = ['FunctionUnitBase', 'FunctionQuantity']
SUPPORTED_UFUNCS = set(getattr(np.core.umath, ufunc) for ufunc in (
'isfinite', 'isinf', 'isnan', 'sign', 'signbit',
'rint', 'floor', 'ceil', 'trunc',
'_ones_like', 'ones_like', 'positive') if hasattr(np.core.umath, ufunc))
# TODO: the following could work if helper changed relative to Quantity:
# - spacing should return dimensionless, not same unit
# - negative should negate unit too,
# - add, subtract, comparisons can work if units added/subtracted
SUPPORTED_FUNCTIONS = set(getattr(np, function) for function in
('clip', 'trace', 'mean', 'min', 'max', 'round'))
# subclassing UnitBase or CompositeUnit was found to be problematic, requiring
# a large number of overrides. Hence, define new class.
class FunctionUnitBase(metaclass=ABCMeta):
"""Abstract base class for function units.
Function units are functions containing a physical unit, such as dB(mW).
Most of the arithmetic operations on function units are defined in this
base class.
While instantiation is defined, this class should not be used directly.
Rather, subclasses should be used that override the abstract properties
`_default_function_unit` and `_quantity_class`, and the abstract methods
`from_physical`, and `to_physical`.
Parameters
----------
physical_unit : `~astropy.units.Unit` or `string`
Unit that is encapsulated within the function unit.
If not given, dimensionless.
function_unit : `~astropy.units.Unit` or `string`
By default, the same as the function unit set by the subclass.
"""
# ↓↓↓ the following four need to be set by subclasses
# Make this a property so we can ensure subclasses define it.
@property
@abstractmethod
def _default_function_unit(self):
"""Default function unit corresponding to the function.
This property should be overridden by subclasses, with, e.g.,
`~astropy.unit.MagUnit` returning `~astropy.unit.mag`.
"""
# This has to be a property because the function quantity will not be
# known at unit definition time, as it gets defined after.
@property
@abstractmethod
def _quantity_class(self):
"""Function quantity class corresponding to this function unit.
This property should be overridden by subclasses, with, e.g.,
`~astropy.unit.MagUnit` returning `~astropy.unit.Magnitude`.
"""
@abstractmethod
def from_physical(self, x):
"""Transformation from value in physical to value in function units.
This method should be overridden by subclasses. It is used to
provide automatic transformations using an equivalency.
"""
@abstractmethod
def to_physical(self, x):
"""Transformation from value in function to value in physical units.
This method should be overridden by subclasses. It is used to
provide automatic transformations using an equivalency.
"""
# ↑↑↑ the above four need to be set by subclasses
# have priority over arrays, regular units, and regular quantities
__array_priority__ = 30000
def __init__(self, physical_unit=None, function_unit=None):
if physical_unit is None:
self._physical_unit = dimensionless_unscaled
else:
self._physical_unit = Unit(physical_unit)
if (not isinstance(self._physical_unit, UnitBase) or
self._physical_unit.is_equivalent(
self._default_function_unit)):
raise UnitConversionError("Unit {0} is not a physical unit."
.format(self._physical_unit))
if function_unit is None:
self._function_unit = self._default_function_unit
else:
# any function unit should be equivalent to subclass default
function_unit = Unit(getattr(function_unit, 'function_unit',
function_unit))
if function_unit.is_equivalent(self._default_function_unit):
self._function_unit = function_unit
else:
raise UnitConversionError(
"Cannot initialize '{0}' instance with function unit '{1}'"
", as it is not equivalent to default function unit '{2}'."
.format(self.__class__.__name__, function_unit,
self._default_function_unit))
def _copy(self, physical_unit=None):
"""Copy oneself, possibly with a different physical unit."""
if physical_unit is None:
physical_unit = self.physical_unit
return self.__class__(physical_unit, self.function_unit)
@property
def physical_unit(self):
return self._physical_unit
@property
def function_unit(self):
return self._function_unit
@property
def equivalencies(self):
"""List of equivalencies between function and physical units.
Uses the `from_physical` and `to_physical` methods.
"""
return [(self, self.physical_unit,
self.to_physical, self.from_physical)]
# ↓↓↓ properties/methods required to behave like a unit
def decompose(self, bases=set()):
"""Copy the current unit with the physical unit decomposed.
For details, see `~astropy.units.UnitBase.decompose`.
"""
return self._copy(self.physical_unit.decompose(bases))
@property
def si(self):
"""Copy the current function unit with the physical unit in SI."""
return self._copy(self.physical_unit.si)
@property
def cgs(self):
"""Copy the current function unit with the physical unit in CGS."""
return self._copy(self.physical_unit.cgs)
def _get_physical_type_id(self):
"""Get physical type corresponding to physical unit."""
return self.physical_unit._get_physical_type_id()
@property
def physical_type(self):
"""Return the physical type of the physical unit (e.g., 'length')."""
return self.physical_unit.physical_type
def is_equivalent(self, other, equivalencies=[]):
"""
Returns `True` if this unit is equivalent to ``other``.
Parameters
----------
other : unit object or string or tuple
The unit to convert to. If a tuple of units is specified, this
method returns true if the unit matches any of those in the tuple.
equivalencies : list of equivalence pairs, optional
A list of equivalence pairs to try if the units are not
directly convertible. See :ref:`unit_equivalencies`.
This list is in addition to the built-in equivalencies between the
function unit and the physical one, as well as possible global
defaults set by, e.g., `~astropy.units.set_enabled_equivalencies`.
Use `None` to turn off any global equivalencies.
Returns
-------
bool
"""
if isinstance(other, tuple):
return any(self.is_equivalent(u, equivalencies=equivalencies)
for u in other)
other_physical_unit = getattr(other, 'physical_unit', (
dimensionless_unscaled if self.function_unit.is_equivalent(other)
else other))
return self.physical_unit.is_equivalent(other_physical_unit,
equivalencies)
def to(self, other, value=1., equivalencies=[]):
"""
Return the converted values in the specified unit.
Parameters
----------
other : `~astropy.units.Unit` object, `~astropy.units.function.FunctionUnitBase` object or string
The unit to convert to.
value : scalar int or float, or sequence convertible to array, optional
Value(s) in the current unit to be converted to the specified unit.
If not provided, defaults to 1.0.
equivalencies : list of equivalence pairs, optional
A list of equivalence pairs to try if the units are not
directly convertible. See :ref:`unit_equivalencies`.
This list is in meant to treat only equivalencies between different
physical units; the build-in equivalency between the function
unit and the physical one is automatically taken into account.
Returns
-------
values : scalar or array
Converted value(s). Input value sequences are returned as
numpy arrays.
Raises
------
UnitsError
If units are inconsistent.
"""
# conversion to one's own physical unit should be fastest
if other is self.physical_unit:
return self.to_physical(value)
other_function_unit = getattr(other, 'function_unit', other)
if self.function_unit.is_equivalent(other_function_unit):
# when other is an equivalent function unit:
# first convert physical units to other's physical units
other_physical_unit = getattr(other, 'physical_unit',
dimensionless_unscaled)
if self.physical_unit != other_physical_unit:
value_other_physical = self.physical_unit.to(
other_physical_unit, self.to_physical(value),
equivalencies)
# make function unit again, in own system
value = self.from_physical(value_other_physical)
# convert possible difference in function unit (e.g., dex->dB)
return self.function_unit.to(other_function_unit, value)
else:
try:
# when other is not a function unit
return self.physical_unit.to(other, self.to_physical(value),
equivalencies)
except UnitConversionError as e:
if self.function_unit == Unit('mag'):
# One can get to raw magnitudes via math that strips the dimensions off.
# Include extra information in the exception to remind users of this.
msg = "Did you perhaps subtract magnitudes so the unit got lost?"
e.args += (msg,)
raise e
else:
raise
def is_unity(self):
return False
def __eq__(self, other):
return (self.physical_unit == getattr(other, 'physical_unit',
dimensionless_unscaled) and
self.function_unit == getattr(other, 'function_unit', other))
def __ne__(self, other):
return not self.__eq__(other)
def __rlshift__(self, other):
"""Unit converstion operator ``<<``"""
try:
return self._quantity_class(other, self, copy=False, subok=True)
except Exception:
return NotImplemented
def __mul__(self, other):
if isinstance(other, (str, UnitBase, FunctionUnitBase)):
if self.physical_unit == dimensionless_unscaled:
# If dimensionless, drop back to normal unit and retry.
return self.function_unit * other
else:
raise UnitsError("Cannot multiply a function unit "
"with a physical dimension with any unit.")
else:
# Anything not like a unit, try initialising as a function quantity.
try:
return self._quantity_class(other, unit=self)
except Exception:
return NotImplemented
def __rmul__(self, other):
return self.__mul__(other)
def __div__(self, other):
if isinstance(other, (str, UnitBase, FunctionUnitBase)):
if self.physical_unit == dimensionless_unscaled:
# If dimensionless, drop back to normal unit and retry.
return self.function_unit / other
else:
raise UnitsError("Cannot divide a function unit "
"with a physical dimension by any unit.")
else:
# Anything not like a unit, try initialising as a function quantity.
try:
return self._quantity_class(1./other, unit=self)
except Exception:
return NotImplemented
def __rdiv__(self, other):
if isinstance(other, (str, UnitBase, FunctionUnitBase)):
if self.physical_unit == dimensionless_unscaled:
# If dimensionless, drop back to normal unit and retry.
return other / self.function_unit
else:
raise UnitsError("Cannot divide a function unit "
"with a physical dimension into any unit")
else:
# Don't know what to do with anything not like a unit.
return NotImplemented
__truediv__ = __div__
__rtruediv__ = __rdiv__
def __pow__(self, power):
if power == 0:
return dimensionless_unscaled
elif power == 1:
return self._copy()
if self.physical_unit == dimensionless_unscaled:
return self.function_unit ** power
raise UnitsError("Cannot raise a function unit "
"with a physical dimension to any power but 0 or 1.")
def __pos__(self):
return self._copy()
def to_string(self, format='generic'):
"""
Output the unit in the given format as a string.
The physical unit is appended, within parentheses, to the function
unit, as in "dB(mW)", with both units set using the given format
Parameters
----------
format : `astropy.units.format.Base` instance or str
The name of a format or a formatter object. If not
provided, defaults to the generic format.
"""
if format not in ('generic', 'unscaled', 'latex'):
raise ValueError("Function units cannot be written in {0} format. "
"Only 'generic', 'unscaled' and 'latex' are "
"supported.".format(format))
self_str = self.function_unit.to_string(format)
pu_str = self.physical_unit.to_string(format)
if pu_str == '':
pu_str = '1'
if format == 'latex':
self_str += r'$\mathrm{{\left( {0} \right)}}$'.format(
pu_str[1:-1]) # need to strip leading and trailing "$"
else:
self_str += '({0})'.format(pu_str)
return self_str
def __str__(self):
"""Return string representation for unit."""
self_str = str(self.function_unit)
pu_str = str(self.physical_unit)
if pu_str:
self_str += '({0})'.format(pu_str)
return self_str
def __repr__(self):
# By default, try to give a representation using `Unit(<string>)`,
# with string such that parsing it would give the correct FunctionUnit.
if callable(self.function_unit):
return 'Unit("{0}")'.format(self.to_string())
else:
return '{0}("{1}"{2})'.format(
self.__class__.__name__, self.physical_unit,
"" if self.function_unit is self._default_function_unit
else ', unit="{0}"'.format(self.function_unit))
def _repr_latex_(self):
"""
Generate latex representation of unit name. This is used by
the IPython notebook to print a unit with a nice layout.
Returns
-------
Latex string
"""
return self.to_string('latex')
def __hash__(self):
return hash((self.function_unit, self.physical_unit))
class FunctionQuantity(Quantity):
"""A representation of a (scaled) function of a number with a unit.
Function quantities are quantities whose units are functions containing a
physical unit, such as dB(mW). Most of the arithmetic operations on
function quantities are defined in this base class.
While instantiation is also defined here, this class should not be
instantiated directly. Rather, subclasses should be made which have
``_unit_class`` pointing back to the corresponding function unit class.
Parameters
----------
value : number, sequence of convertible items, `~astropy.units.Quantity`, or `~astropy.units.function.FunctionQuantity`
The numerical value of the function quantity. If a number or
a `~astropy.units.Quantity` with a function unit, it will be converted
to ``unit`` and the physical unit will be inferred from ``unit``.
If a `~astropy.units.Quantity` with just a physical unit, it will
converted to the function unit, after, if necessary, converting it to
the physical unit inferred from ``unit``.
unit : string, `~astropy.units.UnitBase` or `~astropy.units.function.FunctionUnitBase` instance, optional
For an `~astropy.units.function.FunctionUnitBase` instance, the
physical unit will be taken from it; for other input, it will be
inferred from ``value``. By default, ``unit`` is set by the subclass.
dtype : `~numpy.dtype`, optional
The dtype of the resulting Numpy array or scalar that will
hold the value. If not provided, it is determined from the input,
except that any input that cannot represent float (integer and bool)
is converted to float.
copy : bool, optional
If `True` (default), then the value is copied. Otherwise, a copy will
only be made if ``__array__`` returns a copy, if value is a nested
sequence, or if a copy is needed to satisfy an explicitly given
``dtype``. (The `False` option is intended mostly for internal use,
to speed up initialization where a copy is known to have been made.
Use with care.)
order : {'C', 'F', 'A'}, optional
Specify the order of the array. As in `~numpy.array`. Ignored
if the input does not need to be converted and ``copy=False``.
subok : bool, optional
If `False` (default), the returned array will be forced to be of the
class used. Otherwise, subclasses will be passed through.
ndmin : int, optional
Specifies the minimum number of dimensions that the resulting array
should have. Ones will be pre-pended to the shape as needed to meet
this requirement. This parameter is ignored if the input is a
`~astropy.units.Quantity` and ``copy=False``.
Raises
------
TypeError
If the value provided is not a Python numeric type.
TypeError
If the unit provided is not a `~astropy.units.function.FunctionUnitBase`
or `~astropy.units.Unit` object, or a parseable string unit.
"""
_unit_class = None
"""Default `~astropy.units.function.FunctionUnitBase` subclass.
This should be overridden by subclasses.
"""
# Ensure priority over ndarray, regular Unit & Quantity, and FunctionUnit.
__array_priority__ = 40000
# Define functions that work on FunctionQuantity.
_supported_ufuncs = SUPPORTED_UFUNCS
_supported_functions = SUPPORTED_FUNCTIONS
def __new__(cls, value, unit=None, dtype=None, copy=True, order=None,
subok=False, ndmin=0):
if unit is not None:
# Convert possible string input to a (function) unit.
unit = Unit(unit)
if not isinstance(unit, FunctionUnitBase):
# By default, use value's physical unit.
value_unit = getattr(value, 'unit', None)
if value_unit is None:
# if iterable, see if first item has a unit
# (mixed lists fail in super call below).
try:
value_unit = getattr(value[0], 'unit')
except Exception:
pass
physical_unit = getattr(value_unit, 'physical_unit', value_unit)
unit = cls._unit_class(physical_unit, function_unit=unit)
# initialise!
return super().__new__(cls, value, unit, dtype=dtype, copy=copy,
order=order, subok=subok, ndmin=ndmin)
# ↓↓↓ properties not found in Quantity
@property
def physical(self):
"""The physical quantity corresponding the function one."""
return self.to(self.unit.physical_unit)
@property
def _function_view(self):
"""View as Quantity with function unit, dropping the physical unit.
Use `~astropy.units.quantity.Quantity.value` for just the value.
"""
return self._new_view(unit=self.unit.function_unit)
# ↓↓↓ methods overridden to change the behavior
@property
def si(self):
"""Return a copy with the physical unit in SI units."""
return self.__class__(self.physical.si)
@property
def cgs(self):
"""Return a copy with the physical unit in CGS units."""
return self.__class__(self.physical.cgs)
def decompose(self, bases=[]):
"""Generate a new `FunctionQuantity` with the physical unit decomposed.
For details, see `~astropy.units.Quantity.decompose`.
"""
return self.__class__(self.physical.decompose(bases))
# ↓↓↓ methods overridden to add additional behavior
def __quantity_subclass__(self, unit):
if isinstance(unit, FunctionUnitBase):
return self.__class__, True
else:
return super().__quantity_subclass__(unit)[0], False
def _set_unit(self, unit):
if not isinstance(unit, self._unit_class):
# Have to take care of, e.g., (10*u.mag).view(u.Magnitude)
try:
# "or 'nonsense'" ensures `None` breaks, just in case.
unit = self._unit_class(function_unit=unit or 'nonsense')
except Exception:
raise UnitTypeError(
"{0} instances require {1} function units"
.format(type(self).__name__, self._unit_class.__name__) +
", so cannot set it to '{0}'.".format(unit))
self._unit = unit
def __array_ufunc__(self, function, method, *inputs, **kwargs):
# TODO: it would be more logical to have this in Quantity already,
# instead of in UFUNC_HELPERS, where it cannot be overridden.
# And really it should just return NotImplemented, since possibly
# another argument might know what to do.
if function not in self._supported_ufuncs:
raise UnitTypeError(
"Cannot use ufunc '{0}' with function quantities"
.format(function.__name__))
return super().__array_ufunc__(function, method, *inputs, **kwargs)
# ↓↓↓ methods overridden to change behavior
def __mul__(self, other):
if self.unit.physical_unit == dimensionless_unscaled:
return self._function_view * other
raise UnitTypeError("Cannot multiply function quantities which "
"are not dimensionless with anything.")
def __truediv__(self, other):
if self.unit.physical_unit == dimensionless_unscaled:
return self._function_view / other
raise UnitTypeError("Cannot divide function quantities which "
"are not dimensionless by anything.")
def __rtruediv__(self, other):
if self.unit.physical_unit == dimensionless_unscaled:
return self._function_view.__rdiv__(other)
raise UnitTypeError("Cannot divide function quantities which "
"are not dimensionless into anything.")
def _comparison(self, other, comparison_func):
"""Do a comparison between self and other, raising UnitsError when
other cannot be converted to self because it has different physical
unit, and returning NotImplemented when there are other errors."""
try:
# will raise a UnitsError if physical units not equivalent
other_in_own_unit = self._to_own_unit(other, check_precision=False)
except UnitsError as exc:
if self.unit.physical_unit != dimensionless_unscaled:
raise exc
try:
other_in_own_unit = self._function_view._to_own_unit(
other, check_precision=False)
except Exception:
raise exc
except Exception:
return NotImplemented
return comparison_func(other_in_own_unit)
def __eq__(self, other):
try:
return self._comparison(other, self.value.__eq__)
except UnitsError:
return False
def __ne__(self, other):
try:
return self._comparison(other, self.value.__ne__)
except UnitsError:
return True
def __gt__(self, other):
return self._comparison(other, self.value.__gt__)
def __ge__(self, other):
return self._comparison(other, self.value.__ge__)
def __lt__(self, other):
return self._comparison(other, self.value.__lt__)
def __le__(self, other):
return self._comparison(other, self.value.__le__)
def __lshift__(self, other):
"""Unit converstion operator `<<`"""
try:
other = Unit(other, parse_strict='silent')
except UnitTypeError:
return NotImplemented
return self.__class__(self, other, copy=False, subok=True)
# Ensure Quantity methods are used only if they make sense.
def _wrap_function(self, function, *args, **kwargs):
if function in self._supported_functions:
return super()._wrap_function(function, *args, **kwargs)
# For dimensionless, we can convert to regular quantities.
if all(arg.unit.physical_unit == dimensionless_unscaled
for arg in (self,) + args
if (hasattr(arg, 'unit') and
hasattr(arg.unit, 'physical_unit'))):
args = tuple(getattr(arg, '_function_view', arg) for arg in args)
return self._function_view._wrap_function(function, *args, **kwargs)
raise TypeError("Cannot use method that uses function '{0}' with "
"function quantities that are not dimensionless."
.format(function.__name__))
# Override functions that are supported but do not use _wrap_function
# in Quantity.
def max(self, axis=None, out=None, keepdims=False):
return self._wrap_function(np.max, axis, out=out, keepdims=keepdims)
def min(self, axis=None, out=None, keepdims=False):
return self._wrap_function(np.min, axis, out=out, keepdims=keepdims)
def sum(self, axis=None, dtype=None, out=None, keepdims=False):
return self._wrap_function(np.sum, axis, dtype, out=out,
keepdims=keepdims)
def cumsum(self, axis=None, dtype=None, out=None):
return self._wrap_function(np.cumsum, axis, dtype, out=out)
|
01063464a7202fe5ed95b84fa435596940388cb98b0bcda9e15bc86173900b3e | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
This module has been deprecated and moved to astropy.units.photometric. The
names remain here for backwards compatibility.
"""
from warnings import warn
from astropy.units.photometric import AB, ST
from astropy.utils import deprecated
_ns = globals()
@deprecated(since='3.1', alternative='astropy.units.photometric',
message='The magnitude_zero_points module has been deprecated, and'
' moved to astropy.units.photometric and are enabled by '
'default. magnitude_zero_points is retained as aliases to '
'the new units.')
def enable():
"""
Enable magnitude zero point units so they appear in results of
`~astropy.units.UnitBase.find_equivalent_units` and
`~astropy.units.UnitBase.compose`.
This may be used with the ``with`` statement to enable these
units only temporarily.
"""
# While it may seem like the below can be removed, in fact it needs to
# remain as long as this function is around so that enable acts as a context
# manager
# Local import to avoid cyclical import
from astropy.units.core import add_enabled_units
# Local import to avoid polluting namespace
import inspect
return add_enabled_units(inspect.getmodule(enable))
|
0f863d73de37e1cff52822fa4bc83301cb7cf45429862f74d83f4b008394e71e | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import warnings
import numpy as np
from astropy import units as u
from astropy.utils.decorators import format_doc
from astropy.utils.exceptions import AstropyDeprecationWarning
from astropy.coordinates.angles import Angle
from astropy.coordinates.matrix_utilities import rotation_matrix, matrix_product, matrix_transpose
from astropy.coordinates import representation as r
from astropy.coordinates.baseframe import (BaseCoordinateFrame, frame_transform_graph,
RepresentationMapping, base_doc)
from astropy.coordinates.attributes import (Attribute, CoordinateAttribute,
QuantityAttribute,
DifferentialAttribute)
from astropy.coordinates.transformations import AffineTransform
from astropy.coordinates.errors import ConvertError
from .icrs import ICRS
__all__ = ['Galactocentric']
# Measured by minimizing the difference between a plane of coordinates along
# l=0, b=[-90,90] and the Galactocentric x-z plane
# This is not used directly, but accessed via `get_roll0`. We define it here to
# prevent having to create new Angle objects every time `get_roll0` is called.
_ROLL0 = Angle(58.5986320306*u.degree)
doc_components = """
x : `~astropy.units.Quantity`, optional
Cartesian, Galactocentric :math:`x` position component.
y : `~astropy.units.Quantity`, optional
Cartesian, Galactocentric :math:`y` position component.
z : `~astropy.units.Quantity`, optional
Cartesian, Galactocentric :math:`z` position component.
v_x : `~astropy.units.Quantity`, optional
Cartesian, Galactocentric :math:`v_x` velocity component.
v_y : `~astropy.units.Quantity`, optional
Cartesian, Galactocentric :math:`v_y` velocity component.
v_z : `~astropy.units.Quantity`, optional
Cartesian, Galactocentric :math:`v_z` velocity component.
"""
doc_footer = """
Other parameters
----------------
galcen_coord : `ICRS`, optional, must be keyword
The ICRS coordinates of the Galactic center.
galcen_distance : `~astropy.units.Quantity`, optional, must be keyword
The distance from the sun to the Galactic center.
galcen_v_sun : `~astropy.coordinates.representation.CartesianDifferential`, optional, must be keyword
The velocity of the sun *in the Galactocentric frame* as Cartesian
velocity components.
z_sun : `~astropy.units.Quantity`, optional, must be keyword
The distance from the sun to the Galactic midplane.
roll : `Angle`, optional, must be keyword
The angle to rotate about the final x-axis, relative to the
orientation for Galactic. For example, if this roll angle is 0,
the final x-z plane will align with the Galactic coordinates x-z
plane. Unless you really know what this means, you probably should
not change this!
Examples
--------
To transform to the Galactocentric frame with the default
frame attributes, pass the uninstantiated class name to the
``transform_to()`` method of a coordinate frame or
`~astropy.coordinates.SkyCoord` object::
>>> import astropy.units as u
>>> import astropy.coordinates as coord
>>> c = coord.ICRS(ra=[158.3122, 24.5] * u.degree,
... dec=[-17.3, 81.52] * u.degree,
... distance=[11.5, 24.12] * u.kpc)
>>> c.transform_to(coord.Galactocentric) # doctest: +FLOAT_CMP
<Galactocentric Coordinate (galcen_coord=<ICRS Coordinate: (ra, dec) in deg
( 266.4051, -28.936175)>, galcen_distance=8.3 kpc, galcen_v_sun=( 11.1, 232.24, 7.25) km / s, z_sun=27.0 pc, roll=0.0 deg): (x, y, z) in kpc
[( -9.6083819 , -9.40062188, 6.52056066),
(-21.28302307, 18.76334013, 7.84693855)]>
To specify a custom set of parameters, you have to include extra keyword
arguments when initializing the Galactocentric frame object::
>>> c.transform_to(coord.Galactocentric(galcen_distance=8.1*u.kpc)) # doctest: +FLOAT_CMP
<Galactocentric Coordinate (galcen_coord=<ICRS Coordinate: (ra, dec) in deg
( 266.4051, -28.936175)>, galcen_distance=8.1 kpc, galcen_v_sun=( 11.1, 232.24, 7.25) km / s, z_sun=27.0 pc, roll=0.0 deg): (x, y, z) in kpc
[( -9.40785924, -9.40062188, 6.52066574),
(-21.08239383, 18.76334013, 7.84798135)]>
Similarly, transforming from the Galactocentric frame to another coordinate frame::
>>> c = coord.Galactocentric(x=[-8.3, 4.5] * u.kpc,
... y=[0., 81.52] * u.kpc,
... z=[0.027, 24.12] * u.kpc)
>>> c.transform_to(coord.ICRS) # doctest: +FLOAT_CMP
<ICRS Coordinate: (ra, dec, distance) in (deg, deg, kpc)
[( 86.22349059, 28.83894138, 4.39157788e-05),
( 289.66802652, 49.88763881, 8.59640735e+01)]>
Or, with custom specification of the Galactic center::
>>> c = coord.Galactocentric(x=[-8.0, 4.5] * u.kpc,
... y=[0., 81.52] * u.kpc,
... z=[21.0, 24120.0] * u.pc,
... z_sun=21 * u.pc, galcen_distance=8. * u.kpc)
>>> c.transform_to(coord.ICRS) # doctest: +FLOAT_CMP
<ICRS Coordinate: (ra, dec, distance) in (deg, deg, kpc)
[( 86.2585249 , 28.85773187, 2.75625475e-05),
( 289.77285255, 50.06290457, 8.59216010e+01)]>
"""
@format_doc(base_doc, components=doc_components, footer=doc_footer)
class Galactocentric(BaseCoordinateFrame):
r"""
A coordinate or frame in the Galactocentric system. This frame
requires specifying the Sun-Galactic center distance, and optionally
the height of the Sun above the Galactic midplane.
The position of the Sun is assumed to be on the x axis of the final,
right-handed system. That is, the x axis points from the position of
the Sun projected to the Galactic midplane to the Galactic center --
roughly towards :math:`(l,b) = (0^\circ,0^\circ)`. For the default
transformation (:math:`{\rm roll}=0^\circ`), the y axis points roughly
towards Galactic longitude :math:`l=90^\circ`, and the z axis points
roughly towards the North Galactic Pole (:math:`b=90^\circ`).
The default position of the Galactic Center in ICRS coordinates is
taken from Reid et al. 2004,
http://adsabs.harvard.edu/abs/2004ApJ...616..872R.
.. math::
{\rm RA} = 17:45:37.224~{\rm hr}\\
{\rm Dec} = -28:56:10.23~{\rm deg}
The default distance to the Galactic Center is 8.3 kpc, e.g.,
Gillessen et al. (2009),
https://ui.adsabs.harvard.edu/#abs/2009ApJ...692.1075G/abstract
The default height of the Sun above the Galactic midplane is taken to
be 27 pc, as measured by Chen et al. (2001),
https://ui.adsabs.harvard.edu/#abs/2001ApJ...553..184C/abstract
The default solar motion relative to the Galactic center is taken from a
combination of Schönrich et al. (2010) [for the peculiar velocity] and
Bovy (2015) [for the circular velocity at the solar radius],
https://ui.adsabs.harvard.edu/#abs/2010MNRAS.403.1829S/abstract
https://ui.adsabs.harvard.edu/#abs/2015ApJS..216...29B/abstract
For a more detailed look at the math behind this transformation, see
the document :ref:`coordinates-galactocentric`.
The frame attributes are listed under **Other Parameters**.
"""
default_representation = r.CartesianRepresentation
default_differential = r.CartesianDifferential
# frame attributes
galcen_coord = CoordinateAttribute(default=ICRS(ra=266.4051*u.degree,
dec=-28.936175*u.degree),
frame=ICRS)
galcen_distance = QuantityAttribute(default=8.3*u.kpc)
galcen_v_sun = DifferentialAttribute(
default=r.CartesianDifferential([11.1, 220+12.24, 7.25] * u.km/u.s),
allowed_classes=[r.CartesianDifferential])
z_sun = QuantityAttribute(default=27.*u.pc)
roll = QuantityAttribute(default=0.*u.deg)
def __init__(self, *args, **kwargs):
# backwards-compatibility
if ('galcen_ra' in kwargs or 'galcen_dec' in kwargs):
warnings.warn("The arguments 'galcen_ra', and 'galcen_dec' are "
"deprecated in favor of specifying the sky coordinate"
" as a CoordinateAttribute using the 'galcen_coord' "
"argument", AstropyDeprecationWarning)
galcen_kw = dict()
galcen_kw['ra'] = kwargs.pop('galcen_ra', self.galcen_coord.ra)
galcen_kw['dec'] = kwargs.pop('galcen_dec', self.galcen_coord.dec)
kwargs['galcen_coord'] = ICRS(**galcen_kw)
super().__init__(*args, **kwargs)
@property
def galcen_ra(self):
warnings.warn("The attribute 'galcen_ra' is deprecated. Use "
"'.galcen_coord.ra' instead.", AstropyDeprecationWarning)
return self.galcen_coord.ra
@property
def galcen_dec(self):
warnings.warn("The attribute 'galcen_dec' is deprecated. Use "
"'.galcen_coord.dec' instead.", AstropyDeprecationWarning)
return self.galcen_coord.dec
@classmethod
def get_roll0(cls):
"""
The additional roll angle (about the final x axis) necessary to align
the final z axis to match the Galactic yz-plane. Setting the ``roll``
frame attribute to -this method's return value removes this rotation,
allowing the use of the `Galactocentric` frame in more general contexts.
"""
# note that the actual value is defined at the module level. We make at
# a property here because this module isn't actually part of the public
# API, so it's better for it to be accessable from Galactocentric
return _ROLL0
# ICRS to/from Galactocentric ----------------------->
def get_matrix_vectors(galactocentric_frame, inverse=False):
"""
Use the ``inverse`` argument to get the inverse transformation, matrix and
offsets to go from Galactocentric to ICRS.
"""
# shorthand
gcf = galactocentric_frame
# rotation matrix to align x(ICRS) with the vector to the Galactic center
mat1 = rotation_matrix(-gcf.galcen_coord.dec, 'y')
mat2 = rotation_matrix(gcf.galcen_coord.ra, 'z')
# extra roll away from the Galactic x-z plane
mat0 = rotation_matrix(gcf.get_roll0() - gcf.roll, 'x')
# construct transformation matrix and use it
R = matrix_product(mat0, mat1, mat2)
# Now need to translate by Sun-Galactic center distance around x' and
# rotate about y' to account for tilt due to Sun's height above the plane
translation = r.CartesianRepresentation(gcf.galcen_distance * [1., 0., 0.])
z_d = gcf.z_sun / gcf.galcen_distance
H = rotation_matrix(-np.arcsin(z_d), 'y')
# compute total matrices
A = matrix_product(H, R)
# Now we re-align the translation vector to account for the Sun's height
# above the midplane
offset = -translation.transform(H)
if inverse:
# the inverse of a rotation matrix is a transpose, which is much faster
# and more stable to compute
A = matrix_transpose(A)
offset = (-offset).transform(A)
offset_v = r.CartesianDifferential.from_cartesian(
(-gcf.galcen_v_sun).to_cartesian().transform(A))
offset = offset.with_differentials(offset_v)
else:
offset = offset.with_differentials(gcf.galcen_v_sun)
return A, offset
def _check_coord_repr_diff_types(c):
if isinstance(c.data, r.UnitSphericalRepresentation):
raise ConvertError("Transforming to/from a Galactocentric frame "
"requires a 3D coordinate, e.g. (angle, angle, "
"distance) or (x, y, z).")
if ('s' in c.data.differentials and
isinstance(c.data.differentials['s'],
(r.UnitSphericalDifferential,
r.UnitSphericalCosLatDifferential,
r.RadialDifferential))):
raise ConvertError("Transforming to/from a Galactocentric frame "
"requires a 3D velocity, e.g., proper motion "
"components and radial velocity.")
@frame_transform_graph.transform(AffineTransform, ICRS, Galactocentric)
def icrs_to_galactocentric(icrs_coord, galactocentric_frame):
_check_coord_repr_diff_types(icrs_coord)
return get_matrix_vectors(galactocentric_frame)
@frame_transform_graph.transform(AffineTransform, Galactocentric, ICRS)
def galactocentric_to_icrs(galactocentric_coord, icrs_frame):
_check_coord_repr_diff_types(galactocentric_coord)
return get_matrix_vectors(galactocentric_coord, inverse=True)
|
c7b72be6ab0279bf6186ccd374031edcc5a581f2c99da041bc7239b0434f64aa | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from astropy.coordinates.matrix_utilities import (rotation_matrix,
matrix_product, matrix_transpose)
from astropy.coordinates.baseframe import frame_transform_graph
from astropy.coordinates.transformations import StaticMatrixTransform
from .galactic import Galactic
from .supergalactic import Supergalactic
@frame_transform_graph.transform(StaticMatrixTransform, Galactic, Supergalactic)
def gal_to_supergal():
mat1 = rotation_matrix(90, 'z')
mat2 = rotation_matrix(90 - Supergalactic._nsgp_gal.b.degree, 'y')
mat3 = rotation_matrix(Supergalactic._nsgp_gal.l.degree, 'z')
return matrix_product(mat1, mat2, mat3)
@frame_transform_graph.transform(StaticMatrixTransform, Supergalactic, Galactic)
def supergal_to_gal():
return matrix_transpose(gal_to_supergal())
|
530ee94fda68be1ca7227469504b524bf9e80077c2b4095a24a7f6a4b2cb7c9b | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from astropy.utils.decorators import format_doc
from astropy.coordinates.baseframe import frame_transform_graph, base_doc
from astropy.coordinates.attributes import TimeAttribute
from astropy.coordinates.transformations import DynamicMatrixTransform
from astropy.coordinates import earth_orientation as earth
from .baseradec import BaseRADecFrame, doc_components
from .utils import EQUINOX_J2000
__all__ = ['FK5']
doc_footer = """
Other parameters
----------------
equinox : `~astropy.time.Time`
The equinox of this frame.
"""
@format_doc(base_doc, components=doc_components, footer=doc_footer)
class FK5(BaseRADecFrame):
"""
A coordinate or frame in the FK5 system.
Note that this is a barycentric version of FK5 - that is, the origin for
this frame is the Solar System Barycenter, *not* the Earth geocenter.
The frame attributes are listed under **Other Parameters**.
"""
equinox = TimeAttribute(default=EQUINOX_J2000)
@staticmethod
def _precession_matrix(oldequinox, newequinox):
"""
Compute and return the precession matrix for FK5 based on Capitaine et
al. 2003/IAU2006. Used inside some of the transformation functions.
Parameters
----------
oldequinox : `~astropy.time.Time`
The equinox to precess from.
newequinox : `~astropy.time.Time`
The equinox to precess to.
Returns
-------
newcoord : array
The precession matrix to transform to the new equinox
"""
return earth.precession_matrix_Capitaine(oldequinox, newequinox)
# This is the "self-transform". Defined at module level because the decorator
# needs a reference to the FK5 class
@frame_transform_graph.transform(DynamicMatrixTransform, FK5, FK5)
def fk5_to_fk5(fk5coord1, fk5frame2):
return fk5coord1._precession_matrix(fk5coord1.equinox, fk5frame2.equinox)
|
65c3490f78eabee2bbef3f8cebc41412aa96118b38690e99872a8867706cfc3c | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Contains the transformation functions for getting to/from ITRS, GCRS, and CIRS.
These are distinct from the ICRS and AltAz functions because they are just
rotations without aberration corrections or offsets.
"""
import numpy as np
from astropy.coordinates.baseframe import frame_transform_graph
from astropy.coordinates.transformations import FunctionTransformWithFiniteDifference
from astropy.coordinates.matrix_utilities import matrix_transpose
from astropy import _erfa as erfa
from .gcrs import GCRS, PrecessedGeocentric
from .cirs import CIRS
from .itrs import ITRS
from .utils import get_polar_motion, get_jd12
# # first define helper functions
def gcrs_to_cirs_mat(time):
# celestial-to-intermediate matrix
return erfa.c2i06a(*get_jd12(time, 'tt'))
def cirs_to_itrs_mat(time):
# compute the polar motion p-matrix
xp, yp = get_polar_motion(time)
sp = erfa.sp00(*get_jd12(time, 'tt'))
pmmat = erfa.pom00(xp, yp, sp)
# now determine the Earth Rotation Angle for the input obstime
# era00 accepts UT1, so we convert if need be
era = erfa.era00(*get_jd12(time, 'ut1'))
# c2tcio expects a GCRS->CIRS matrix, but we just set that to an I-matrix
# because we're already in CIRS
return erfa.c2tcio(np.eye(3), era, pmmat)
def gcrs_precession_mat(equinox):
gamb, phib, psib, epsa = erfa.pfw06(*get_jd12(equinox, 'tt'))
return erfa.fw2m(gamb, phib, psib, epsa)
# now the actual transforms
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, GCRS, CIRS)
def gcrs_to_cirs(gcrs_coo, cirs_frame):
# first get us to a 0 pos/vel GCRS at the target obstime
gcrs_coo2 = gcrs_coo.transform_to(GCRS(obstime=cirs_frame.obstime))
# now get the pmatrix
pmat = gcrs_to_cirs_mat(cirs_frame.obstime)
crepr = gcrs_coo2.cartesian.transform(pmat)
return cirs_frame.realize_frame(crepr)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, CIRS, GCRS)
def cirs_to_gcrs(cirs_coo, gcrs_frame):
# compute the pmatrix, and then multiply by its transpose
pmat = gcrs_to_cirs_mat(cirs_coo.obstime)
newrepr = cirs_coo.cartesian.transform(matrix_transpose(pmat))
gcrs = GCRS(newrepr, obstime=cirs_coo.obstime)
# now do any needed offsets (no-op if same obstime and 0 pos/vel)
return gcrs.transform_to(gcrs_frame)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, CIRS, ITRS)
def cirs_to_itrs(cirs_coo, itrs_frame):
# first get us to CIRS at the target obstime
cirs_coo2 = cirs_coo.transform_to(CIRS(obstime=itrs_frame.obstime))
# now get the pmatrix
pmat = cirs_to_itrs_mat(itrs_frame.obstime)
crepr = cirs_coo2.cartesian.transform(pmat)
return itrs_frame.realize_frame(crepr)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, ITRS, CIRS)
def itrs_to_cirs(itrs_coo, cirs_frame):
# compute the pmatrix, and then multiply by its transpose
pmat = cirs_to_itrs_mat(itrs_coo.obstime)
newrepr = itrs_coo.cartesian.transform(matrix_transpose(pmat))
cirs = CIRS(newrepr, obstime=itrs_coo.obstime)
# now do any needed offsets (no-op if same obstime)
return cirs.transform_to(cirs_frame)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, ITRS, ITRS)
def itrs_to_itrs(from_coo, to_frame):
# this self-transform goes through CIRS right now, which implicitly also
# goes back to ICRS
return from_coo.transform_to(CIRS).transform_to(to_frame)
# TODO: implement GCRS<->CIRS if there's call for it. The thing that's awkward
# is that they both have obstimes, so an extra set of transformations are necessary.
# so unless there's a specific need for that, better to just have it go through the above
# two steps anyway
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, GCRS, PrecessedGeocentric)
def gcrs_to_precessedgeo(from_coo, to_frame):
# first get us to GCRS with the right attributes (might be a no-op)
gcrs_coo = from_coo.transform_to(GCRS(obstime=to_frame.obstime,
obsgeoloc=to_frame.obsgeoloc,
obsgeovel=to_frame.obsgeovel))
# now precess to the requested equinox
pmat = gcrs_precession_mat(to_frame.equinox)
crepr = gcrs_coo.cartesian.transform(pmat)
return to_frame.realize_frame(crepr)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, PrecessedGeocentric, GCRS)
def precessedgeo_to_gcrs(from_coo, to_frame):
# first un-precess
pmat = gcrs_precession_mat(from_coo.equinox)
crepr = from_coo.cartesian.transform(matrix_transpose(pmat))
gcrs_coo = GCRS(crepr, obstime=to_frame.obstime,
obsgeoloc=to_frame.obsgeoloc,
obsgeovel=to_frame.obsgeovel)
# then move to the GCRS that's actually desired
return gcrs_coo.transform_to(to_frame)
|
849b688ccf16f57c1114bcb4afa42bc0df3f4dcbdfe0af41f313c7a607358ffd | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from astropy.utils.decorators import format_doc
from astropy.coordinates.attributes import TimeAttribute
from .utils import DEFAULT_OBSTIME
from astropy.coordinates.baseframe import base_doc
from .baseradec import BaseRADecFrame, doc_components
__all__ = ['HCRS']
doc_footer = """
Other parameters
----------------
obstime : `~astropy.time.Time`
The time at which the observation is taken. Used for determining the
position of the Sun.
"""
@format_doc(base_doc, components=doc_components, footer=doc_footer)
class HCRS(BaseRADecFrame):
"""
A coordinate or frame in a Heliocentric system, with axes aligned to ICRS.
The ICRS has an origin at the Barycenter and axes which are fixed with
respect to space.
This coordinate system is distinct from ICRS mainly in that it is relative
to the Sun's center-of-mass rather than the solar system Barycenter.
In principle, therefore, this frame should include the effects of
aberration (unlike ICRS), but this is not done, since they are very small,
of the order of 8 milli-arcseconds.
For more background on the ICRS and related coordinate transformations, see
the references provided in the :ref:`astropy-coordinates-seealso` section of
the documentation.
The frame attributes are listed under **Other Parameters**.
"""
obstime = TimeAttribute(default=DEFAULT_OBSTIME)
# Transformations are defined in icrs_circ_transforms.py
|
f570e62cd35dc3517734a380d9ac52eb4dc1ba08cbc2d38170618f7d6fd2dfad | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import numpy as np
from astropy import units as u
from astropy.utils.decorators import format_doc
from astropy.coordinates.baseframe import frame_transform_graph, base_doc
from astropy.coordinates.attributes import TimeAttribute
from astropy.coordinates.transformations import (FunctionTransformWithFiniteDifference,
FunctionTransform, DynamicMatrixTransform)
from astropy.coordinates.representation import (CartesianRepresentation,
UnitSphericalRepresentation)
from astropy.coordinates import earth_orientation as earth
from .utils import EQUINOX_B1950
from .baseradec import doc_components, BaseRADecFrame
__all__ = ['FK4', 'FK4NoETerms']
doc_footer_fk4 = """
Other parameters
----------------
equinox : `~astropy.time.Time`
The equinox of this frame.
obstime : `~astropy.time.Time`
The time this frame was observed. If ``None``, will be the same as
``equinox``.
"""
@format_doc(base_doc, components=doc_components, footer=doc_footer_fk4)
class FK4(BaseRADecFrame):
"""
A coordinate or frame in the FK4 system.
Note that this is a barycentric version of FK4 - that is, the origin for
this frame is the Solar System Barycenter, *not* the Earth geocenter.
The frame attributes are listed under **Other Parameters**.
"""
equinox = TimeAttribute(default=EQUINOX_B1950)
obstime = TimeAttribute(default=None, secondary_attribute='equinox')
# the "self" transform
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, FK4, FK4)
def fk4_to_fk4(fk4coord1, fk4frame2):
# deceptively complicated: need to transform to No E-terms FK4, precess, and
# then come back, because precession is non-trivial with E-terms
fnoe_w_eqx1 = fk4coord1.transform_to(FK4NoETerms(equinox=fk4coord1.equinox))
fnoe_w_eqx2 = fnoe_w_eqx1.transform_to(FK4NoETerms(equinox=fk4frame2.equinox))
return fnoe_w_eqx2.transform_to(fk4frame2)
@format_doc(base_doc, components=doc_components, footer=doc_footer_fk4)
class FK4NoETerms(BaseRADecFrame):
"""
A coordinate or frame in the FK4 system, but with the E-terms of aberration
removed.
The frame attributes are listed under **Other Parameters**.
"""
equinox = TimeAttribute(default=EQUINOX_B1950)
obstime = TimeAttribute(default=None, secondary_attribute='equinox')
@staticmethod
def _precession_matrix(oldequinox, newequinox):
"""
Compute and return the precession matrix for FK4 using Newcomb's method.
Used inside some of the transformation functions.
Parameters
----------
oldequinox : `~astropy.time.Time`
The equinox to precess from.
newequinox : `~astropy.time.Time`
The equinox to precess to.
Returns
-------
newcoord : array
The precession matrix to transform to the new equinox
"""
return earth._precession_matrix_besselian(oldequinox.byear, newequinox.byear)
# the "self" transform
@frame_transform_graph.transform(DynamicMatrixTransform, FK4NoETerms, FK4NoETerms)
def fk4noe_to_fk4noe(fk4necoord1, fk4neframe2):
return fk4necoord1._precession_matrix(fk4necoord1.equinox, fk4neframe2.equinox)
# FK4-NO-E to/from FK4 ----------------------------->
# Unlike other frames, this module include *two* frame classes for FK4
# coordinates - one including the E-terms of aberration (FK4), and
# one not including them (FK4NoETerms). The following functions
# implement the transformation between these two.
def fk4_e_terms(equinox):
"""
Return the e-terms of aberation vector
Parameters
----------
equinox : Time object
The equinox for which to compute the e-terms
"""
# Constant of aberration at J2000; from Explanatory Supplement to the
# Astronomical Almanac (Seidelmann, 2005).
k = 0.0056932 # in degrees (v_earth/c ~ 1e-4 rad ~ 0.0057 deg)
k = np.radians(k)
# Eccentricity of the Earth's orbit
e = earth.eccentricity(equinox.jd)
# Mean longitude of perigee of the solar orbit
g = earth.mean_lon_of_perigee(equinox.jd)
g = np.radians(g)
# Obliquity of the ecliptic
o = earth.obliquity(equinox.jd, algorithm=1980)
o = np.radians(o)
return e * k * np.sin(g), \
-e * k * np.cos(g) * np.cos(o), \
-e * k * np.cos(g) * np.sin(o)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, FK4, FK4NoETerms)
def fk4_to_fk4_no_e(fk4coord, fk4noeframe):
# Extract cartesian vector
rep = fk4coord.cartesian
# Find distance (for re-normalization)
d_orig = rep.norm()
rep /= d_orig
# Apply E-terms of aberration. Note that this depends on the equinox (not
# the observing time/epoch) of the coordinates. See issue #1496 for a
# discussion of this.
eterms_a = CartesianRepresentation(
u.Quantity(fk4_e_terms(fk4coord.equinox), u.dimensionless_unscaled,
copy=False), copy=False)
rep = rep - eterms_a + eterms_a.dot(rep) * rep
# Find new distance (for re-normalization)
d_new = rep.norm()
# Renormalize
rep *= d_orig / d_new
# now re-cast into an appropriate Representation, and precess if need be
if isinstance(fk4coord.data, UnitSphericalRepresentation):
rep = rep.represent_as(UnitSphericalRepresentation)
# if no obstime was given in the new frame, use the old one for consistency
newobstime = fk4coord._obstime if fk4noeframe._obstime is None else fk4noeframe._obstime
fk4noe = FK4NoETerms(rep, equinox=fk4coord.equinox, obstime=newobstime)
if fk4coord.equinox != fk4noeframe.equinox:
# precession
fk4noe = fk4noe.transform_to(fk4noeframe)
return fk4noe
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, FK4NoETerms, FK4)
def fk4_no_e_to_fk4(fk4noecoord, fk4frame):
# first precess, if necessary
if fk4noecoord.equinox != fk4frame.equinox:
fk4noe_w_fk4equinox = FK4NoETerms(equinox=fk4frame.equinox,
obstime=fk4noecoord.obstime)
fk4noecoord = fk4noecoord.transform_to(fk4noe_w_fk4equinox)
# Extract cartesian vector
rep = fk4noecoord.cartesian
# Find distance (for re-normalization)
d_orig = rep.norm()
rep /= d_orig
# Apply E-terms of aberration. Note that this depends on the equinox (not
# the observing time/epoch) of the coordinates. See issue #1496 for a
# discussion of this.
eterms_a = CartesianRepresentation(
u.Quantity(fk4_e_terms(fk4noecoord.equinox), u.dimensionless_unscaled,
copy=False), copy=False)
rep0 = rep.copy()
for _ in range(10):
rep = (eterms_a + rep0) / (1. + eterms_a.dot(rep))
# Find new distance (for re-normalization)
d_new = rep.norm()
# Renormalize
rep *= d_orig / d_new
# now re-cast into an appropriate Representation, and precess if need be
if isinstance(fk4noecoord.data, UnitSphericalRepresentation):
rep = rep.represent_as(UnitSphericalRepresentation)
return fk4frame.realize_frame(rep)
|
847fc986a60dc8c0dddc18ad8939d3fd3d137bb3a8a223aec01aee9c8837fabc | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from astropy.utils.decorators import format_doc
from astropy.coordinates import representation as r
from astropy.coordinates.baseframe import BaseCoordinateFrame, RepresentationMapping, base_doc
__all__ = ['BaseRADecFrame']
doc_components = """
ra : `Angle`, optional, must be keyword
The RA for this object (``dec`` must also be given and ``representation``
must be None).
dec : `Angle`, optional, must be keyword
The Declination for this object (``ra`` must also be given and
``representation`` must be None).
distance : `~astropy.units.Quantity`, optional, must be keyword
The Distance for this object along the line-of-sight.
(``representation`` must be None).
pm_ra_cosdec : :class:`~astropy.units.Quantity`, optional, must be keyword
The proper motion in Right Ascension (including the ``cos(dec)`` factor)
for this object (``pm_dec`` must also be given).
pm_dec : :class:`~astropy.units.Quantity`, optional, must be keyword
The proper motion in Declination for this object (``pm_ra_cosdec`` must
also be given).
radial_velocity : :class:`~astropy.units.Quantity`, optional, must be keyword
The radial velocity of this object.
"""
@format_doc(base_doc, components=doc_components, footer="")
class BaseRADecFrame(BaseCoordinateFrame):
"""
A base class that defines default representation info for frames that
represent longitude and latitude as Right Ascension and Declination
following typical "equatorial" conventions.
"""
frame_specific_representation_info = {
r.SphericalRepresentation: [
RepresentationMapping('lon', 'ra'),
RepresentationMapping('lat', 'dec')
]
}
default_representation = r.SphericalRepresentation
default_differential = r.SphericalCosLatDifferential
|
e272b8dd7d90cb9b2e3382c46c6b1a69d0295188ba94131bf879d575dd3dae4f | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
This package contains the coordinate frames actually implemented by astropy.
Users shouldn't use this module directly, but rather import from the
`astropy.coordinates` module. While it is likely to exist for the long-term,
the existence of this package and details of its organization should be
considered an implementation detail, and is not guaranteed to hold for future
versions of astropy.
Notes
-----
The builtin frame classes are all imported automatically into this package's
namespace, so there's no need to access the sub-modules directly.
To implement a new frame in Astropy, a developer should add the frame as a new
module in this package. Any "self" transformations (i.e., those that transform
from one frame to another frame of the same class) should be included in that
module. Transformation functions connecting the new frame to other frames
should be in a separate module, which should be imported in this package's
``__init__.py`` to ensure the transformations are hooked up when this package is
imported. Placing the trasnformation functions in separate modules avoids
circular dependencies, because they need references to the frame classes.
"""
from .baseradec import BaseRADecFrame
from .icrs import ICRS
from .fk5 import FK5
from .fk4 import FK4, FK4NoETerms
from .galactic import Galactic
from .galactocentric import Galactocentric
from .lsr import LSR, GalacticLSR
from .supergalactic import Supergalactic
from .altaz import AltAz
from .gcrs import GCRS, PrecessedGeocentric
from .cirs import CIRS
from .itrs import ITRS
from .hcrs import HCRS
from .ecliptic import * # there are a lot of these so we don't list them all explicitly
from .skyoffset import SkyOffsetFrame
# need to import transformations so that they get registered in the graph
from . import icrs_fk5_transforms
from . import fk4_fk5_transforms
from . import galactic_transforms
from . import supergalactic_transforms
from . import icrs_cirs_transforms
from . import cirs_observed_transforms
from . import intermediate_rotation_transforms
from . import ecliptic_transforms
from astropy.coordinates.baseframe import frame_transform_graph
# we define an __all__ because otherwise the transformation modules
# get included
__all__ = ['ICRS', 'FK5', 'FK4', 'FK4NoETerms', 'Galactic', 'Galactocentric',
'Supergalactic', 'AltAz', 'GCRS', 'CIRS', 'ITRS', 'HCRS',
'PrecessedGeocentric', 'GeocentricMeanEcliptic',
'BarycentricMeanEcliptic', 'HeliocentricMeanEcliptic',
'GeocentricTrueEcliptic', 'BarycentricTrueEcliptic',
'HeliocentricTrueEcliptic',
'SkyOffsetFrame', 'GalacticLSR', 'LSR',
'BaseEclipticFrame', 'BaseRADecFrame', 'make_transform_graph_docs']
def make_transform_graph_docs(transform_graph):
"""
Generates a string that can be used in other docstrings to include a
transformation graph, showing the available transforms and
coordinate systems.
Parameters
----------
transform_graph : `~.coordinates.TransformGraph`
Returns
-------
docstring : str
A string that can be added to the end of a docstring to show the
transform graph.
"""
from textwrap import dedent
coosys = [transform_graph.lookup_name(item) for
item in transform_graph.get_names()]
# currently, all of the priorities are set to 1, so we don't need to show
# then in the transform graph.
graphstr = transform_graph.to_dot_graph(addnodes=coosys,
priorities=False)
docstr = """
The diagram below shows all of the built in coordinate systems,
their aliases (useful for converting other coordinates to them using
attribute-style access) and the pre-defined transformations between
them. The user is free to override any of these transformations by
defining new transformations between these systems, but the
pre-defined transformations should be sufficient for typical usage.
The color of an edge in the graph (i.e. the transformations between two
frames) is set by the type of transformation; the legend box defines the
mapping from transform class name to color.
.. Wrap the graph in a div with a custom class to allow themeing.
.. container:: frametransformgraph
.. graphviz::
"""
docstr = dedent(docstr) + ' ' + graphstr.replace('\n', '\n ')
# colors are in dictionary at the bottom of transformations.py
from astropy.coordinates.transformations import trans_to_color
html_list_items = []
for cls, color in trans_to_color.items():
block = u"""
<li style='list-style: none;'>
<p style="font-size: 12px;line-height: 24px;font-weight: normal;color: #848484;padding: 0;margin: 0;">
<b>{0}:</b>
<span style="font-size: 24px; color: {1};"><b>➝</b></span>
</p>
</li>
""".format(cls.__name__, color)
html_list_items.append(block)
graph_legend = u"""
.. raw:: html
<ul>
{}
</ul>
""".format("\n".join(html_list_items))
docstr = docstr + dedent(graph_legend)
return docstr
_transform_graph_docs = make_transform_graph_docs(frame_transform_graph)
|
86adbb837239a609551689ad75204e35e324d607ad7fd88be6234ee9ed233eda | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from astropy import units as u
from astropy.utils.decorators import format_doc
from astropy.coordinates import representation as r
from astropy.coordinates.baseframe import BaseCoordinateFrame, RepresentationMapping, base_doc
from .galactic import Galactic
__all__ = ['Supergalactic']
doc_components = """
sgl : `Angle`, optional, must be keyword
The supergalactic longitude for this object (``sgb`` must also be given and
``representation`` must be None).
sgb : `Angle`, optional, must be keyword
The supergalactic latitude for this object (``sgl`` must also be given and
``representation`` must be None).
distance : `~astropy.units.Quantity`, optional, must be keyword
The Distance for this object along the line-of-sight.
pm_sgl_cossgb : :class:`~astropy.units.Quantity`, optional, must be keyword
The proper motion in Right Ascension for this object (``pm_sgb`` must
also be given).
pm_sgb : :class:`~astropy.units.Quantity`, optional, must be keyword
The proper motion in Declination for this object (``pm_sgl_cossgb`` must
also be given).
radial_velocity : :class:`~astropy.units.Quantity`, optional, must be keyword
The radial velocity of this object.
"""
@format_doc(base_doc, components=doc_components, footer="")
class Supergalactic(BaseCoordinateFrame):
"""
Supergalactic Coordinates
(see Lahav et al. 2000, <http://adsabs.harvard.edu/abs/2000MNRAS.312..166L>,
and references therein).
"""
frame_specific_representation_info = {
r.SphericalRepresentation: [
RepresentationMapping('lon', 'sgl'),
RepresentationMapping('lat', 'sgb')
],
r.CartesianRepresentation: [
RepresentationMapping('x', 'sgx'),
RepresentationMapping('y', 'sgy'),
RepresentationMapping('z', 'sgz')
],
r.CartesianDifferential: [
RepresentationMapping('d_x', 'v_x', u.km/u.s),
RepresentationMapping('d_y', 'v_y', u.km/u.s),
RepresentationMapping('d_z', 'v_z', u.km/u.s)
],
}
default_representation = r.SphericalRepresentation
default_differential = r.SphericalCosLatDifferential
# North supergalactic pole in Galactic coordinates.
# Needed for transformations to/from Galactic coordinates.
_nsgp_gal = Galactic(l=47.37*u.degree, b=+6.32*u.degree)
|
d43e8dfb1efc70504e34a6a0fe4156669f9a7b6b8498fcc2ecd1652ae661670f | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from astropy.utils.decorators import format_doc
from astropy.coordinates.baseframe import base_doc
from .baseradec import BaseRADecFrame, doc_components
__all__ = ['ICRS']
@format_doc(base_doc, components=doc_components, footer="")
class ICRS(BaseRADecFrame):
"""
A coordinate or frame in the ICRS system.
If you're looking for "J2000" coordinates, and aren't sure if you want to
use this or `~astropy.coordinates.FK5`, you probably want to use ICRS. It's
more well-defined as a catalog coordinate and is an inertial system, and is
very close (within tens of milliarcseconds) to J2000 equatorial.
For more background on the ICRS and related coordinate transformations, see the
references provided in the :ref:`astropy-coordinates-seealso` section of the
documentation.
"""
|
105e0d2d0174ee2c900b98327ecb8c18c50eef1ba2d6451dbfa24157ff9681ed | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from astropy import units as u
from astropy.utils.decorators import format_doc
from astropy.coordinates.attributes import (TimeAttribute,
CartesianRepresentationAttribute)
from .utils import DEFAULT_OBSTIME, EQUINOX_J2000
from astropy.coordinates.baseframe import base_doc
from .baseradec import BaseRADecFrame, doc_components
__all__ = ['GCRS', 'PrecessedGeocentric']
doc_footer_gcrs = """
Other parameters
----------------
obstime : `~astropy.time.Time`
The time at which the observation is taken. Used for determining the
position of the Earth.
obsgeoloc : `~astropy.coordinates.CartesianRepresentation`, `~astropy.units.Quantity`
The position of the observer relative to the center-of-mass of the
Earth, oriented the same as BCRS/ICRS. Either [0, 0, 0],
`~astropy.coordinates.CartesianRepresentation`, or proper input for one,
i.e., a `~astropy.units.Quantity` with shape (3, ...) and length units.
Defaults to [0, 0, 0], meaning "true" GCRS.
obsgeovel : `~astropy.coordinates.CartesianRepresentation`, `~astropy.units.Quantity`
The velocity of the observer relative to the center-of-mass of the
Earth, oriented the same as BCRS/ICRS. Either [0, 0, 0],
`~astropy.coordinates.CartesianRepresentation`, or proper input for one,
i.e., a `~astropy.units.Quantity` with shape (3, ...) and velocity
units. Defaults to [0, 0, 0], meaning "true" GCRS.
"""
@format_doc(base_doc, components=doc_components, footer=doc_footer_gcrs)
class GCRS(BaseRADecFrame):
"""
A coordinate or frame in the Geocentric Celestial Reference System (GCRS).
GCRS is distinct form ICRS mainly in that it is relative to the Earth's
center-of-mass rather than the solar system Barycenter. That means this
frame includes the effects of aberration (unlike ICRS). For more background
on the GCRS, see the references provided in the
:ref:`astropy-coordinates-seealso` section of the documentation. (Of
particular note is Section 1.2 of
`USNO Circular 179 <http://aa.usno.navy.mil/publications/docs/Circular_179.php>`_)
This frame also includes frames that are defined *relative* to the Earth,
but that are offset (in both position and velocity) from the Earth.
The frame attributes are listed under **Other Parameters**.
"""
obstime = TimeAttribute(default=DEFAULT_OBSTIME)
obsgeoloc = CartesianRepresentationAttribute(default=[0, 0, 0],
unit=u.m)
obsgeovel = CartesianRepresentationAttribute(default=[0, 0, 0],
unit=u.m/u.s)
# The "self-transform" is defined in icrs_cirs_transformations.py, because in
# the current implementation it goes through ICRS (like CIRS)
doc_footer_prec_geo = """
Other parameters
----------------
equinox : `~astropy.time.Time`
The (mean) equinox to precess the coordinates to.
obstime : `~astropy.time.Time`
The time at which the observation is taken. Used for determining the
position of the Earth.
obsgeoloc : `~astropy.coordinates.CartesianRepresentation`, `~astropy.units.Quantity`
The position of the observer relative to the center-of-mass of the
Earth, oriented the same as BCRS/ICRS. Either [0, 0, 0],
`~astropy.coordinates.CartesianRepresentation`, or proper input for one,
i.e., a `~astropy.units.Quantity` with shape (3, ...) and length units.
Defaults to [0, 0, 0], meaning "true" Geocentric.
obsgeovel : `~astropy.coordinates.CartesianRepresentation`, `~astropy.units.Quantity`
The velocity of the observer relative to the center-of-mass of the
Earth, oriented the same as BCRS/ICRS. Either 0,
`~astropy.coordinates.CartesianRepresentation`, or proper input for one,
i.e., a `~astropy.units.Quantity` with shape (3, ...) and velocity
units. Defaults to [0, 0, 0], meaning "true" Geocentric.
"""
@format_doc(base_doc, components=doc_components, footer=doc_footer_prec_geo)
class PrecessedGeocentric(BaseRADecFrame):
"""
A coordinate frame defined in a similar manner as GCRS, but precessed to a
requested (mean) equinox. Note that this does *not* end up the same as
regular GCRS even for J2000 equinox, because the GCRS orientation is fixed
to that of ICRS, which is not quite the same as the dynamical J2000
orientation.
The frame attributes are listed under **Other Parameters**
"""
equinox = TimeAttribute(default=EQUINOX_J2000)
obstime = TimeAttribute(default=DEFAULT_OBSTIME)
obsgeoloc = CartesianRepresentationAttribute(default=[0, 0, 0], unit=u.m)
obsgeovel = CartesianRepresentationAttribute(default=[0, 0, 0], unit=u.m/u.s)
|
cfc8e8ea8524e107a763fc8996398f71e509a3c058184f4c4c0796960f495689 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from astropy import units as u
from astropy.utils.decorators import format_doc
from astropy.coordinates import representation as r
from astropy.coordinates.baseframe import BaseCoordinateFrame, RepresentationMapping, base_doc
from astropy.coordinates.attributes import TimeAttribute, QuantityAttribute
from .utils import EQUINOX_J2000, DEFAULT_OBSTIME
__all__ = ['GeocentricMeanEcliptic', 'BarycentricMeanEcliptic',
'HeliocentricMeanEcliptic', 'BaseEclipticFrame',
'GeocentricTrueEcliptic', 'BarycentricTrueEcliptic',
'HeliocentricTrueEcliptic',
'HeliocentricEclipticIAU76', 'CustomBarycentricEcliptic']
doc_components_ecl = """
lon : `Angle`, optional, must be keyword
The ecliptic longitude for this object (``lat`` must also be given and
``representation`` must be None).
lat : `Angle`, optional, must be keyword
The ecliptic latitude for this object (``lon`` must also be given and
``representation`` must be None).
distance : `~astropy.units.Quantity`, optional, must be keyword
The distance for this object from the {0}.
(``representation`` must be None).
pm_lon_coslat : `Angle`, optional, must be keyword
The proper motion in the ecliptic longitude (including the ``cos(lat)``
factor) for this object (``pm_lat`` must also be given).
pm_lat : `Angle`, optional, must be keyword
The proper motion in the ecliptic latitude for this object
(``pm_lon_coslat`` must also be given).
radial_velocity : :class:`~astropy.units.Quantity`, optional, must be keyword
The radial velocity of this object.
"""
@format_doc(base_doc,
components=doc_components_ecl.format('specified location'),
footer="")
class BaseEclipticFrame(BaseCoordinateFrame):
"""
A base class for frames that have names and conventions like that of
ecliptic frames.
.. warning::
In the current version of astropy, the ecliptic frames do not yet have
stringent accuracy tests. We recommend you test to "known-good" cases
to ensure this frames are what you are looking for. (and then ideally
you would contribute these tests to Astropy!)
"""
default_representation = r.SphericalRepresentation
default_differential = r.SphericalCosLatDifferential
doc_footer_geo = """
Other parameters
----------------
equinox : `~astropy.time.Time`, optional
The date to assume for this frame. Determines the location of the
x-axis and the location of the Earth (necessary for transformation to
non-geocentric systems). Defaults to the 'J2000' equinox.
obstime : `~astropy.time.Time`, optional
The time at which the observation is taken. Used for determining the
position of the Earth. Defaults to J2000.
"""
@format_doc(base_doc, components=doc_components_ecl.format('geocenter'),
footer=doc_footer_geo)
class GeocentricMeanEcliptic(BaseEclipticFrame):
"""
Geocentric mean ecliptic coordinates. These origin of the coordinates are the
geocenter (Earth), with the x axis pointing to the *mean* (not true) equinox
at the time specified by the ``equinox`` attribute, and the xy-plane in the
plane of the ecliptic for that date.
Be aware that the definition of "geocentric" here means that this frame
*includes* light deflection from the sun, aberration, etc when transforming
to/from e.g. ICRS.
The frame attributes are listed under **Other Parameters**.
"""
equinox = TimeAttribute(default=EQUINOX_J2000)
obstime = TimeAttribute(default=DEFAULT_OBSTIME)
@format_doc(base_doc, components=doc_components_ecl.format('geocenter'),
footer=doc_footer_geo)
class GeocentricTrueEcliptic(BaseEclipticFrame):
"""
Geocentric true ecliptic coordinates. These origin of the coordinates are the
geocenter (Earth), with the x axis pointing to the *true* (not mean) equinox
at the time specified by the ``equinox`` attribute, and the xy-plane in the
plane of the ecliptic for that date.
Be aware that the definition of "geocentric" here means that this frame
*includes* light deflection from the sun, aberration, etc when transforming
to/from e.g. ICRS.
The frame attributes are listed under **Other Parameters**.
"""
equinox = TimeAttribute(default=EQUINOX_J2000)
obstime = TimeAttribute(default=DEFAULT_OBSTIME)
doc_footer_bary = """
Other parameters
----------------
equinox : `~astropy.time.Time`, optional
The date to assume for this frame. Determines the location of the
x-axis and the location of the Earth and Sun.
Defaults to the 'J2000' equinox.
"""
@format_doc(base_doc, components=doc_components_ecl.format("barycenter"),
footer=doc_footer_bary)
class BarycentricMeanEcliptic(BaseEclipticFrame):
"""
Barycentric mean ecliptic coordinates. These origin of the coordinates are the
barycenter of the solar system, with the x axis pointing in the direction of
the *mean* (not true) equinox as at the time specified by the ``equinox``
attribute (as seen from Earth), and the xy-plane in the plane of the
ecliptic for that date.
The frame attributes are listed under **Other Parameters**.
"""
equinox = TimeAttribute(default=EQUINOX_J2000)
@format_doc(base_doc, components=doc_components_ecl.format("barycenter"),
footer=doc_footer_bary)
class BarycentricTrueEcliptic(BaseEclipticFrame):
"""
Barycentric true ecliptic coordinates. These origin of the coordinates are the
barycenter of the solar system, with the x axis pointing in the direction of
the *true* (not mean) equinox as at the time specified by the ``equinox``
attribute (as seen from Earth), and the xy-plane in the plane of the
ecliptic for that date.
The frame attributes are listed under **Other Parameters**.
"""
equinox = TimeAttribute(default=EQUINOX_J2000)
doc_footer_helio = """
Other parameters
----------------
equinox : `~astropy.time.Time`, optional
The date to assume for this frame. Determines the location of the
x-axis and the location of the Earth and Sun.
Defaults to the 'J2000' equinox.
obstime : `~astropy.time.Time`, optional
The time at which the observation is taken. Used for determining the
position of the Sun. Defaults to J2000.
"""
@format_doc(base_doc, components=doc_components_ecl.format("sun's center"),
footer=doc_footer_helio)
class HeliocentricMeanEcliptic(BaseEclipticFrame):
"""
Heliocentric mean ecliptic coordinates. These origin of the coordinates are the
center of the sun, with the x axis pointing in the direction of
the *mean* (not true) equinox as at the time specified by the ``equinox``
attribute (as seen from Earth), and the xy-plane in the plane of the
ecliptic for that date.
The frame attributes are listed under **Other Parameters**.
{params}
"""
equinox = TimeAttribute(default=EQUINOX_J2000)
obstime = TimeAttribute(default=DEFAULT_OBSTIME)
@format_doc(base_doc, components=doc_components_ecl.format("sun's center"),
footer=doc_footer_helio)
class HeliocentricTrueEcliptic(BaseEclipticFrame):
"""
Heliocentric true ecliptic coordinates. These origin of the coordinates are the
center of the sun, with the x axis pointing in the direction of
the *true* (not mean) equinox as at the time specified by the ``equinox``
attribute (as seen from Earth), and the xy-plane in the plane of the
ecliptic for that date.
The frame attributes are listed under **Other Parameters**.
{params}
"""
equinox = TimeAttribute(default=EQUINOX_J2000)
obstime = TimeAttribute(default=DEFAULT_OBSTIME)
@format_doc(base_doc, components=doc_components_ecl.format("sun's center"),
footer="")
class HeliocentricEclipticIAU76(BaseEclipticFrame):
"""
Heliocentric mean (IAU 1976) ecliptic coordinates. These origin of the coordinates are the
center of the sun, with the x axis pointing in the direction of
the *mean* (not true) equinox of J2000, and the xy-plane in the plane of the
ecliptic of J2000 (according to the IAU 1976/1980 obliquity model).
It has, therefore, a fixed equinox and an older obliquity value
than the rest of the frames.
The frame attributes are listed under **Other Parameters**.
{params}
"""
obstime = TimeAttribute(default=DEFAULT_OBSTIME)
@format_doc(base_doc, components=doc_components_ecl.format("barycenter"),
footer="")
class CustomBarycentricEcliptic(BaseEclipticFrame):
"""
Barycentric ecliptic coordinates with custom obliquity.
These origin of the coordinates are the
barycenter of the solar system, with the x axis pointing in the direction of
the *mean* (not true) equinox of J2000, and the xy-plane in the plane of the
ecliptic tilted a custom obliquity angle.
The frame attributes are listed under **Other Parameters**.
"""
obliquity = QuantityAttribute(default=84381.448 * u.arcsec, unit=u.arcsec)
|
3da705e55e58e535f54f1e400d081c7ba30fe0c1e7df2e13811668d1b8c2b19d | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from astropy.utils.decorators import format_doc
from astropy.coordinates.representation import CartesianRepresentation, CartesianDifferential
from astropy.coordinates.baseframe import BaseCoordinateFrame, base_doc
from astropy.coordinates.attributes import TimeAttribute
from .utils import DEFAULT_OBSTIME
__all__ = ['ITRS']
@format_doc(base_doc, components="", footer="")
class ITRS(BaseCoordinateFrame):
"""
A coordinate or frame in the International Terrestrial Reference System
(ITRS). This is approximately a geocentric system, although strictly it is
defined by a series of reference locations near the surface of the Earth.
For more background on the ITRS, see the references provided in the
:ref:`astropy-coordinates-seealso` section of the documentation.
"""
default_representation = CartesianRepresentation
default_differential = CartesianDifferential
obstime = TimeAttribute(default=DEFAULT_OBSTIME)
@property
def earth_location(self):
"""
The data in this frame as an `~astropy.coordinates.EarthLocation` class.
"""
from astropy.coordinates.earth import EarthLocation
cart = self.represent_as(CartesianRepresentation)
return EarthLocation(x=cart.x, y=cart.y, z=cart.z)
# Self-transform is in intermediate_rotation_transforms.py with all the other
# ITRS transforms
|
114119261c1b227db86a5f1331e136fa75d504452c53297c1c9e26170b95d45b | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
This module contains functions/values used repeatedly in different modules of
the ``builtin_frames`` package.
"""
import warnings
import numpy as np
from astropy import units as u
from astropy import _erfa as erfa
from astropy.time import Time
from astropy.utils import iers
from astropy.utils.exceptions import AstropyWarning
# We use tt as the time scale for this equinoxes, primarily because it is the
# convention for J2000 (it is unclear if there is any "right answer" for B1950)
# while #8600 makes this the default behavior, we show it here to ensure it's
# clear which is used here
EQUINOX_J2000 = Time('J2000', scale='tt')
EQUINOX_B1950 = Time('B1950', scale='tt')
# This is a time object that is the default "obstime" when such an attribute is
# necessary. Currently, we use J2000.
DEFAULT_OBSTIME = Time('J2000', scale='tt')
PIOVER2 = np.pi / 2.
# comes from the mean of the 1962-2014 IERS B data
_DEFAULT_PM = (0.035, 0.29)*u.arcsec
def get_polar_motion(time):
"""
gets the two polar motion components in radians for use with apio13
"""
# Get the polar motion from the IERS table
xp, yp, status = iers.IERS_Auto.open().pm_xy(time, return_status=True)
wmsg = None
if np.any(status == iers.TIME_BEFORE_IERS_RANGE):
wmsg = ('Tried to get polar motions for times before IERS data is '
'valid. Defaulting to polar motion from the 50-yr mean for those. '
'This may affect precision at the 10s of arcsec level')
xp.ravel()[status.ravel() == iers.TIME_BEFORE_IERS_RANGE] = _DEFAULT_PM[0]
yp.ravel()[status.ravel() == iers.TIME_BEFORE_IERS_RANGE] = _DEFAULT_PM[1]
warnings.warn(wmsg, AstropyWarning)
if np.any(status == iers.TIME_BEYOND_IERS_RANGE):
wmsg = ('Tried to get polar motions for times after IERS data is '
'valid. Defaulting to polar motion from the 50-yr mean for those. '
'This may affect precision at the 10s of arcsec level')
xp.ravel()[status.ravel() == iers.TIME_BEYOND_IERS_RANGE] = _DEFAULT_PM[0]
yp.ravel()[status.ravel() == iers.TIME_BEYOND_IERS_RANGE] = _DEFAULT_PM[1]
warnings.warn(wmsg, AstropyWarning)
return xp.to_value(u.radian), yp.to_value(u.radian)
def _warn_iers(ierserr):
"""
Generate a warning for an IERSRangeerror
Parameters
----------
ierserr : An `~astropy.utils.iers.IERSRangeError`
"""
msg = '{0} Assuming UT1-UTC=0 for coordinate transformations.'
warnings.warn(msg.format(ierserr.args[0]), AstropyWarning)
def get_dut1utc(time):
"""
This function is used to get UT1-UTC in coordinates because normally it
gives an error outside the IERS range, but in coordinates we want to allow
it to go through but with a warning.
"""
try:
return time.delta_ut1_utc
except iers.IERSRangeError as e:
_warn_iers(e)
return np.zeros(time.shape)
def get_jd12(time, scale):
"""
Gets ``jd1`` and ``jd2`` from a time object in a particular scale.
Parameters
----------
time : `~astropy.time.Time`
The time to get the jds for
scale : str
The time scale to get the jds for
Returns
-------
jd1 : float
jd2 : float
"""
if time.scale == scale:
newtime = time
else:
try:
newtime = getattr(time, scale)
except iers.IERSRangeError as e:
_warn_iers(e)
newtime = time
return newtime.jd1, newtime.jd2
def norm(p):
"""
Normalise a p-vector.
"""
if np.__version__ == '1.14.0':
# there is a bug in numpy v1.14.0 (fixed in 1.14.1) that causes
# this einsum call to break with the default of optimize=True
# see https://github.com/astropy/astropy/issues/7051
return p / np.sqrt(np.einsum('...i,...i', p, p, optimize=False))[..., np.newaxis]
else:
return p / np.sqrt(np.einsum('...i,...i', p, p))[..., np.newaxis]
def get_cip(jd1, jd2):
"""
Find the X, Y coordinates of the CIP and the CIO locator, s.
Parameters
----------
jd1 : float or `np.ndarray`
First part of two part Julian date (TDB)
jd2 : float or `np.ndarray`
Second part of two part Julian date (TDB)
Returns
--------
x : float or `np.ndarray`
x coordinate of the CIP
y : float or `np.ndarray`
y coordinate of the CIP
s : float or `np.ndarray`
CIO locator, s
"""
# classical NPB matrix, IAU 2006/2000A
rpnb = erfa.pnm06a(jd1, jd2)
# CIP X, Y coordinates from array
x, y = erfa.bpn2xy(rpnb)
# CIO locator, s
s = erfa.s06(jd1, jd2, x, y)
return x, y, s
def aticq(ri, di, astrom):
"""
A slightly modified version of the ERFA function ``eraAticq``.
``eraAticq`` performs the transformations between two coordinate systems,
with the details of the transformation being encoded into the ``astrom`` array.
The companion function ``eraAtciqz`` is meant to be its inverse. However, this
is not true for directions close to the Solar centre, since the light deflection
calculations are numerically unstable and therefore not reversible.
This version sidesteps that problem by artificially reducing the light deflection
for directions which are within 90 arcseconds of the Sun's position. This is the
same approach used by the ERFA functions above, except that they use a threshold of
9 arcseconds.
Parameters
----------
ri : float or `~numpy.ndarray`
right ascension, radians
di : float or `~numpy.ndarray`
declination, radians
astrom : eraASTROM array
ERFA astrometry context, as produced by, e.g. ``eraApci13`` or ``eraApcs13``
Returns
--------
rc : float or `~numpy.ndarray`
dc : float or `~numpy.ndarray`
"""
# RA, Dec to cartesian unit vectors
pos = erfa.s2c(ri, di)
# Bias-precession-nutation, giving GCRS proper direction.
ppr = erfa.trxp(astrom['bpn'], pos)
# Aberration, giving GCRS natural direction
d = np.zeros_like(ppr)
for j in range(2):
before = norm(ppr-d)
after = erfa.ab(before, astrom['v'], astrom['em'], astrom['bm1'])
d = after - before
pnat = norm(ppr-d)
# Light deflection by the Sun, giving BCRS coordinate direction
d = np.zeros_like(pnat)
for j in range(5):
before = norm(pnat-d)
after = erfa.ld(1.0, before, before, astrom['eh'], astrom['em'], 5e-8)
d = after - before
pco = norm(pnat-d)
# ICRS astrometric RA, Dec
rc, dc = erfa.c2s(pco)
return erfa.anp(rc), dc
def atciqz(rc, dc, astrom):
"""
A slightly modified version of the ERFA function ``eraAtciqz``.
``eraAtciqz`` performs the transformations between two coordinate systems,
with the details of the transformation being encoded into the ``astrom`` array.
The companion function ``eraAticq`` is meant to be its inverse. However, this
is not true for directions close to the Solar centre, since the light deflection
calculations are numerically unstable and therefore not reversible.
This version sidesteps that problem by artificially reducing the light deflection
for directions which are within 90 arcseconds of the Sun's position. This is the
same approach used by the ERFA functions above, except that they use a threshold of
9 arcseconds.
Parameters
----------
rc : float or `~numpy.ndarray`
right ascension, radians
dc : float or `~numpy.ndarray`
declination, radians
astrom : eraASTROM array
ERFA astrometry context, as produced by, e.g. ``eraApci13`` or ``eraApcs13``
Returns
--------
ri : float or `~numpy.ndarray`
di : float or `~numpy.ndarray`
"""
# BCRS coordinate direction (unit vector).
pco = erfa.s2c(rc, dc)
# Light deflection by the Sun, giving BCRS natural direction.
pnat = erfa.ld(1.0, pco, pco, astrom['eh'], astrom['em'], 5e-8)
# Aberration, giving GCRS proper direction.
ppr = erfa.ab(pnat, astrom['v'], astrom['em'], astrom['bm1'])
# Bias-precession-nutation, giving CIRS proper direction.
# Has no effect if matrix is identity matrix, in which case gives GCRS ppr.
pi = erfa.rxp(astrom['bpn'], ppr)
# CIRS (GCRS) RA, Dec
ri, di = erfa.c2s(pi)
return erfa.anp(ri), di
def prepare_earth_position_vel(time):
"""
Get barycentric position and velocity, and heliocentric position of Earth
Parameters
-----------
time : `~astropy.time.Time`
time at which to calculate position and velocity of Earth
Returns
--------
earth_pv : `np.ndarray`
Barycentric position and velocity of Earth, in au and au/day
earth_helio : `np.ndarray`
Heliocentric position of Earth in au
"""
# this goes here to avoid circular import errors
from astropy.coordinates.solar_system import (get_body_barycentric, get_body_barycentric_posvel)
# get barycentric position and velocity of earth
earth_p, earth_v = get_body_barycentric_posvel('earth', time)
# get heliocentric position of earth, preparing it for passing to erfa.
sun = get_body_barycentric('sun', time)
earth_heliocentric = (earth_p -
sun).get_xyz(xyz_axis=-1).to_value(u.au)
# Also prepare earth_pv for passing to erfa, which wants it as
# a structured dtype.
earth_pv = erfa.pav2pv(
earth_p.get_xyz(xyz_axis=-1).to_value(u.au),
earth_v.get_xyz(xyz_axis=-1).to_value(u.au/u.d))
return earth_pv, earth_heliocentric
|
d41dbd4403fde735de1c4300dc82648ba91529e7dd9e80976bc9cebd36137c0e | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Contains the transformation functions for getting to/from ecliptic systems.
"""
from astropy import units as u
from astropy.coordinates.baseframe import frame_transform_graph
from astropy.coordinates.transformations import (
FunctionTransformWithFiniteDifference, DynamicMatrixTransform,
AffineTransform,
)
from astropy.coordinates.matrix_utilities import (rotation_matrix,
matrix_product, matrix_transpose)
from astropy.coordinates.representation import CartesianRepresentation
from astropy import _erfa as erfa
from .icrs import ICRS
from .gcrs import GCRS
from .ecliptic import (GeocentricMeanEcliptic, BarycentricMeanEcliptic, HeliocentricMeanEcliptic,
GeocentricTrueEcliptic, BarycentricTrueEcliptic, HeliocentricTrueEcliptic,
HeliocentricEclipticIAU76, CustomBarycentricEcliptic)
from .utils import get_jd12, EQUINOX_J2000
from astropy.coordinates.errors import UnitsError
def _mean_ecliptic_rotation_matrix(equinox):
# This code calls pmat06 from ERFA, which retrieves the precession
# matrix (including frame bias) according to the IAU 2006 model, but
# leaves out the nutation. This matches what ERFA does in the ecm06
# function and also brings the results closer to what other libraries
# give (see https://github.com/astropy/astropy/pull/6508).
jd1, jd2 = get_jd12(equinox, 'tt')
rbp = erfa.pmat06(jd1, jd2)
obl = erfa.obl06(jd1, jd2)*u.radian
return matrix_product(rotation_matrix(obl, 'x'), rbp)
def _true_ecliptic_rotation_matrix(equinox):
# This code calls pnm06a from ERFA, which retrieves the precession
# matrix (including frame bias) according to the IAU 2006 model, and
# including the nutation. This family of systems is less popular
# (see https://github.com/astropy/astropy/pull/6508).
jd1, jd2 = get_jd12(equinox, 'tt')
rnpb = erfa.pnm06a(jd1, jd2)
obl = erfa.obl06(jd1, jd2)*u.radian
return matrix_product(rotation_matrix(obl, 'x'), rnpb)
def _obliquity_only_rotation_matrix(obl=erfa.obl80(EQUINOX_J2000.jd1, EQUINOX_J2000.jd2) * u.radian):
# This code only accounts for the obliquity,
# which can be passed explicitly.
# The default value is the IAU 1980 value for J2000,
# which is computed using obl80 from ERFA:
#
# obl = _erfa.obl80(EQUINOX_J2000.jd1, EQUINOX_J2000.jd2) * u.radian
return rotation_matrix(obl, "x")
# MeanEcliptic frames
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference,
GCRS, GeocentricMeanEcliptic,
finite_difference_frameattr_name='equinox')
def gcrs_to_geoecliptic(gcrs_coo, to_frame):
# first get us to a 0 pos/vel GCRS at the target equinox
gcrs_coo2 = gcrs_coo.transform_to(GCRS(obstime=to_frame.obstime))
rmat = _mean_ecliptic_rotation_matrix(to_frame.equinox)
newrepr = gcrs_coo2.cartesian.transform(rmat)
return to_frame.realize_frame(newrepr)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, GeocentricMeanEcliptic, GCRS)
def geoecliptic_to_gcrs(from_coo, gcrs_frame):
rmat = _mean_ecliptic_rotation_matrix(from_coo.equinox)
newrepr = from_coo.cartesian.transform(matrix_transpose(rmat))
gcrs = GCRS(newrepr, obstime=from_coo.obstime)
# now do any needed offsets (no-op if same obstime and 0 pos/vel)
return gcrs.transform_to(gcrs_frame)
@frame_transform_graph.transform(DynamicMatrixTransform, ICRS, BarycentricMeanEcliptic)
def icrs_to_baryecliptic(from_coo, to_frame):
return _mean_ecliptic_rotation_matrix(to_frame.equinox)
@frame_transform_graph.transform(DynamicMatrixTransform, BarycentricMeanEcliptic, ICRS)
def baryecliptic_to_icrs(from_coo, to_frame):
return matrix_transpose(icrs_to_baryecliptic(to_frame, from_coo))
_NEED_ORIGIN_HINT = ("The input {0} coordinates do not have length units. This "
"probably means you created coordinates with lat/lon but "
"no distance. Heliocentric<->ICRS transforms cannot "
"function in this case because there is an origin shift.")
@frame_transform_graph.transform(AffineTransform,
ICRS, HeliocentricMeanEcliptic)
def icrs_to_helioecliptic(from_coo, to_frame):
if not u.m.is_equivalent(from_coo.cartesian.x.unit):
raise UnitsError(_NEED_ORIGIN_HINT.format(from_coo.__class__.__name__))
# get barycentric sun coordinate
# this goes here to avoid circular import errors
from astropy.coordinates.solar_system import get_body_barycentric
bary_sun_pos = get_body_barycentric('sun', to_frame.obstime)
# now compute the matrix to precess to the right orientation
rmat = _mean_ecliptic_rotation_matrix(to_frame.equinox)
return rmat, (-bary_sun_pos).transform(rmat)
@frame_transform_graph.transform(AffineTransform,
HeliocentricMeanEcliptic, ICRS)
def helioecliptic_to_icrs(from_coo, to_frame):
if not u.m.is_equivalent(from_coo.cartesian.x.unit):
raise UnitsError(_NEED_ORIGIN_HINT.format(from_coo.__class__.__name__))
# first un-precess from ecliptic to ICRS orientation
rmat = _mean_ecliptic_rotation_matrix(from_coo.equinox)
# now offset back to barycentric, which is the correct center for ICRS
# this goes here to avoid circular import errors
from astropy.coordinates.solar_system import get_body_barycentric
# get barycentric sun coordinate
bary_sun_pos = get_body_barycentric('sun', from_coo.obstime)
return matrix_transpose(rmat), bary_sun_pos
# TrueEcliptic frames
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference,
GCRS, GeocentricTrueEcliptic,
finite_difference_frameattr_name='equinox')
def gcrs_to_true_geoecliptic(gcrs_coo, to_frame):
# first get us to a 0 pos/vel GCRS at the target equinox
gcrs_coo2 = gcrs_coo.transform_to(GCRS(obstime=to_frame.obstime))
rmat = _true_ecliptic_rotation_matrix(to_frame.equinox)
newrepr = gcrs_coo2.cartesian.transform(rmat)
return to_frame.realize_frame(newrepr)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, GeocentricTrueEcliptic, GCRS)
def true_geoecliptic_to_gcrs(from_coo, gcrs_frame):
rmat = _true_ecliptic_rotation_matrix(from_coo.equinox)
newrepr = from_coo.cartesian.transform(matrix_transpose(rmat))
gcrs = GCRS(newrepr, obstime=from_coo.obstime)
# now do any needed offsets (no-op if same obstime and 0 pos/vel)
return gcrs.transform_to(gcrs_frame)
@frame_transform_graph.transform(DynamicMatrixTransform, ICRS, BarycentricTrueEcliptic)
def icrs_to_true_baryecliptic(from_coo, to_frame):
return _true_ecliptic_rotation_matrix(to_frame.equinox)
@frame_transform_graph.transform(DynamicMatrixTransform, BarycentricTrueEcliptic, ICRS)
def true_baryecliptic_to_icrs(from_coo, to_frame):
return matrix_transpose(icrs_to_true_baryecliptic(to_frame, from_coo))
@frame_transform_graph.transform(AffineTransform,
ICRS, HeliocentricTrueEcliptic)
def icrs_to_true_helioecliptic(from_coo, to_frame):
if not u.m.is_equivalent(from_coo.cartesian.x.unit):
raise UnitsError(_NEED_ORIGIN_HINT.format(from_coo.__class__.__name__))
# get barycentric sun coordinate
# this goes here to avoid circular import errors
from astropy.coordinates.solar_system import get_body_barycentric
bary_sun_pos = get_body_barycentric('sun', to_frame.obstime)
# now compute the matrix to precess to the right orientation
rmat = _true_ecliptic_rotation_matrix(to_frame.equinox)
return rmat, (-bary_sun_pos).transform(rmat)
@frame_transform_graph.transform(AffineTransform,
HeliocentricTrueEcliptic, ICRS)
def true_helioecliptic_to_icrs(from_coo, to_frame):
if not u.m.is_equivalent(from_coo.cartesian.x.unit):
raise UnitsError(_NEED_ORIGIN_HINT.format(from_coo.__class__.__name__))
# first un-precess from ecliptic to ICRS orientation
rmat = _true_ecliptic_rotation_matrix(from_coo.equinox)
# now offset back to barycentric, which is the correct center for ICRS
# this goes here to avoid circular import errors
from astropy.coordinates.solar_system import get_body_barycentric
# get barycentric sun coordinate
bary_sun_pos = get_body_barycentric('sun', from_coo.obstime)
return matrix_transpose(rmat), bary_sun_pos
# Other ecliptic frames
@frame_transform_graph.transform(AffineTransform,
HeliocentricEclipticIAU76, ICRS)
def ecliptic_to_iau76_icrs(from_coo, to_frame):
# first un-precess from ecliptic to ICRS orientation
rmat = _obliquity_only_rotation_matrix()
# now offset back to barycentric, which is the correct center for ICRS
# get barycentric sun coordinate
# this goes here to avoid circular import errors
from astropy.coordinates.solar_system import get_body_barycentric
bary_sun_pos = get_body_barycentric("sun", from_coo.obstime)
return matrix_transpose(rmat), bary_sun_pos
@frame_transform_graph.transform(AffineTransform,
ICRS, HeliocentricEclipticIAU76)
def icrs_to_iau76_ecliptic(from_coo, to_frame):
# get barycentric sun coordinate
# this goes here to avoid circular import errors
from astropy.coordinates.solar_system import get_body_barycentric
bary_sun_pos = get_body_barycentric("sun", to_frame.obstime)
# now compute the matrix to precess to the right orientation
rmat = _obliquity_only_rotation_matrix()
return rmat, (-bary_sun_pos).transform(rmat)
@frame_transform_graph.transform(DynamicMatrixTransform,
ICRS, CustomBarycentricEcliptic)
def icrs_to_custombaryecliptic(from_coo, to_frame):
return _obliquity_only_rotation_matrix(to_frame.obliquity)
@frame_transform_graph.transform(DynamicMatrixTransform,
CustomBarycentricEcliptic, ICRS)
def custombaryecliptic_to_icrs(from_coo, to_frame):
return icrs_to_custombaryecliptic(to_frame, from_coo).T
|
026a7f4f86218a1c985abf14794e877d1dfc865093c7b4c5b5fe1fe183c6275f | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Contains the transformation functions for getting from ICRS/HCRS to CIRS and
anything in between (currently that means GCRS)
"""
import numpy as np
from astropy import units as u
from astropy.coordinates.baseframe import frame_transform_graph
from astropy.coordinates.transformations import FunctionTransformWithFiniteDifference, AffineTransform
from astropy.coordinates.representation import (SphericalRepresentation, CartesianRepresentation,
UnitSphericalRepresentation)
from astropy import _erfa as erfa
from .icrs import ICRS
from .gcrs import GCRS
from .cirs import CIRS
from .hcrs import HCRS
from .utils import get_jd12, aticq, atciqz, get_cip, prepare_earth_position_vel
# First the ICRS/CIRS related transforms
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, ICRS, CIRS)
def icrs_to_cirs(icrs_coo, cirs_frame):
# first set up the astrometry context for ICRS<->CIRS
jd1, jd2 = get_jd12(cirs_frame.obstime, 'tdb')
x, y, s = get_cip(jd1, jd2)
earth_pv, earth_heliocentric = prepare_earth_position_vel(cirs_frame.obstime)
astrom = erfa.apci(jd1, jd2, earth_pv, earth_heliocentric, x, y, s)
if icrs_coo.data.get_name() == 'unitspherical' or icrs_coo.data.to_cartesian().x.unit == u.one:
# if no distance, just do the infinite-distance/no parallax calculation
usrepr = icrs_coo.represent_as(UnitSphericalRepresentation)
i_ra = usrepr.lon.to_value(u.radian)
i_dec = usrepr.lat.to_value(u.radian)
cirs_ra, cirs_dec = atciqz(i_ra, i_dec, astrom)
newrep = UnitSphericalRepresentation(lat=u.Quantity(cirs_dec, u.radian, copy=False),
lon=u.Quantity(cirs_ra, u.radian, copy=False),
copy=False)
else:
# When there is a distance, we first offset for parallax to get the
# astrometric coordinate direction and *then* run the ERFA transform for
# no parallax/PM. This ensures reversibility and is more sensible for
# inside solar system objects
astrom_eb = CartesianRepresentation(astrom['eb'], unit=u.au,
xyz_axis=-1, copy=False)
newcart = icrs_coo.cartesian - astrom_eb
srepr = newcart.represent_as(SphericalRepresentation)
i_ra = srepr.lon.to_value(u.radian)
i_dec = srepr.lat.to_value(u.radian)
cirs_ra, cirs_dec = atciqz(i_ra, i_dec, astrom)
newrep = SphericalRepresentation(lat=u.Quantity(cirs_dec, u.radian, copy=False),
lon=u.Quantity(cirs_ra, u.radian, copy=False),
distance=srepr.distance, copy=False)
return cirs_frame.realize_frame(newrep)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, CIRS, ICRS)
def cirs_to_icrs(cirs_coo, icrs_frame):
srepr = cirs_coo.represent_as(SphericalRepresentation)
cirs_ra = srepr.lon.to_value(u.radian)
cirs_dec = srepr.lat.to_value(u.radian)
# set up the astrometry context for ICRS<->cirs and then convert to
# astrometric coordinate direction
jd1, jd2 = get_jd12(cirs_coo.obstime, 'tdb')
x, y, s = get_cip(jd1, jd2)
earth_pv, earth_heliocentric = prepare_earth_position_vel(cirs_coo.obstime)
astrom = erfa.apci(jd1, jd2, earth_pv, earth_heliocentric, x, y, s)
i_ra, i_dec = aticq(cirs_ra, cirs_dec, astrom)
if cirs_coo.data.get_name() == 'unitspherical' or cirs_coo.data.to_cartesian().x.unit == u.one:
# if no distance, just use the coordinate direction to yield the
# infinite-distance/no parallax answer
newrep = UnitSphericalRepresentation(lat=u.Quantity(i_dec, u.radian, copy=False),
lon=u.Quantity(i_ra, u.radian, copy=False),
copy=False)
else:
# When there is a distance, apply the parallax/offset to the SSB as the
# last step - ensures round-tripping with the icrs_to_cirs transform
# the distance in intermedrep is *not* a real distance as it does not
# include the offset back to the SSB
intermedrep = SphericalRepresentation(lat=u.Quantity(i_dec, u.radian, copy=False),
lon=u.Quantity(i_ra, u.radian, copy=False),
distance=srepr.distance,
copy=False)
astrom_eb = CartesianRepresentation(astrom['eb'], unit=u.au,
xyz_axis=-1, copy=False)
newrep = intermedrep + astrom_eb
return icrs_frame.realize_frame(newrep)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, CIRS, CIRS)
def cirs_to_cirs(from_coo, to_frame):
if np.all(from_coo.obstime == to_frame.obstime):
return to_frame.realize_frame(from_coo.data)
else:
# the CIRS<-> CIRS transform actually goes through ICRS. This has a
# subtle implication that a point in CIRS is uniquely determined
# by the corresponding astrometric ICRS coordinate *at its
# current time*. This has some subtle implications in terms of GR, but
# is sort of glossed over in the current scheme because we are dropping
# distances anyway.
return from_coo.transform_to(ICRS).transform_to(to_frame)
# Now the GCRS-related transforms to/from ICRS
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, ICRS, GCRS)
def icrs_to_gcrs(icrs_coo, gcrs_frame):
# first set up the astrometry context for ICRS<->GCRS. There are a few steps...
# get the position and velocity arrays for the observatory. Need to
# have xyz in last dimension, and pos/vel in one-but-last.
# (Note could use np.stack once our minimum numpy version is >=1.10.)
obs_pv = erfa.pav2pv(
gcrs_frame.obsgeoloc.get_xyz(xyz_axis=-1).to_value(u.m),
gcrs_frame.obsgeovel.get_xyz(xyz_axis=-1).to_value(u.m/u.s))
# find the position and velocity of earth
jd1, jd2 = get_jd12(gcrs_frame.obstime, 'tdb')
earth_pv, earth_heliocentric = prepare_earth_position_vel(gcrs_frame.obstime)
# get astrometry context object, astrom.
astrom = erfa.apcs(jd1, jd2, obs_pv, earth_pv, earth_heliocentric)
if icrs_coo.data.get_name() == 'unitspherical' or icrs_coo.data.to_cartesian().x.unit == u.one:
# if no distance, just do the infinite-distance/no parallax calculation
usrepr = icrs_coo.represent_as(UnitSphericalRepresentation)
i_ra = usrepr.lon.to_value(u.radian)
i_dec = usrepr.lat.to_value(u.radian)
gcrs_ra, gcrs_dec = atciqz(i_ra, i_dec, astrom)
newrep = UnitSphericalRepresentation(lat=u.Quantity(gcrs_dec, u.radian, copy=False),
lon=u.Quantity(gcrs_ra, u.radian, copy=False),
copy=False)
else:
# When there is a distance, we first offset for parallax to get the
# BCRS coordinate direction and *then* run the ERFA transform for no
# parallax/PM. This ensures reversibility and is more sensible for
# inside solar system objects
astrom_eb = CartesianRepresentation(astrom['eb'], unit=u.au,
xyz_axis=-1, copy=False)
newcart = icrs_coo.cartesian - astrom_eb
srepr = newcart.represent_as(SphericalRepresentation)
i_ra = srepr.lon.to_value(u.radian)
i_dec = srepr.lat.to_value(u.radian)
gcrs_ra, gcrs_dec = atciqz(i_ra, i_dec, astrom)
newrep = SphericalRepresentation(lat=u.Quantity(gcrs_dec, u.radian, copy=False),
lon=u.Quantity(gcrs_ra, u.radian, copy=False),
distance=srepr.distance, copy=False)
return gcrs_frame.realize_frame(newrep)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference,
GCRS, ICRS)
def gcrs_to_icrs(gcrs_coo, icrs_frame):
srepr = gcrs_coo.represent_as(SphericalRepresentation)
gcrs_ra = srepr.lon.to_value(u.radian)
gcrs_dec = srepr.lat.to_value(u.radian)
# set up the astrometry context for ICRS<->GCRS and then convert to BCRS
# coordinate direction
obs_pv = erfa.pav2pv(
gcrs_coo.obsgeoloc.get_xyz(xyz_axis=-1).to_value(u.m),
gcrs_coo.obsgeovel.get_xyz(xyz_axis=-1).to_value(u.m/u.s))
jd1, jd2 = get_jd12(gcrs_coo.obstime, 'tdb')
earth_pv, earth_heliocentric = prepare_earth_position_vel(gcrs_coo.obstime)
astrom = erfa.apcs(jd1, jd2, obs_pv, earth_pv, earth_heliocentric)
i_ra, i_dec = aticq(gcrs_ra, gcrs_dec, astrom)
if gcrs_coo.data.get_name() == 'unitspherical' or gcrs_coo.data.to_cartesian().x.unit == u.one:
# if no distance, just use the coordinate direction to yield the
# infinite-distance/no parallax answer
newrep = UnitSphericalRepresentation(lat=u.Quantity(i_dec, u.radian, copy=False),
lon=u.Quantity(i_ra, u.radian, copy=False),
copy=False)
else:
# When there is a distance, apply the parallax/offset to the SSB as the
# last step - ensures round-tripping with the icrs_to_gcrs transform
# the distance in intermedrep is *not* a real distance as it does not
# include the offset back to the SSB
intermedrep = SphericalRepresentation(lat=u.Quantity(i_dec, u.radian, copy=False),
lon=u.Quantity(i_ra, u.radian, copy=False),
distance=srepr.distance,
copy=False)
astrom_eb = CartesianRepresentation(astrom['eb'], unit=u.au,
xyz_axis=-1, copy=False)
newrep = intermedrep + astrom_eb
return icrs_frame.realize_frame(newrep)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, GCRS, GCRS)
def gcrs_to_gcrs(from_coo, to_frame):
if (np.all(from_coo.obstime == to_frame.obstime)
and np.all(from_coo.obsgeoloc == to_frame.obsgeoloc)):
return to_frame.realize_frame(from_coo.data)
else:
# like CIRS, we do this self-transform via ICRS
return from_coo.transform_to(ICRS).transform_to(to_frame)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, GCRS, HCRS)
def gcrs_to_hcrs(gcrs_coo, hcrs_frame):
if np.any(gcrs_coo.obstime != hcrs_frame.obstime):
# if they GCRS obstime and HCRS obstime are not the same, we first
# have to move to a GCRS where they are.
frameattrs = gcrs_coo.get_frame_attr_names()
frameattrs['obstime'] = hcrs_frame.obstime
gcrs_coo = gcrs_coo.transform_to(GCRS(**frameattrs))
srepr = gcrs_coo.represent_as(SphericalRepresentation)
gcrs_ra = srepr.lon.to_value(u.radian)
gcrs_dec = srepr.lat.to_value(u.radian)
# set up the astrometry context for ICRS<->GCRS and then convert to ICRS
# coordinate direction
obs_pv = erfa.pav2pv(
gcrs_coo.obsgeoloc.get_xyz(xyz_axis=-1).to_value(u.m),
gcrs_coo.obsgeovel.get_xyz(xyz_axis=-1).to_value(u.m/u.s))
jd1, jd2 = get_jd12(hcrs_frame.obstime, 'tdb')
earth_pv, earth_heliocentric = prepare_earth_position_vel(gcrs_coo.obstime)
astrom = erfa.apcs(jd1, jd2, obs_pv, earth_pv, earth_heliocentric)
i_ra, i_dec = aticq(gcrs_ra, gcrs_dec, astrom)
# convert to Quantity objects
i_ra = u.Quantity(i_ra, u.radian, copy=False)
i_dec = u.Quantity(i_dec, u.radian, copy=False)
if gcrs_coo.data.get_name() == 'unitspherical' or gcrs_coo.data.to_cartesian().x.unit == u.one:
# if no distance, just use the coordinate direction to yield the
# infinite-distance/no parallax answer
newrep = UnitSphericalRepresentation(lat=i_dec, lon=i_ra, copy=False)
else:
# When there is a distance, apply the parallax/offset to the
# Heliocentre as the last step to ensure round-tripping with the
# hcrs_to_gcrs transform
# Note that the distance in intermedrep is *not* a real distance as it
# does not include the offset back to the Heliocentre
intermedrep = SphericalRepresentation(lat=i_dec, lon=i_ra,
distance=srepr.distance,
copy=False)
# astrom['eh'] and astrom['em'] contain Sun to observer unit vector,
# and distance, respectively. Shapes are (X) and (X,3), where (X) is the
# shape resulting from broadcasting the shape of the times object
# against the shape of the pv array.
# broadcast em to eh and scale eh
eh = astrom['eh'] * astrom['em'][..., np.newaxis]
eh = CartesianRepresentation(eh, unit=u.au, xyz_axis=-1, copy=False)
newrep = intermedrep.to_cartesian() + eh
return hcrs_frame.realize_frame(newrep)
_NEED_ORIGIN_HINT = ("The input {0} coordinates do not have length units. This "
"probably means you created coordinates with lat/lon but "
"no distance. Heliocentric<->ICRS transforms cannot "
"function in this case because there is an origin shift.")
@frame_transform_graph.transform(AffineTransform, HCRS, ICRS)
def hcrs_to_icrs(hcrs_coo, icrs_frame):
# this is just an origin translation so without a distance it cannot go ahead
if isinstance(hcrs_coo.data, UnitSphericalRepresentation):
raise u.UnitsError(_NEED_ORIGIN_HINT.format(hcrs_coo.__class__.__name__))
if hcrs_coo.data.differentials:
from astropy.coordinates.solar_system import get_body_barycentric_posvel
bary_sun_pos, bary_sun_vel = get_body_barycentric_posvel('sun',
hcrs_coo.obstime)
bary_sun_pos = bary_sun_pos.with_differentials(bary_sun_vel)
else:
from astropy.coordinates.solar_system import get_body_barycentric
bary_sun_pos = get_body_barycentric('sun', hcrs_coo.obstime)
bary_sun_vel = None
return None, bary_sun_pos
@frame_transform_graph.transform(AffineTransform, ICRS, HCRS)
def icrs_to_hcrs(icrs_coo, hcrs_frame):
# this is just an origin translation so without a distance it cannot go ahead
if isinstance(icrs_coo.data, UnitSphericalRepresentation):
raise u.UnitsError(_NEED_ORIGIN_HINT.format(icrs_coo.__class__.__name__))
if icrs_coo.data.differentials:
from astropy.coordinates.solar_system import get_body_barycentric_posvel
bary_sun_pos, bary_sun_vel = get_body_barycentric_posvel('sun',
hcrs_frame.obstime)
bary_sun_pos = -bary_sun_pos.with_differentials(-bary_sun_vel)
else:
from astropy.coordinates.solar_system import get_body_barycentric
bary_sun_pos = -get_body_barycentric('sun', hcrs_frame.obstime)
bary_sun_vel = None
return None, bary_sun_pos
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, HCRS, HCRS)
def hcrs_to_hcrs(from_coo, to_frame):
if np.all(from_coo.obstime == to_frame.obstime):
return to_frame.realize_frame(from_coo.data)
else:
# like CIRS, we do this self-transform via ICRS
return from_coo.transform_to(ICRS).transform_to(to_frame)
|
2649d2d151cae481b77b256e7d27bef2b885a979f04b0a6adc618b56b3e0835b | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from astropy import units as u
from astropy.utils.compat import namedtuple_asdict
from astropy.coordinates import representation as r
from astropy.coordinates.transformations import DynamicMatrixTransform, FunctionTransform
from astropy.coordinates.baseframe import (frame_transform_graph, RepresentationMapping,
BaseCoordinateFrame)
from astropy.coordinates.attributes import CoordinateAttribute, QuantityAttribute
from astropy.coordinates.matrix_utilities import (rotation_matrix,
matrix_product, matrix_transpose)
_skyoffset_cache = {}
def make_skyoffset_cls(framecls):
"""
Create a new class that is the sky offset frame for a specific class of
origin frame. If such a class has already been created for this frame, the
same class will be returned.
The new class will always have component names for spherical coordinates of
``lon``/``lat``.
Parameters
----------
framecls : coordinate frame class (i.e., subclass of `~astropy.coordinates.BaseCoordinateFrame`)
The class to create the SkyOffsetFrame of.
Returns
-------
skyoffsetframecls : class
The class for the new skyoffset frame.
Notes
-----
This function is necessary because Astropy's frame transformations depend
on connection between specific frame *classes*. So each type of frame
needs its own distinct skyoffset frame class. This function generates
just that class, as well as ensuring that only one example of such a class
actually gets created in any given python session.
"""
if framecls in _skyoffset_cache:
return _skyoffset_cache[framecls]
# the class of a class object is the metaclass
framemeta = framecls.__class__
class SkyOffsetMeta(framemeta):
"""
This metaclass renames the class to be "SkyOffset<framecls>" and also
adjusts the frame specific representation info so that spherical names
are always "lon" and "lat" (instead of e.g. "ra" and "dec").
"""
def __new__(cls, name, bases, members):
# Only 'origin' is needed here, to set the origin frame properly.
members['origin'] = CoordinateAttribute(frame=framecls, default=None)
# This has to be done because FrameMeta will set these attributes
# to the defaults from BaseCoordinateFrame when it creates the base
# SkyOffsetFrame class initially.
members['_default_representation'] = framecls._default_representation
members['_default_differential'] = framecls._default_differential
newname = name[:-5] if name.endswith('Frame') else name
newname += framecls.__name__
return super().__new__(cls, newname, bases, members)
# We need this to handle the intermediate metaclass correctly, otherwise we could
# just subclass SkyOffsetFrame.
_SkyOffsetFramecls = SkyOffsetMeta('SkyOffsetFrame', (SkyOffsetFrame, framecls),
{'__doc__': SkyOffsetFrame.__doc__})
@frame_transform_graph.transform(FunctionTransform, _SkyOffsetFramecls, _SkyOffsetFramecls)
def skyoffset_to_skyoffset(from_skyoffset_coord, to_skyoffset_frame):
"""Transform between two skyoffset frames."""
# This transform goes through the parent frames on each side.
# from_frame -> from_frame.origin -> to_frame.origin -> to_frame
intermediate_from = from_skyoffset_coord.transform_to(from_skyoffset_coord.origin)
intermediate_to = intermediate_from.transform_to(to_skyoffset_frame.origin)
return intermediate_to.transform_to(to_skyoffset_frame)
@frame_transform_graph.transform(DynamicMatrixTransform, framecls, _SkyOffsetFramecls)
def reference_to_skyoffset(reference_frame, skyoffset_frame):
"""Convert a reference coordinate to an sky offset frame."""
# Define rotation matrices along the position angle vector, and
# relative to the origin.
origin = skyoffset_frame.origin.spherical
mat1 = rotation_matrix(-skyoffset_frame.rotation, 'x')
mat2 = rotation_matrix(-origin.lat, 'y')
mat3 = rotation_matrix(origin.lon, 'z')
return matrix_product(mat1, mat2, mat3)
@frame_transform_graph.transform(DynamicMatrixTransform, _SkyOffsetFramecls, framecls)
def skyoffset_to_reference(skyoffset_coord, reference_frame):
"""Convert an sky offset frame coordinate to the reference frame"""
# use the forward transform, but just invert it
R = reference_to_skyoffset(reference_frame, skyoffset_coord)
# transpose is the inverse because R is a rotation matrix
return matrix_transpose(R)
_skyoffset_cache[framecls] = _SkyOffsetFramecls
return _SkyOffsetFramecls
class SkyOffsetFrame(BaseCoordinateFrame):
"""
A frame which is relative to some specific position and oriented to match
its frame.
SkyOffsetFrames always have component names for spherical coordinates
of ``lon``/``lat``, *not* the component names for the frame of ``origin``.
This is useful for calculating offsets and dithers in the frame of the sky
relative to an arbitrary position. Coordinates in this frame are both centered on the position specified by the
``origin`` coordinate, *and* they are oriented in the same manner as the
``origin`` frame. E.g., if ``origin`` is `~astropy.coordinates.ICRS`, this
object's ``lat`` will be pointed in the direction of Dec, while ``lon``
will point in the direction of RA.
For more on skyoffset frames, see :ref:`astropy-skyoffset-frames`.
Parameters
----------
representation : `BaseRepresentation` or None
A representation object or None to have no data (or use the other keywords)
origin : `SkyCoord` or low-level coordinate object.
The coordinate which specifies the origin of this frame. Note that this
origin is used purely for on-sky location/rotation. It can have a
``distance`` but it will not be used by this ``SkyOffsetFrame``.
rotation : `~astropy.coordinates.Angle` or `~astropy.units.Quantity` with angle units
The final rotation of the frame about the ``origin``. The sign of
the rotation is the left-hand rule. That is, an object at a
particular position angle in the un-rotated system will be sent to
the positive latitude (z) direction in the final frame.
Notes
-----
``SkyOffsetFrame`` is a factory class. That is, the objects that it
yields are *not* actually objects of class ``SkyOffsetFrame``. Instead,
distinct classes are created on-the-fly for whatever the frame class is
of ``origin``.
"""
rotation = QuantityAttribute(default=0, unit=u.deg)
origin = CoordinateAttribute(default=None, frame=None)
def __new__(cls, *args, **kwargs):
# We don't want to call this method if we've already set up
# an skyoffset frame for this class.
if not (issubclass(cls, SkyOffsetFrame) and cls is not SkyOffsetFrame):
# We get the origin argument, and handle it here.
try:
origin_frame = kwargs['origin']
except KeyError:
raise TypeError("Can't initialize an SkyOffsetFrame without origin= keyword.")
if hasattr(origin_frame, 'frame'):
origin_frame = origin_frame.frame
newcls = make_skyoffset_cls(origin_frame.__class__)
return newcls.__new__(newcls, *args, **kwargs)
# http://stackoverflow.com/questions/19277399/why-does-object-new-work-differently-in-these-three-cases
# See above for why this is necessary. Basically, because some child
# may override __new__, we must override it here to never pass
# arguments to the object.__new__ method.
if super().__new__ is object.__new__:
return super().__new__(cls)
return super().__new__(cls, *args, **kwargs)
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
if self.origin is not None and not self.origin.has_data:
raise ValueError('The origin supplied to SkyOffsetFrame has no '
'data.')
if self.has_data and hasattr(self.data, 'lon'):
self.data.lon.wrap_angle = 180*u.deg
|
7c201742d728f80b4dbbfc869c7063677ed3f4ae7f53eb299ba06287b9fbb108 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Contains the transformation functions for getting to "observed" systems from CIRS.
Currently that just means AltAz.
"""
import numpy as np
from astropy import units as u
from astropy.coordinates.baseframe import frame_transform_graph
from astropy.coordinates.transformations import FunctionTransformWithFiniteDifference
from astropy.coordinates.representation import (SphericalRepresentation,
UnitSphericalRepresentation)
from astropy import _erfa as erfa
from .cirs import CIRS
from .altaz import AltAz
from .utils import get_polar_motion, get_dut1utc, get_jd12, PIOVER2
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, CIRS, AltAz)
def cirs_to_altaz(cirs_coo, altaz_frame):
if np.any(cirs_coo.obstime != altaz_frame.obstime):
# the only frame attribute for the current CIRS is the obstime, but this
# would need to be updated if a future change allowed specifying an
# Earth location algorithm or something
cirs_coo = cirs_coo.transform_to(CIRS(obstime=altaz_frame.obstime))
# we use the same obstime everywhere now that we know they're the same
obstime = cirs_coo.obstime
# if the data are UnitSphericalRepresentation, we can skip the distance calculations
is_unitspherical = (isinstance(cirs_coo.data, UnitSphericalRepresentation) or
cirs_coo.cartesian.x.unit == u.one)
if is_unitspherical:
usrepr = cirs_coo.represent_as(UnitSphericalRepresentation)
cirs_ra = usrepr.lon.to_value(u.radian)
cirs_dec = usrepr.lat.to_value(u.radian)
else:
# compute an "astrometric" ra/dec -i.e., the direction of the
# displacement vector from the observer to the target in CIRS
loccirs = altaz_frame.location.get_itrs(cirs_coo.obstime).transform_to(cirs_coo)
diffrepr = (cirs_coo.cartesian - loccirs.cartesian).represent_as(UnitSphericalRepresentation)
cirs_ra = diffrepr.lon.to_value(u.radian)
cirs_dec = diffrepr.lat.to_value(u.radian)
lon, lat, height = altaz_frame.location.to_geodetic('WGS84')
xp, yp = get_polar_motion(obstime)
# first set up the astrometry context for CIRS<->AltAz
jd1, jd2 = get_jd12(obstime, 'utc')
astrom = erfa.apio13(jd1, jd2,
get_dut1utc(obstime),
lon.to_value(u.radian), lat.to_value(u.radian),
height.to_value(u.m),
xp, yp, # polar motion
# all below are already in correct units because they are QuantityFrameAttribues
altaz_frame.pressure.value,
altaz_frame.temperature.value,
altaz_frame.relative_humidity.value,
altaz_frame.obswl.value)
az, zen, _, _, _ = erfa.atioq(cirs_ra, cirs_dec, astrom)
if is_unitspherical:
rep = UnitSphericalRepresentation(lat=u.Quantity(PIOVER2 - zen, u.radian, copy=False),
lon=u.Quantity(az, u.radian, copy=False),
copy=False)
else:
# now we get the distance as the cartesian distance from the earth
# location to the coordinate location
locitrs = altaz_frame.location.get_itrs(obstime)
distance = locitrs.separation_3d(cirs_coo)
rep = SphericalRepresentation(lat=u.Quantity(PIOVER2 - zen, u.radian, copy=False),
lon=u.Quantity(az, u.radian, copy=False),
distance=distance,
copy=False)
return altaz_frame.realize_frame(rep)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, AltAz, CIRS)
def altaz_to_cirs(altaz_coo, cirs_frame):
usrepr = altaz_coo.represent_as(UnitSphericalRepresentation)
az = usrepr.lon.to_value(u.radian)
zen = PIOVER2 - usrepr.lat.to_value(u.radian)
lon, lat, height = altaz_coo.location.to_geodetic('WGS84')
xp, yp = get_polar_motion(altaz_coo.obstime)
# first set up the astrometry context for ICRS<->CIRS at the altaz_coo time
jd1, jd2 = get_jd12(altaz_coo.obstime, 'utc')
astrom = erfa.apio13(jd1, jd2,
get_dut1utc(altaz_coo.obstime),
lon.to_value(u.radian), lat.to_value(u.radian),
height.to_value(u.m),
xp, yp, # polar motion
# all below are already in correct units because they are QuantityFrameAttribues
altaz_coo.pressure.value,
altaz_coo.temperature.value,
altaz_coo.relative_humidity.value,
altaz_coo.obswl.value)
# the 'A' indicates zen/az inputs
cirs_ra, cirs_dec = erfa.atoiq('A', az, zen, astrom)*u.radian
if isinstance(altaz_coo.data, UnitSphericalRepresentation) or altaz_coo.cartesian.x.unit == u.one:
cirs_at_aa_time = CIRS(ra=cirs_ra, dec=cirs_dec, distance=None,
obstime=altaz_coo.obstime)
else:
# treat the output of atoiq as an "astrometric" RA/DEC, so to get the
# actual RA/Dec from the observers vantage point, we have to reverse
# the vector operation of cirs_to_altaz (see there for more detail)
loccirs = altaz_coo.location.get_itrs(altaz_coo.obstime).transform_to(cirs_frame)
astrometric_rep = SphericalRepresentation(lon=cirs_ra, lat=cirs_dec,
distance=altaz_coo.distance)
newrepr = astrometric_rep + loccirs.cartesian
cirs_at_aa_time = CIRS(newrepr, obstime=altaz_coo.obstime)
# this final transform may be a no-op if the obstimes are the same
return cirs_at_aa_time.transform_to(cirs_frame)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference, AltAz, AltAz)
def altaz_to_altaz(from_coo, to_frame):
# for now we just implement this through CIRS to make sure we get everything
# covered
return from_coo.transform_to(CIRS(obstime=from_coo.obstime)).transform_to(to_frame)
|
a09b4cea66391b784ec8471fd5fb2a9cd358f1282cde614fd00ee26db815c250 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import numpy as np
from astropy import units as u
from astropy.utils.decorators import format_doc
from astropy.coordinates import representation as r
from astropy.coordinates.baseframe import BaseCoordinateFrame, RepresentationMapping, base_doc
from astropy.coordinates.attributes import (Attribute, TimeAttribute,
QuantityAttribute, EarthLocationAttribute)
__all__ = ['AltAz']
_90DEG = 90*u.deg
doc_components = """
az : `Angle`, optional, must be keyword
The Azimuth for this object (``alt`` must also be given and
``representation`` must be None).
alt : `Angle`, optional, must be keyword
The Altitude for this object (``az`` must also be given and
``representation`` must be None).
distance : :class:`~astropy.units.Quantity`, optional, must be keyword
The Distance for this object along the line-of-sight.
pm_az_cosalt : :class:`~astropy.units.Quantity`, optional, must be keyword
The proper motion in azimuth (including the ``cos(alt)`` factor) for
this object (``pm_alt`` must also be given).
pm_alt : :class:`~astropy.units.Quantity`, optional, must be keyword
The proper motion in altitude for this object (``pm_az_cosalt`` must
also be given).
radial_velocity : :class:`~astropy.units.Quantity`, optional, must be keyword
The radial velocity of this object."""
doc_footer = """
Other parameters
----------------
obstime : `~astropy.time.Time`
The time at which the observation is taken. Used for determining the
position and orientation of the Earth.
location : `~astropy.coordinates.EarthLocation`
The location on the Earth. This can be specified either as an
`~astropy.coordinates.EarthLocation` object or as anything that can be
transformed to an `~astropy.coordinates.ITRS` frame.
pressure : `~astropy.units.Quantity`
The atmospheric pressure as an `~astropy.units.Quantity` with pressure
units. This is necessary for performing refraction corrections.
Setting this to 0 (the default) will disable refraction calculations
when transforming to/from this frame.
temperature : `~astropy.units.Quantity`
The ground-level temperature as an `~astropy.units.Quantity` in
deg C. This is necessary for performing refraction corrections.
relative_humidity`` : `~astropy.units.Quantity` or number.
The relative humidity as a dimensionless quantity between 0 to 1.
This is necessary for performing refraction corrections.
obswl : `~astropy.units.Quantity`
The average wavelength of observations as an `~astropy.units.Quantity`
with length units. This is necessary for performing refraction
corrections.
Notes
-----
The refraction model is based on that implemented in ERFA, which is fast
but becomes inaccurate for altitudes below about 5 degrees. Near and below
altitudes of 0, it can even give meaningless answers, and in this case
transforming to AltAz and back to another frame can give highly discrepant
results. For much better numerical stability, leaving the ``pressure`` at
``0`` (the default), disabling the refraction correction (yielding
"topocentric" horizontal coordinates).
"""
@format_doc(base_doc, components=doc_components, footer=doc_footer)
class AltAz(BaseCoordinateFrame):
"""
A coordinate or frame in the Altitude-Azimuth system (Horizontal
coordinates). Azimuth is oriented East of North (i.e., N=0, E=90 degrees).
This frame is assumed to *include* refraction effects if the ``pressure``
frame attribute is non-zero.
The frame attributes are listed under **Other Parameters**, which are
necessary for transforming from AltAz to some other system.
"""
frame_specific_representation_info = {
r.SphericalRepresentation: [
RepresentationMapping('lon', 'az'),
RepresentationMapping('lat', 'alt')
]
}
default_representation = r.SphericalRepresentation
default_differential = r.SphericalCosLatDifferential
obstime = TimeAttribute(default=None)
location = EarthLocationAttribute(default=None)
pressure = QuantityAttribute(default=0, unit=u.hPa)
temperature = QuantityAttribute(default=0, unit=u.deg_C)
relative_humidity = QuantityAttribute(default=0, unit=u.dimensionless_unscaled)
obswl = QuantityAttribute(default=1*u.micron, unit=u.micron)
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
@property
def secz(self):
"""
Secant if the zenith angle for this coordinate, a common estimate of the
airmass.
"""
return 1/np.sin(self.alt)
@property
def zen(self):
"""
The zenith angle for this coordinate
"""
return _90DEG.to(self.alt.unit) - self.alt
# self-transform defined in cirs_observed_transforms.py
|
1d821bf7ef3be20a1c0afbcc4bf54da15cfe05397f8836136fe9111326672016 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from astropy import units as u
from astropy.utils.decorators import format_doc
from astropy.time import Time
from astropy.coordinates import representation as r
from astropy.coordinates.baseframe import (BaseCoordinateFrame, RepresentationMapping,
frame_transform_graph, base_doc)
from astropy.coordinates.transformations import AffineTransform
from astropy.coordinates.attributes import DifferentialAttribute
from .baseradec import BaseRADecFrame, doc_components as doc_components_radec
from .icrs import ICRS
from .galactic import Galactic
# For speed
J2000 = Time('J2000')
v_bary_Schoenrich2010 = r.CartesianDifferential([11.1, 12.24, 7.25]*u.km/u.s)
__all__ = ['LSR', 'GalacticLSR']
doc_footer_lsr = """
Other parameters
----------------
v_bary : `~astropy.coordinates.representation.CartesianDifferential`
The velocity of the solar system barycenter with respect to the LSR, in
Galactic cartesian velocity components.
"""
@format_doc(base_doc, components=doc_components_radec, footer=doc_footer_lsr)
class LSR(BaseRADecFrame):
r"""A coordinate or frame in the Local Standard of Rest (LSR).
This coordinate frame is axis-aligned and co-spatial with `ICRS`, but has
a velocity offset relative to the solar system barycenter to remove the
peculiar motion of the sun relative to the LSR. Roughly, the LSR is the mean
velocity of the stars in the solar neighborhood, but the precise definition
of which depends on the study. As defined in Schönrich et al. (2010):
"The LSR is the rest frame at the location of the Sun of a star that would
be on a circular orbit in the gravitational potential one would obtain by
azimuthally averaging away non-axisymmetric features in the actual Galactic
potential." No such orbit truly exists, but it is still a commonly used
velocity frame.
We use default values from Schönrich et al. (2010) for the barycentric
velocity relative to the LSR, which is defined in Galactic (right-handed)
cartesian velocity components
:math:`(U, V, W) = (11.1, 12.24, 7.25)~{{\rm km}}~{{\rm s}}^{{-1}}`. These
values are customizable via the ``v_bary`` argument which specifies the
velocity of the solar system barycenter with respect to the LSR.
The frame attributes are listed under **Other Parameters**.
"""
# frame attributes:
v_bary = DifferentialAttribute(default=v_bary_Schoenrich2010,
allowed_classes=[r.CartesianDifferential])
@frame_transform_graph.transform(AffineTransform, ICRS, LSR)
def icrs_to_lsr(icrs_coord, lsr_frame):
v_bary_gal = Galactic(lsr_frame.v_bary.to_cartesian())
v_bary_icrs = v_bary_gal.transform_to(icrs_coord)
v_offset = v_bary_icrs.data.represent_as(r.CartesianDifferential)
offset = r.CartesianRepresentation([0, 0, 0]*u.au, differentials=v_offset)
return None, offset
@frame_transform_graph.transform(AffineTransform, LSR, ICRS)
def lsr_to_icrs(lsr_coord, icrs_frame):
v_bary_gal = Galactic(lsr_coord.v_bary.to_cartesian())
v_bary_icrs = v_bary_gal.transform_to(icrs_frame)
v_offset = v_bary_icrs.data.represent_as(r.CartesianDifferential)
offset = r.CartesianRepresentation([0, 0, 0]*u.au, differentials=-v_offset)
return None, offset
# ------------------------------------------------------------------------------
doc_components_gal = """
l : `Angle`, optional, must be keyword
The Galactic longitude for this object (``b`` must also be given and
``representation`` must be None).
b : `Angle`, optional, must be keyword
The Galactic latitude for this object (``l`` must also be given and
``representation`` must be None).
distance : `~astropy.units.Quantity`, optional, must be keyword
The Distance for this object along the line-of-sight.
(``representation`` must be None).
pm_l_cosb : :class:`~astropy.units.Quantity`, optional, must be keyword
The proper motion in Galactic longitude (including the ``cos(b)`` term)
for this object (``pm_b`` must also be given).
pm_b : :class:`~astropy.units.Quantity`, optional, must be keyword
The proper motion in Galactic latitude for this object (``pm_l_cosb``
must also be given).
radial_velocity : :class:`~astropy.units.Quantity`, optional, must be keyword
The radial velocity of this object.
"""
@format_doc(base_doc, components=doc_components_gal, footer=doc_footer_lsr)
class GalacticLSR(BaseCoordinateFrame):
r"""A coordinate or frame in the Local Standard of Rest (LSR), axis-aligned
to the `Galactic` frame.
This coordinate frame is axis-aligned and co-spatial with `ICRS`, but has
a velocity offset relative to the solar system barycenter to remove the
peculiar motion of the sun relative to the LSR. Roughly, the LSR is the mean
velocity of the stars in the solar neighborhood, but the precise definition
of which depends on the study. As defined in Schönrich et al. (2010):
"The LSR is the rest frame at the location of the Sun of a star that would
be on a circular orbit in the gravitational potential one would obtain by
azimuthally averaging away non-axisymmetric features in the actual Galactic
potential." No such orbit truly exists, but it is still a commonly used
velocity frame.
We use default values from Schönrich et al. (2010) for the barycentric
velocity relative to the LSR, which is defined in Galactic (right-handed)
cartesian velocity components
:math:`(U, V, W) = (11.1, 12.24, 7.25)~{{\rm km}}~{{\rm s}}^{{-1}}`. These
values are customizable via the ``v_bary`` argument which specifies the
velocity of the solar system barycenter with respect to the LSR.
The frame attributes are listed under **Other Parameters**.
"""
frame_specific_representation_info = {
r.SphericalRepresentation: [
RepresentationMapping('lon', 'l'),
RepresentationMapping('lat', 'b')
]
}
default_representation = r.SphericalRepresentation
default_differential = r.SphericalCosLatDifferential
# frame attributes:
v_bary = DifferentialAttribute(default=v_bary_Schoenrich2010)
@frame_transform_graph.transform(AffineTransform, Galactic, GalacticLSR)
def galactic_to_galacticlsr(galactic_coord, lsr_frame):
v_bary_gal = Galactic(lsr_frame.v_bary.to_cartesian())
v_offset = v_bary_gal.data.represent_as(r.CartesianDifferential)
offset = r.CartesianRepresentation([0, 0, 0]*u.au, differentials=v_offset)
return None, offset
@frame_transform_graph.transform(AffineTransform, GalacticLSR, Galactic)
def galacticlsr_to_galactic(lsr_coord, galactic_frame):
v_bary_gal = Galactic(lsr_coord.v_bary.to_cartesian())
v_offset = v_bary_gal.data.represent_as(r.CartesianDifferential)
offset = r.CartesianRepresentation([0, 0, 0]*u.au, differentials=-v_offset)
return None, offset
|
c5359a834ab83148c5c589c18b320d082a511a1d2b24dc34db19ab05102e6402 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from astropy.coordinates.matrix_utilities import (rotation_matrix,
matrix_product, matrix_transpose)
from astropy.coordinates.baseframe import frame_transform_graph
from astropy.coordinates.transformations import DynamicMatrixTransform
from .fk5 import FK5
from .fk4 import FK4NoETerms
from .utils import EQUINOX_B1950, EQUINOX_J2000
from .galactic import Galactic
# Galactic to/from FK4/FK5 ----------------------->
# can't be static because the equinox is needed
@frame_transform_graph.transform(DynamicMatrixTransform, FK5, Galactic)
def fk5_to_gal(fk5coord, galframe):
# need precess to J2000 first
pmat = fk5coord._precession_matrix(fk5coord.equinox, EQUINOX_J2000)
mat1 = rotation_matrix(180 - Galactic._lon0_J2000.degree, 'z')
mat2 = rotation_matrix(90 - Galactic._ngp_J2000.dec.degree, 'y')
mat3 = rotation_matrix(Galactic._ngp_J2000.ra.degree, 'z')
return matrix_product(mat1, mat2, mat3, pmat)
@frame_transform_graph.transform(DynamicMatrixTransform, Galactic, FK5)
def _gal_to_fk5(galcoord, fk5frame):
return matrix_transpose(fk5_to_gal(fk5frame, galcoord))
@frame_transform_graph.transform(DynamicMatrixTransform, FK4NoETerms, Galactic)
def fk4_to_gal(fk4coords, galframe):
mat1 = rotation_matrix(180 - Galactic._lon0_B1950.degree, 'z')
mat2 = rotation_matrix(90 - Galactic._ngp_B1950.dec.degree, 'y')
mat3 = rotation_matrix(Galactic._ngp_B1950.ra.degree, 'z')
matprec = fk4coords._precession_matrix(fk4coords.equinox, EQUINOX_B1950)
return matrix_product(mat1, mat2, mat3, matprec)
@frame_transform_graph.transform(DynamicMatrixTransform, Galactic, FK4NoETerms)
def gal_to_fk4(galcoords, fk4frame):
return matrix_transpose(fk4_to_gal(fk4frame, galcoords))
|
5d00674914628b7948aac3edd6248672039eeddb2066f5b45475046a3102b7d9 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from astropy import units as u
from astropy.utils.decorators import format_doc
from astropy.coordinates.angles import Angle
from astropy.coordinates import representation as r
from astropy.coordinates.baseframe import BaseCoordinateFrame, RepresentationMapping, base_doc
# these are needed for defining the NGP
from .fk5 import FK5
from .fk4 import FK4NoETerms
__all__ = ['Galactic']
doc_components = """
l : `Angle`, optional, must be keyword
The Galactic longitude for this object (``b`` must also be given and
``representation`` must be None).
b : `Angle`, optional, must be keyword
The Galactic latitude for this object (``l`` must also be given and
``representation`` must be None).
distance : `~astropy.units.Quantity`, optional, must be keyword
The Distance for this object along the line-of-sight.
pm_l_cosb : :class:`~astropy.units.Quantity`, optional, must be keyword
The proper motion in Galactic longitude (including the ``cos(b)`` term)
for this object (``pm_b`` must also be given).
pm_b : :class:`~astropy.units.Quantity`, optional, must be keyword
The proper motion in Galactic latitude for this object (``pm_l_cosb``
must also be given).
radial_velocity : :class:`~astropy.units.Quantity`, optional, must be keyword
The radial velocity of this object.
"""
doc_footer = """
Notes
-----
.. [1] Blaauw, A.; Gum, C. S.; Pawsey, J. L.; Westerhout, G. (1960), "The
new I.A.U. system of galactic coordinates (1958 revision),"
`MNRAS, Vol 121, pp.123 <http://adsabs.harvard.edu/abs/1960MNRAS.121..123B>`_.
"""
@format_doc(base_doc, components=doc_components, footer=doc_footer)
class Galactic(BaseCoordinateFrame):
"""
A coordinate or frame in the Galactic coordinate system.
This frame is used in a variety of Galactic contexts because it has as its
x-y plane the plane of the Milky Way. The positive x direction (i.e., the
l=0, b=0 direction) points to the center of the Milky Way and the z-axis
points toward the North Galactic Pole (following the IAU's 1958 definition
[1]_). However, unlike the `~astropy.coordinates.Galactocentric` frame, the
*origin* of this frame in 3D space is the solar system barycenter, not
the center of the Milky Way.
"""
frame_specific_representation_info = {
r.SphericalRepresentation: [
RepresentationMapping('lon', 'l'),
RepresentationMapping('lat', 'b')
],
r.CartesianRepresentation: [
RepresentationMapping('x', 'u'),
RepresentationMapping('y', 'v'),
RepresentationMapping('z', 'w')
],
r.CartesianDifferential: [
RepresentationMapping('d_x', 'U', u.km/u.s),
RepresentationMapping('d_y', 'V', u.km/u.s),
RepresentationMapping('d_z', 'W', u.km/u.s)
]
}
default_representation = r.SphericalRepresentation
default_differential = r.SphericalCosLatDifferential
# North galactic pole and zeropoint of l in FK4/FK5 coordinates. Needed for
# transformations to/from FK4/5
# These are from the IAU's definition of galactic coordinates
_ngp_B1950 = FK4NoETerms(ra=192.25*u.degree, dec=27.4*u.degree)
_lon0_B1950 = Angle(123, u.degree)
# These are *not* from Reid & Brunthaler 2004 - instead, they were
# derived by doing:
#
# >>> FK4NoETerms(ra=192.25*u.degree, dec=27.4*u.degree).transform_to(FK5)
#
# This gives better consistency with other codes than using the values
# from Reid & Brunthaler 2004 and the best self-consistency between FK5
# -> Galactic and FK5 -> FK4 -> Galactic. The lon0 angle was found by
# optimizing the self-consistency.
_ngp_J2000 = FK5(ra=192.8594812065348*u.degree, dec=27.12825118085622*u.degree)
_lon0_J2000 = Angle(122.9319185680026, u.degree)
|
4b2605de01c4c465c3ca5a265e0dddb39a54d4459ecafa3b18a804641f7e5029 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from astropy.coordinates.matrix_utilities import (rotation_matrix,
matrix_product, matrix_transpose)
from astropy.coordinates.baseframe import frame_transform_graph
from astropy.coordinates.transformations import DynamicMatrixTransform
from .fk5 import FK5
from .icrs import ICRS
from .utils import EQUINOX_J2000
def _icrs_to_fk5_matrix():
"""
B-matrix from USNO circular 179. Used by the ICRS->FK5 transformation
functions.
"""
eta0 = -19.9 / 3600000.
xi0 = 9.1 / 3600000.
da0 = -22.9 / 3600000.
m1 = rotation_matrix(-eta0, 'x')
m2 = rotation_matrix(xi0, 'y')
m3 = rotation_matrix(da0, 'z')
return matrix_product(m1, m2, m3)
# define this here because it only needs to be computed once
_ICRS_TO_FK5_J2000_MAT = _icrs_to_fk5_matrix()
@frame_transform_graph.transform(DynamicMatrixTransform, ICRS, FK5)
def icrs_to_fk5(icrscoord, fk5frame):
# ICRS is by design very close to J2000 equinox
pmat = fk5frame._precession_matrix(EQUINOX_J2000, fk5frame.equinox)
return matrix_product(pmat, _ICRS_TO_FK5_J2000_MAT)
# can't be static because the equinox is needed
@frame_transform_graph.transform(DynamicMatrixTransform, FK5, ICRS)
def fk5_to_icrs(fk5coord, icrsframe):
# ICRS is by design very close to J2000 equinox
pmat = fk5coord._precession_matrix(fk5coord.equinox, EQUINOX_J2000)
return matrix_product(matrix_transpose(_ICRS_TO_FK5_J2000_MAT), pmat)
|
3cbb95e0c8323b568321a04a6a49e86b33dc1009098649534ca50b7f9acefccc | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from astropy.utils.decorators import format_doc
from astropy.coordinates.attributes import TimeAttribute
from astropy.coordinates.baseframe import base_doc
from .baseradec import doc_components, BaseRADecFrame
from .utils import DEFAULT_OBSTIME
__all__ = ['CIRS']
doc_footer = """
Other parameters
----------------
obstime : `~astropy.time.Time`
The time at which the observation is taken. Used for determining the
position of the Earth and its precession.
"""
@format_doc(base_doc, components=doc_components, footer=doc_footer)
class CIRS(BaseRADecFrame):
"""
A coordinate or frame in the Celestial Intermediate Reference System (CIRS).
The frame attributes are listed under **Other Parameters**.
"""
obstime = TimeAttribute(default=DEFAULT_OBSTIME)
# The "self-transform" is defined in icrs_cirs_transformations.py, because in
# the current implementation it goes through ICRS (like GCRS)
|
aaf5e868cdec9f697ba6d981ac0ba262168d44251e08f6b86520f0312a0003e5 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from copy import deepcopy
import numpy as np
from astropy import units as u
from astropy.tests.helper import (catch_warnings, pytest,
assert_quantity_allclose as assert_allclose)
from astropy.utils import OrderedDescriptorContainer
from astropy.utils.compat import NUMPY_LT_1_14
from astropy.utils.exceptions import AstropyWarning
from astropy.coordinates import representation as r
from astropy.coordinates.representation import REPRESENTATION_CLASSES
from astropy.units import allclose
from .test_representation import unitphysics # this fixture is used below
def setup_function(func):
func.REPRESENTATION_CLASSES_ORIG = deepcopy(REPRESENTATION_CLASSES)
def teardown_function(func):
REPRESENTATION_CLASSES.clear()
REPRESENTATION_CLASSES.update(func.REPRESENTATION_CLASSES_ORIG)
def test_frame_attribute_descriptor():
""" Unit tests of the Attribute descriptor """
from astropy.coordinates.attributes import Attribute
class TestAttributes(metaclass=OrderedDescriptorContainer):
attr_none = Attribute()
attr_2 = Attribute(default=2)
attr_3_attr2 = Attribute(default=3, secondary_attribute='attr_2')
attr_none_attr2 = Attribute(default=None, secondary_attribute='attr_2')
attr_none_nonexist = Attribute(default=None, secondary_attribute='nonexist')
t = TestAttributes()
# Defaults
assert t.attr_none is None
assert t.attr_2 == 2
assert t.attr_3_attr2 == 3
assert t.attr_none_attr2 == t.attr_2
assert t.attr_none_nonexist is None # No default and non-existent secondary attr
# Setting values via '_'-prefixed internal vars (as would normally done in __init__)
t._attr_none = 10
assert t.attr_none == 10
t._attr_2 = 20
assert t.attr_2 == 20
assert t.attr_3_attr2 == 3
assert t.attr_none_attr2 == t.attr_2
t._attr_none_attr2 = 40
assert t.attr_none_attr2 == 40
# Make sure setting values via public attribute fails
with pytest.raises(AttributeError) as err:
t.attr_none = 5
assert 'Cannot set frame attribute' in str(err)
def test_frame_subclass_attribute_descriptor():
from astropy.coordinates.builtin_frames import FK4
from astropy.coordinates.attributes import Attribute, TimeAttribute
from astropy.time import Time
_EQUINOX_B1980 = Time('B1980', scale='tai')
class MyFK4(FK4):
# equinox inherited from FK4, obstime overridden, and newattr is new
obstime = TimeAttribute(default=_EQUINOX_B1980)
newattr = Attribute(default='newattr')
mfk4 = MyFK4()
assert mfk4.equinox.value == 'B1950.000'
assert mfk4.obstime.value == 'B1980.000'
assert mfk4.newattr == 'newattr'
assert set(mfk4.get_frame_attr_names()) == set(['equinox', 'obstime', 'newattr'])
mfk4 = MyFK4(equinox='J1980.0', obstime='J1990.0', newattr='world')
assert mfk4.equinox.value == 'J1980.000'
assert mfk4.obstime.value == 'J1990.000'
assert mfk4.newattr == 'world'
def test_create_data_frames():
from astropy.coordinates.builtin_frames import ICRS
# from repr
i1 = ICRS(r.SphericalRepresentation(1*u.deg, 2*u.deg, 3*u.kpc))
i2 = ICRS(r.UnitSphericalRepresentation(lon=1*u.deg, lat=2*u.deg))
# from preferred name
i3 = ICRS(ra=1*u.deg, dec=2*u.deg, distance=3*u.kpc)
i4 = ICRS(ra=1*u.deg, dec=2*u.deg)
assert i1.data.lat == i3.data.lat
assert i1.data.lon == i3.data.lon
assert i1.data.distance == i3.data.distance
assert i2.data.lat == i4.data.lat
assert i2.data.lon == i4.data.lon
# now make sure the preferred names work as properties
assert_allclose(i1.ra, i3.ra)
assert_allclose(i2.ra, i4.ra)
assert_allclose(i1.distance, i3.distance)
with pytest.raises(AttributeError):
i1.ra = [11.]*u.deg
def test_create_orderered_data():
from astropy.coordinates.builtin_frames import ICRS, Galactic, AltAz
TOL = 1e-10*u.deg
i = ICRS(1*u.deg, 2*u.deg)
assert (i.ra - 1*u.deg) < TOL
assert (i.dec - 2*u.deg) < TOL
g = Galactic(1*u.deg, 2*u.deg)
assert (g.l - 1*u.deg) < TOL
assert (g.b - 2*u.deg) < TOL
a = AltAz(1*u.deg, 2*u.deg)
assert (a.az - 1*u.deg) < TOL
assert (a.alt - 2*u.deg) < TOL
with pytest.raises(TypeError):
ICRS(1*u.deg, 2*u.deg, 1*u.deg, 2*u.deg)
with pytest.raises(TypeError):
sph = r.SphericalRepresentation(1*u.deg, 2*u.deg, 3*u.kpc)
ICRS(sph, 1*u.deg, 2*u.deg)
def test_create_nodata_frames():
from astropy.coordinates.builtin_frames import ICRS, FK4, FK5
i = ICRS()
assert len(i.get_frame_attr_names()) == 0
f5 = FK5()
assert f5.equinox == FK5.get_frame_attr_names()['equinox']
f4 = FK4()
assert f4.equinox == FK4.get_frame_attr_names()['equinox']
# obstime is special because it's a property that uses equinox if obstime is not set
assert f4.obstime in (FK4.get_frame_attr_names()['obstime'],
FK4.get_frame_attr_names()['equinox'])
def test_no_data_nonscalar_frames():
from astropy.coordinates.builtin_frames import AltAz
from astropy.time import Time
a1 = AltAz(obstime=Time('2012-01-01') + np.arange(10.) * u.day,
temperature=np.ones((3, 1)) * u.deg_C)
assert a1.obstime.shape == (3, 10)
assert a1.temperature.shape == (3, 10)
assert a1.shape == (3, 10)
with pytest.raises(ValueError) as exc:
AltAz(obstime=Time('2012-01-01') + np.arange(10.) * u.day,
temperature=np.ones((3,)) * u.deg_C)
assert 'inconsistent shapes' in str(exc)
def test_frame_repr():
from astropy.coordinates.builtin_frames import ICRS, FK5
i = ICRS()
assert repr(i) == '<ICRS Frame>'
f5 = FK5()
assert repr(f5).startswith('<FK5 Frame (equinox=')
i2 = ICRS(ra=1*u.deg, dec=2*u.deg)
i3 = ICRS(ra=1*u.deg, dec=2*u.deg, distance=3*u.kpc)
assert repr(i2) == ('<ICRS Coordinate: (ra, dec) in deg\n'
' ({})>').format(' 1., 2.' if NUMPY_LT_1_14
else '1., 2.')
assert repr(i3) == ('<ICRS Coordinate: (ra, dec, distance) in (deg, deg, kpc)\n'
' ({})>').format(' 1., 2., 3.' if NUMPY_LT_1_14
else '1., 2., 3.')
# try with arrays
i2 = ICRS(ra=[1.1, 2.1]*u.deg, dec=[2.1, 3.1]*u.deg)
i3 = ICRS(ra=[1.1, 2.1]*u.deg, dec=[-15.6, 17.1]*u.deg, distance=[11., 21.]*u.kpc)
assert repr(i2) == ('<ICRS Coordinate: (ra, dec) in deg\n'
' [{}]>').format('( 1.1, 2.1), ( 2.1, 3.1)'
if NUMPY_LT_1_14 else
'(1.1, 2.1), (2.1, 3.1)')
if NUMPY_LT_1_14:
assert repr(i3) == ('<ICRS Coordinate: (ra, dec, distance) in (deg, deg, kpc)\n'
' [( 1.1, -15.6, 11.), ( 2.1, 17.1, 21.)]>')
else:
assert repr(i3) == ('<ICRS Coordinate: (ra, dec, distance) in (deg, deg, kpc)\n'
' [(1.1, -15.6, 11.), (2.1, 17.1, 21.)]>')
def test_frame_repr_vels():
from astropy.coordinates.builtin_frames import ICRS
i = ICRS(ra=1*u.deg, dec=2*u.deg,
pm_ra_cosdec=1*u.marcsec/u.yr, pm_dec=2*u.marcsec/u.yr)
# unit comes out as mas/yr because of the preferred units defined in the
# frame RepresentationMapping
assert repr(i) == ('<ICRS Coordinate: (ra, dec) in deg\n'
' ({0})\n'
' (pm_ra_cosdec, pm_dec) in mas / yr\n'
' ({0})>').format(' 1., 2.' if NUMPY_LT_1_14 else
'1., 2.')
def test_converting_units():
import re
from astropy.coordinates.baseframe import RepresentationMapping
from astropy.coordinates.builtin_frames import ICRS, FK5
# this is a regular expression that with split (see below) removes what's
# the decimal point to fix rounding problems
rexrepr = re.compile(r'(.*?=\d\.).*?( .*?=\d\.).*?( .*)')
# Use values that aren't subject to rounding down to X.9999...
i2 = ICRS(ra=2.*u.deg, dec=2.*u.deg)
i2_many = ICRS(ra=[2., 4.]*u.deg, dec=[2., -8.1]*u.deg)
# converting from FK5 to ICRS and back changes the *internal* representation,
# but it should still come out in the preferred form
i4 = i2.transform_to(FK5).transform_to(ICRS)
i4_many = i2_many.transform_to(FK5).transform_to(ICRS)
ri2 = ''.join(rexrepr.split(repr(i2)))
ri4 = ''.join(rexrepr.split(repr(i4)))
assert ri2 == ri4
assert i2.data.lon.unit != i4.data.lon.unit # Internal repr changed
ri2_many = ''.join(rexrepr.split(repr(i2_many)))
ri4_many = ''.join(rexrepr.split(repr(i4_many)))
assert ri2_many == ri4_many
assert i2_many.data.lon.unit != i4_many.data.lon.unit # Internal repr changed
# but that *shouldn't* hold if we turn off units for the representation
class FakeICRS(ICRS):
frame_specific_representation_info = {
'spherical': [RepresentationMapping('lon', 'ra', u.hourangle),
RepresentationMapping('lat', 'dec', None),
RepresentationMapping('distance', 'distance')] # should fall back to default of None unit
}
fi = FakeICRS(i4.data)
ri2 = ''.join(rexrepr.split(repr(i2)))
rfi = ''.join(rexrepr.split(repr(fi)))
rfi = re.sub('FakeICRS', 'ICRS', rfi) # Force frame name to match
assert ri2 != rfi
# the attributes should also get the right units
assert i2.dec.unit == i4.dec.unit
# unless no/explicitly given units
assert i2.dec.unit != fi.dec.unit
assert i2.ra.unit != fi.ra.unit
assert fi.ra.unit == u.hourangle
def test_representation_info():
from astropy.coordinates.baseframe import RepresentationMapping
from astropy.coordinates.builtin_frames import ICRS
class NewICRS1(ICRS):
frame_specific_representation_info = {
r.SphericalRepresentation: [
RepresentationMapping('lon', 'rara', u.hourangle),
RepresentationMapping('lat', 'decdec', u.degree),
RepresentationMapping('distance', 'distance', u.kpc)]
}
i1 = NewICRS1(rara=10*u.degree, decdec=-12*u.deg, distance=1000*u.pc,
pm_rara_cosdecdec=100*u.mas/u.yr,
pm_decdec=17*u.mas/u.yr,
radial_velocity=10*u.km/u.s)
assert allclose(i1.rara, 10*u.deg)
assert i1.rara.unit == u.hourangle
assert allclose(i1.decdec, -12*u.deg)
assert allclose(i1.distance, 1000*u.pc)
assert i1.distance.unit == u.kpc
assert allclose(i1.pm_rara_cosdecdec, 100*u.mas/u.yr)
assert allclose(i1.pm_decdec, 17*u.mas/u.yr)
# this should auto-set the names of UnitSpherical:
i1.set_representation_cls(r.UnitSphericalRepresentation,
s=r.UnitSphericalCosLatDifferential)
assert allclose(i1.rara, 10*u.deg)
assert allclose(i1.decdec, -12*u.deg)
assert allclose(i1.pm_rara_cosdecdec, 100*u.mas/u.yr)
assert allclose(i1.pm_decdec, 17*u.mas/u.yr)
# For backwards compatibility, we also support the string name in the
# representation info dictionary:
class NewICRS2(ICRS):
frame_specific_representation_info = {
'spherical': [
RepresentationMapping('lon', 'ang1', u.hourangle),
RepresentationMapping('lat', 'ang2', u.degree),
RepresentationMapping('distance', 'howfar', u.kpc)]
}
i2 = NewICRS2(ang1=10*u.degree, ang2=-12*u.deg, howfar=1000*u.pc)
assert allclose(i2.ang1, 10*u.deg)
assert i2.ang1.unit == u.hourangle
assert allclose(i2.ang2, -12*u.deg)
assert allclose(i2.howfar, 1000*u.pc)
assert i2.howfar.unit == u.kpc
# Test that the differential kwargs get overridden
class NewICRS3(ICRS):
frame_specific_representation_info = {
r.SphericalCosLatDifferential: [
RepresentationMapping('d_lon_coslat', 'pm_ang1', u.hourangle/u.year),
RepresentationMapping('d_lat', 'pm_ang2'),
RepresentationMapping('d_distance', 'vlos', u.kpc/u.Myr)]
}
i3 = NewICRS3(lon=10*u.degree, lat=-12*u.deg, distance=1000*u.pc,
pm_ang1=1*u.mas/u.yr, pm_ang2=2*u.mas/u.yr,
vlos=100*u.km/u.s)
assert allclose(i3.pm_ang1, 1*u.mas/u.yr)
assert i3.pm_ang1.unit == u.hourangle/u.year
assert allclose(i3.pm_ang2, 2*u.mas/u.yr)
assert allclose(i3.vlos, 100*u.km/u.s)
assert i3.vlos.unit == u.kpc/u.Myr
def test_realizing():
from astropy.coordinates.builtin_frames import ICRS, FK5
from astropy.time import Time
rep = r.SphericalRepresentation(1*u.deg, 2*u.deg, 3*u.kpc)
i = ICRS()
i2 = i.realize_frame(rep)
assert not i.has_data
assert i2.has_data
f = FK5(equinox=Time('J2001'))
f2 = f.realize_frame(rep)
assert not f.has_data
assert f2.has_data
assert f2.equinox == f.equinox
assert f2.equinox != FK5.get_frame_attr_names()['equinox']
# Check that a nicer error message is returned:
with pytest.raises(TypeError) as excinfo:
f.realize_frame(f.representation_type)
assert ('Class passed as data instead of a representation' in
excinfo.value.args[0])
def test_replicating():
from astropy.coordinates.builtin_frames import ICRS, AltAz
from astropy.time import Time
i = ICRS(ra=[1]*u.deg, dec=[2]*u.deg)
icopy = i.replicate(copy=True)
irepl = i.replicate(copy=False)
i.data._lat[:] = 0*u.deg
assert np.all(i.data.lat == irepl.data.lat)
assert np.all(i.data.lat != icopy.data.lat)
iclone = i.replicate_without_data()
assert i.has_data
assert not iclone.has_data
aa = AltAz(alt=1*u.deg, az=2*u.deg, obstime=Time('J2000'))
aaclone = aa.replicate_without_data(obstime=Time('J2001'))
assert not aaclone.has_data
assert aa.obstime != aaclone.obstime
assert aa.pressure == aaclone.pressure
assert aa.obswl == aaclone.obswl
def test_getitem():
from astropy.coordinates.builtin_frames import ICRS
rep = r.SphericalRepresentation(
[1, 2, 3]*u.deg, [4, 5, 6]*u.deg, [7, 8, 9]*u.kpc)
i = ICRS(rep)
assert len(i.ra) == 3
iidx = i[1:]
assert len(iidx.ra) == 2
iidx2 = i[0]
assert iidx2.ra.isscalar
def test_transform():
"""
This test just makes sure the transform architecture works, but does *not*
actually test all the builtin transforms themselves are accurate
"""
from astropy.coordinates.builtin_frames import ICRS, FK4, FK5, Galactic
from astropy.time import Time
i = ICRS(ra=[1, 2]*u.deg, dec=[3, 4]*u.deg)
f = i.transform_to(FK5)
i2 = f.transform_to(ICRS)
assert i2.data.__class__ == r.UnitSphericalRepresentation
assert_allclose(i.ra, i2.ra)
assert_allclose(i.dec, i2.dec)
i = ICRS(ra=[1, 2]*u.deg, dec=[3, 4]*u.deg, distance=[5, 6]*u.kpc)
f = i.transform_to(FK5)
i2 = f.transform_to(ICRS)
assert i2.data.__class__ != r.UnitSphericalRepresentation
f = FK5(ra=1*u.deg, dec=2*u.deg, equinox=Time('J2001'))
f4 = f.transform_to(FK4)
f4_2 = f.transform_to(FK4(equinox=f.equinox))
# make sure attributes are copied over correctly
assert f4.equinox == FK4.get_frame_attr_names()['equinox']
assert f4_2.equinox == f.equinox
# make sure self-transforms also work
i = ICRS(ra=[1, 2]*u.deg, dec=[3, 4]*u.deg)
i2 = i.transform_to(ICRS)
assert_allclose(i.ra, i2.ra)
assert_allclose(i.dec, i2.dec)
f = FK5(ra=1*u.deg, dec=2*u.deg, equinox=Time('J2001'))
f2 = f.transform_to(FK5) # default equinox, so should be *different*
assert f2.equinox == FK5().equinox
with pytest.raises(AssertionError):
assert_allclose(f.ra, f2.ra)
with pytest.raises(AssertionError):
assert_allclose(f.dec, f2.dec)
# finally, check Galactic round-tripping
i1 = ICRS(ra=[1, 2]*u.deg, dec=[3, 4]*u.deg)
i2 = i1.transform_to(Galactic).transform_to(ICRS)
assert_allclose(i1.ra, i2.ra)
assert_allclose(i1.dec, i2.dec)
def test_transform_to_nonscalar_nodata_frame():
# https://github.com/astropy/astropy/pull/5254#issuecomment-241592353
from astropy.coordinates.builtin_frames import ICRS, FK5
from astropy.time import Time
times = Time('2016-08-23') + np.linspace(0, 10, 12)*u.day
coo1 = ICRS(ra=[[0.], [10.], [20.]]*u.deg,
dec=[[-30.], [30.], [60.]]*u.deg)
coo2 = coo1.transform_to(FK5(equinox=times))
assert coo2.shape == (3, 12)
def test_sep():
from astropy.coordinates.builtin_frames import ICRS
i1 = ICRS(ra=0*u.deg, dec=1*u.deg)
i2 = ICRS(ra=0*u.deg, dec=2*u.deg)
sep = i1.separation(i2)
assert sep.deg == 1
i3 = ICRS(ra=[1, 2]*u.deg, dec=[3, 4]*u.deg, distance=[5, 6]*u.kpc)
i4 = ICRS(ra=[1, 2]*u.deg, dec=[3, 4]*u.deg, distance=[4, 5]*u.kpc)
sep3d = i3.separation_3d(i4)
assert_allclose(sep3d.to(u.kpc), np.array([1, 1])*u.kpc)
# check that it works even with velocities
i5 = ICRS(ra=[1, 2]*u.deg, dec=[3, 4]*u.deg, distance=[5, 6]*u.kpc,
pm_ra_cosdec=[1, 2]*u.mas/u.yr, pm_dec=[3, 4]*u.mas/u.yr,
radial_velocity=[5, 6]*u.km/u.s)
i6 = ICRS(ra=[1, 2]*u.deg, dec=[3, 4]*u.deg, distance=[7, 8]*u.kpc,
pm_ra_cosdec=[1, 2]*u.mas/u.yr, pm_dec=[3, 4]*u.mas/u.yr,
radial_velocity=[5, 6]*u.km/u.s)
sep3d = i5.separation_3d(i6)
assert_allclose(sep3d.to(u.kpc), np.array([2, 2])*u.kpc)
def test_time_inputs():
"""
Test validation and conversion of inputs for equinox and obstime attributes.
"""
from astropy.time import Time
from astropy.coordinates.builtin_frames import FK4
c = FK4(1 * u.deg, 2 * u.deg, equinox='J2001.5', obstime='2000-01-01 12:00:00')
assert c.equinox == Time('J2001.5')
assert c.obstime == Time('2000-01-01 12:00:00')
with pytest.raises(ValueError) as err:
c = FK4(1 * u.deg, 2 * u.deg, equinox=1.5)
assert 'Invalid time input' in str(err)
with pytest.raises(ValueError) as err:
c = FK4(1 * u.deg, 2 * u.deg, obstime='hello')
assert 'Invalid time input' in str(err)
# A vector time should work if the shapes match, but we don't automatically
# broadcast the basic data (just like time).
FK4([1, 2] * u.deg, [2, 3] * u.deg, obstime=['J2000', 'J2001'])
with pytest.raises(ValueError) as err:
FK4(1 * u.deg, 2 * u.deg, obstime=['J2000', 'J2001'])
assert 'shape' in str(err)
def test_is_frame_attr_default():
"""
Check that the `is_frame_attr_default` machinery works as expected
"""
from astropy.time import Time
from astropy.coordinates.builtin_frames import FK5
c1 = FK5(ra=1*u.deg, dec=1*u.deg)
c2 = FK5(ra=1*u.deg, dec=1*u.deg, equinox=FK5.get_frame_attr_names()['equinox'])
c3 = FK5(ra=1*u.deg, dec=1*u.deg, equinox=Time('J2001.5'))
assert c1.equinox == c2.equinox
assert c1.equinox != c3.equinox
assert c1.is_frame_attr_default('equinox')
assert not c2.is_frame_attr_default('equinox')
assert not c3.is_frame_attr_default('equinox')
c4 = c1.realize_frame(r.UnitSphericalRepresentation(3*u.deg, 4*u.deg))
c5 = c2.realize_frame(r.UnitSphericalRepresentation(3*u.deg, 4*u.deg))
assert c4.is_frame_attr_default('equinox')
assert not c5.is_frame_attr_default('equinox')
def test_altaz_attributes():
from astropy.time import Time
from astropy.coordinates import EarthLocation, AltAz
aa = AltAz(1*u.deg, 2*u.deg)
assert aa.obstime is None
assert aa.location is None
aa2 = AltAz(1*u.deg, 2*u.deg, obstime='J2000')
assert aa2.obstime == Time('J2000')
aa3 = AltAz(1*u.deg, 2*u.deg, location=EarthLocation(0*u.deg, 0*u.deg, 0*u.m))
assert isinstance(aa3.location, EarthLocation)
def test_representation():
"""
Test the getter and setter properties for `representation`
"""
from astropy.coordinates.builtin_frames import ICRS
# Create the frame object.
icrs = ICRS(ra=1*u.deg, dec=1*u.deg)
data = icrs.data
# Create some representation objects.
icrs_cart = icrs.cartesian
icrs_spher = icrs.spherical
# Testing when `_representation` set to `CartesianRepresentation`.
icrs.representation_type = r.CartesianRepresentation
assert icrs.representation_type == r.CartesianRepresentation
assert icrs_cart.x == icrs.x
assert icrs_cart.y == icrs.y
assert icrs_cart.z == icrs.z
assert icrs.data == data
# Testing that an ICRS object in CartesianRepresentation must not have spherical attributes.
for attr in ('ra', 'dec', 'distance'):
with pytest.raises(AttributeError) as err:
getattr(icrs, attr)
assert 'object has no attribute' in str(err)
# Testing when `_representation` set to `CylindricalRepresentation`.
icrs.representation_type = r.CylindricalRepresentation
assert icrs.representation_type == r.CylindricalRepresentation
assert icrs.data == data
# Testing setter input using text argument for spherical.
icrs.representation_type = 'spherical'
assert icrs.representation_type is r.SphericalRepresentation
assert icrs_spher.lat == icrs.dec
assert icrs_spher.lon == icrs.ra
assert icrs_spher.distance == icrs.distance
assert icrs.data == data
# Testing that an ICRS object in SphericalRepresentation must not have cartesian attributes.
for attr in ('x', 'y', 'z'):
with pytest.raises(AttributeError) as err:
getattr(icrs, attr)
assert 'object has no attribute' in str(err)
# Testing setter input using text argument for cylindrical.
icrs.representation_type = 'cylindrical'
assert icrs.representation_type is r.CylindricalRepresentation
assert icrs.data == data
with pytest.raises(ValueError) as err:
icrs.representation_type = 'WRONG'
assert 'but must be a BaseRepresentation class' in str(err)
with pytest.raises(ValueError) as err:
icrs.representation_type = ICRS
assert 'but must be a BaseRepresentation class' in str(err)
def test_represent_as():
from astropy.coordinates.builtin_frames import ICRS
icrs = ICRS(ra=1*u.deg, dec=1*u.deg)
cart1 = icrs.represent_as('cartesian')
cart2 = icrs.represent_as(r.CartesianRepresentation)
cart1.x == cart2.x
cart1.y == cart2.y
cart1.z == cart2.z
# now try with velocities
icrs = ICRS(ra=0*u.deg, dec=0*u.deg, distance=10*u.kpc,
pm_ra_cosdec=0*u.mas/u.yr, pm_dec=0*u.mas/u.yr,
radial_velocity=1*u.km/u.s)
# single string
rep2 = icrs.represent_as('cylindrical')
assert isinstance(rep2, r.CylindricalRepresentation)
assert isinstance(rep2.differentials['s'], r.CylindricalDifferential)
# single class with positional in_frame_units, verify that warning raised
with catch_warnings() as w:
icrs.represent_as(r.CylindricalRepresentation, False)
assert len(w) == 1
assert w[0].category == AstropyWarning
assert 'argument position' in str(w[0].message)
# TODO: this should probably fail in the future once we figure out a better
# workaround for dealing with UnitSphericalRepresentation's with
# RadialDifferential's
# two classes
# rep2 = icrs.represent_as(r.CartesianRepresentation,
# r.SphericalCosLatDifferential)
# assert isinstance(rep2, r.CartesianRepresentation)
# assert isinstance(rep2.differentials['s'], r.SphericalCosLatDifferential)
with pytest.raises(ValueError):
icrs.represent_as('odaigahara')
def test_shorthand_representations():
from astropy.coordinates.builtin_frames import ICRS
rep = r.CartesianRepresentation([1, 2, 3]*u.pc)
dif = r.CartesianDifferential([1, 2, 3]*u.km/u.s)
rep = rep.with_differentials(dif)
icrs = ICRS(rep)
sph = icrs.spherical
assert isinstance(sph, r.SphericalRepresentation)
assert isinstance(sph.differentials['s'], r.SphericalDifferential)
sph = icrs.sphericalcoslat
assert isinstance(sph, r.SphericalRepresentation)
assert isinstance(sph.differentials['s'], r.SphericalCosLatDifferential)
def test_dynamic_attrs():
from astropy.coordinates.builtin_frames import ICRS
c = ICRS(1*u.deg, 2*u.deg)
assert 'ra' in dir(c)
assert 'dec' in dir(c)
with pytest.raises(AttributeError) as err:
c.blahblah
assert "object has no attribute 'blahblah'" in str(err)
with pytest.raises(AttributeError) as err:
c.ra = 1
assert "Cannot set any frame attribute" in str(err)
c.blahblah = 1
assert c.blahblah == 1
def test_nodata_error():
from astropy.coordinates.builtin_frames import ICRS
i = ICRS()
with pytest.raises(ValueError) as excinfo:
i.data
assert 'does not have associated data' in str(excinfo.value)
def test_len0_data():
from astropy.coordinates.builtin_frames import ICRS
i = ICRS([]*u.deg, []*u.deg)
assert i.has_data
repr(i)
def test_quantity_attributes():
from astropy.coordinates.builtin_frames import GCRS
# make sure we can create a GCRS frame with valid inputs
GCRS(obstime='J2002', obsgeoloc=[1, 2, 3]*u.km, obsgeovel=[4, 5, 6]*u.km/u.s)
# make sure it fails for invalid lovs or vels
with pytest.raises(TypeError):
GCRS(obsgeoloc=[1, 2, 3]) # no unit
with pytest.raises(u.UnitsError):
GCRS(obsgeoloc=[1, 2, 3]*u.km/u.s) # incorrect unit
with pytest.raises(ValueError):
GCRS(obsgeoloc=[1, 3]*u.km) # incorrect shape
@pytest.mark.remote_data
def test_eloc_attributes():
from astropy.coordinates import AltAz, ITRS, GCRS, EarthLocation
el = EarthLocation(lon=12.3*u.deg, lat=45.6*u.deg, height=1*u.km)
it = ITRS(r.SphericalRepresentation(lon=12.3*u.deg, lat=45.6*u.deg, distance=1*u.km))
gc = GCRS(ra=12.3*u.deg, dec=45.6*u.deg, distance=6375*u.km)
el1 = AltAz(location=el).location
assert isinstance(el1, EarthLocation)
# these should match *exactly* because the EarthLocation
assert el1.lat == el.lat
assert el1.lon == el.lon
assert el1.height == el.height
el2 = AltAz(location=it).location
assert isinstance(el2, EarthLocation)
# these should *not* match because giving something in Spherical ITRS is
# *not* the same as giving it as an EarthLocation: EarthLocation is on an
# elliptical geoid. So the longitude should match (because flattening is
# only along the z-axis), but latitude should not. Also, height is relative
# to the *surface* in EarthLocation, but the ITRS distance is relative to
# the center of the Earth
assert not allclose(el2.lat, it.spherical.lat)
assert allclose(el2.lon, it.spherical.lon)
assert el2.height < -6000*u.km
el3 = AltAz(location=gc).location
# GCRS inputs implicitly get transformed to ITRS and then onto
# EarthLocation's elliptical geoid. So both lat and lon shouldn't match
assert isinstance(el3, EarthLocation)
assert not allclose(el3.lat, gc.dec)
assert not allclose(el3.lon, gc.ra)
assert np.abs(el3.height) < 500*u.km
def test_equivalent_frames():
from astropy.coordinates import SkyCoord
from astropy.coordinates.builtin_frames import ICRS, FK4, FK5, AltAz
i = ICRS()
i2 = ICRS(1*u.deg, 2*u.deg)
assert i.is_equivalent_frame(i)
assert i.is_equivalent_frame(i2)
with pytest.raises(TypeError):
assert i.is_equivalent_frame(10)
with pytest.raises(TypeError):
assert i2.is_equivalent_frame(SkyCoord(i2))
f0 = FK5() # this J2000 is TT
f1 = FK5(equinox='J2000')
f2 = FK5(1*u.deg, 2*u.deg, equinox='J2000')
f3 = FK5(equinox='J2010')
f4 = FK4(equinox='J2010')
assert f1.is_equivalent_frame(f1)
assert not i.is_equivalent_frame(f1)
assert f0.is_equivalent_frame(f1)
assert f1.is_equivalent_frame(f2)
assert not f1.is_equivalent_frame(f3)
assert not f3.is_equivalent_frame(f4)
aa1 = AltAz()
aa2 = AltAz(obstime='J2010')
assert aa2.is_equivalent_frame(aa2)
assert not aa1.is_equivalent_frame(i)
assert not aa1.is_equivalent_frame(aa2)
def test_representation_subclass():
# Regression test for #3354
from astropy.coordinates.builtin_frames import FK5
# Normally when instantiating a frame without a distance the frame will try
# and use UnitSphericalRepresentation internally instead of
# SphericalRepresentation.
frame = FK5(representation_type=r.SphericalRepresentation, ra=32 * u.deg, dec=20 * u.deg)
assert type(frame._data) == r.UnitSphericalRepresentation
assert frame.representation_type == r.SphericalRepresentation
# If using a SphericalRepresentation class this used to not work, so we
# test here that this is now fixed.
class NewSphericalRepresentation(r.SphericalRepresentation):
attr_classes = r.SphericalRepresentation.attr_classes
frame = FK5(representation_type=NewSphericalRepresentation, lon=32 * u.deg, lat=20 * u.deg)
assert type(frame._data) == r.UnitSphericalRepresentation
assert frame.representation_type == NewSphericalRepresentation
# A similar issue then happened in __repr__ with subclasses of
# SphericalRepresentation.
assert repr(frame) == ("<FK5 Coordinate (equinox=J2000.000): (lon, lat) in deg\n"
" ({})>").format(' 32., 20.' if NUMPY_LT_1_14
else '32., 20.')
# A more subtle issue is when specifying a custom
# UnitSphericalRepresentation subclass for the data and
# SphericalRepresentation or a subclass for the representation.
class NewUnitSphericalRepresentation(r.UnitSphericalRepresentation):
attr_classes = r.UnitSphericalRepresentation.attr_classes
def __repr__(self):
return "<NewUnitSphericalRepresentation: spam spam spam>"
frame = FK5(NewUnitSphericalRepresentation(lon=32 * u.deg, lat=20 * u.deg),
representation_type=NewSphericalRepresentation)
assert repr(frame) == "<FK5 Coordinate (equinox=J2000.000): spam spam spam>"
def test_getitem_representation():
"""
Make sure current representation survives __getitem__ even if different
from data representation.
"""
from astropy.coordinates.builtin_frames import ICRS
c = ICRS([1, 1] * u.deg, [2, 2] * u.deg)
c.representation_type = 'cartesian'
assert c[0].representation_type is r.CartesianRepresentation
def test_component_error_useful():
"""
Check that a data-less frame gives useful error messages about not having
data when the attributes asked for are possible coordinate components
"""
from astropy.coordinates.builtin_frames import ICRS
i = ICRS()
with pytest.raises(ValueError) as excinfo:
i.ra
assert 'does not have associated data' in str(excinfo.value)
with pytest.raises(AttributeError) as excinfo1:
i.foobar
with pytest.raises(AttributeError) as excinfo2:
i.lon # lon is *not* the component name despite being the underlying representation's name
assert "object has no attribute 'foobar'" in str(excinfo1.value)
assert "object has no attribute 'lon'" in str(excinfo2.value)
def test_cache_clear():
from astropy.coordinates.builtin_frames import ICRS
i = ICRS(1*u.deg, 2*u.deg)
# Add an in frame units version of the rep to the cache.
repr(i)
assert len(i.cache['representation']) == 2
i.cache.clear()
assert len(i.cache['representation']) == 0
def test_inplace_array():
from astropy.coordinates.builtin_frames import ICRS
i = ICRS([[1, 2], [3, 4]]*u.deg, [[10, 20], [30, 40]]*u.deg)
# Add an in frame units version of the rep to the cache.
repr(i)
# Check that repr() has added a rep to the cache
assert len(i.cache['representation']) == 2
# Modify the data
i.data.lon[:, 0] = [100, 200]*u.deg
# Clear the cache
i.cache.clear()
# This will use a second (potentially cached rep)
assert_allclose(i.ra, [[100, 2], [200, 4]]*u.deg)
assert_allclose(i.dec, [[10, 20], [30, 40]]*u.deg)
def test_inplace_change():
from astropy.coordinates.builtin_frames import ICRS
i = ICRS(1*u.deg, 2*u.deg)
# Add an in frame units version of the rep to the cache.
repr(i)
# Check that repr() has added a rep to the cache
assert len(i.cache['representation']) == 2
# Modify the data
i.data.lon[()] = 10*u.deg
# Clear the cache
i.cache.clear()
# This will use a second (potentially cached rep)
assert i.ra == 10 * u.deg
assert i.dec == 2 * u.deg
def test_representation_with_multiple_differentials():
from astropy.coordinates.builtin_frames import ICRS
dif1 = r.CartesianDifferential([1, 2, 3]*u.km/u.s)
dif2 = r.CartesianDifferential([1, 2, 3]*u.km/u.s**2)
rep = r.CartesianRepresentation([1, 2, 3]*u.pc,
differentials={'s': dif1, 's2': dif2})
# check warning is raised for a scalar
with pytest.raises(ValueError):
ICRS(rep)
def test_representation_arg_backwards_compatibility():
# TODO: this test can be removed when the `representation` argument is
# removed from the BaseCoordinateFrame initializer.
from astropy.coordinates.builtin_frames import ICRS
c1 = ICRS(x=1*u.pc, y=2*u.pc, z=3*u.pc,
representation_type=r.CartesianRepresentation)
c2 = ICRS(x=1*u.pc, y=2*u.pc, z=3*u.pc,
representation_type=r.CartesianRepresentation)
c3 = ICRS(x=1*u.pc, y=2*u.pc, z=3*u.pc,
representation_type='cartesian')
assert c1.x == c2.x
assert c1.y == c2.y
assert c1.z == c2.z
assert c1.x == c3.x
assert c1.y == c3.y
assert c1.z == c3.z
assert c1.representation_type == c1.representation_type
with pytest.raises(ValueError):
ICRS(x=1*u.pc, y=2*u.pc, z=3*u.pc,
representation_type='cartesian',
representation='cartesian')
def test_missing_component_error_names():
"""
This test checks that the component names are frame component names, not
representation or differential names, when referenced in an exception raised
when not passing in enough data. For example:
ICRS(ra=10*u.deg)
should state:
TypeError: __init__() missing 1 required positional argument: 'dec'
"""
from astropy.coordinates.builtin_frames import ICRS
with pytest.raises(TypeError) as e:
ICRS(ra=150 * u.deg)
assert "missing 1 required positional argument: 'dec'" in str(e)
with pytest.raises(TypeError) as e:
ICRS(ra=150*u.deg, dec=-11*u.deg,
pm_ra=100*u.mas/u.yr, pm_dec=10*u.mas/u.yr)
assert "pm_ra_cosdec" in str(e)
def test_non_spherical_representation_unit_creation(unitphysics):
from astropy.coordinates.builtin_frames import ICRS
class PhysicsICRS(ICRS):
default_representation = r.PhysicsSphericalRepresentation
pic = PhysicsICRS(phi=1*u.deg, theta=25*u.deg, r=1*u.kpc)
assert isinstance(pic.data, r.PhysicsSphericalRepresentation)
picu = PhysicsICRS(phi=1*u.deg, theta=25*u.deg)
assert isinstance(picu.data, unitphysics)
def test_attribute_repr():
from astropy.coordinates.attributes import Attribute
from astropy.coordinates.baseframe import BaseCoordinateFrame
class Spam:
def _astropy_repr_in_frame(self):
return "TEST REPR"
class TestFrame(BaseCoordinateFrame):
attrtest = Attribute(default=Spam())
assert "TEST REPR" in repr(TestFrame())
|
a4c5586aa11c1ee30a8c3281296350e45e9ed76db4a80add8384b658407b72f6 | """
This file tests the behavior of subclasses of Representation and Frames
"""
from copy import deepcopy
from collections import OrderedDict
import pytest
from astropy.coordinates import Longitude, Latitude
from astropy.coordinates.representation import (REPRESENTATION_CLASSES,
SphericalRepresentation,
UnitSphericalRepresentation,
_invalidate_reprdiff_cls_hash)
from astropy.coordinates.baseframe import frame_transform_graph
from astropy.coordinates.transformations import FunctionTransform
from astropy.coordinates import ICRS
from astropy.coordinates.baseframe import RepresentationMapping
import astropy.units as u
import astropy.coordinates
# Classes setup, borrowed from SunPy.
# Here we define the classes *inside* the tests to make sure that we can wipe
# the slate clean when the tests have finished running.
def setup_function(func):
func.REPRESENTATION_CLASSES_ORIG = deepcopy(REPRESENTATION_CLASSES)
def teardown_function(func):
REPRESENTATION_CLASSES.clear()
REPRESENTATION_CLASSES.update(func.REPRESENTATION_CLASSES_ORIG)
_invalidate_reprdiff_cls_hash()
@pytest.mark.remote_data
def test_unit_representation_subclass():
class Longitude180(Longitude):
def __new__(cls, angle, unit=None, wrap_angle=180*u.deg, **kwargs):
self = super().__new__(cls, angle, unit=unit, wrap_angle=wrap_angle,
**kwargs)
return self
class UnitSphericalWrap180Representation(UnitSphericalRepresentation):
attr_classes = OrderedDict([('lon', Longitude180),
('lat', Latitude)])
class SphericalWrap180Representation(SphericalRepresentation):
attr_classes = OrderedDict([('lon', Longitude180),
('lat', Latitude),
('distance', u.Quantity)])
_unit_representation = UnitSphericalWrap180Representation
class MyFrame(ICRS):
default_representation = SphericalWrap180Representation
frame_specific_representation_info = {
'spherical': [
RepresentationMapping('lon', 'ra'),
RepresentationMapping('lat', 'dec')]
}
frame_specific_representation_info['unitsphericalwrap180'] = \
frame_specific_representation_info['sphericalwrap180'] = \
frame_specific_representation_info['spherical']
@frame_transform_graph.transform(FunctionTransform,
MyFrame, astropy.coordinates.ICRS)
def myframe_to_icrs(myframe_coo, icrs):
return icrs.realize_frame(myframe_coo._data)
f = MyFrame(10*u.deg, 10*u.deg)
assert isinstance(f._data, UnitSphericalWrap180Representation)
assert isinstance(f.ra, Longitude180)
g = f.transform_to(astropy.coordinates.ICRS)
assert isinstance(g, astropy.coordinates.ICRS)
assert isinstance(g._data, UnitSphericalWrap180Representation)
frame_transform_graph.remove_transform(MyFrame,
astropy.coordinates.ICRS,
None)
|
73e8bdf441c39764971631b1d533f4fb6b523c4ef971cad7634aa57aed0122fe |
import pytest
import numpy as np
from astropy.time import Time
from astropy import units as u
from astropy.constants import c
from astropy.coordinates.builtin_frames import GCRS
from astropy.coordinates.earth import EarthLocation
from astropy.coordinates.sky_coordinate import SkyCoord
from astropy.coordinates.solar_system import (get_body, get_moon, BODY_NAME_TO_KERNEL_SPEC,
_apparent_position_in_true_coordinates,
get_body_barycentric, get_body_barycentric_posvel)
from astropy.coordinates.funcs import get_sun
from astropy.tests.helper import assert_quantity_allclose
from astropy.units import allclose as quantity_allclose
try:
import jplephem # pylint: disable=W0611
except ImportError:
HAS_JPLEPHEM = False
else:
HAS_JPLEPHEM = True
try:
from skyfield.api import load # pylint: disable=W0611
except ImportError:
HAS_SKYFIELD = False
else:
HAS_SKYFIELD = True
de432s_separation_tolerance_planets = 5*u.arcsec
de432s_separation_tolerance_moon = 5*u.arcsec
de432s_distance_tolerance = 20*u.km
skyfield_angular_separation_tolerance = 1*u.arcsec
skyfield_separation_tolerance = 10*u.km
@pytest.mark.remote_data
@pytest.mark.skipif(str('not HAS_SKYFIELD'))
def test_positions_skyfield():
"""
Test positions against those generated by skyfield.
"""
t = Time('1980-03-25 00:00')
location = None
# skyfield ephemeris
planets = load('de421.bsp')
ts = load.timescale()
mercury, jupiter, moon = planets['mercury'], planets['jupiter barycenter'], planets['moon']
earth = planets['earth']
skyfield_t = ts.from_astropy(t)
if location is not None:
earth = earth.topos(latitude_degrees=location.lat.to_value(u.deg),
longitude_degrees=location.lon.to_value(u.deg),
elevation_m=location.height.to_value(u.m))
skyfield_mercury = earth.at(skyfield_t).observe(mercury).apparent()
skyfield_jupiter = earth.at(skyfield_t).observe(jupiter).apparent()
skyfield_moon = earth.at(skyfield_t).observe(moon).apparent()
if location is not None:
obsgeoloc, obsgeovel = location.get_gcrs_posvel(t)
frame = GCRS(obstime=t, obsgeoloc=obsgeoloc, obsgeovel=obsgeovel)
else:
frame = GCRS(obstime=t)
ra, dec, dist = skyfield_mercury.radec(epoch='date')
skyfield_mercury = SkyCoord(ra.to(u.deg), dec.to(u.deg), distance=dist.to(u.km),
frame=frame)
ra, dec, dist = skyfield_jupiter.radec(epoch='date')
skyfield_jupiter = SkyCoord(ra.to(u.deg), dec.to(u.deg), distance=dist.to(u.km),
frame=frame)
ra, dec, dist = skyfield_moon.radec(epoch='date')
skyfield_moon = SkyCoord(ra.to(u.deg), dec.to(u.deg), distance=dist.to(u.km),
frame=frame)
moon_astropy = get_moon(t, location, ephemeris='de430')
mercury_astropy = get_body('mercury', t, location, ephemeris='de430')
jupiter_astropy = get_body('jupiter', t, location, ephemeris='de430')
# convert to true equator and equinox
jupiter_astropy = _apparent_position_in_true_coordinates(jupiter_astropy)
mercury_astropy = _apparent_position_in_true_coordinates(mercury_astropy)
moon_astropy = _apparent_position_in_true_coordinates(moon_astropy)
assert (moon_astropy.separation(skyfield_moon) <
skyfield_angular_separation_tolerance)
assert (moon_astropy.separation_3d(skyfield_moon) < skyfield_separation_tolerance)
assert (jupiter_astropy.separation(skyfield_jupiter) <
skyfield_angular_separation_tolerance)
assert (jupiter_astropy.separation_3d(skyfield_jupiter) <
skyfield_separation_tolerance)
assert (mercury_astropy.separation(skyfield_mercury) <
skyfield_angular_separation_tolerance)
assert (mercury_astropy.separation_3d(skyfield_mercury) <
skyfield_separation_tolerance)
class TestPositionsGeocentric:
"""
Test positions against those generated by JPL Horizons accessed on
2016-03-28, with refraction turned on.
"""
def setup(self):
self.t = Time('1980-03-25 00:00')
self.frame = GCRS(obstime=self.t)
# Results returned by JPL Horizons web interface
self.horizons = {
'mercury': SkyCoord(ra='22h41m47.78s', dec='-08d29m32.0s',
distance=c*6.323037*u.min, frame=self.frame),
'moon': SkyCoord(ra='07h32m02.62s', dec='+18d34m05.0s',
distance=c*0.021921*u.min, frame=self.frame),
'jupiter': SkyCoord(ra='10h17m12.82s', dec='+12d02m57.0s',
distance=c*37.694557*u.min, frame=self.frame),
'sun': SkyCoord(ra='00h16m31.00s', dec='+01d47m16.9s',
distance=c*8.294858*u.min, frame=self.frame)}
@pytest.mark.parametrize(('body', 'sep_tol', 'dist_tol'),
(('mercury', 7.*u.arcsec, 1000*u.km),
('jupiter', 78.*u.arcsec, 76000*u.km),
('moon', 20.*u.arcsec, 80*u.km),
('sun', 5.*u.arcsec, 11.*u.km)))
def test_erfa_planet(self, body, sep_tol, dist_tol):
"""Test predictions using erfa/plan94.
Accuracies are maximum deviations listed in erfa/plan94.c, for Jupiter and
Mercury, and that quoted in Meeus "Astronomical Algorithms" (1998) for the Moon.
"""
astropy = get_body(body, self.t, ephemeris='builtin')
horizons = self.horizons[body]
# convert to true equator and equinox
astropy = _apparent_position_in_true_coordinates(astropy)
# Assert sky coordinates are close.
assert astropy.separation(horizons) < sep_tol
# Assert distances are close.
assert_quantity_allclose(astropy.distance, horizons.distance,
atol=dist_tol)
@pytest.mark.remote_data
@pytest.mark.skipif('not HAS_JPLEPHEM')
@pytest.mark.parametrize('body', ('mercury', 'jupiter', 'sun'))
def test_de432s_planet(self, body):
astropy = get_body(body, self.t, ephemeris='de432s')
horizons = self.horizons[body]
# convert to true equator and equinox
astropy = _apparent_position_in_true_coordinates(astropy)
# Assert sky coordinates are close.
assert (astropy.separation(horizons) <
de432s_separation_tolerance_planets)
# Assert distances are close.
assert_quantity_allclose(astropy.distance, horizons.distance,
atol=de432s_distance_tolerance)
@pytest.mark.remote_data
@pytest.mark.skipif('not HAS_JPLEPHEM')
def test_de432s_moon(self):
astropy = get_moon(self.t, ephemeris='de432s')
horizons = self.horizons['moon']
# convert to true equator and equinox
astropy = _apparent_position_in_true_coordinates(astropy)
# Assert sky coordinates are close.
assert (astropy.separation(horizons) <
de432s_separation_tolerance_moon)
# Assert distances are close.
assert_quantity_allclose(astropy.distance, horizons.distance,
atol=de432s_distance_tolerance)
@pytest.mark.remote_data
class TestPositionKittPeak:
"""
Test positions against those generated by JPL Horizons accessed on
2016-03-28, with refraction turned on.
"""
def setup(self):
kitt_peak = EarthLocation.from_geodetic(lon=-111.6*u.deg,
lat=31.963333333333342*u.deg,
height=2120*u.m)
self.t = Time('2014-09-25T00:00', location=kitt_peak)
obsgeoloc, obsgeovel = kitt_peak.get_gcrs_posvel(self.t)
self.frame = GCRS(obstime=self.t,
obsgeoloc=obsgeoloc, obsgeovel=obsgeovel)
# Results returned by JPL Horizons web interface
self.horizons = {
'mercury': SkyCoord(ra='13h38m58.50s', dec='-13d34m42.6s',
distance=c*7.699020*u.min, frame=self.frame),
'moon': SkyCoord(ra='12h33m12.85s', dec='-05d17m54.4s',
distance=c*0.022054*u.min, frame=self.frame),
'jupiter': SkyCoord(ra='09h09m55.55s', dec='+16d51m57.8s',
distance=c*49.244937*u.min, frame=self.frame)}
@pytest.mark.parametrize(('body', 'sep_tol', 'dist_tol'),
(('mercury', 7.*u.arcsec, 500*u.km),
('jupiter', 78.*u.arcsec, 82000*u.km)))
def test_erfa_planet(self, body, sep_tol, dist_tol):
"""Test predictions using erfa/plan94.
Accuracies are maximum deviations listed in erfa/plan94.c.
"""
# Add uncertainty in position of Earth
dist_tol = dist_tol + 1300 * u.km
astropy = get_body(body, self.t, ephemeris='builtin')
horizons = self.horizons[body]
# convert to true equator and equinox
astropy = _apparent_position_in_true_coordinates(astropy)
# Assert sky coordinates are close.
assert astropy.separation(horizons) < sep_tol
# Assert distances are close.
assert_quantity_allclose(astropy.distance, horizons.distance,
atol=dist_tol)
@pytest.mark.remote_data
@pytest.mark.skipif('not HAS_JPLEPHEM')
@pytest.mark.parametrize('body', ('mercury', 'jupiter'))
def test_de432s_planet(self, body):
astropy = get_body(body, self.t, ephemeris='de432s')
horizons = self.horizons[body]
# convert to true equator and equinox
astropy = _apparent_position_in_true_coordinates(astropy)
# Assert sky coordinates are close.
assert (astropy.separation(horizons) <
de432s_separation_tolerance_planets)
# Assert distances are close.
assert_quantity_allclose(astropy.distance, horizons.distance,
atol=de432s_distance_tolerance)
@pytest.mark.remote_data
@pytest.mark.skipif('not HAS_JPLEPHEM')
def test_de432s_moon(self):
astropy = get_moon(self.t, ephemeris='de432s')
horizons = self.horizons['moon']
# convert to true equator and equinox
astropy = _apparent_position_in_true_coordinates(astropy)
# Assert sky coordinates are close.
assert (astropy.separation(horizons) <
de432s_separation_tolerance_moon)
# Assert distances are close.
assert_quantity_allclose(astropy.distance, horizons.distance,
atol=de432s_distance_tolerance)
@pytest.mark.remote_data
@pytest.mark.skipif('not HAS_JPLEPHEM')
@pytest.mark.parametrize('bodyname', ('mercury', 'jupiter'))
def test_custom_kernel_spec_body(self, bodyname):
"""
Checks that giving a kernel specifier instead of a body name works
"""
coord_by_name = get_body(bodyname, self.t, ephemeris='de432s')
kspec = BODY_NAME_TO_KERNEL_SPEC[bodyname]
coord_by_kspec = get_body(kspec, self.t, ephemeris='de432s')
assert_quantity_allclose(coord_by_name.ra, coord_by_kspec.ra)
assert_quantity_allclose(coord_by_name.dec, coord_by_kspec.dec)
assert_quantity_allclose(coord_by_name.distance, coord_by_kspec.distance)
@pytest.mark.remote_data
@pytest.mark.skipif('not HAS_JPLEPHEM')
@pytest.mark.parametrize('time', (Time('1960-01-12 00:00'),
Time('1980-03-25 00:00'),
Time('2010-10-13 00:00')))
def test_get_sun_consistency(time):
"""
Test that the sun from JPL and the builtin get_sun match
"""
sun_jpl_gcrs = get_body('sun', time, ephemeris='de432s')
builtin_get_sun = get_sun(time)
sep = builtin_get_sun.separation(sun_jpl_gcrs)
assert sep < 0.1*u.arcsec
def test_get_moon_nonscalar_regression():
"""
Test that the builtin ephemeris works with non-scalar times.
See Issue #5069.
"""
times = Time(["2015-08-28 03:30", "2015-09-05 10:30"])
# the following line will raise an Exception if the bug recurs.
get_moon(times, ephemeris='builtin')
def test_barycentric_pos_posvel_same():
# Check that the two routines give identical results.
ep1 = get_body_barycentric('earth', Time('2016-03-20T12:30:00'))
ep2, _ = get_body_barycentric_posvel('earth', Time('2016-03-20T12:30:00'))
assert np.all(ep1.xyz == ep2.xyz)
def test_earth_barycentric_velocity_rough():
# Check that a time near the equinox gives roughly the right result.
ep, ev = get_body_barycentric_posvel('earth', Time('2016-03-20T12:30:00'))
assert_quantity_allclose(ep.xyz, [-1., 0., 0.]*u.AU, atol=0.01*u.AU)
expected = u.Quantity([0.*u.one,
np.cos(23.5*u.deg),
np.sin(23.5*u.deg)]) * -30. * u.km / u.s
assert_quantity_allclose(ev.xyz, expected, atol=1.*u.km/u.s)
def test_earth_barycentric_velocity_multi_d():
# Might as well test it with a multidimensional array too.
t = Time('2016-03-20T12:30:00') + np.arange(8.).reshape(2, 2, 2) * u.yr / 2.
ep, ev = get_body_barycentric_posvel('earth', t)
# note: assert_quantity_allclose doesn't like the shape mismatch.
# this is a problem with np.testing.assert_allclose.
assert quantity_allclose(ep.get_xyz(xyz_axis=-1),
[[-1., 0., 0.], [+1., 0., 0.]]*u.AU,
atol=0.06*u.AU)
expected = u.Quantity([0.*u.one,
np.cos(23.5*u.deg),
np.sin(23.5*u.deg)]) * ([[-30.], [30.]] * u.km / u.s)
assert quantity_allclose(ev.get_xyz(xyz_axis=-1), expected,
atol=2.*u.km/u.s)
@pytest.mark.remote_data
@pytest.mark.skipif('not HAS_JPLEPHEM')
@pytest.mark.parametrize(('body', 'pos_tol', 'vel_tol'),
(('mercury', 1000.*u.km, 1.*u.km/u.s),
('jupiter', 100000.*u.km, 2.*u.km/u.s),
('earth', 10*u.km, 10*u.mm/u.s)))
def test_barycentric_velocity_consistency(body, pos_tol, vel_tol):
# Tolerances are about 1.5 times the rms listed for plan94 and epv00,
# except for Mercury (which nominally is 334 km rms)
t = Time('2016-03-20T12:30:00')
ep, ev = get_body_barycentric_posvel(body, t, ephemeris='builtin')
dp, dv = get_body_barycentric_posvel(body, t, ephemeris='de432s')
assert_quantity_allclose(ep.xyz, dp.xyz, atol=pos_tol)
assert_quantity_allclose(ev.xyz, dv.xyz, atol=vel_tol)
# Might as well test it with a multidimensional array too.
t = Time('2016-03-20T12:30:00') + np.arange(8.).reshape(2, 2, 2) * u.yr / 2.
ep, ev = get_body_barycentric_posvel(body, t, ephemeris='builtin')
dp, dv = get_body_barycentric_posvel(body, t, ephemeris='de432s')
assert_quantity_allclose(ep.xyz, dp.xyz, atol=pos_tol)
assert_quantity_allclose(ev.xyz, dv.xyz, atol=vel_tol)
|
81733c70d799d556b81a018b0806652e65c007ba4bde9a1363b684f4657a5720 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import numpy as np
import pytest
from astropy import units as u
from astropy.coordinates import transformations as t
from astropy.coordinates.builtin_frames import ICRS, FK5, FK4, FK4NoETerms, Galactic, AltAz
from astropy.coordinates import representation as r
from astropy.coordinates.baseframe import frame_transform_graph
from astropy.tests.helper import (assert_quantity_allclose as assert_allclose,
catch_warnings)
from astropy.time import Time
from astropy.units import allclose as quantity_allclose
# Coordinates just for these tests.
class TCoo1(ICRS):
pass
class TCoo2(ICRS):
pass
class TCoo3(ICRS):
pass
def test_transform_classes():
"""
Tests the class-based/OO syntax for creating transforms
"""
tfun = lambda c, f: f.__class__(ra=c.ra, dec=c.dec)
trans1 = t.FunctionTransform(tfun, TCoo1, TCoo2,
register_graph=frame_transform_graph)
c1 = TCoo1(ra=1*u.radian, dec=0.5*u.radian)
c2 = c1.transform_to(TCoo2)
assert_allclose(c2.ra.radian, 1)
assert_allclose(c2.dec.radian, 0.5)
def matfunc(coo, fr):
return [[1, 0, 0],
[0, coo.ra.degree, 0],
[0, 0, 1]]
trans2 = t.DynamicMatrixTransform(matfunc, TCoo1, TCoo2)
trans2.register(frame_transform_graph)
c3 = TCoo1(ra=1*u.deg, dec=2*u.deg)
c4 = c3.transform_to(TCoo2)
assert_allclose(c4.ra.degree, 1)
assert_allclose(c4.ra.degree, 1)
# be sure to unregister the second one - no need for trans1 because it
# already got unregistered when trans2 was created.
trans2.unregister(frame_transform_graph)
def test_transform_decos():
"""
Tests the decorator syntax for creating transforms
"""
c1 = TCoo1(ra=1*u.deg, dec=2*u.deg)
@frame_transform_graph.transform(t.FunctionTransform, TCoo1, TCoo2)
def trans(coo1, f):
return TCoo2(ra=coo1.ra, dec=coo1.dec * 2)
c2 = c1.transform_to(TCoo2)
assert_allclose(c2.ra.degree, 1)
assert_allclose(c2.dec.degree, 4)
c3 = TCoo1(r.CartesianRepresentation(x=1*u.pc, y=1*u.pc, z=2*u.pc))
@frame_transform_graph.transform(t.StaticMatrixTransform, TCoo1, TCoo2)
def matrix():
return [[2, 0, 0],
[0, 1, 0],
[0, 0, 1]]
c4 = c3.transform_to(TCoo2)
assert_allclose(c4.cartesian.x, 2*u.pc)
assert_allclose(c4.cartesian.y, 1*u.pc)
assert_allclose(c4.cartesian.z, 2*u.pc)
def test_shortest_path():
class FakeTransform:
def __init__(self, pri):
self.priority = pri
g = t.TransformGraph()
# cheating by adding graph elements directly that are not classes - the
# graphing algorithm still works fine with integers - it just isn't a valid
# TransformGraph
# the graph looks is a down-going diamond graph with the lower-right slightly
# heavier and a cycle from the bottom to the top
# also, a pair of nodes isolated from 1
g._graph[1][2] = FakeTransform(1)
g._graph[1][3] = FakeTransform(1)
g._graph[2][4] = FakeTransform(1)
g._graph[3][4] = FakeTransform(2)
g._graph[4][1] = FakeTransform(5)
g._graph[5][6] = FakeTransform(1)
path, d = g.find_shortest_path(1, 2)
assert path == [1, 2]
assert d == 1
path, d = g.find_shortest_path(1, 3)
assert path == [1, 3]
assert d == 1
path, d = g.find_shortest_path(1, 4)
print('Cached paths:', g._shortestpaths)
assert path == [1, 2, 4]
assert d == 2
# unreachable
path, d = g.find_shortest_path(1, 5)
assert path is None
assert d == float('inf')
path, d = g.find_shortest_path(5, 6)
assert path == [5, 6]
assert d == 1
def test_sphere_cart():
"""
Tests the spherical <-> cartesian transform functions
"""
from astropy.utils import NumpyRNGContext
from astropy.coordinates import spherical_to_cartesian, cartesian_to_spherical
x, y, z = spherical_to_cartesian(1, 0, 0)
assert_allclose(x, 1)
assert_allclose(y, 0)
assert_allclose(z, 0)
x, y, z = spherical_to_cartesian(0, 1, 1)
assert_allclose(x, 0)
assert_allclose(y, 0)
assert_allclose(z, 0)
x, y, z = spherical_to_cartesian(5, 0, np.arcsin(4. / 5.))
assert_allclose(x, 3)
assert_allclose(y, 4)
assert_allclose(z, 0)
r, lat, lon = cartesian_to_spherical(0, 1, 0)
assert_allclose(r, 1)
assert_allclose(lat, 0 * u.deg)
assert_allclose(lon, np.pi / 2 * u.rad)
# test round-tripping
with NumpyRNGContext(13579):
x, y, z = np.random.randn(3, 5)
r, lat, lon = cartesian_to_spherical(x, y, z)
x2, y2, z2 = spherical_to_cartesian(r, lat, lon)
assert_allclose(x, x2)
assert_allclose(y, y2)
assert_allclose(z, z2)
def test_transform_path_pri():
"""
This checks that the transformation path prioritization works by
making sure the ICRS -> Gal transformation always goes through FK5
and not FK4.
"""
frame_transform_graph.invalidate_cache()
tpath, td = frame_transform_graph.find_shortest_path(ICRS, Galactic)
assert tpath == [ICRS, FK5, Galactic]
assert td == 2
# but direct from FK4 to Galactic should still be possible
tpath, td = frame_transform_graph.find_shortest_path(FK4, Galactic)
assert tpath == [FK4, FK4NoETerms, Galactic]
assert td == 2
def test_obstime():
"""
Checks to make sure observation time is
accounted for at least in FK4 <-> ICRS transformations
"""
b1950 = Time('B1950')
j1975 = Time('J1975')
fk4_50 = FK4(ra=1*u.deg, dec=2*u.deg, obstime=b1950)
fk4_75 = FK4(ra=1*u.deg, dec=2*u.deg, obstime=j1975)
icrs_50 = fk4_50.transform_to(ICRS)
icrs_75 = fk4_75.transform_to(ICRS)
# now check that the resulting coordinates are *different* - they should be,
# because the obstime is different
assert icrs_50.ra.degree != icrs_75.ra.degree
assert icrs_50.dec.degree != icrs_75.dec.degree
# ------------------------------------------------------------------------------
# Affine transform tests and helpers:
# just acting as a namespace
class transfunc:
rep = r.CartesianRepresentation(np.arange(3)*u.pc)
dif = r.CartesianDifferential(*np.arange(3, 6)*u.pc/u.Myr)
rep0 = r.CartesianRepresentation(np.zeros(3)*u.pc)
@classmethod
def both(cls, coo, fr):
# exchange x <-> z and offset
M = np.array([[0., 0., 1.],
[0., 1., 0.],
[1., 0., 0.]])
return M, cls.rep.with_differentials(cls.dif)
@classmethod
def just_matrix(cls, coo, fr):
# exchange x <-> z and offset
M = np.array([[0., 0., 1.],
[0., 1., 0.],
[1., 0., 0.]])
return M, None
@classmethod
def no_matrix(cls, coo, fr):
return None, cls.rep.with_differentials(cls.dif)
@classmethod
def no_pos(cls, coo, fr):
return None, cls.rep0.with_differentials(cls.dif)
@classmethod
def no_vel(cls, coo, fr):
return None, cls.rep
@pytest.mark.parametrize('transfunc', [transfunc.both, transfunc.no_matrix,
transfunc.no_pos, transfunc.no_vel,
transfunc.just_matrix])
@pytest.mark.parametrize('rep', [
r.CartesianRepresentation(5, 6, 7, unit=u.pc),
r.CartesianRepresentation(5, 6, 7, unit=u.pc,
differentials=r.CartesianDifferential(8, 9, 10,
unit=u.pc/u.Myr)),
r.CartesianRepresentation(5, 6, 7, unit=u.pc,
differentials=r.CartesianDifferential(8, 9, 10,
unit=u.pc/u.Myr))
.represent_as(r.CylindricalRepresentation, r.CylindricalDifferential)
])
def test_affine_transform_succeed(transfunc, rep):
c = TCoo1(rep)
# compute expected output
M, offset = transfunc(c, TCoo2)
_rep = rep.to_cartesian()
diffs = dict([(k, diff.represent_as(r.CartesianDifferential, rep))
for k, diff in rep.differentials.items()])
expected_rep = _rep.with_differentials(diffs)
if M is not None:
expected_rep = expected_rep.transform(M)
expected_pos = expected_rep.without_differentials()
if offset is not None:
expected_pos = expected_pos + offset.without_differentials()
expected_vel = None
if c.data.differentials:
expected_vel = expected_rep.differentials['s']
if offset and offset.differentials:
expected_vel = (expected_vel + offset.differentials['s'])
# register and do the transformation and check against expected
trans = t.AffineTransform(transfunc, TCoo1, TCoo2)
trans.register(frame_transform_graph)
c2 = c.transform_to(TCoo2)
assert quantity_allclose(c2.data.to_cartesian().xyz,
expected_pos.to_cartesian().xyz)
if expected_vel is not None:
diff = c2.data.differentials['s'].to_cartesian(base=c2.data)
assert quantity_allclose(diff.xyz, expected_vel.d_xyz)
trans.unregister(frame_transform_graph)
# these should fail
def transfunc_invalid_matrix(coo, fr):
return np.eye(4), None
# Leaving this open in case we want to add more functions to check for failures
@pytest.mark.parametrize('transfunc', [transfunc_invalid_matrix])
def test_affine_transform_fail(transfunc):
diff = r.CartesianDifferential(8, 9, 10, unit=u.pc/u.Myr)
rep = r.CartesianRepresentation(5, 6, 7, unit=u.pc, differentials=diff)
c = TCoo1(rep)
# register and do the transformation and check against expected
trans = t.AffineTransform(transfunc, TCoo1, TCoo2)
trans.register(frame_transform_graph)
with pytest.raises(ValueError):
c2 = c.transform_to(TCoo2)
trans.unregister(frame_transform_graph)
def test_too_many_differentials():
dif1 = r.CartesianDifferential(*np.arange(3, 6)*u.pc/u.Myr)
dif2 = r.CartesianDifferential(*np.arange(3, 6)*u.pc/u.Myr**2)
rep = r.CartesianRepresentation(np.arange(3)*u.pc,
differentials={'s': dif1, 's2': dif2})
with pytest.raises(ValueError):
c = TCoo1(rep)
# register and do the transformation and check against expected
trans = t.AffineTransform(transfunc.both, TCoo1, TCoo2)
trans.register(frame_transform_graph)
# Check that if frame somehow gets through to transformation, multiple
# differentials are caught
c = TCoo1(rep.without_differentials())
c._data = c._data.with_differentials({'s': dif1, 's2': dif2})
with pytest.raises(ValueError):
c2 = c.transform_to(TCoo2)
trans.unregister(frame_transform_graph)
# A matrix transform of a unit spherical with differentials should work
@pytest.mark.parametrize('rep', [
r.UnitSphericalRepresentation(lon=15*u.degree, lat=-11*u.degree,
differentials=r.SphericalDifferential(d_lon=15*u.mas/u.yr,
d_lat=11*u.mas/u.yr,
d_distance=-110*u.km/u.s)),
r.UnitSphericalRepresentation(lon=15*u.degree, lat=-11*u.degree,
differentials={'s': r.RadialDifferential(d_distance=-110*u.km/u.s)}),
r.SphericalRepresentation(lon=15*u.degree, lat=-11*u.degree,
distance=150*u.pc,
differentials={'s': r.RadialDifferential(d_distance=-110*u.km/u.s)})
])
def test_unit_spherical_with_differentials(rep):
c = TCoo1(rep)
# register and do the transformation and check against expected
trans = t.AffineTransform(transfunc.just_matrix, TCoo1, TCoo2)
trans.register(frame_transform_graph)
c2 = c.transform_to(TCoo2)
assert 's' in rep.differentials
assert isinstance(c2.data.differentials['s'],
rep.differentials['s'].__class__)
if isinstance(rep.differentials['s'], r.RadialDifferential):
assert c2.data.differentials['s'] is rep.differentials['s']
trans.unregister(frame_transform_graph)
# should fail if we have to do offsets
trans = t.AffineTransform(transfunc.both, TCoo1, TCoo2)
trans.register(frame_transform_graph)
with pytest.raises(TypeError):
c.transform_to(TCoo2)
trans.unregister(frame_transform_graph)
@pytest.mark.remote_data
def test_vel_transformation_obstime_err():
# TODO: replace after a final decision on PR #6280
from astropy.coordinates.sites import get_builtin_sites
diff = r.CartesianDifferential([.1, .2, .3]*u.km/u.s)
rep = r.CartesianRepresentation([1, 2, 3]*u.au, differentials=diff)
loc = get_builtin_sites()['example_site']
aaf = AltAz(obstime='J2010', location=loc)
aaf2 = AltAz(obstime=aaf.obstime + 3*u.day, location=loc)
aaf3 = AltAz(obstime=aaf.obstime + np.arange(3)*u.day, location=loc)
aaf4 = AltAz(obstime=aaf.obstime, location=loc)
aa = aaf.realize_frame(rep)
with pytest.raises(NotImplementedError) as exc:
aa.transform_to(aaf2)
assert 'cannot transform' in exc.value.args[0]
with pytest.raises(NotImplementedError) as exc:
aa.transform_to(aaf3)
assert 'cannot transform' in exc.value.args[0]
aa.transform_to(aaf4)
aa.transform_to(ICRS())
def test_function_transform_with_differentials():
tfun = lambda c, f: f.__class__(ra=c.ra, dec=c.dec)
ftrans = t.FunctionTransform(tfun, TCoo3, TCoo2,
register_graph=frame_transform_graph)
t3 = TCoo3(ra=1*u.deg, dec=2*u.deg, pm_ra_cosdec=1*u.marcsec/u.yr,
pm_dec=1*u.marcsec/u.yr,)
with catch_warnings() as w:
t2 = t3.transform_to(TCoo2)
assert len(w) == 1
assert 'they have been dropped' in str(w[0].message)
def test_frame_override_component_with_attribute():
"""
It was previously possible to define a frame with an attribute with the
same name as a component. We don't want to allow this!
"""
from astropy.coordinates.baseframe import BaseCoordinateFrame
from astropy.coordinates.attributes import Attribute
class BorkedFrame(BaseCoordinateFrame):
ra = Attribute(default=150)
dec = Attribute(default=150)
def trans_func(coo1, f):
pass
trans = t.FunctionTransform(trans_func, BorkedFrame, ICRS)
with pytest.raises(ValueError) as exc:
trans.register(frame_transform_graph)
assert ('BorkedFrame' in exc.value.args[0] and
"'ra'" in exc.value.args[0] and
"'dec'" in exc.value.args[0])
def test_static_matrix_combine_paths():
"""
Check that combined staticmatrixtransform matrices provide the same
transformation as using an intermediate transformation.
This is somewhat of a regression test for #7706
"""
from astropy.coordinates.baseframe import BaseCoordinateFrame
from astropy.coordinates.matrix_utilities import rotation_matrix
class AFrame(BaseCoordinateFrame):
default_representation = r.SphericalRepresentation
default_differential = r.SphericalCosLatDifferential
t1 = t.StaticMatrixTransform(rotation_matrix(30.*u.deg, 'z'),
ICRS, AFrame)
t1.register(frame_transform_graph)
t2 = t.StaticMatrixTransform(rotation_matrix(30.*u.deg, 'z').T,
AFrame, ICRS)
t2.register(frame_transform_graph)
class BFrame(BaseCoordinateFrame):
default_representation = r.SphericalRepresentation
default_differential = r.SphericalCosLatDifferential
t3 = t.StaticMatrixTransform(rotation_matrix(30.*u.deg, 'x'),
ICRS, BFrame)
t3.register(frame_transform_graph)
t4 = t.StaticMatrixTransform(rotation_matrix(30.*u.deg, 'x').T,
BFrame, ICRS)
t4.register(frame_transform_graph)
c = Galactic(123*u.deg, 45*u.deg)
c1 = c.transform_to(BFrame) # direct
c2 = c.transform_to(AFrame).transform_to(BFrame) # thru A
c3 = c.transform_to(ICRS).transform_to(BFrame) # thru ICRS
assert quantity_allclose(c1.lon, c2.lon)
assert quantity_allclose(c1.lat, c2.lat)
assert quantity_allclose(c1.lon, c3.lon)
assert quantity_allclose(c1.lat, c3.lat)
for t_ in [t1, t2, t3, t4]:
t_.unregister(frame_transform_graph)
|
2bdff7b8a32f35f9a6729dd235a810476e3424c35bf40edf134d20479df02dd8 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import pytest
import numpy as np
from astropy import units as u
from astropy.coordinates import (SphericalRepresentation, Longitude, Latitude,
SphericalDifferential)
class TestManipulation():
"""Manipulation of Representation shapes.
Checking that attributes are manipulated correctly.
Even more exhaustive tests are done in time.tests.test_methods
"""
def setup(self):
lon = Longitude(np.arange(0, 24, 4), u.hourangle)
lat = Latitude(np.arange(-90, 91, 30), u.deg)
# With same-sized arrays
self.s0 = SphericalRepresentation(
lon[:, np.newaxis] * np.ones(lat.shape),
lat * np.ones(lon.shape)[:, np.newaxis],
np.ones(lon.shape + lat.shape) * u.kpc)
self.diff = SphericalDifferential(
d_lon=np.ones(self.s0.shape)*u.mas/u.yr,
d_lat=np.ones(self.s0.shape)*u.mas/u.yr,
d_distance=np.ones(self.s0.shape)*u.km/u.s)
self.s0 = self.s0.with_differentials(self.diff)
# With unequal arrays -> these will be broadcasted.
self.s1 = SphericalRepresentation(lon[:, np.newaxis], lat, 1. * u.kpc,
differentials=self.diff)
# For completeness on some tests, also a cartesian one
self.c0 = self.s0.to_cartesian()
def test_ravel(self):
s0_ravel = self.s0.ravel()
assert type(s0_ravel) is type(self.s0)
assert s0_ravel.shape == (self.s0.size,)
assert np.all(s0_ravel.lon == self.s0.lon.ravel())
assert np.may_share_memory(s0_ravel.lon, self.s0.lon)
assert np.may_share_memory(s0_ravel.lat, self.s0.lat)
assert np.may_share_memory(s0_ravel.distance, self.s0.distance)
assert s0_ravel.differentials['s'].shape == (self.s0.size,)
# Since s1 was broadcast, ravel needs to make a copy.
s1_ravel = self.s1.ravel()
assert type(s1_ravel) is type(self.s1)
assert s1_ravel.shape == (self.s1.size,)
assert s1_ravel.differentials['s'].shape == (self.s1.size,)
assert np.all(s1_ravel.lon == self.s1.lon.ravel())
assert not np.may_share_memory(s1_ravel.lat, self.s1.lat)
def test_copy(self):
s0_copy = self.s0.copy()
s0_copy_diff = s0_copy.differentials['s']
assert s0_copy.shape == self.s0.shape
assert np.all(s0_copy.lon == self.s0.lon)
assert np.all(s0_copy.lat == self.s0.lat)
# Check copy was made of internal data.
assert not np.may_share_memory(s0_copy.distance, self.s0.distance)
assert not np.may_share_memory(s0_copy_diff.d_lon, self.diff.d_lon)
def test_flatten(self):
s0_flatten = self.s0.flatten()
s0_diff = s0_flatten.differentials['s']
assert s0_flatten.shape == (self.s0.size,)
assert s0_diff.shape == (self.s0.size,)
assert np.all(s0_flatten.lon == self.s0.lon.flatten())
assert np.all(s0_diff.d_lon == self.diff.d_lon.flatten())
# Flatten always copies.
assert not np.may_share_memory(s0_flatten.distance, self.s0.distance)
assert not np.may_share_memory(s0_diff.d_lon, self.diff.d_lon)
s1_flatten = self.s1.flatten()
assert s1_flatten.shape == (self.s1.size,)
assert np.all(s1_flatten.lon == self.s1.lon.flatten())
assert not np.may_share_memory(s1_flatten.lat, self.s1.lat)
def test_transpose(self):
s0_transpose = self.s0.transpose()
s0_diff = s0_transpose.differentials['s']
assert s0_transpose.shape == (7, 6)
assert s0_diff.shape == s0_transpose.shape
assert np.all(s0_transpose.lon == self.s0.lon.transpose())
assert np.all(s0_diff.d_lon == self.diff.d_lon.transpose())
assert np.may_share_memory(s0_transpose.distance, self.s0.distance)
assert np.may_share_memory(s0_diff.d_lon, self.diff.d_lon)
s1_transpose = self.s1.transpose()
s1_diff = s1_transpose.differentials['s']
assert s1_transpose.shape == (7, 6)
assert s1_diff.shape == s1_transpose.shape
assert np.all(s1_transpose.lat == self.s1.lat.transpose())
assert np.all(s1_diff.d_lon == self.diff.d_lon.transpose())
assert np.may_share_memory(s1_transpose.lat, self.s1.lat)
assert np.may_share_memory(s1_diff.d_lon, self.diff.d_lon)
# Only one check on T, since it just calls transpose anyway.
# Doing it on the CartesianRepresentation just for variety's sake.
c0_T = self.c0.T
assert c0_T.shape == (7, 6)
assert np.all(c0_T.x == self.c0.x.T)
assert np.may_share_memory(c0_T.y, self.c0.y)
def test_diagonal(self):
s0_diagonal = self.s0.diagonal()
s0_diff = s0_diagonal.differentials['s']
assert s0_diagonal.shape == (6,)
assert s0_diff.shape == s0_diagonal.shape
assert np.all(s0_diagonal.lat == self.s0.lat.diagonal())
assert np.all(s0_diff.d_lon == self.diff.d_lon.diagonal())
assert np.may_share_memory(s0_diagonal.lat, self.s0.lat)
assert np.may_share_memory(s0_diff.d_lon, self.diff.d_lon)
def test_swapaxes(self):
s1_swapaxes = self.s1.swapaxes(0, 1)
s1_diff = s1_swapaxes.differentials['s']
assert s1_swapaxes.shape == (7, 6)
assert s1_diff.shape == s1_swapaxes.shape
assert np.all(s1_swapaxes.lat == self.s1.lat.swapaxes(0, 1))
assert np.all(s1_diff.d_lon == self.diff.d_lon.swapaxes(0, 1))
assert np.may_share_memory(s1_swapaxes.lat, self.s1.lat)
assert np.may_share_memory(s1_diff.d_lon, self.diff.d_lon)
def test_reshape(self):
s0_reshape = self.s0.reshape(2, 3, 7)
s0_diff = s0_reshape.differentials['s']
assert s0_reshape.shape == (2, 3, 7)
assert s0_diff.shape == s0_reshape.shape
assert np.all(s0_reshape.lon == self.s0.lon.reshape(2, 3, 7))
assert np.all(s0_reshape.lat == self.s0.lat.reshape(2, 3, 7))
assert np.all(s0_reshape.distance == self.s0.distance.reshape(2, 3, 7))
assert np.may_share_memory(s0_reshape.lon, self.s0.lon)
assert np.may_share_memory(s0_reshape.lat, self.s0.lat)
assert np.may_share_memory(s0_reshape.distance, self.s0.distance)
s1_reshape = self.s1.reshape(3, 2, 7)
s1_diff = s1_reshape.differentials['s']
assert s1_reshape.shape == (3, 2, 7)
assert s1_diff.shape == s1_reshape.shape
assert np.all(s1_reshape.lat == self.s1.lat.reshape(3, 2, 7))
assert np.all(s1_diff.d_lon == self.diff.d_lon.reshape(3, 2, 7))
assert np.may_share_memory(s1_reshape.lat, self.s1.lat)
assert np.may_share_memory(s1_diff.d_lon, self.diff.d_lon)
# For reshape(3, 14), copying is necessary for lon, lat, but not for d
s1_reshape2 = self.s1.reshape(3, 14)
assert s1_reshape2.shape == (3, 14)
assert np.all(s1_reshape2.lon == self.s1.lon.reshape(3, 14))
assert not np.may_share_memory(s1_reshape2.lon, self.s1.lon)
assert s1_reshape2.distance.shape == (3, 14)
assert np.may_share_memory(s1_reshape2.distance, self.s1.distance)
def test_shape_setting(self):
# Shape-setting should be on the object itself, since copying removes
# zero-strides due to broadcasting. We reset the objects at the end.
self.s0.shape = (2, 3, 7)
assert self.s0.shape == (2, 3, 7)
assert self.s0.lon.shape == (2, 3, 7)
assert self.s0.lat.shape == (2, 3, 7)
assert self.s0.distance.shape == (2, 3, 7)
assert self.diff.shape == (2, 3, 7)
assert self.diff.d_lon.shape == (2, 3, 7)
assert self.diff.d_lat.shape == (2, 3, 7)
assert self.diff.d_distance.shape == (2, 3, 7)
# this works with the broadcasting.
self.s1.shape = (2, 3, 7)
assert self.s1.shape == (2, 3, 7)
assert self.s1.lon.shape == (2, 3, 7)
assert self.s1.lat.shape == (2, 3, 7)
assert self.s1.distance.shape == (2, 3, 7)
assert self.s1.distance.strides == (0, 0, 0)
# but this one does not.
oldshape = self.s1.shape
with pytest.raises(AttributeError):
self.s1.shape = (42,)
assert self.s1.shape == oldshape
assert self.s1.lon.shape == oldshape
assert self.s1.lat.shape == oldshape
assert self.s1.distance.shape == oldshape
# Finally, a more complicated one that checks that things get reset
# properly if it is not the first component that fails.
s2 = SphericalRepresentation(self.s1.lon.copy(), self.s1.lat,
self.s1.distance, copy=False)
assert 0 not in s2.lon.strides
assert 0 in s2.lat.strides
with pytest.raises(AttributeError):
s2.shape = (42,)
assert s2.shape == oldshape
assert s2.lon.shape == oldshape
assert s2.lat.shape == oldshape
assert s2.distance.shape == oldshape
assert 0 not in s2.lon.strides
assert 0 in s2.lat.strides
self.setup()
def test_squeeze(self):
s0_squeeze = self.s0.reshape(3, 1, 2, 1, 7).squeeze()
s0_diff = s0_squeeze.differentials['s']
assert s0_squeeze.shape == (3, 2, 7)
assert s0_diff.shape == s0_squeeze.shape
assert np.all(s0_squeeze.lat == self.s0.lat.reshape(3, 2, 7))
assert np.all(s0_diff.d_lon == self.diff.d_lon.reshape(3, 2, 7))
assert np.may_share_memory(s0_squeeze.lat, self.s0.lat)
def test_add_dimension(self):
s0_adddim = self.s0[:, np.newaxis, :]
s0_diff = s0_adddim.differentials['s']
assert s0_adddim.shape == (6, 1, 7)
assert s0_diff.shape == s0_adddim.shape
assert np.all(s0_adddim.lon == self.s0.lon[:, np.newaxis, :])
assert np.all(s0_diff.d_lon == self.diff.d_lon[:, np.newaxis, :])
assert np.may_share_memory(s0_adddim.lat, self.s0.lat)
def test_take(self):
s0_take = self.s0.take((5, 2))
s0_diff = s0_take.differentials['s']
assert s0_take.shape == (2,)
assert s0_diff.shape == s0_take.shape
assert np.all(s0_take.lon == self.s0.lon.take((5, 2)))
assert np.all(s0_diff.d_lon == self.diff.d_lon.take((5, 2)))
def test_broadcast_to(self):
s0_broadcast = self.s0._apply(np.broadcast_to, (3, 6, 7), subok=True)
s0_diff = s0_broadcast.differentials['s']
assert type(s0_broadcast) is type(self.s0)
assert s0_broadcast.shape == (3, 6, 7)
assert s0_diff.shape == s0_broadcast.shape
assert np.all(s0_broadcast.lon == self.s0.lon)
assert np.all(s0_broadcast.lat == self.s0.lat)
assert np.all(s0_broadcast.distance == self.s0.distance)
assert np.may_share_memory(s0_broadcast.lon, self.s0.lon)
assert np.may_share_memory(s0_broadcast.lat, self.s0.lat)
assert np.may_share_memory(s0_broadcast.distance, self.s0.distance)
s1_broadcast = self.s1._apply(np.broadcast_to, shape=(3, 6, 7),
subok=True)
s1_diff = s1_broadcast.differentials['s']
assert s1_broadcast.shape == (3, 6, 7)
assert s1_diff.shape == s1_broadcast.shape
assert np.all(s1_broadcast.lat == self.s1.lat)
assert np.all(s1_broadcast.lon == self.s1.lon)
assert np.all(s1_broadcast.distance == self.s1.distance)
assert s1_broadcast.distance.shape == (3, 6, 7)
assert np.may_share_memory(s1_broadcast.lat, self.s1.lat)
assert np.may_share_memory(s1_broadcast.lon, self.s1.lon)
assert np.may_share_memory(s1_broadcast.distance, self.s1.distance)
# A final test that "may_share_memory" equals "does_share_memory"
# Do this on a copy, to keep self.s0 unchanged.
sc = self.s0.copy()
assert not np.may_share_memory(sc.lon, self.s0.lon)
assert not np.may_share_memory(sc.lat, self.s0.lat)
sc_broadcast = sc._apply(np.broadcast_to, (3, 6, 7), subok=True)
assert np.may_share_memory(sc_broadcast.lon, sc.lon)
# Can only write to copy, not to broadcast version.
sc.lon[0, 0] = 22. * u.hourangle
assert np.all(sc_broadcast.lon[:, 0, 0] == 22. * u.hourangle)
|
7566c933a11f5cba0d5bb7d9f73697f69886d9b821e3a40c596b96469e7461d6 |
import pytest
import numpy as np
from astropy.tests.helper import assert_quantity_allclose
from astropy import units as u
from astropy.time import Time
from astropy.coordinates import EarthLocation, SkyCoord, Angle
from astropy.coordinates.sites import get_builtin_sites
@pytest.mark.remote_data
@pytest.mark.parametrize('kind', ['heliocentric', 'barycentric'])
def test_basic(kind):
t0 = Time('2015-1-1')
loc = get_builtin_sites()['example_site']
sc = SkyCoord(0, 0, unit=u.deg, obstime=t0, location=loc)
rvc0 = sc.radial_velocity_correction(kind)
assert rvc0.shape == ()
assert rvc0.unit.is_equivalent(u.km/u.s)
scs = SkyCoord(0, 0, unit=u.deg, obstime=t0 + np.arange(10)*u.day,
location=loc)
rvcs = scs.radial_velocity_correction(kind)
assert rvcs.shape == (10,)
assert rvcs.unit.is_equivalent(u.km/u.s)
test_input_time = Time(2457244.5, format='jd')
# test_input_loc = EarthLocation.of_site('Cerro Paranal')
# to avoid the network hit we just copy here what that yields
test_input_loc = EarthLocation.from_geodetic(lon=-70.403*u.deg,
lat=-24.6252*u.deg,
height=2635*u.m)
@pytest.mark.remote_data
def test_helio_iraf():
"""
Compare the heliocentric correction to the IRAF rvcorrect.
`generate_IRAF_input` function is provided to show how the comparison data
was produced
"""
# this is based on running IRAF with the output of `generate_IRAF_input` below
rvcorr_result = """
# RVCORRECT: Observatory parameters for European Southern Observatory: Paranal
# latitude = -24:37.5
# longitude = 70:24.2
# altitude = 2635
## HJD VOBS VHELIO VLSR VDIURNAL VLUNAR VANNUAL VSOLAR
2457244.50120 0.00 -10.36 -20.35 -0.034 -0.001 -10.325 -9.993
2457244.50025 0.00 -14.20 -23.86 -0.115 -0.004 -14.085 -9.656
2457244.50278 0.00 -2.29 -11.75 0.115 0.004 -2.413 -9.459
2457244.50025 0.00 -14.20 -23.86 -0.115 -0.004 -14.085 -9.656
2457244.49929 0.00 -17.41 -26.30 -0.192 -0.006 -17.214 -8.888
2457244.50317 0.00 -17.19 -17.44 0.078 0.001 -17.269 -0.253
2457244.50348 0.00 2.35 -6.21 0.192 0.006 2.156 -8.560
2457244.49959 0.00 2.13 -15.06 -0.078 -0.000 2.211 -17.194
2457244.49929 0.00 -17.41 -26.30 -0.192 -0.006 -17.214 -8.888
2457244.49835 0.00 -19.84 -27.56 -0.259 -0.008 -19.573 -7.721
2457244.50186 0.00 -24.47 -22.16 -0.038 -0.004 -24.433 2.313
2457244.50470 0.00 -11.11 -8.57 0.221 0.005 -11.332 2.534
2457244.50402 0.00 6.90 -0.38 0.259 0.008 6.629 -7.277
2457244.50051 0.00 11.53 -5.78 0.038 0.004 11.489 -17.311
2457244.49768 0.00 -1.84 -19.37 -0.221 -0.004 -1.612 -17.533
2457244.49835 0.00 -19.84 -27.56 -0.259 -0.008 -19.573 -7.721
2457244.49749 0.00 -21.38 -27.59 -0.315 -0.010 -21.056 -6.209
2457244.50109 0.00 -27.69 -22.90 -0.096 -0.006 -27.584 4.785
2457244.50457 0.00 -17.00 -9.30 0.196 0.003 -17.201 7.704
2457244.50532 0.00 2.62 2.97 0.340 0.009 2.276 0.349
2457244.50277 0.00 16.42 4.67 0.228 0.009 16.178 -11.741
2457244.49884 0.00 13.98 -5.48 -0.056 0.002 14.039 -19.463
2457244.49649 0.00 -2.84 -19.84 -0.297 -0.007 -2.533 -17.000
2457244.49749 0.00 -21.38 -27.59 -0.315 -0.010 -21.056 -6.209
2457244.49675 0.00 -21.97 -26.39 -0.357 -0.011 -21.598 -4.419
2457244.50025 0.00 -29.30 -22.47 -0.149 -0.008 -29.146 6.831
2457244.50398 0.00 -21.55 -9.88 0.146 0.001 -21.700 11.670
2457244.50577 0.00 -3.26 4.00 0.356 0.009 -3.623 7.263
2457244.50456 0.00 14.87 11.06 0.357 0.011 14.497 -3.808
2457244.50106 0.00 22.20 7.14 0.149 0.008 22.045 -15.058
2457244.49732 0.00 14.45 -5.44 -0.146 -0.001 14.600 -19.897
2457244.49554 0.00 -3.84 -19.33 -0.356 -0.008 -3.478 -15.491
2457244.49675 0.00 -21.97 -26.39 -0.357 -0.011 -21.598 -4.419
2457244.49615 0.00 -21.57 -24.00 -0.383 -0.012 -21.172 -2.432
2457244.49942 0.00 -29.36 -20.83 -0.193 -0.009 -29.157 8.527
2457244.50312 0.00 -24.26 -9.75 0.088 -0.001 -24.348 14.511
2457244.50552 0.00 -8.66 4.06 0.327 0.007 -8.996 12.721
2457244.50549 0.00 10.14 14.13 0.413 0.012 9.715 3.994
2457244.50305 0.00 23.35 15.76 0.306 0.011 23.031 -7.586
2457244.49933 0.00 24.78 8.18 0.056 0.006 24.721 -16.601
2457244.49609 0.00 13.77 -5.06 -0.221 -0.003 13.994 -18.832
2457244.49483 0.00 -4.53 -17.77 -0.394 -0.010 -4.131 -13.237
2457244.49615 0.00 -21.57 -24.00 -0.383 -0.012 -21.172 -2.432
2457244.49572 0.00 -20.20 -20.54 -0.392 -0.013 -19.799 -0.335
2457244.49907 0.00 -28.17 -17.30 -0.197 -0.009 -27.966 10.874
2457244.50285 0.00 -22.96 -5.96 0.090 -0.001 -23.048 16.995
2457244.50531 0.00 -7.00 8.16 0.335 0.007 -7.345 15.164
2457244.50528 0.00 12.23 18.47 0.423 0.012 11.795 6.238
2457244.50278 0.00 25.74 20.13 0.313 0.012 25.416 -5.607
2457244.49898 0.00 27.21 12.38 0.057 0.006 27.144 -14.829
2457244.49566 0.00 15.94 -1.17 -0.226 -0.003 16.172 -17.111
2457244.49437 0.00 -2.78 -14.17 -0.403 -0.010 -2.368 -11.387
2457244.49572 0.00 -20.20 -20.54 -0.392 -0.013 -19.799 -0.335
2457244.49548 0.00 -17.94 -16.16 -0.383 -0.012 -17.541 1.776
2457244.49875 0.00 -25.73 -12.99 -0.193 -0.009 -25.525 12.734
2457244.50246 0.00 -20.63 -1.91 0.088 -0.001 -20.716 18.719
2457244.50485 0.00 -5.03 11.90 0.327 0.007 -5.365 16.928
2457244.50482 0.00 13.77 21.97 0.413 0.012 13.347 8.202
2457244.50238 0.00 26.98 23.60 0.306 0.011 26.663 -3.378
2457244.49867 0.00 28.41 16.02 0.056 0.005 28.353 -12.393
2457244.49542 0.00 17.40 2.78 -0.221 -0.003 17.625 -14.625
2457244.49416 0.00 -0.90 -9.93 -0.394 -0.010 -0.499 -9.029
2457244.49548 0.00 -17.94 -16.16 -0.383 -0.012 -17.541 1.776
2457244.49544 0.00 -14.87 -11.06 -0.357 -0.011 -14.497 3.808
2457244.49894 0.00 -22.20 -7.14 -0.149 -0.008 -22.045 15.058
2457244.50268 0.00 -14.45 5.44 0.146 0.001 -14.600 19.897
2457244.50446 0.00 3.84 19.33 0.356 0.008 3.478 15.491
2457244.50325 0.00 21.97 26.39 0.357 0.011 21.598 4.419
2457244.49975 0.00 29.30 22.47 0.149 0.008 29.146 -6.831
2457244.49602 0.00 21.55 9.88 -0.146 -0.001 21.700 -11.670
2457244.49423 0.00 3.26 -4.00 -0.356 -0.009 3.623 -7.263
2457244.49544 0.00 -14.87 -11.06 -0.357 -0.011 -14.497 3.808
2457244.49561 0.00 -11.13 -5.46 -0.315 -0.010 -10.805 5.670
2457244.49921 0.00 -17.43 -0.77 -0.096 -0.006 -17.333 16.664
2457244.50269 0.00 -6.75 12.83 0.196 0.003 -6.949 19.583
2457244.50344 0.00 12.88 25.10 0.340 0.009 12.527 12.227
2457244.50089 0.00 26.67 26.80 0.228 0.009 26.430 0.137
2457244.49696 0.00 24.24 16.65 -0.056 0.002 24.290 -7.584
2457244.49461 0.00 7.42 2.29 -0.297 -0.007 7.719 -5.122
2457244.49561 0.00 -11.13 -5.46 -0.315 -0.010 -10.805 5.670
2457244.49598 0.00 -6.90 0.38 -0.259 -0.008 -6.629 7.277
2457244.49949 0.00 -11.53 5.78 -0.038 -0.004 -11.489 17.311
2457244.50232 0.00 1.84 19.37 0.221 0.004 1.612 17.533
2457244.50165 0.00 19.84 27.56 0.259 0.008 19.573 7.721
2457244.49814 0.00 24.47 22.16 0.038 0.004 24.433 -2.313
2457244.49530 0.00 11.11 8.57 -0.221 -0.005 11.332 -2.534
2457244.49598 0.00 -6.90 0.38 -0.259 -0.008 -6.629 7.277
2457244.49652 0.00 -2.35 6.21 -0.192 -0.006 -2.156 8.560
2457244.50041 0.00 -2.13 15.06 0.078 0.000 -2.211 17.194
2457244.50071 0.00 17.41 26.30 0.192 0.006 17.214 8.888
2457244.49683 0.00 17.19 17.44 -0.078 -0.001 17.269 0.253
2457244.49652 0.00 -2.35 6.21 -0.192 -0.006 -2.156 8.560
2457244.49722 0.00 2.29 11.75 -0.115 -0.004 2.413 9.459
2457244.49975 0.00 14.20 23.86 0.115 0.004 14.085 9.656
2457244.49722 0.00 2.29 11.75 -0.115 -0.004 2.413 9.459
2457244.49805 0.00 6.84 16.77 -0.034 -0.001 6.874 9.935
"""
vhs_iraf = []
for line in rvcorr_result.strip().split('\n'):
if not line.strip().startswith('#'):
vhs_iraf.append(float(line.split()[2]))
vhs_iraf = vhs_iraf*u.km/u.s
targets = SkyCoord(_get_test_input_radecs(), obstime=test_input_time,
location=test_input_loc)
vhs_astropy = targets.radial_velocity_correction('heliocentric')
assert_quantity_allclose(vhs_astropy, vhs_iraf, atol=150*u.m/u.s)
return vhs_astropy, vhs_iraf # for interactively examination
def generate_IRAF_input(writefn=None):
dt = test_input_time.utc.datetime
coos = _get_test_input_radecs()
lines = []
for ra, dec in zip(coos.ra, coos.dec):
rastr = Angle(ra).to_string(u.hour, sep=':')
decstr = Angle(dec).to_string(u.deg, sep=':')
msg = '{yr} {mo} {day} {uth}:{utmin} {ra} {dec}'
lines.append(msg.format(yr=dt.year, mo=dt.month, day=dt.day,
uth=dt.hour, utmin=dt.minute,
ra=rastr, dec=decstr))
if writefn:
with open(writefn, 'w') as f:
for l in lines:
f.write(l)
else:
for l in lines:
print(l)
print('Run IRAF as:\nastutil\nrvcorrect f=<filename> observatory=Paranal')
def _get_test_input_radecs():
ras = []
decs = []
for dec in np.linspace(-85, 85, 15):
nra = int(np.round(10*np.cos(dec*u.deg)).value)
ras1 = np.linspace(-180, 180-1e-6, nra)
ras.extend(ras1)
decs.extend([dec]*len(ras1))
return SkyCoord(ra=ras, dec=decs, unit=u.deg)
@pytest.mark.remote_data
def test_barycorr():
# this is the result of calling _get_barycorr_bvcs
barycorr_bvcs = u.Quantity([
-10335.93326096, -14198.47605491, -2237.60012494, -14198.47595363,
-17425.46512587, -17131.70901174, 2424.37095076, 2130.61519166,
-17425.46495779, -19872.50026998, -24442.37091097, -11017.08975893,
6978.0622355, 11547.93333743, -1877.34772637, -19872.50004258,
-21430.08240017, -27669.14280689, -16917.08506807, 2729.57222968,
16476.49569232, 13971.97171764, -2898.04250914, -21430.08212368,
-22028.51337105, -29301.92349394, -21481.13036199, -3147.44828909,
14959.50065514, 22232.91155425, 14412.11903105, -3921.56359768,
-22028.51305781, -21641.01479409, -29373.0512649, -24205.90521765,
-8557.34138828, 10250.50350732, 23417.2299926, 24781.98057941,
13706.17339044, -4627.70005932, -21641.01445812, -20284.92627505,
-28193.91696959, -22908.51624166, -6901.82132125, 12336.45758056,
25804.51614607, 27200.50029664, 15871.21385688, -2882.24738355,
-20284.9259314, -18020.92947805, -25752.96564978, -20585.81957567,
-4937.25573801, 13870.58916957, 27037.31568441, 28402.06636994,
17326.25977035, -1007.62209045, -18020.92914212, -14950.33284575,
-22223.74260839, -14402.94943965, 3930.73265119, 22037.68163353,
29311.09265126, 21490.30070307, 3156.62229843, -14950.33253252,
-11210.53846867, -17449.59867676, -6697.54090389, 12949.11642965,
26696.03999586, 24191.5164355, 7321.50355488, -11210.53819218,
-6968.89359681, -11538.76423011, 1886.51695238, 19881.66902396,
24451.54039956, 11026.26000765, -6968.89336945, -2415.20201758,
-2121.44599781, 17434.63406085, 17140.87871753, -2415.2018495,
2246.76923076, 14207.64513054, 2246.76933194, 6808.40787728],
u.m/u.s)
# this tries the *other* way of calling radial_velocity_correction relative
# to the IRAF tests
targets = _get_test_input_radecs()
bvcs_astropy = targets.radial_velocity_correction(obstime=test_input_time,
location=test_input_loc,
kind='barycentric')
assert_quantity_allclose(bvcs_astropy, barycorr_bvcs, atol=10*u.mm/u.s)
return bvcs_astropy, barycorr_bvcs # for interactively examination
def _get_barycorr_bvcs(coos, loc, injupyter=False):
"""
Gets the barycentric correction of the test data from the
http://astroutils.astronomy.ohio-state.edu/exofast/barycorr.html web site.
Requires the https://github.com/tronsgaard/barycorr python interface to that
site.
Provided to reproduce the test data above, but not required to actually run
the tests.
"""
import barycorr
from astropy.utils.console import ProgressBar
bvcs = []
for ra, dec in ProgressBar(list(zip(coos.ra.deg, coos.dec.deg)),
ipython_widget=injupyter):
res = barycorr.bvc(test_input_time.utc.jd, ra, dec,
lat=loc.geodetic[1].deg,
lon=loc.geodetic[0].deg,
elevation=loc.geodetic[2].to(u.m).value)
bvcs.append(res)
return bvcs*u.m/u.s
@pytest.mark.remote_data
def test_rvcorr_multiple_obstimes_onskycoord():
loc = EarthLocation(-2309223 * u.m, -3695529 * u.m, -4641767 * u.m)
arrtime = Time('2005-03-21 00:00:00') + np.linspace(-1, 1, 10)*u.day
sc = SkyCoord(1*u.deg, 2*u.deg, 100*u.kpc, obstime=arrtime, location=loc)
rvcbary_sc2 = sc.radial_velocity_correction(kind='barycentric')
assert len(rvcbary_sc2) == 10
# check the multiple-obstime and multi- mode
sc = SkyCoord(([1]*10)*u.deg, 2*u.deg, 100*u.kpc,
obstime=arrtime, location=loc)
rvcbary_sc3 = sc.radial_velocity_correction(kind='barycentric')
assert len(rvcbary_sc3) == 10
@pytest.mark.remote_data
def test_invalid_argument_combos():
loc = EarthLocation(-2309223 * u.m, -3695529 * u.m, -4641767 * u.m)
time = Time('2005-03-21 00:00:00')
timel = Time('2005-03-21 00:00:00', location=loc)
scwattrs = SkyCoord(1*u.deg, 2*u.deg, obstime=time, location=loc)
scwoattrs = SkyCoord(1*u.deg, 2*u.deg)
scwattrs.radial_velocity_correction()
with pytest.raises(ValueError):
scwattrs.radial_velocity_correction(obstime=time, location=loc)
with pytest.raises(TypeError):
scwoattrs.radial_velocity_correction(obstime=time)
scwoattrs.radial_velocity_correction(obstime=time, location=loc)
with pytest.raises(TypeError):
scwoattrs.radial_velocity_correction()
with pytest.raises(ValueError):
scwattrs.radial_velocity_correction(timel)
|
54070e3741e30ed250d0f6a59dca7557c1a7dfdce23bebdf45668bce7ec47840 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import numpy as np
import pytest
from astropy import units as u
from astropy.coordinates import Longitude, Latitude, EarthLocation, SkyCoord
# test on frame with most complicated frame attributes.
from astropy.coordinates.builtin_frames import ICRS, AltAz, GCRS
from astropy.time import Time
@pytest.mark.remote_data
class TestManipulation():
"""Manipulation of Frame shapes.
Checking that attributes are manipulated correctly.
Even more exhaustive tests are done in time.tests.test_methods
"""
def setup(self):
lon = Longitude(np.arange(0, 24, 4), u.hourangle)
lat = Latitude(np.arange(-90, 91, 30), u.deg)
# With same-sized arrays, no attributes
self.s0 = ICRS(lon[:, np.newaxis] * np.ones(lat.shape),
lat * np.ones(lon.shape)[:, np.newaxis])
# Make an AltAz frame since that has many types of attributes.
# Match one axis with times.
self.obstime = (Time('2012-01-01') +
np.arange(len(lon))[:, np.newaxis] * u.s)
# And another with location.
self.location = EarthLocation(20.*u.deg, lat, 100*u.m)
# Ensure we have a quantity scalar.
self.pressure = 1000 * u.hPa
# As well as an array.
self.temperature = np.random.uniform(
0., 20., size=(lon.size, lat.size)) * u.deg_C
self.s1 = AltAz(az=lon[:, np.newaxis], alt=lat,
obstime=self.obstime,
location=self.location,
pressure=self.pressure,
temperature=self.temperature)
# For some tests, also try a GCRS, since that has representation
# attributes. We match the second dimension (via the location)
self.obsgeoloc, self.obsgeovel = self.location.get_gcrs_posvel(
self.obstime[0, 0])
self.s2 = GCRS(ra=lon[:, np.newaxis], dec=lat,
obstime=self.obstime,
obsgeoloc=self.obsgeoloc,
obsgeovel=self.obsgeovel)
# For completeness, also some tests on an empty frame.
self.s3 = GCRS(obstime=self.obstime,
obsgeoloc=self.obsgeoloc,
obsgeovel=self.obsgeovel)
# And make a SkyCoord
self.sc = SkyCoord(ra=lon[:, np.newaxis], dec=lat, frame=self.s3)
def test_ravel(self):
s0_ravel = self.s0.ravel()
assert s0_ravel.shape == (self.s0.size,)
assert np.all(s0_ravel.data.lon == self.s0.data.lon.ravel())
assert np.may_share_memory(s0_ravel.data.lon, self.s0.data.lon)
assert np.may_share_memory(s0_ravel.data.lat, self.s0.data.lat)
# Since s1 lon, lat were broadcast, ravel needs to make a copy.
s1_ravel = self.s1.ravel()
assert s1_ravel.shape == (self.s1.size,)
assert np.all(s1_ravel.data.lon == self.s1.data.lon.ravel())
assert not np.may_share_memory(s1_ravel.data.lat, self.s1.data.lat)
assert np.all(s1_ravel.obstime == self.s1.obstime.ravel())
assert not np.may_share_memory(s1_ravel.obstime.jd1,
self.s1.obstime.jd1)
assert np.all(s1_ravel.location == self.s1.location.ravel())
assert not np.may_share_memory(s1_ravel.location, self.s1.location)
assert np.all(s1_ravel.temperature == self.s1.temperature.ravel())
assert np.may_share_memory(s1_ravel.temperature, self.s1.temperature)
assert s1_ravel.pressure == self.s1.pressure
s2_ravel = self.s2.ravel()
assert s2_ravel.shape == (self.s2.size,)
assert np.all(s2_ravel.data.lon == self.s2.data.lon.ravel())
assert not np.may_share_memory(s2_ravel.data.lat, self.s2.data.lat)
assert np.all(s2_ravel.obstime == self.s2.obstime.ravel())
assert not np.may_share_memory(s2_ravel.obstime.jd1,
self.s2.obstime.jd1)
# CartesianRepresentation do not allow direct comparisons, as this is
# too tricky to get right in the face of rounding issues. Here, though,
# it cannot be an issue, so we compare the xyz quantities.
assert np.all(s2_ravel.obsgeoloc.xyz == self.s2.obsgeoloc.ravel().xyz)
assert not np.may_share_memory(s2_ravel.obsgeoloc.x,
self.s2.obsgeoloc.x)
s3_ravel = self.s3.ravel()
assert s3_ravel.shape == (42,) # cannot use .size on frame w/o data.
assert np.all(s3_ravel.obstime == self.s3.obstime.ravel())
assert not np.may_share_memory(s3_ravel.obstime.jd1,
self.s3.obstime.jd1)
assert np.all(s3_ravel.obsgeoloc.xyz == self.s3.obsgeoloc.ravel().xyz)
assert not np.may_share_memory(s3_ravel.obsgeoloc.x,
self.s3.obsgeoloc.x)
sc_ravel = self.sc.ravel()
assert sc_ravel.shape == (self.sc.size,)
assert np.all(sc_ravel.data.lon == self.sc.data.lon.ravel())
assert not np.may_share_memory(sc_ravel.data.lat, self.sc.data.lat)
assert np.all(sc_ravel.obstime == self.sc.obstime.ravel())
assert not np.may_share_memory(sc_ravel.obstime.jd1,
self.sc.obstime.jd1)
assert np.all(sc_ravel.obsgeoloc.xyz == self.sc.obsgeoloc.ravel().xyz)
assert not np.may_share_memory(sc_ravel.obsgeoloc.x,
self.sc.obsgeoloc.x)
def test_flatten(self):
s0_flatten = self.s0.flatten()
assert s0_flatten.shape == (self.s0.size,)
assert np.all(s0_flatten.data.lon == self.s0.data.lon.flatten())
# Flatten always copies.
assert not np.may_share_memory(s0_flatten.data.lat, self.s0.data.lat)
s1_flatten = self.s1.flatten()
assert s1_flatten.shape == (self.s1.size,)
assert np.all(s1_flatten.data.lat == self.s1.data.lat.flatten())
assert not np.may_share_memory(s1_flatten.data.lon, self.s1.data.lat)
assert np.all(s1_flatten.obstime == self.s1.obstime.flatten())
assert not np.may_share_memory(s1_flatten.obstime.jd1,
self.s1.obstime.jd1)
assert np.all(s1_flatten.location == self.s1.location.flatten())
assert not np.may_share_memory(s1_flatten.location, self.s1.location)
assert np.all(s1_flatten.temperature == self.s1.temperature.flatten())
assert not np.may_share_memory(s1_flatten.temperature,
self.s1.temperature)
assert s1_flatten.pressure == self.s1.pressure
def test_transpose(self):
s0_transpose = self.s0.transpose()
assert s0_transpose.shape == (7, 6)
assert np.all(s0_transpose.data.lon == self.s0.data.lon.transpose())
assert np.may_share_memory(s0_transpose.data.lat, self.s0.data.lat)
s1_transpose = self.s1.transpose()
assert s1_transpose.shape == (7, 6)
assert np.all(s1_transpose.data.lat == self.s1.data.lat.transpose())
assert np.may_share_memory(s1_transpose.data.lon, self.s1.data.lon)
assert np.all(s1_transpose.obstime == self.s1.obstime.transpose())
assert np.may_share_memory(s1_transpose.obstime.jd1,
self.s1.obstime.jd1)
assert np.all(s1_transpose.location == self.s1.location.transpose())
assert np.may_share_memory(s1_transpose.location, self.s1.location)
assert np.all(s1_transpose.temperature ==
self.s1.temperature.transpose())
assert np.may_share_memory(s1_transpose.temperature,
self.s1.temperature)
assert s1_transpose.pressure == self.s1.pressure
# Only one check on T, since it just calls transpose anyway.
s1_T = self.s1.T
assert s1_T.shape == (7, 6)
assert np.all(s1_T.temperature == self.s1.temperature.T)
assert np.may_share_memory(s1_T.location, self.s1.location)
def test_diagonal(self):
s0_diagonal = self.s0.diagonal()
assert s0_diagonal.shape == (6,)
assert np.all(s0_diagonal.data.lat == self.s0.data.lat.diagonal())
assert np.may_share_memory(s0_diagonal.data.lat, self.s0.data.lat)
def test_swapaxes(self):
s1_swapaxes = self.s1.swapaxes(0, 1)
assert s1_swapaxes.shape == (7, 6)
assert np.all(s1_swapaxes.data.lat == self.s1.data.lat.swapaxes(0, 1))
assert np.may_share_memory(s1_swapaxes.data.lat, self.s1.data.lat)
assert np.all(s1_swapaxes.obstime == self.s1.obstime.swapaxes(0, 1))
assert np.may_share_memory(s1_swapaxes.obstime.jd1,
self.s1.obstime.jd1)
assert np.all(s1_swapaxes.location == self.s1.location.swapaxes(0, 1))
assert s1_swapaxes.location.shape == (7, 6)
assert np.may_share_memory(s1_swapaxes.location, self.s1.location)
assert np.all(s1_swapaxes.temperature ==
self.s1.temperature.swapaxes(0, 1))
assert np.may_share_memory(s1_swapaxes.temperature,
self.s1.temperature)
assert s1_swapaxes.pressure == self.s1.pressure
def test_reshape(self):
s0_reshape = self.s0.reshape(2, 3, 7)
assert s0_reshape.shape == (2, 3, 7)
assert np.all(s0_reshape.data.lon == self.s0.data.lon.reshape(2, 3, 7))
assert np.all(s0_reshape.data.lat == self.s0.data.lat.reshape(2, 3, 7))
assert np.may_share_memory(s0_reshape.data.lon, self.s0.data.lon)
assert np.may_share_memory(s0_reshape.data.lat, self.s0.data.lat)
s1_reshape = self.s1.reshape(3, 2, 7)
assert s1_reshape.shape == (3, 2, 7)
assert np.all(s1_reshape.data.lat == self.s1.data.lat.reshape(3, 2, 7))
assert np.may_share_memory(s1_reshape.data.lat, self.s1.data.lat)
assert np.all(s1_reshape.obstime == self.s1.obstime.reshape(3, 2, 7))
assert np.may_share_memory(s1_reshape.obstime.jd1,
self.s1.obstime.jd1)
assert np.all(s1_reshape.location == self.s1.location.reshape(3, 2, 7))
assert np.may_share_memory(s1_reshape.location, self.s1.location)
assert np.all(s1_reshape.temperature ==
self.s1.temperature.reshape(3, 2, 7))
assert np.may_share_memory(s1_reshape.temperature,
self.s1.temperature)
assert s1_reshape.pressure == self.s1.pressure
# For reshape(3, 14), copying is necessary for lon, lat, location, time
s1_reshape2 = self.s1.reshape(3, 14)
assert s1_reshape2.shape == (3, 14)
assert np.all(s1_reshape2.data.lon == self.s1.data.lon.reshape(3, 14))
assert not np.may_share_memory(s1_reshape2.data.lon, self.s1.data.lon)
assert np.all(s1_reshape2.obstime == self.s1.obstime.reshape(3, 14))
assert not np.may_share_memory(s1_reshape2.obstime.jd1,
self.s1.obstime.jd1)
assert np.all(s1_reshape2.location == self.s1.location.reshape(3, 14))
assert not np.may_share_memory(s1_reshape2.location, self.s1.location)
assert np.all(s1_reshape2.temperature ==
self.s1.temperature.reshape(3, 14))
assert np.may_share_memory(s1_reshape2.temperature,
self.s1.temperature)
assert s1_reshape2.pressure == self.s1.pressure
s2_reshape = self.s2.reshape(3, 2, 7)
assert s2_reshape.shape == (3, 2, 7)
assert np.all(s2_reshape.data.lon == self.s2.data.lon.reshape(3, 2, 7))
assert np.may_share_memory(s2_reshape.data.lat, self.s2.data.lat)
assert np.all(s2_reshape.obstime == self.s2.obstime.reshape(3, 2, 7))
assert np.may_share_memory(s2_reshape.obstime.jd1, self.s2.obstime.jd1)
assert np.all(s2_reshape.obsgeoloc.xyz ==
self.s2.obsgeoloc.reshape(3, 2, 7).xyz)
assert np.may_share_memory(s2_reshape.obsgeoloc.x, self.s2.obsgeoloc.x)
s3_reshape = self.s3.reshape(3, 2, 7)
assert s3_reshape.shape == (3, 2, 7)
assert np.all(s3_reshape.obstime == self.s3.obstime.reshape(3, 2, 7))
assert np.may_share_memory(s3_reshape.obstime.jd1, self.s3.obstime.jd1)
assert np.all(s3_reshape.obsgeoloc.xyz ==
self.s3.obsgeoloc.reshape(3, 2, 7).xyz)
assert np.may_share_memory(s3_reshape.obsgeoloc.x, self.s3.obsgeoloc.x)
sc_reshape = self.sc.reshape(3, 2, 7)
assert sc_reshape.shape == (3, 2, 7)
assert np.all(sc_reshape.data.lon == self.sc.data.lon.reshape(3, 2, 7))
assert np.may_share_memory(sc_reshape.data.lat, self.sc.data.lat)
assert np.all(sc_reshape.obstime == self.sc.obstime.reshape(3, 2, 7))
assert np.may_share_memory(sc_reshape.obstime.jd1, self.sc.obstime.jd1)
assert np.all(sc_reshape.obsgeoloc.xyz ==
self.sc.obsgeoloc.reshape(3, 2, 7).xyz)
assert np.may_share_memory(sc_reshape.obsgeoloc.x, self.sc.obsgeoloc.x)
# For reshape(3, 14), the arrays all need to be copied.
sc_reshape2 = self.sc.reshape(3, 14)
assert sc_reshape2.shape == (3, 14)
assert np.all(sc_reshape2.data.lon == self.sc.data.lon.reshape(3, 14))
assert not np.may_share_memory(sc_reshape2.data.lat,
self.sc.data.lat)
assert np.all(sc_reshape2.obstime == self.sc.obstime.reshape(3, 14))
assert not np.may_share_memory(sc_reshape2.obstime.jd1,
self.sc.obstime.jd1)
assert np.all(sc_reshape2.obsgeoloc.xyz ==
self.sc.obsgeoloc.reshape(3, 14).xyz)
assert not np.may_share_memory(sc_reshape2.obsgeoloc.x,
self.sc.obsgeoloc.x)
def test_squeeze(self):
s0_squeeze = self.s0.reshape(3, 1, 2, 1, 7).squeeze()
assert s0_squeeze.shape == (3, 2, 7)
assert np.all(s0_squeeze.data.lat == self.s0.data.lat.reshape(3, 2, 7))
assert np.may_share_memory(s0_squeeze.data.lat, self.s0.data.lat)
def test_add_dimension(self):
s0_adddim = self.s0[:, np.newaxis, :]
assert s0_adddim.shape == (6, 1, 7)
assert np.all(s0_adddim.data.lon == self.s0.data.lon[:, np.newaxis, :])
assert np.may_share_memory(s0_adddim.data.lat, self.s0.data.lat)
def test_take(self):
s0_take = self.s0.take((5, 2))
assert s0_take.shape == (2,)
assert np.all(s0_take.data.lon == self.s0.data.lon.take((5, 2)))
|
d62b69cf6cce600732f9a875d38867f7df63d072b7750fc8059db43e81d8a63d | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import pytest
import numpy as np
from astropy import units as u
from astropy.coordinates.builtin_frames import ICRS, Galactic, Galactocentric
from astropy.coordinates import builtin_frames as bf
from astropy.units import allclose as quantity_allclose
from astropy.coordinates.errors import ConvertError
from astropy.coordinates import representation as r
def test_api():
# transform observed Barycentric velocities to full-space Galactocentric
gc_frame = Galactocentric()
icrs = ICRS(ra=151.*u.deg, dec=-16*u.deg, distance=101*u.pc,
pm_ra_cosdec=21*u.mas/u.yr, pm_dec=-71*u.mas/u.yr,
radial_velocity=71*u.km/u.s)
icrs.transform_to(gc_frame)
# transform a set of ICRS proper motions to Galactic
icrs = ICRS(ra=151.*u.deg, dec=-16*u.deg,
pm_ra_cosdec=21*u.mas/u.yr, pm_dec=-71*u.mas/u.yr)
icrs.transform_to(Galactic)
# transform a Barycentric RV to a GSR RV
icrs = ICRS(ra=151.*u.deg, dec=-16*u.deg, distance=1.*u.pc,
pm_ra_cosdec=0*u.mas/u.yr, pm_dec=0*u.mas/u.yr,
radial_velocity=71*u.km/u.s)
icrs.transform_to(Galactocentric)
all_kwargs = [
dict(ra=37.4*u.deg, dec=-55.8*u.deg),
dict(ra=37.4*u.deg, dec=-55.8*u.deg, distance=150*u.pc),
dict(ra=37.4*u.deg, dec=-55.8*u.deg,
pm_ra_cosdec=-21.2*u.mas/u.yr, pm_dec=17.1*u.mas/u.yr),
dict(ra=37.4*u.deg, dec=-55.8*u.deg, distance=150*u.pc,
pm_ra_cosdec=-21.2*u.mas/u.yr, pm_dec=17.1*u.mas/u.yr),
dict(ra=37.4*u.deg, dec=-55.8*u.deg,
radial_velocity=105.7*u.km/u.s),
dict(ra=37.4*u.deg, dec=-55.8*u.deg, distance=150*u.pc,
radial_velocity=105.7*u.km/u.s),
dict(ra=37.4*u.deg, dec=-55.8*u.deg,
radial_velocity=105.7*u.km/u.s,
pm_ra_cosdec=-21.2*u.mas/u.yr, pm_dec=17.1*u.mas/u.yr),
dict(ra=37.4*u.deg, dec=-55.8*u.deg, distance=150*u.pc,
pm_ra_cosdec=-21.2*u.mas/u.yr, pm_dec=17.1*u.mas/u.yr,
radial_velocity=105.7*u.km/u.s),
# Now test other representation/differential types:
dict(x=100.*u.pc, y=200*u.pc, z=300*u.pc,
representation_type='cartesian'),
dict(x=100.*u.pc, y=200*u.pc, z=300*u.pc,
representation_type=r.CartesianRepresentation),
dict(x=100.*u.pc, y=200*u.pc, z=300*u.pc,
v_x=100.*u.km/u.s, v_y=200*u.km/u.s, v_z=300*u.km/u.s,
representation_type=r.CartesianRepresentation,
differential_type=r.CartesianDifferential),
dict(x=100.*u.pc, y=200*u.pc, z=300*u.pc,
v_x=100.*u.km/u.s, v_y=200*u.km/u.s, v_z=300*u.km/u.s,
representation_type=r.CartesianRepresentation,
differential_type='cartesian'),
]
@pytest.mark.parametrize('kwargs', all_kwargs)
def test_all_arg_options(kwargs):
# Above is a list of all possible valid combinations of arguments.
# Here we do a simple thing and just verify that passing them in, we have
# access to the relevant attributes from the resulting object
icrs = ICRS(**kwargs)
gal = icrs.transform_to(Galactic)
repr_gal = repr(gal)
for k in kwargs:
if k == 'differential_type':
continue
getattr(icrs, k)
if 'pm_ra_cosdec' in kwargs: # should have both
assert 'pm_l_cosb' in repr_gal
assert 'pm_b' in repr_gal
assert 'mas / yr' in repr_gal
if 'radial_velocity' not in kwargs:
assert 'radial_velocity' not in repr_gal
if 'radial_velocity' in kwargs:
assert 'radial_velocity' in repr_gal
assert 'km / s' in repr_gal
if 'pm_ra_cosdec' not in kwargs:
assert 'pm_l_cosb' not in repr_gal
assert 'pm_b' not in repr_gal
@pytest.mark.parametrize('cls,lon,lat', [
[bf.ICRS, 'ra', 'dec'], [bf.FK4, 'ra', 'dec'], [bf.FK4NoETerms, 'ra', 'dec'],
[bf.FK5, 'ra', 'dec'], [bf.GCRS, 'ra', 'dec'], [bf.HCRS, 'ra', 'dec'],
[bf.LSR, 'ra', 'dec'], [bf.CIRS, 'ra', 'dec'], [bf.Galactic, 'l', 'b'],
[bf.AltAz, 'az', 'alt'], [bf.Supergalactic, 'sgl', 'sgb'],
[bf.GalacticLSR, 'l', 'b'], [bf.HeliocentricMeanEcliptic, 'lon', 'lat'],
[bf.GeocentricMeanEcliptic, 'lon', 'lat'],
[bf.BarycentricMeanEcliptic, 'lon', 'lat'],
[bf.PrecessedGeocentric, 'ra', 'dec']
])
def test_expected_arg_names(cls, lon, lat):
kwargs = {lon: 37.4*u.deg, lat: -55.8*u.deg, 'distance': 150*u.pc,
'pm_{0}_cos{1}'.format(lon, lat): -21.2*u.mas/u.yr,
'pm_{0}'.format(lat): 17.1*u.mas/u.yr,
'radial_velocity': 105.7*u.km/u.s}
frame = cls(**kwargs)
# these data are extracted from the vizier copy of XHIP:
# http://vizier.u-strasbg.fr/viz-bin/VizieR-3?-source=+V/137A/XHIP
_xhip_head = """
------ ------------ ------------ -------- -------- ------------ ------------ ------- -------- -------- ------- ------ ------ ------
R D pmRA pmDE Di pmGLon pmGLat RV U V W
HIP AJ2000 (deg) EJ2000 (deg) (mas/yr) (mas/yr) GLon (deg) GLat (deg) st (pc) (mas/yr) (mas/yr) (km/s) (km/s) (km/s) (km/s)
------ ------------ ------------ -------- -------- ------------ ------------ ------- -------- -------- ------- ------ ------ ------
"""[1:-1]
_xhip_data = """
19 000.05331690 +38.30408633 -3.17 -15.37 112.00026470 -23.47789171 247.12 -6.40 -14.33 6.30 7.3 2.0 -17.9
20 000.06295067 +23.52928427 36.11 -22.48 108.02779304 -37.85659811 95.90 29.35 -30.78 37.80 -19.3 16.1 -34.2
21 000.06623581 +08.00723430 61.48 -0.23 101.69697120 -52.74179515 183.68 58.06 -20.23 -11.72 -45.2 -30.9 -1.3
24917 080.09698238 -33.39874984 -4.30 13.40 236.92324669 -32.58047131 107.38 -14.03 -1.15 36.10 -22.4 -21.3 -19.9
59207 182.13915108 +65.34963517 18.17 5.49 130.04157185 51.18258601 56.00 -18.98 -0.49 5.70 1.5 6.1 4.4
87992 269.60730667 +36.87462906 -89.58 72.46 62.98053142 25.90148234 129.60 45.64 105.79 -4.00 -39.5 -15.8 56.7
115110 349.72322473 -28.74087144 48.86 -9.25 23.00447250 -69.52799804 116.87 -8.37 -49.02 15.00 -16.8 -12.2 -23.6
"""[1:-1]
# in principal we could parse the above as a table, but doing it "manually"
# makes this test less tied to Table working correctly
@pytest.mark.parametrize('hip,ra,dec,pmra,pmdec,glon,glat,dist,pmglon,pmglat,rv,U,V,W',
[[float(val) for val in row.split()] for row in _xhip_data.split('\n')])
def test_xhip_galactic(hip, ra, dec, pmra, pmdec, glon, glat, dist, pmglon, pmglat, rv, U, V, W):
i = ICRS(ra*u.deg, dec*u.deg, dist*u.pc,
pm_ra_cosdec=pmra*u.marcsec/u.yr, pm_dec=pmdec*u.marcsec/u.yr,
radial_velocity=rv*u.km/u.s)
g = i.transform_to(Galactic)
# precision is limited by 2-deciimal digit string representation of pms
assert quantity_allclose(g.pm_l_cosb, pmglon*u.marcsec/u.yr, atol=.01*u.marcsec/u.yr)
assert quantity_allclose(g.pm_b, pmglat*u.marcsec/u.yr, atol=.01*u.marcsec/u.yr)
# make sure UVW also makes sense
uvwg = g.cartesian.differentials['s']
# precision is limited by 1-decimal digit string representation of vels
assert quantity_allclose(uvwg.d_x, U*u.km/u.s, atol=.1*u.km/u.s)
assert quantity_allclose(uvwg.d_y, V*u.km/u.s, atol=.1*u.km/u.s)
assert quantity_allclose(uvwg.d_z, W*u.km/u.s, atol=.1*u.km/u.s)
@pytest.mark.parametrize('kwargs,expect_success', [
[dict(ra=37.4*u.deg, dec=-55.8*u.deg), False],
[dict(ra=37.4*u.deg, dec=-55.8*u.deg, distance=150*u.pc), True],
[dict(ra=37.4*u.deg, dec=-55.8*u.deg,
pm_ra_cosdec=-21.2*u.mas/u.yr, pm_dec=17.1*u.mas/u.yr), False],
[dict(ra=37.4*u.deg, dec=-55.8*u.deg, radial_velocity=105.7*u.km/u.s), False],
[dict(ra=37.4*u.deg, dec=-55.8*u.deg, distance=150*u.pc,
radial_velocity=105.7*u.km/u.s), False],
[dict(ra=37.4*u.deg, dec=-55.8*u.deg,
radial_velocity=105.7*u.km/u.s,
pm_ra_cosdec=-21.2*u.mas/u.yr, pm_dec=17.1*u.mas/u.yr), False],
[dict(ra=37.4*u.deg, dec=-55.8*u.deg, distance=150*u.pc,
pm_ra_cosdec=-21.2*u.mas/u.yr, pm_dec=17.1*u.mas/u.yr,
radial_velocity=105.7*u.km/u.s), True]
])
def test_frame_affinetransform(kwargs, expect_success):
"""There are already tests in test_transformations.py that check that
an AffineTransform fails without full-space data, but this just checks that
things work as expected at the frame level as well.
"""
icrs = ICRS(**kwargs)
if expect_success:
gc = icrs.transform_to(Galactocentric)
else:
with pytest.raises(ConvertError):
icrs.transform_to(Galactocentric)
def test_differential_type_arg():
"""
Test passing in an explicit differential class to the initializer or
changing the differential class via set_representation_cls
"""
from astropy.coordinates.builtin_frames import ICRS
icrs = ICRS(ra=1*u.deg, dec=60*u.deg,
pm_ra=10*u.mas/u.yr, pm_dec=-11*u.mas/u.yr,
differential_type=r.UnitSphericalDifferential)
assert icrs.pm_ra == 10*u.mas/u.yr
icrs = ICRS(ra=1*u.deg, dec=60*u.deg,
pm_ra=10*u.mas/u.yr, pm_dec=-11*u.mas/u.yr,
differential_type={'s': r.UnitSphericalDifferential})
assert icrs.pm_ra == 10*u.mas/u.yr
icrs = ICRS(ra=1*u.deg, dec=60*u.deg,
pm_ra_cosdec=10*u.mas/u.yr, pm_dec=-11*u.mas/u.yr)
icrs.set_representation_cls(s=r.UnitSphericalDifferential)
assert quantity_allclose(icrs.pm_ra, 20*u.mas/u.yr)
# incompatible representation and differential
with pytest.raises(TypeError):
ICRS(ra=1*u.deg, dec=60*u.deg,
v_x=1*u.km/u.s, v_y=-2*u.km/u.s, v_z=-2*u.km/u.s,
differential_type=r.CartesianDifferential)
# specify both
icrs = ICRS(x=1*u.pc, y=2*u.pc, z=3*u.pc,
v_x=1*u.km/u.s, v_y=2*u.km/u.s, v_z=3*u.km/u.s,
representation_type=r.CartesianRepresentation,
differential_type=r.CartesianDifferential)
assert icrs.x == 1*u.pc
assert icrs.y == 2*u.pc
assert icrs.z == 3*u.pc
assert icrs.v_x == 1*u.km/u.s
assert icrs.v_y == 2*u.km/u.s
assert icrs.v_z == 3*u.km/u.s
def test_slicing_preserves_differential():
icrs = ICRS(ra=37.4*u.deg, dec=-55.8*u.deg, distance=150*u.pc,
pm_ra_cosdec=-21.2*u.mas/u.yr, pm_dec=17.1*u.mas/u.yr,
radial_velocity=105.7*u.km/u.s)
icrs2 = icrs.reshape(1,1)[:1,0]
for name in icrs.representation_component_names.keys():
assert getattr(icrs, name) == getattr(icrs2, name)[0]
for name in icrs.get_representation_component_names('s').keys():
assert getattr(icrs, name) == getattr(icrs2, name)[0]
def test_shorthand_attributes():
# Check that attribute access works
# for array data:
n = 4
icrs1 = ICRS(ra=np.random.uniform(0, 360, n)*u.deg,
dec=np.random.uniform(-90, 90, n)*u.deg,
distance=100*u.pc,
pm_ra_cosdec=np.random.normal(0, 100, n)*u.mas/u.yr,
pm_dec=np.random.normal(0, 100, n)*u.mas/u.yr,
radial_velocity=np.random.normal(0, 100, n)*u.km/u.s)
v = icrs1.velocity
pm = icrs1.proper_motion
assert quantity_allclose(pm[0], icrs1.pm_ra_cosdec)
assert quantity_allclose(pm[1], icrs1.pm_dec)
# for scalar data:
icrs2 = ICRS(ra=37.4*u.deg, dec=-55.8*u.deg, distance=150*u.pc,
pm_ra_cosdec=-21.2*u.mas/u.yr, pm_dec=17.1*u.mas/u.yr,
radial_velocity=105.7*u.km/u.s)
v = icrs2.velocity
pm = icrs2.proper_motion
assert quantity_allclose(pm[0], icrs2.pm_ra_cosdec)
assert quantity_allclose(pm[1], icrs2.pm_dec)
# check that it fails where we expect:
# no distance
rv = 105.7*u.km/u.s
icrs3 = ICRS(ra=37.4*u.deg, dec=-55.8*u.deg,
pm_ra_cosdec=-21.2*u.mas/u.yr, pm_dec=17.1*u.mas/u.yr,
radial_velocity=rv)
with pytest.raises(ValueError):
icrs3.velocity
icrs3.set_representation_cls('cartesian')
assert hasattr(icrs3, 'radial_velocity')
assert quantity_allclose(icrs3.radial_velocity, rv)
icrs4 = ICRS(x=30*u.pc, y=20*u.pc, z=11*u.pc,
v_x=10*u.km/u.s, v_y=10*u.km/u.s, v_z=10*u.km/u.s,
representation_type=r.CartesianRepresentation,
differential_type=r.CartesianDifferential)
icrs4.radial_velocity
def test_negative_distance():
""" Regression test: #7408
Make sure that negative parallaxes turned into distances are handled right
"""
RA = 150 * u.deg
DEC = -11*u.deg
c = ICRS(ra=RA, dec=DEC,
distance=(-10*u.mas).to(u.pc, u.parallax()),
pm_ra_cosdec=10*u.mas/u.yr,
pm_dec=10*u.mas/u.yr)
assert quantity_allclose(c.ra, RA)
assert quantity_allclose(c.dec, DEC)
c = ICRS(ra=RA, dec=DEC,
distance=(-10*u.mas).to(u.pc, u.parallax()))
assert quantity_allclose(c.ra, RA)
assert quantity_allclose(c.dec, DEC)
|
638b3ba2ef95de2e7ba2fd3ade5481267125dd2d342f1479b8c35f79d84e3d27 | # -*- coding: utf-8 -*-
"""
Tests the Angle string formatting capabilities. SkyCoord formatting is in
test_sky_coord
"""
from astropy.coordinates.angles import Angle
from astropy import units as u
def test_to_string_precision():
# There are already some tests in test_api.py, but this is a regression
# test for the bug in issue #1319 which caused incorrect formatting of the
# seconds for precision=0
angle = Angle(-1.23456789, unit=u.degree)
assert angle.to_string(precision=3) == '-1d14m04.444s'
assert angle.to_string(precision=1) == '-1d14m04.4s'
assert angle.to_string(precision=0) == '-1d14m04s'
angle2 = Angle(-1.23456789, unit=u.hourangle)
assert angle2.to_string(precision=3, unit=u.hour) == '-1h14m04.444s'
assert angle2.to_string(precision=1, unit=u.hour) == '-1h14m04.4s'
assert angle2.to_string(precision=0, unit=u.hour) == '-1h14m04s'
# Regression test for #7141
angle3 = Angle(-0.5, unit=u.degree)
assert angle3.to_string(precision=0, fields=3) == '-0d30m00s'
assert angle3.to_string(precision=0, fields=2) == '-0d30m'
assert angle3.to_string(precision=0, fields=1) == '-1d'
def test_to_string_decimal():
# There are already some tests in test_api.py, but this is a regression
# test for the bug in issue #1323 which caused decimal formatting to not
# work
angle1 = Angle(2., unit=u.degree)
assert angle1.to_string(decimal=True, precision=3) == '2.000'
assert angle1.to_string(decimal=True, precision=1) == '2.0'
assert angle1.to_string(decimal=True, precision=0) == '2'
angle2 = Angle(3., unit=u.hourangle)
assert angle2.to_string(decimal=True, precision=3) == '3.000'
assert angle2.to_string(decimal=True, precision=1) == '3.0'
assert angle2.to_string(decimal=True, precision=0) == '3'
angle3 = Angle(4., unit=u.radian)
assert angle3.to_string(decimal=True, precision=3) == '4.000'
assert angle3.to_string(decimal=True, precision=1) == '4.0'
assert angle3.to_string(decimal=True, precision=0) == '4'
def test_to_string_formats():
a = Angle(1.113355, unit=u.deg)
assert a.to_string(format='latex') == r'$1^\circ06{}^\prime48.078{}^{\prime\prime}$'
assert a.to_string(format='unicode') == '1°06′48.078″'
a = Angle(1.113355, unit=u.hour)
assert a.to_string(format='latex') == r'$1^\mathrm{h}06^\mathrm{m}48.078^\mathrm{s}$'
assert a.to_string(format='unicode') == '1ʰ06ᵐ48.078ˢ'
a = Angle(1.113355, unit=u.radian)
assert a.to_string(format='latex') == r'$1.11336\mathrm{rad}$'
assert a.to_string(format='unicode') == '1.11336rad'
def test_to_string_fields():
a = Angle(1.113355, unit=u.deg)
assert a.to_string(fields=1) == r'1d'
assert a.to_string(fields=2) == r'1d07m'
assert a.to_string(fields=3) == r'1d06m48.078s'
def test_to_string_padding():
a = Angle(0.5653, unit=u.deg)
assert a.to_string(unit='deg', sep=':', pad=True) == r'00:33:55.08'
# Test to make sure negative angles are padded correctly
a = Angle(-0.5653, unit=u.deg)
assert a.to_string(unit='deg', sep=':', pad=True) == r'-00:33:55.08'
def test_sexagesimal_rounding_up():
a = Angle(359.9999999999, unit=u.deg)
assert a.to_string(precision=None) == '360d00m00s'
assert a.to_string(precision=4) == '360d00m00.0000s'
assert a.to_string(precision=5) == '360d00m00.00000s'
assert a.to_string(precision=6) == '360d00m00.000000s'
assert a.to_string(precision=7) == '359d59m59.9999996s'
a = Angle(3.999999, unit=u.deg)
assert a.to_string(fields=2, precision=None) == '4d00m'
assert a.to_string(fields=2, precision=1) == '4d00m'
assert a.to_string(fields=2, precision=5) == '4d00m'
assert a.to_string(fields=1, precision=1) == '4d'
assert a.to_string(fields=1, precision=5) == '4d'
def test_to_string_scalar():
a = Angle(1.113355, unit=u.deg)
assert isinstance(a.to_string(), str)
def test_to_string_radian_with_precision():
"""
Regression test for a bug that caused ``to_string`` to crash for angles in
radians when specifying the precision.
"""
# Check that specifying the precision works
a = Angle(3., unit=u.rad)
assert a.to_string(precision=3, sep='fromunit') == '3.000rad'
def test_sexagesimal_round_down():
a1 = Angle(1, u.deg).to(u.hourangle)
a2 = Angle(2, u.deg)
assert a1.to_string() == '0h04m00s'
assert a2.to_string() == '2d00m00s'
def test_to_string_fields_colon():
a = Angle(1.113355, unit=u.deg)
assert a.to_string(fields=2, sep=':') == '1:07'
assert a.to_string(fields=3, sep=':') == '1:06:48.078'
assert a.to_string(fields=1, sep=':') == '1'
|
7f280e33446d62e2382a3b6a2cbe6e1eac5199f8af377bb835b1a632f2d46724 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import pytest
import numpy as np
from astropy import units as u
from astropy.coordinates.distances import Distance
from astropy.coordinates.builtin_frames import ICRS, FK5, Galactic, AltAz, SkyOffsetFrame
from astropy.coordinates import SkyCoord, EarthLocation
from astropy.time import Time
from astropy.tests.helper import assert_quantity_allclose as assert_allclose
@pytest.mark.parametrize("inradec,expectedlatlon, tolsep", [
((45, 45)*u.deg, (0, 0)*u.deg, .001*u.arcsec),
((45, 0)*u.deg, (0, -45)*u.deg, .001*u.arcsec),
((45, 90)*u.deg, (0, 45)*u.deg, .001*u.arcsec),
((46, 45)*u.deg, (1*np.cos(45*u.deg), 0)*u.deg, 16*u.arcsec),
])
def test_skyoffset(inradec, expectedlatlon, tolsep, originradec=(45, 45)*u.deg):
origin = ICRS(*originradec)
skyoffset_frame = SkyOffsetFrame(origin=origin)
skycoord = SkyCoord(*inradec, frame=ICRS)
skycoord_inaf = skycoord.transform_to(skyoffset_frame)
assert hasattr(skycoord_inaf, 'lon')
assert hasattr(skycoord_inaf, 'lat')
expected = SkyCoord(*expectedlatlon, frame=skyoffset_frame)
assert skycoord_inaf.separation(expected) < tolsep
def test_skyoffset_functional_ra():
# we do the 12)[1:-1] business because sometimes machine precision issues
# lead to results that are either ~0 or ~360, which mucks up the final
# comparison and leads to spurious failures. So this just avoids that by
# staying away from the edges
input_ra = np.linspace(0, 360, 12)[1:-1]
input_dec = np.linspace(-90, 90, 12)[1:-1]
icrs_coord = ICRS(ra=input_ra*u.deg,
dec=input_dec*u.deg,
distance=1.*u.kpc)
for ra in np.linspace(0, 360, 24):
# expected rotation
expected = ICRS(ra=np.linspace(0-ra, 360-ra, 12)[1:-1]*u.deg,
dec=np.linspace(-90, 90, 12)[1:-1]*u.deg,
distance=1.*u.kpc)
expected_xyz = expected.cartesian.xyz
# actual transformation to the frame
skyoffset_frame = SkyOffsetFrame(origin=ICRS(ra*u.deg, 0*u.deg))
actual = icrs_coord.transform_to(skyoffset_frame)
actual_xyz = actual.cartesian.xyz
# back to ICRS
roundtrip = actual.transform_to(ICRS)
roundtrip_xyz = roundtrip.cartesian.xyz
# Verify
assert_allclose(actual_xyz, expected_xyz, atol=1E-5*u.kpc)
assert_allclose(icrs_coord.ra, roundtrip.ra, atol=1E-5*u.deg)
assert_allclose(icrs_coord.dec, roundtrip.dec, atol=1E-5*u.deg)
assert_allclose(icrs_coord.distance, roundtrip.distance, atol=1E-5*u.kpc)
def test_skyoffset_functional_dec():
# we do the 12)[1:-1] business because sometimes machine precision issues
# lead to results that are either ~0 or ~360, which mucks up the final
# comparison and leads to spurious failures. So this just avoids that by
# staying away from the edges
input_ra = np.linspace(0, 360, 12)[1:-1]
input_dec = np.linspace(-90, 90, 12)[1:-1]
input_ra_rad = np.deg2rad(input_ra)
input_dec_rad = np.deg2rad(input_dec)
icrs_coord = ICRS(ra=input_ra*u.deg,
dec=input_dec*u.deg,
distance=1.*u.kpc)
# Dec rotations
# Done in xyz space because dec must be [-90,90]
for dec in np.linspace(-90, 90, 13):
# expected rotation
dec_rad = -np.deg2rad(dec)
expected_x = (-np.sin(input_dec_rad) * np.sin(dec_rad) +
np.cos(input_ra_rad) * np.cos(input_dec_rad) * np.cos(dec_rad))
expected_y = (np.sin(input_ra_rad) * np.cos(input_dec_rad))
expected_z = (np.sin(input_dec_rad) * np.cos(dec_rad) +
np.sin(dec_rad) * np.cos(input_ra_rad) * np.cos(input_dec_rad))
expected = SkyCoord(x=expected_x,
y=expected_y,
z=expected_z, unit='kpc', representation_type='cartesian')
expected_xyz = expected.cartesian.xyz
# actual transformation to the frame
skyoffset_frame = SkyOffsetFrame(origin=ICRS(0*u.deg, dec*u.deg))
actual = icrs_coord.transform_to(skyoffset_frame)
actual_xyz = actual.cartesian.xyz
# back to ICRS
roundtrip = actual.transform_to(ICRS)
# Verify
assert_allclose(actual_xyz, expected_xyz, atol=1E-5*u.kpc)
assert_allclose(icrs_coord.ra, roundtrip.ra, atol=1E-5*u.deg)
assert_allclose(icrs_coord.dec, roundtrip.dec, atol=1E-5*u.deg)
assert_allclose(icrs_coord.distance, roundtrip.distance, atol=1E-5*u.kpc)
def test_skyoffset_functional_ra_dec():
# we do the 12)[1:-1] business because sometimes machine precision issues
# lead to results that are either ~0 or ~360, which mucks up the final
# comparison and leads to spurious failures. So this just avoids that by
# staying away from the edges
input_ra = np.linspace(0, 360, 12)[1:-1]
input_dec = np.linspace(-90, 90, 12)[1:-1]
input_ra_rad = np.deg2rad(input_ra)
input_dec_rad = np.deg2rad(input_dec)
icrs_coord = ICRS(ra=input_ra*u.deg,
dec=input_dec*u.deg,
distance=1.*u.kpc)
for ra in np.linspace(0, 360, 10):
for dec in np.linspace(-90, 90, 5):
# expected rotation
dec_rad = -np.deg2rad(dec)
ra_rad = np.deg2rad(ra)
expected_x = (-np.sin(input_dec_rad) * np.sin(dec_rad) +
np.cos(input_ra_rad) * np.cos(input_dec_rad) * np.cos(dec_rad) * np.cos(ra_rad) +
np.sin(input_ra_rad) * np.cos(input_dec_rad) * np.cos(dec_rad) * np.sin(ra_rad))
expected_y = (np.sin(input_ra_rad) * np.cos(input_dec_rad) * np.cos(ra_rad) -
np.cos(input_ra_rad) * np.cos(input_dec_rad) * np.sin(ra_rad))
expected_z = (np.sin(input_dec_rad) * np.cos(dec_rad) +
np.sin(dec_rad) * np.cos(ra_rad) * np.cos(input_ra_rad) * np.cos(input_dec_rad) +
np.sin(dec_rad) * np.sin(ra_rad) * np.sin(input_ra_rad) * np.cos(input_dec_rad))
expected = SkyCoord(x=expected_x,
y=expected_y,
z=expected_z, unit='kpc', representation_type='cartesian')
expected_xyz = expected.cartesian.xyz
# actual transformation to the frame
skyoffset_frame = SkyOffsetFrame(origin=ICRS(ra*u.deg, dec*u.deg))
actual = icrs_coord.transform_to(skyoffset_frame)
actual_xyz = actual.cartesian.xyz
# back to ICRS
roundtrip = actual.transform_to(ICRS)
# Verify
assert_allclose(actual_xyz, expected_xyz, atol=1E-5*u.kpc)
assert_allclose(icrs_coord.ra, roundtrip.ra, atol=1E-4*u.deg)
assert_allclose(icrs_coord.dec, roundtrip.dec, atol=1E-5*u.deg)
assert_allclose(icrs_coord.distance, roundtrip.distance, atol=1E-5*u.kpc)
def test_skycoord_skyoffset_frame():
m31 = SkyCoord(10.6847083, 41.26875, frame='icrs', unit=u.deg)
m33 = SkyCoord(23.4621, 30.6599417, frame='icrs', unit=u.deg)
m31_astro = m31.skyoffset_frame()
m31_in_m31 = m31.transform_to(m31_astro)
m33_in_m31 = m33.transform_to(m31_astro)
assert_allclose([m31_in_m31.lon, m31_in_m31.lat], [0, 0]*u.deg, atol=1e-10*u.deg)
assert_allclose([m33_in_m31.lon, m33_in_m31.lat], [11.13135175, -9.79084759]*u.deg)
assert_allclose(m33.separation(m31),
np.hypot(m33_in_m31.lon, m33_in_m31.lat),
atol=.1*u.deg)
# used below in the next parametrized test
m31_sys = [ICRS, FK5, Galactic]
m31_coo = [(10.6847929, 41.2690650), (10.6847929, 41.2690650), (121.1744050, -21.5729360)]
m31_dist = Distance(770, u.kpc)
convert_precision = 1 * u.arcsec
roundtrip_precision = 1e-4 * u.degree
dist_precision = 1e-9 * u.kpc
m31_params = []
for i in range(len(m31_sys)):
for j in range(len(m31_sys)):
if i < j:
m31_params.append((m31_sys[i], m31_sys[j], m31_coo[i], m31_coo[j]))
@pytest.mark.parametrize(('fromsys', 'tosys', 'fromcoo', 'tocoo'), m31_params)
def test_m31_coord_transforms(fromsys, tosys, fromcoo, tocoo):
"""
This tests a variety of coordinate conversions for the Chandra point-source
catalog location of M31 from NED, via SkyOffsetFrames
"""
from_origin = fromsys(fromcoo[0]*u.deg, fromcoo[1]*u.deg,
distance=m31_dist)
from_pos = SkyOffsetFrame(1*u.deg, 1*u.deg, origin=from_origin)
to_origin = tosys(tocoo[0]*u.deg, tocoo[1]*u.deg, distance=m31_dist)
to_astroframe = SkyOffsetFrame(origin=to_origin)
target_pos = from_pos.transform_to(to_astroframe)
assert_allclose(to_origin.separation(target_pos),
np.hypot(from_pos.lon, from_pos.lat),
atol=convert_precision)
roundtrip_pos = target_pos.transform_to(from_pos)
assert_allclose([roundtrip_pos.lon.wrap_at(180*u.deg), roundtrip_pos.lat],
[1.0*u.deg, 1.0*u.deg], atol=convert_precision)
@pytest.mark.remote_data
def test_altaz_attribute_transforms():
"""Test transforms between AltAz frames with different attributes."""
el1 = EarthLocation(0*u.deg, 0*u.deg, 0*u.m)
origin1 = AltAz(0 * u.deg, 0*u.deg, obstime=Time("2000-01-01T12:00:00"),
location=el1)
frame1 = SkyOffsetFrame(origin=origin1)
coo1 = SkyCoord(1 * u.deg, 1 * u.deg, frame=frame1)
el2 = EarthLocation(0*u.deg, 0*u.deg, 0*u.m)
origin2 = AltAz(0 * u.deg, 0*u.deg, obstime=Time("2000-01-01T11:00:00"),
location=el2)
frame2 = SkyOffsetFrame(origin=origin2)
coo2 = coo1.transform_to(frame2)
coo2_expected = [1.22522446, 0.70624298] * u.deg
assert_allclose([coo2.lon.wrap_at(180*u.deg), coo2.lat],
coo2_expected, atol=convert_precision)
el3 = EarthLocation(0*u.deg, 90*u.deg, 0*u.m)
origin3 = AltAz(0 * u.deg, 90*u.deg, obstime=Time("2000-01-01T12:00:00"),
location=el3)
frame3 = SkyOffsetFrame(origin=origin3)
coo3 = coo2.transform_to(frame3)
assert_allclose([coo3.lon.wrap_at(180*u.deg), coo3.lat],
[1*u.deg, 1*u.deg], atol=convert_precision)
@pytest.mark.parametrize("rotation, expectedlatlon", [
(0*u.deg, [0, 1]*u.deg),
(180*u.deg, [0, -1]*u.deg),
(90*u.deg, [-1, 0]*u.deg),
(-90*u.deg, [1, 0]*u.deg)
])
def test_rotation(rotation, expectedlatlon):
origin = ICRS(45*u.deg, 45*u.deg)
target = ICRS(45*u.deg, 46*u.deg)
aframe = SkyOffsetFrame(origin=origin, rotation=rotation)
trans = target.transform_to(aframe)
assert_allclose([trans.lon.wrap_at(180*u.deg), trans.lat],
expectedlatlon, atol=1e-10*u.deg)
@pytest.mark.parametrize("rotation, expectedlatlon", [
(0*u.deg, [0, 1]*u.deg),
(180*u.deg, [0, -1]*u.deg),
(90*u.deg, [-1, 0]*u.deg),
(-90*u.deg, [1, 0]*u.deg)
])
def test_skycoord_skyoffset_frame_rotation(rotation, expectedlatlon):
"""Test if passing a rotation argument via SkyCoord works"""
origin = SkyCoord(45*u.deg, 45*u.deg)
target = SkyCoord(45*u.deg, 46*u.deg)
aframe = origin.skyoffset_frame(rotation=rotation)
trans = target.transform_to(aframe)
assert_allclose([trans.lon.wrap_at(180*u.deg), trans.lat],
expectedlatlon, atol=1e-10*u.deg)
def test_skyoffset_names():
origin1 = ICRS(45*u.deg, 45*u.deg)
aframe1 = SkyOffsetFrame(origin=origin1)
assert type(aframe1).__name__ == 'SkyOffsetICRS'
origin2 = Galactic(45*u.deg, 45*u.deg)
aframe2 = SkyOffsetFrame(origin=origin2)
assert type(aframe2).__name__ == 'SkyOffsetGalactic'
def test_skyoffset_origindata():
origin = ICRS()
with pytest.raises(ValueError):
SkyOffsetFrame(origin=origin)
def test_skyoffset_lonwrap():
origin = ICRS(45*u.deg, 45*u.deg)
sc = SkyCoord(190*u.deg, -45*u.deg, frame=SkyOffsetFrame(origin=origin))
assert sc.lon < 180 * u.deg
def test_skyoffset_velocity():
c = ICRS(ra=170.9*u.deg, dec=-78.4*u.deg,
pm_ra_cosdec=74.4134*u.mas/u.yr,
pm_dec=-93.2342*u.mas/u.yr)
skyoffset_frame = SkyOffsetFrame(origin=c)
c_skyoffset = c.transform_to(skyoffset_frame)
assert_allclose(c_skyoffset.pm_lon_coslat, c.pm_ra_cosdec)
assert_allclose(c_skyoffset.pm_lat, c.pm_dec)
@pytest.mark.parametrize("rotation, expectedpmlonlat", [
(0*u.deg, [1, 2]*u.mas/u.yr),
(45*u.deg, [-2**-0.5, 3*2**-0.5]*u.mas/u.yr),
(90*u.deg, [-2, 1]*u.mas/u.yr),
(180*u.deg, [-1, -2]*u.mas/u.yr),
(-90*u.deg, [2, -1]*u.mas/u.yr)
])
def test_skyoffset_velocity_rotation(rotation, expectedpmlonlat):
sc = SkyCoord(ra=170.9*u.deg, dec=-78.4*u.deg,
pm_ra_cosdec=1*u.mas/u.yr,
pm_dec=2*u.mas/u.yr)
c_skyoffset0 = sc.transform_to(sc.skyoffset_frame(rotation=rotation))
assert_allclose(c_skyoffset0.pm_lon_coslat, expectedpmlonlat[0])
assert_allclose(c_skyoffset0.pm_lat, expectedpmlonlat[1])
|
bcf7389e56983781fe8ecf4b3ce341dff2f8aea109a6f635dfcbbeb949182246 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
This module contains tests for the name resolve convenience module.
"""
import time
import urllib.request
import pytest
import numpy as np
from astropy.coordinates.name_resolve import (get_icrs_coordinates, NameResolveError,
sesame_database, _parse_response, sesame_url)
from astropy.coordinates.sky_coordinate import SkyCoord
from astropy import units as u
_cached_ngc3642 = dict()
_cached_ngc3642["simbad"] = """# NGC 3642 #Q22523669
#=S=Simbad (via url): 1
%@ 503952
%I.0 NGC 3642
%C.0 LIN
%C.N0 15.15.01.00
%J 170.5750583 +59.0742417 = 11:22:18.01 +59:04:27.2
%V z 1593 0.005327 [0.000060] D 2002LEDA.........0P
%D 1.673 1.657 75 (32767) (I) C 2006AJ....131.1163S
%T 5 =32800000 D 2011A&A...532A..74B
%#B 140
#====Done (2013-Feb-12,16:37:11z)===="""
_cached_ngc3642["vizier"] = """# NGC 3642 #Q22523677
#=V=VizieR (local): 1
%J 170.56 +59.08 = 11:22.2 +59:05
%I.0 {NGC} 3642
#====Done (2013-Feb-12,16:37:42z)===="""
_cached_ngc3642["all"] = """# ngc3642 #Q22523722
#=S=Simbad (via url): 1
%@ 503952
%I.0 NGC 3642
%C.0 LIN
%C.N0 15.15.01.00
%J 170.5750583 +59.0742417 = 11:22:18.01 +59:04:27.2
%V z 1593 0.005327 [0.000060] D 2002LEDA.........0P
%D 1.673 1.657 75 (32767) (I) C 2006AJ....131.1163S
%T 5 =32800000 D 2011A&A...532A..74B
%#B 140
#=V=VizieR (local): 1
%J 170.56 +59.08 = 11:22.2 +59:05
%I.0 {NGC} 3642
#!N=NED : *** Could not access the server ***
#====Done (2013-Feb-12,16:39:48z)===="""
_cached_castor = dict()
_cached_castor["all"] = """# castor #Q22524249
#=S=Simbad (via url): 1
%@ 983633
%I.0 NAME CASTOR
%C.0 **
%C.N0 12.13.00.00
%J 113.649471640 +31.888282216 = 07:34:35.87 +31:53:17.8
%J.E [34.72 25.95 0] A 2007A&A...474..653V
%P -191.45 -145.19 [3.95 2.95 0] A 2007A&A...474..653V
%X 64.12 [3.75] A 2007A&A...474..653V
%S A1V+A2Vm =0.0000D200.0030.0110000000100000 C 2001AJ....122.3466M
%#B 179
#!V=VizieR (local): No table found for: castor
#!N=NED: ****object name not recognized by NED name interpreter
#!N=NED: ***Not recognized by NED: castor
#====Done (2013-Feb-12,16:52:02z)===="""
_cached_castor["simbad"] = """# castor #Q22524495
#=S=Simbad (via url): 1
%@ 983633
%I.0 NAME CASTOR
%C.0 **
%C.N0 12.13.00.00
%J 113.649471640 +31.888282216 = 07:34:35.87 +31:53:17.8
%J.E [34.72 25.95 0] A 2007A&A...474..653V
%P -191.45 -145.19 [3.95 2.95 0] A 2007A&A...474..653V
%X 64.12 [3.75] A 2007A&A...474..653V
%S A1V+A2Vm =0.0000D200.0030.0110000000100000 C 2001AJ....122.3466M
%#B 179
#====Done (2013-Feb-12,17:00:39z)===="""
@pytest.mark.remote_data
def test_names():
# First check that sesame is up
if urllib.request.urlopen("http://cdsweb.u-strasbg.fr/cgi-bin/nph-sesame").getcode() != 200:
pytest.skip("SESAME appears to be down, skipping test_name_resolve.py:test_names()...")
with pytest.raises(NameResolveError):
get_icrs_coordinates("m87h34hhh")
try:
icrs = get_icrs_coordinates("NGC 3642")
except NameResolveError:
ra, dec = _parse_response(_cached_ngc3642["all"])
icrs = SkyCoord(ra=float(ra)*u.degree, dec=float(dec)*u.degree)
icrs_true = SkyCoord(ra="11h 22m 18.014s", dec="59d 04m 27.27s")
# use precision of only 1 decimal here and below because the result can
# change due to Sesame server-side changes.
np.testing.assert_almost_equal(icrs.ra.degree, icrs_true.ra.degree, 1)
np.testing.assert_almost_equal(icrs.dec.degree, icrs_true.dec.degree, 1)
try:
icrs = get_icrs_coordinates("castor")
except NameResolveError:
ra, dec = _parse_response(_cached_castor["all"])
icrs = SkyCoord(ra=float(ra)*u.degree, dec=float(dec)*u.degree)
icrs_true = SkyCoord(ra="07h 34m 35.87s", dec="+31d 53m 17.8s")
np.testing.assert_almost_equal(icrs.ra.degree, icrs_true.ra.degree, 1)
np.testing.assert_almost_equal(icrs.dec.degree, icrs_true.dec.degree, 1)
def test_names_parse():
# a few test cases for parsing embedded coordinates from object name
test_names = ['CRTS SSS100805 J194428-420209',
'MASTER OT J061451.7-272535.5',
'2MASS J06495091-0737408',
'1RXS J042555.8-194534',
'SDSS J132411.57+032050.5',
'DENIS-P J203137.5-000511',
'2QZ J142438.9-022739',
'CXOU J141312.3-652013']
for name in test_names:
sc = get_icrs_coordinates(name, parse=True)
@pytest.mark.remote_data
@pytest.mark.parametrize(("name", "db_dict"), [('NGC 3642', _cached_ngc3642),
('castor', _cached_castor)])
def test_database_specify(name, db_dict):
# First check that at least some sesame mirror is up
for url in sesame_url.get():
if urllib.request.urlopen(url).getcode() == 200:
break
else:
pytest.skip("All SESAME mirrors appear to be down, skipping "
"test_name_resolve.py:test_database_specify()...")
for db in db_dict.keys():
with sesame_database.set(db):
icrs = SkyCoord.from_name(name)
time.sleep(1)
|
6823c6e0a3cf9fc1a0db6561df99e8420d3e87b6c329cd31bcca0708a4938a8d | import pickle
import pytest
import numpy as np
from astropy.coordinates import Longitude
from astropy import coordinates as coord
from astropy.tests.helper import pickle_protocol, check_pickling_recovery # noqa
# Can't test distances without scipy due to cosmology deps
try:
import scipy # pylint: disable=W0611
HAS_SCIPY = True
except ImportError:
HAS_SCIPY = False
def test_basic():
lon1 = Longitude(1.23, "radian", wrap_angle='180d')
s = pickle.dumps(lon1)
lon2 = pickle.loads(s)
def test_pickle_longitude_wrap_angle():
a = Longitude(1.23, "radian", wrap_angle='180d')
s = pickle.dumps(a)
b = pickle.loads(s)
assert a.rad == b.rad
assert a.wrap_angle == b.wrap_angle
_names = [coord.Angle,
coord.Distance,
coord.DynamicMatrixTransform,
coord.ICRS,
coord.Latitude,
coord.Longitude,
coord.StaticMatrixTransform,
]
_xfail = [False,
not HAS_SCIPY,
True,
True,
False,
True,
False]
_args = [[0.0],
[],
[lambda *args: np.identity(3), coord.ICRS, coord.ICRS],
[0, 0],
[0],
[0],
[np.identity(3), coord.ICRS, coord.ICRS],
]
_kwargs = [{'unit': 'radian'},
{'z': 0.23},
{},
{'unit': ['radian', 'radian']},
{'unit': 'radian'},
{'unit': 'radian'},
{},
]
@pytest.mark.parametrize(("name", "args", "kwargs", "xfail"),
zip(_names, _args, _kwargs, _xfail))
def test_simple_object(pickle_protocol, name, args, kwargs, xfail):
# Tests easily instantiated objects
if xfail:
pytest.xfail()
original = name(*args, **kwargs)
check_pickling_recovery(original, pickle_protocol)
|
3ca12f052a4bfb3d8e7f8596f9a32a51ffc6014aace7e296b7e310b7a4122339 | import pytest
import warnings
# autouse makes this an all-coordinates-tests fixture
# this can be eliminated if/when warnings in pytest are all turned to errors (gh issue #7928)
@pytest.fixture(autouse=True)
def representation_deprecation_to_error():
warnings.filterwarnings('error', 'The `representation` keyword/property name is deprecated in favor of `representation_type`')
filt = warnings.filters[0]
yield
try:
warnings.filters.remove(filt)
except ValueError:
pass # already removed
|
a0a49e3ff03eb8a07561b69ffa6cc4e493a9c846944aadff1f3dc8a278d50107 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import pytest
import numpy as np
from astropy import units as u
from astropy.coordinates.distances import Distance
from astropy.coordinates.builtin_frames import (ICRS, FK5, FK4, FK4NoETerms, Galactic,
Supergalactic, Galactocentric, HCRS, GCRS, LSR)
from astropy.coordinates import SkyCoord
from astropy.tests.helper import assert_quantity_allclose as assert_allclose
from astropy.coordinates import EarthLocation, CartesianRepresentation
from astropy.time import Time
from astropy.units import allclose
# used below in the next parametrized test
m31_sys = [ICRS, FK5, FK4, Galactic]
m31_coo = [(10.6847929, 41.2690650), (10.6847929, 41.2690650), (10.0004738, 40.9952444), (121.1744050, -21.5729360)]
m31_dist = Distance(770, u.kpc)
convert_precision = 1 * u.arcsec
roundtrip_precision = 1e-4 * u.degree
dist_precision = 1e-9 * u.kpc
m31_params = []
for i in range(len(m31_sys)):
for j in range(len(m31_sys)):
if i < j:
m31_params.append((m31_sys[i], m31_sys[j], m31_coo[i], m31_coo[j]))
@pytest.mark.parametrize(('fromsys', 'tosys', 'fromcoo', 'tocoo'), m31_params)
def test_m31_coord_transforms(fromsys, tosys, fromcoo, tocoo):
"""
This tests a variety of coordinate conversions for the Chandra point-source
catalog location of M31 from NED.
"""
coo1 = fromsys(ra=fromcoo[0]*u.deg, dec=fromcoo[1]*u.deg, distance=m31_dist)
coo2 = coo1.transform_to(tosys)
if tosys is FK4:
coo2_prec = coo2.transform_to(FK4(equinox=Time('B1950')))
assert (coo2_prec.spherical.lon - tocoo[0]*u.deg) < convert_precision # <1 arcsec
assert (coo2_prec.spherical.lat - tocoo[1]*u.deg) < convert_precision
else:
assert (coo2.spherical.lon - tocoo[0]*u.deg) < convert_precision # <1 arcsec
assert (coo2.spherical.lat - tocoo[1]*u.deg) < convert_precision
assert coo1.distance.unit == u.kpc
assert coo2.distance.unit == u.kpc
assert m31_dist.unit == u.kpc
assert (coo2.distance - m31_dist) < dist_precision
# check round-tripping
coo1_2 = coo2.transform_to(fromsys)
assert (coo1_2.spherical.lon - fromcoo[0]*u.deg) < roundtrip_precision
assert (coo1_2.spherical.lat - fromcoo[1]*u.deg) < roundtrip_precision
assert (coo1_2.distance - m31_dist) < dist_precision
def test_precession():
"""
Ensures that FK4 and FK5 coordinates precess their equinoxes
"""
j2000 = Time('J2000')
b1950 = Time('B1950')
j1975 = Time('J1975')
b1975 = Time('B1975')
fk4 = FK4(ra=1*u.radian, dec=0.5*u.radian)
assert fk4.equinox.byear == b1950.byear
fk4_2 = fk4.transform_to(FK4(equinox=b1975))
assert fk4_2.equinox.byear == b1975.byear
fk5 = FK5(ra=1*u.radian, dec=0.5*u.radian)
assert fk5.equinox.jyear == j2000.jyear
fk5_2 = fk5.transform_to(FK4(equinox=j1975))
assert fk5_2.equinox.jyear == j1975.jyear
def test_fk5_galactic():
"""
Check that FK5 -> Galactic gives the same as FK5 -> FK4 -> Galactic.
"""
fk5 = FK5(ra=1*u.deg, dec=2*u.deg)
direct = fk5.transform_to(Galactic)
indirect = fk5.transform_to(FK4).transform_to(Galactic)
assert direct.separation(indirect).degree < 1.e-10
direct = fk5.transform_to(Galactic)
indirect = fk5.transform_to(FK4NoETerms).transform_to(Galactic)
assert direct.separation(indirect).degree < 1.e-10
def test_galactocentric():
# when z_sun=0, transformation should be very similar to Galactic
icrs_coord = ICRS(ra=np.linspace(0, 360, 10)*u.deg,
dec=np.linspace(-90, 90, 10)*u.deg,
distance=1.*u.kpc)
g_xyz = icrs_coord.transform_to(Galactic).cartesian.xyz
gc_xyz = icrs_coord.transform_to(Galactocentric(z_sun=0*u.kpc)).cartesian.xyz
diff = np.abs(g_xyz - gc_xyz)
assert allclose(diff[0], 8.3*u.kpc, atol=1E-5*u.kpc)
assert allclose(diff[1:], 0*u.kpc, atol=1E-5*u.kpc)
# generate some test coordinates
g = Galactic(l=[0, 0, 45, 315]*u.deg, b=[-45, 45, 0, 0]*u.deg,
distance=[np.sqrt(2)]*4*u.kpc)
xyz = g.transform_to(Galactocentric(galcen_distance=1.*u.kpc, z_sun=0.*u.pc)).cartesian.xyz
true_xyz = np.array([[0, 0, -1.], [0, 0, 1], [0, 1, 0], [0, -1, 0]]).T*u.kpc
assert allclose(xyz.to(u.kpc), true_xyz.to(u.kpc), atol=1E-5*u.kpc)
# check that ND arrays work
# from Galactocentric to Galactic
x = np.linspace(-10., 10., 100) * u.kpc
y = np.linspace(-10., 10., 100) * u.kpc
z = np.zeros_like(x)
g1 = Galactocentric(x=x, y=y, z=z)
g2 = Galactocentric(x=x.reshape(100, 1, 1), y=y.reshape(100, 1, 1),
z=z.reshape(100, 1, 1))
g1t = g1.transform_to(Galactic)
g2t = g2.transform_to(Galactic)
assert_allclose(g1t.cartesian.xyz, g2t.cartesian.xyz[:, :, 0, 0])
# from Galactic to Galactocentric
l = np.linspace(15, 30., 100) * u.deg
b = np.linspace(-10., 10., 100) * u.deg
d = np.ones_like(l.value) * u.kpc
g1 = Galactic(l=l, b=b, distance=d)
g2 = Galactic(l=l.reshape(100, 1, 1), b=b.reshape(100, 1, 1),
distance=d.reshape(100, 1, 1))
g1t = g1.transform_to(Galactocentric)
g2t = g2.transform_to(Galactocentric)
np.testing.assert_almost_equal(g1t.cartesian.xyz.value,
g2t.cartesian.xyz.value[:, :, 0, 0])
def test_supergalactic():
"""
Check Galactic<->Supergalactic and Galactic<->ICRS conversion.
"""
# Check supergalactic North pole.
npole = Galactic(l=47.37*u.degree, b=+6.32*u.degree)
assert allclose(npole.transform_to(Supergalactic).sgb.deg, +90, atol=1e-9)
# Check the origin of supergalactic longitude.
lon0 = Supergalactic(sgl=0*u.degree, sgb=0*u.degree)
lon0_gal = lon0.transform_to(Galactic)
assert allclose(lon0_gal.l.deg, 137.37, atol=1e-9)
assert allclose(lon0_gal.b.deg, 0, atol=1e-9)
# Test Galactic<->ICRS with some positions that appear in Foley et al. 2008
# (http://adsabs.harvard.edu/abs/2008A%26A...484..143F)
# GRB 021219
supergalactic = Supergalactic(sgl=29.91*u.degree, sgb=+73.72*u.degree)
icrs = SkyCoord('18h50m27s +31d57m17s')
assert supergalactic.separation(icrs) < 0.005 * u.degree
# GRB 030320
supergalactic = Supergalactic(sgl=-174.44*u.degree, sgb=+46.17*u.degree)
icrs = SkyCoord('17h51m36s -25d18m52s')
assert supergalactic.separation(icrs) < 0.005 * u.degree
class TestHCRS():
"""
Check HCRS<->ICRS coordinate conversions.
Uses ICRS Solar positions predicted by get_body_barycentric; with `t1` and
`tarr` as defined below, the ICRS Solar positions were predicted using, e.g.
coord.ICRS(coord.get_body_barycentric(tarr, 'sun')).
"""
def setup(self):
self.t1 = Time("2013-02-02T23:00")
self.t2 = Time("2013-08-02T23:00")
self.tarr = Time(["2013-02-02T23:00", "2013-08-02T23:00"])
self.sun_icrs_scalar = ICRS(ra=244.52984668*u.deg,
dec=-22.36943723*u.deg,
distance=406615.66347377*u.km)
# array of positions corresponds to times in `tarr`
self.sun_icrs_arr = ICRS(ra=[244.52989062, 271.40976248]*u.deg,
dec=[-22.36943605, -25.07431079]*u.deg,
distance=[406615.66347377, 375484.13558956]*u.km)
# corresponding HCRS positions
self.sun_hcrs_t1 = HCRS(CartesianRepresentation([0.0, 0.0, 0.0] * u.km),
obstime=self.t1)
twod_rep = CartesianRepresentation([[0.0, 0.0], [0.0, 0.0], [0.0, 0.0]] * u.km)
self.sun_hcrs_tarr = HCRS(twod_rep, obstime=self.tarr)
self.tolerance = 5*u.km
def test_from_hcrs(self):
# test scalar transform
transformed = self.sun_hcrs_t1.transform_to(ICRS())
separation = transformed.separation_3d(self.sun_icrs_scalar)
assert_allclose(separation, 0*u.km, atol=self.tolerance)
# test non-scalar positions and times
transformed = self.sun_hcrs_tarr.transform_to(ICRS())
separation = transformed.separation_3d(self.sun_icrs_arr)
assert_allclose(separation, 0*u.km, atol=self.tolerance)
def test_from_icrs(self):
# scalar positions
transformed = self.sun_icrs_scalar.transform_to(HCRS(obstime=self.t1))
separation = transformed.separation_3d(self.sun_hcrs_t1)
assert_allclose(separation, 0*u.km, atol=self.tolerance)
# nonscalar positions
transformed = self.sun_icrs_arr.transform_to(HCRS(obstime=self.tarr))
separation = transformed.separation_3d(self.sun_hcrs_tarr)
assert_allclose(separation, 0*u.km, atol=self.tolerance)
class TestHelioBaryCentric():
"""
Check GCRS<->Heliocentric and Barycentric coordinate conversions.
Uses the WHT observing site (information grabbed from data/sites.json).
"""
def setup(self):
wht = EarthLocation(342.12*u.deg, 28.758333333333333*u.deg, 2327*u.m)
self.obstime = Time("2013-02-02T23:00")
self.wht_itrs = wht.get_itrs(obstime=self.obstime)
@pytest.mark.remote_data
def test_heliocentric(self):
gcrs = self.wht_itrs.transform_to(GCRS(obstime=self.obstime))
helio = gcrs.transform_to(HCRS(obstime=self.obstime))
# Check it doesn't change from previous times.
previous = [-1.02597256e+11, 9.71725820e+10, 4.21268419e+10] * u.m
assert_allclose(helio.cartesian.xyz, previous)
# And that it agrees with SLALIB to within 14km
helio_slalib = [-0.685820296, 0.6495585893, 0.2816005464] * u.au
assert np.sqrt(((helio.cartesian.xyz -
helio_slalib)**2).sum()) < 14. * u.km
@pytest.mark.remote_data
def test_barycentric(self):
gcrs = self.wht_itrs.transform_to(GCRS(obstime=self.obstime))
bary = gcrs.transform_to(ICRS())
previous = [-1.02758958e+11, 9.68331109e+10, 4.19720938e+10] * u.m
assert_allclose(bary.cartesian.xyz, previous)
# And that it agrees with SLALIB answer to within 14km
bary_slalib = [-0.6869012079, 0.6472893646, 0.2805661191] * u.au
assert np.sqrt(((bary.cartesian.xyz -
bary_slalib)**2).sum()) < 14. * u.km
def test_lsr_sanity():
# random numbers, but zero velocity in ICRS frame
icrs = ICRS(ra=15.1241*u.deg, dec=17.5143*u.deg, distance=150.12*u.pc,
pm_ra_cosdec=0*u.mas/u.yr, pm_dec=0*u.mas/u.yr,
radial_velocity=0*u.km/u.s)
lsr = icrs.transform_to(LSR)
lsr_diff = lsr.data.differentials['s']
cart_lsr_vel = lsr_diff.represent_as(CartesianRepresentation, base=lsr.data)
lsr_vel = ICRS(cart_lsr_vel)
gal_lsr = lsr_vel.transform_to(Galactic).cartesian.xyz
assert allclose(gal_lsr.to(u.km/u.s, u.dimensionless_angles()),
lsr.v_bary.d_xyz)
# moving with LSR velocity
lsr = LSR(ra=15.1241*u.deg, dec=17.5143*u.deg, distance=150.12*u.pc,
pm_ra_cosdec=0*u.mas/u.yr, pm_dec=0*u.mas/u.yr,
radial_velocity=0*u.km/u.s)
icrs = lsr.transform_to(ICRS)
icrs_diff = icrs.data.differentials['s']
cart_vel = icrs_diff.represent_as(CartesianRepresentation, base=icrs.data)
vel = ICRS(cart_vel)
gal_icrs = vel.transform_to(Galactic).cartesian.xyz
assert allclose(gal_icrs.to(u.km/u.s, u.dimensionless_angles()),
-lsr.v_bary.d_xyz)
|
ef823756f472a07446c0bafe21b5269a71701c545c00352e1c903c52a2cd301e | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Test initalization and other aspects of Angle and subclasses"""
import pytest
import numpy as np
from numpy.testing import assert_allclose, assert_array_equal
from astropy.coordinates.angles import Longitude, Latitude, Angle
from astropy import units as u
from astropy.coordinates.errors import (IllegalSecondError, IllegalMinuteError, IllegalHourError,
IllegalSecondWarning, IllegalMinuteWarning)
def test_create_angles():
"""
Tests creating and accessing Angle objects
"""
''' The "angle" is a fundamental object. The internal
representation is stored in radians, but this is transparent to the user.
Units *must* be specified rather than a default value be assumed. This is
as much for self-documenting code as anything else.
Angle objects simply represent a single angular coordinate. More specific
angular coordinates (e.g. Longitude, Latitude) are subclasses of Angle.'''
a1 = Angle(54.12412, unit=u.degree)
a2 = Angle("54.12412", unit=u.degree)
a3 = Angle("54:07:26.832", unit=u.degree)
a4 = Angle("54.12412 deg")
a5 = Angle("54.12412 degrees")
a6 = Angle("54.12412°") # because we like Unicode
a7 = Angle((54, 7, 26.832), unit=u.degree)
a8 = Angle("54°07'26.832\"")
# (deg,min,sec) *tuples* are acceptable, but lists/arrays are *not*
# because of the need to eventually support arrays of coordinates
a9 = Angle([54, 7, 26.832], unit=u.degree)
assert_allclose(a9.value, [54, 7, 26.832])
assert a9.unit is u.degree
a10 = Angle(3.60827466667, unit=u.hour)
a11 = Angle("3:36:29.7888000120", unit=u.hour)
a12 = Angle((3, 36, 29.7888000120), unit=u.hour) # *must* be a tuple
# Regression test for #5001
a13 = Angle((3, 36, 29.7888000120), unit='hour')
Angle(0.944644098745, unit=u.radian)
with pytest.raises(u.UnitsError):
Angle(54.12412)
# raises an exception because this is ambiguous
with pytest.raises(u.UnitsError):
Angle(54.12412, unit=u.m)
with pytest.raises(ValueError):
Angle(12.34, unit="not a unit")
a14 = Angle("03h36m29.7888000120") # no trailing 's', but unambiguous
a15 = Angle("5h4m3s") # single digits, no decimal
assert a15.unit == u.hourangle
a16 = Angle("1 d")
a17 = Angle("1 degree")
assert a16.degree == 1
assert a17.degree == 1
a18 = Angle("54 07.4472", unit=u.degree)
a19 = Angle("54:07.4472", unit=u.degree)
a20 = Angle("54d07.4472m", unit=u.degree)
a21 = Angle("3h36m", unit=u.hour)
a22 = Angle("3.6h", unit=u.hour)
a23 = Angle("- 3h", unit=u.hour)
a24 = Angle("+ 3h", unit=u.hour)
# ensure the above angles that should match do
assert a1 == a2 == a3 == a4 == a5 == a6 == a7 == a8 == a18 == a19 == a20
assert_allclose(a1.radian, a2.radian)
assert_allclose(a2.degree, a3.degree)
assert_allclose(a3.radian, a4.radian)
assert_allclose(a4.radian, a5.radian)
assert_allclose(a5.radian, a6.radian)
assert_allclose(a6.radian, a7.radian)
assert_allclose(a10.degree, a11.degree)
assert a11 == a12 == a13 == a14
assert a21 == a22
assert a23 == -a24
# check for illegal ranges / values
with pytest.raises(IllegalSecondError):
a = Angle("12 32 99", unit=u.degree)
with pytest.raises(IllegalMinuteError):
a = Angle("12 99 23", unit=u.degree)
with pytest.raises(IllegalSecondError):
a = Angle("12 32 99", unit=u.hour)
with pytest.raises(IllegalMinuteError):
a = Angle("12 99 23", unit=u.hour)
with pytest.raises(IllegalHourError):
a = Angle("99 25 51.0", unit=u.hour)
with pytest.raises(ValueError):
a = Angle("12 25 51.0xxx", unit=u.hour)
with pytest.raises(ValueError):
a = Angle("12h34321m32.2s")
assert a1 is not None
def test_angle_from_view():
q = np.arange(3.) * u.deg
a = q.view(Angle)
assert type(a) is Angle
assert a.unit is q.unit
assert np.all(a == q)
q2 = np.arange(4) * u.m
with pytest.raises(u.UnitTypeError):
q2.view(Angle)
def test_angle_ops():
"""
Tests operations on Angle objects
"""
# Angles can be added and subtracted. Multiplication and division by a
# scalar is also permitted. A negative operator is also valid. All of
# these operate in a single dimension. Attempting to multiply or divide two
# Angle objects will return a quantity. An exception will be raised if it
# is attempted to store output with a non-angular unit in an Angle [#2718].
a1 = Angle(3.60827466667, unit=u.hour)
a2 = Angle("54:07:26.832", unit=u.degree)
a1 + a2 # creates new Angle object
a1 - a2
-a1
assert_allclose((a1 * 2).hour, 2 * 3.6082746666700003)
assert abs((a1 / 3.123456).hour - 3.60827466667 / 3.123456) < 1e-10
# commutativity
assert (2 * a1).hour == (a1 * 2).hour
a3 = Angle(a1) # makes a *copy* of the object, but identical content as a1
assert_allclose(a1.radian, a3.radian)
assert a1 is not a3
a4 = abs(-a1)
assert a4.radian == a1.radian
a5 = Angle(5.0, unit=u.hour)
assert a5 > a1
assert a5 >= a1
assert a1 < a5
assert a1 <= a5
# check operations with non-angular result give Quantity.
a6 = Angle(45., u.degree)
a7 = a6 * a5
assert type(a7) is u.Quantity
# but those with angular result yield Angle.
# (a9 is regression test for #5327)
a8 = a1 + 1.*u.deg
assert type(a8) is Angle
a9 = 1.*u.deg + a1
assert type(a9) is Angle
with pytest.raises(TypeError):
a6 *= a5
with pytest.raises(TypeError):
a6 *= u.m
with pytest.raises(TypeError):
np.sin(a6, out=a6)
def test_angle_methods():
# Most methods tested as part of the Quantity tests.
# A few tests here which caused problems before: #8368
a = Angle([0., 2.], 'deg')
a_mean = a.mean()
assert type(a_mean) is Angle
assert a_mean == 1. * u.degree
a_std = a.std()
assert type(a_std) is Angle
assert a_std == 1. * u.degree
a_var = a.var()
assert type(a_var) is u.Quantity
assert a_var == 1. * u.degree ** 2
a_ptp = a.ptp()
assert type(a_ptp) is Angle
assert a_ptp == 2. * u.degree
a_max = a.max()
assert type(a_max) is Angle
assert a_max == 2. * u.degree
a_min = a.min()
assert type(a_min) is Angle
assert a_min == 0. * u.degree
def test_angle_convert():
"""
Test unit conversion of Angle objects
"""
angle = Angle("54.12412", unit=u.degree)
assert_allclose(angle.hour, 3.60827466667)
assert_allclose(angle.radian, 0.944644098745)
assert_allclose(angle.degree, 54.12412)
assert len(angle.hms) == 3
assert isinstance(angle.hms, tuple)
assert angle.hms[0] == 3
assert angle.hms[1] == 36
assert_allclose(angle.hms[2], 29.78879999999947)
# also check that the namedtuple attribute-style access works:
assert angle.hms.h == 3
assert angle.hms.m == 36
assert_allclose(angle.hms.s, 29.78879999999947)
assert len(angle.dms) == 3
assert isinstance(angle.dms, tuple)
assert angle.dms[0] == 54
assert angle.dms[1] == 7
assert_allclose(angle.dms[2], 26.831999999992036)
# also check that the namedtuple attribute-style access works:
assert angle.dms.d == 54
assert angle.dms.m == 7
assert_allclose(angle.dms.s, 26.831999999992036)
assert isinstance(angle.dms[0], float)
assert isinstance(angle.hms[0], float)
# now make sure dms and signed_dms work right for negative angles
negangle = Angle("-54.12412", unit=u.degree)
assert negangle.dms.d == -54
assert negangle.dms.m == -7
assert_allclose(negangle.dms.s, -26.831999999992036)
assert negangle.signed_dms.sign == -1
assert negangle.signed_dms.d == 54
assert negangle.signed_dms.m == 7
assert_allclose(negangle.signed_dms.s, 26.831999999992036)
def test_angle_formatting():
"""
Tests string formatting for Angle objects
"""
'''
The string method of Angle has this signature:
def string(self, unit=DEGREE, decimal=False, sep=" ", precision=5,
pad=False):
The "decimal" parameter defaults to False since if you need to print the
Angle as a decimal, there's no need to use the "format" method (see
above).
'''
angle = Angle("54.12412", unit=u.degree)
# __str__ is the default `format`
assert str(angle) == angle.to_string()
res = 'Angle as HMS: 3h36m29.7888s'
assert "Angle as HMS: {0}".format(angle.to_string(unit=u.hour)) == res
res = 'Angle as HMS: 3:36:29.7888'
assert "Angle as HMS: {0}".format(angle.to_string(unit=u.hour, sep=":")) == res
res = 'Angle as HMS: 3:36:29.79'
assert "Angle as HMS: {0}".format(angle.to_string(unit=u.hour, sep=":",
precision=2)) == res
# Note that you can provide one, two, or three separators passed as a
# tuple or list
res = 'Angle as HMS: 3h36m29.7888s'
assert "Angle as HMS: {0}".format(angle.to_string(unit=u.hour,
sep=("h", "m", "s"),
precision=4)) == res
res = 'Angle as HMS: 3-36|29.7888'
assert "Angle as HMS: {0}".format(angle.to_string(unit=u.hour, sep=["-", "|"],
precision=4)) == res
res = 'Angle as HMS: 3-36-29.7888'
assert "Angle as HMS: {0}".format(angle.to_string(unit=u.hour, sep="-",
precision=4)) == res
res = 'Angle as HMS: 03h36m29.7888s'
assert "Angle as HMS: {0}".format(angle.to_string(unit=u.hour, precision=4,
pad=True)) == res
# Same as above, in degrees
angle = Angle("3 36 29.78880", unit=u.degree)
res = 'Angle as DMS: 3d36m29.7888s'
assert "Angle as DMS: {0}".format(angle.to_string(unit=u.degree)) == res
res = 'Angle as DMS: 3:36:29.7888'
assert "Angle as DMS: {0}".format(angle.to_string(unit=u.degree, sep=":")) == res
res = 'Angle as DMS: 3:36:29.79'
assert "Angle as DMS: {0}".format(angle.to_string(unit=u.degree, sep=":",
precision=2)) == res
# Note that you can provide one, two, or three separators passed as a
# tuple or list
res = 'Angle as DMS: 3d36m29.7888s'
assert "Angle as DMS: {0}".format(angle.to_string(unit=u.degree,
sep=("d", "m", "s"),
precision=4)) == res
res = 'Angle as DMS: 3-36|29.7888'
assert "Angle as DMS: {0}".format(angle.to_string(unit=u.degree, sep=["-", "|"],
precision=4)) == res
res = 'Angle as DMS: 3-36-29.7888'
assert "Angle as DMS: {0}".format(angle.to_string(unit=u.degree, sep="-",
precision=4)) == res
res = 'Angle as DMS: 03d36m29.7888s'
assert "Angle as DMS: {0}".format(angle.to_string(unit=u.degree, precision=4,
pad=True)) == res
res = 'Angle as rad: 0.0629763rad'
assert "Angle as rad: {0}".format(angle.to_string(unit=u.radian)) == res
res = 'Angle as rad decimal: 0.0629763'
assert "Angle as rad decimal: {0}".format(angle.to_string(unit=u.radian, decimal=True)) == res
# check negative angles
angle = Angle(-1.23456789, unit=u.degree)
angle2 = Angle(-1.23456789, unit=u.hour)
assert angle.to_string() == '-1d14m04.4444s'
assert angle.to_string(pad=True) == '-01d14m04.4444s'
assert angle.to_string(unit=u.hour) == '-0h04m56.2963s'
assert angle2.to_string(unit=u.hour, pad=True) == '-01h14m04.4444s'
assert angle.to_string(unit=u.radian, decimal=True) == '-0.0215473'
def test_to_string_vector():
# Regression test for the fact that vectorize doesn't work with Numpy 1.6
assert Angle([1./7., 1./7.], unit='deg').to_string()[0] == "0d08m34.2857s"
assert Angle([1./7.], unit='deg').to_string()[0] == "0d08m34.2857s"
assert Angle(1./7., unit='deg').to_string() == "0d08m34.2857s"
def test_angle_format_roundtripping():
"""
Ensures that the string representation of an angle can be used to create a
new valid Angle.
"""
a1 = Angle(0, unit=u.radian)
a2 = Angle(10, unit=u.degree)
a3 = Angle(0.543, unit=u.degree)
a4 = Angle('1d2m3.4s')
assert Angle(str(a1)).degree == a1.degree
assert Angle(str(a2)).degree == a2.degree
assert Angle(str(a3)).degree == a3.degree
assert Angle(str(a4)).degree == a4.degree
# also check Longitude/Latitude
ra = Longitude('1h2m3.4s')
dec = Latitude('1d2m3.4s')
assert_allclose(Angle(str(ra)).degree, ra.degree)
assert_allclose(Angle(str(dec)).degree, dec.degree)
def test_radec():
"""
Tests creation/operations of Longitude and Latitude objects
"""
'''
Longitude and Latitude are objects that are subclassed from Angle. As with Angle, Longitude
and Latitude can parse any unambiguous format (tuples, formatted strings, etc.).
The intention is not to create an Angle subclass for every possible
coordinate object (e.g. galactic l, galactic b). However, equatorial Longitude/Latitude
are so prevalent in astronomy that it's worth creating ones for these
units. They will be noted as "special" in the docs and use of the just the
Angle class is to be used for other coordinate systems.
'''
with pytest.raises(u.UnitsError):
ra = Longitude("4:08:15.162342") # error - hours or degrees?
with pytest.raises(u.UnitsError):
ra = Longitude("-4:08:15.162342")
# the "smart" initializer allows >24 to automatically do degrees, but the
# Angle-based one does not
# TODO: adjust in 0.3 for whatever behavior is decided on
# ra = Longitude("26:34:15.345634") # unambiguous b/c hours don't go past 24
# assert_allclose(ra.degree, 26.570929342)
with pytest.raises(u.UnitsError):
ra = Longitude("26:34:15.345634")
# ra = Longitude(68)
with pytest.raises(u.UnitsError):
ra = Longitude(68)
with pytest.raises(u.UnitsError):
ra = Longitude(12)
with pytest.raises(ValueError):
ra = Longitude("garbage containing a d and no units")
ra = Longitude("12h43m23s")
assert_allclose(ra.hour, 12.7230555556)
ra = Longitude((56, 14, 52.52), unit=u.degree) # can accept tuples
# TODO: again, fix based on >24 behavior
# ra = Longitude((56,14,52.52))
with pytest.raises(u.UnitsError):
ra = Longitude((56, 14, 52.52))
with pytest.raises(u.UnitsError):
ra = Longitude((12, 14, 52)) # ambiguous w/o units
ra = Longitude((12, 14, 52), unit=u.hour)
ra = Longitude([56, 64, 52.2], unit=u.degree) # ...but not arrays (yet)
# Units can be specified
ra = Longitude("4:08:15.162342", unit=u.hour)
# TODO: this was the "smart" initializer behavior - adjust in 0.3 appropriately
# Where Longitude values are commonly found in hours or degrees, declination is
# nearly always specified in degrees, so this is the default.
# dec = Latitude("-41:08:15.162342")
with pytest.raises(u.UnitsError):
dec = Latitude("-41:08:15.162342")
dec = Latitude("-41:08:15.162342", unit=u.degree) # same as above
def test_negative_zero_dms():
# Test for DMS parser
a = Angle('-00:00:10', u.deg)
assert_allclose(a.degree, -10. / 3600.)
# Unicode minus
a = Angle('−00:00:10', u.deg)
assert_allclose(a.degree, -10. / 3600.)
def test_negative_zero_dm():
# Test for DM parser
a = Angle('-00:10', u.deg)
assert_allclose(a.degree, -10. / 60.)
def test_negative_zero_hms():
# Test for HMS parser
a = Angle('-00:00:10', u.hour)
assert_allclose(a.hour, -10. / 3600.)
def test_negative_zero_hm():
# Test for HM parser
a = Angle('-00:10', u.hour)
assert_allclose(a.hour, -10. / 60.)
def test_negative_sixty_hm():
# Test for HM parser
with pytest.warns(IllegalMinuteWarning):
a = Angle('-00:60', u.hour)
assert_allclose(a.hour, -1.)
def test_plus_sixty_hm():
# Test for HM parser
with pytest.warns(IllegalMinuteWarning):
a = Angle('00:60', u.hour)
assert_allclose(a.hour, 1.)
def test_negative_fifty_nine_sixty_dms():
# Test for DMS parser
with pytest.warns(IllegalSecondWarning):
a = Angle('-00:59:60', u.deg)
assert_allclose(a.degree, -1.)
def test_plus_fifty_nine_sixty_dms():
# Test for DMS parser
with pytest.warns(IllegalSecondWarning):
a = Angle('+00:59:60', u.deg)
assert_allclose(a.degree, 1.)
def test_negative_sixty_dms():
# Test for DMS parser
with pytest.warns(IllegalSecondWarning):
a = Angle('-00:00:60', u.deg)
assert_allclose(a.degree, -1. / 60.)
def test_plus_sixty_dms():
# Test for DMS parser
with pytest.warns(IllegalSecondWarning):
a = Angle('+00:00:60', u.deg)
assert_allclose(a.degree, 1. / 60.)
def test_angle_to_is_angle():
with pytest.warns(IllegalSecondWarning):
a = Angle('00:00:60', u.deg)
assert isinstance(a, Angle)
assert isinstance(a.to(u.rad), Angle)
def test_angle_to_quantity():
with pytest.warns(IllegalSecondWarning):
a = Angle('00:00:60', u.deg)
q = u.Quantity(a)
assert isinstance(q, u.Quantity)
assert q.unit is u.deg
def test_quantity_to_angle():
a = Angle(1.0*u.deg)
assert isinstance(a, Angle)
with pytest.raises(u.UnitsError):
Angle(1.0*u.meter)
a = Angle(1.0*u.hour)
assert isinstance(a, Angle)
assert a.unit is u.hourangle
with pytest.raises(u.UnitsError):
Angle(1.0*u.min)
def test_angle_string():
with pytest.warns(IllegalSecondWarning):
a = Angle('00:00:60', u.deg)
assert str(a) == '0d01m00s'
a = Angle('-00:00:10', u.hour)
assert str(a) == '-0h00m10s'
a = Angle(3.2, u.radian)
assert str(a) == '3.2rad'
a = Angle(4.2, u.microarcsecond)
assert str(a) == '4.2uarcsec'
a = Angle('1.0uarcsec')
assert a.value == 1.0
assert a.unit == u.microarcsecond
a = Angle("3d")
assert_allclose(a.value, 3.0)
assert a.unit == u.degree
a = Angle('10"')
assert_allclose(a.value, 10.0)
assert a.unit == u.arcsecond
a = Angle("10'")
assert_allclose(a.value, 10.0)
assert a.unit == u.arcminute
def test_angle_repr():
assert 'Angle' in repr(Angle(0, u.deg))
assert 'Longitude' in repr(Longitude(0, u.deg))
assert 'Latitude' in repr(Latitude(0, u.deg))
a = Angle(0, u.deg)
repr(a)
def test_large_angle_representation():
"""Test that angles above 360 degrees can be output as strings,
in repr, str, and to_string. (regression test for #1413)"""
a = Angle(350, u.deg) + Angle(350, u.deg)
a.to_string()
a.to_string(u.hourangle)
repr(a)
repr(a.to(u.hourangle))
str(a)
str(a.to(u.hourangle))
def test_wrap_at_inplace():
a = Angle([-20, 150, 350, 360] * u.deg)
out = a.wrap_at('180d', inplace=True)
assert out is None
assert np.all(a.degree == np.array([-20., 150., -10., 0.]))
def test_latitude():
with pytest.raises(ValueError):
lat = Latitude(['91d', '89d'])
with pytest.raises(ValueError):
lat = Latitude('-91d')
lat = Latitude(['90d', '89d'])
# check that one can get items
assert lat[0] == 90 * u.deg
assert lat[1] == 89 * u.deg
# and that comparison with angles works
assert np.all(lat == Angle(['90d', '89d']))
# check setitem works
lat[1] = 45. * u.deg
assert np.all(lat == Angle(['90d', '45d']))
# but not with values out of range
with pytest.raises(ValueError):
lat[0] = 90.001 * u.deg
with pytest.raises(ValueError):
lat[0] = -90.001 * u.deg
# these should also not destroy input (#1851)
assert np.all(lat == Angle(['90d', '45d']))
# conserve type on unit change (closes #1423)
angle = lat.to('radian')
assert type(angle) is Latitude
# but not on calculations
angle = lat - 190 * u.deg
assert type(angle) is Angle
assert angle[0] == -100 * u.deg
lat = Latitude('80d')
angle = lat / 2.
assert type(angle) is Angle
assert angle == 40 * u.deg
angle = lat * 2.
assert type(angle) is Angle
assert angle == 160 * u.deg
angle = -lat
assert type(angle) is Angle
assert angle == -80 * u.deg
# Test errors when trying to interoperate with longitudes.
with pytest.raises(TypeError) as excinfo:
lon = Longitude(10, 'deg')
lat = Latitude(lon)
assert "A Latitude angle cannot be created from a Longitude angle" in str(excinfo)
with pytest.raises(TypeError) as excinfo:
lon = Longitude(10, 'deg')
lat = Latitude([20], 'deg')
lat[0] = lon
assert "A Longitude angle cannot be assigned to a Latitude angle" in str(excinfo)
# Check we can work around the Lat vs Long checks by casting explicitly to Angle.
lon = Longitude(10, 'deg')
lat = Latitude(Angle(lon))
assert lat.value == 10.0
# Check setitem.
lon = Longitude(10, 'deg')
lat = Latitude([20], 'deg')
lat[0] = Angle(lon)
assert lat.value[0] == 10.0
def test_longitude():
# Default wrapping at 360d with an array input
lon = Longitude(['370d', '88d'])
assert np.all(lon == Longitude(['10d', '88d']))
assert np.all(lon == Angle(['10d', '88d']))
# conserve type on unit change and keep wrap_angle (closes #1423)
angle = lon.to('hourangle')
assert type(angle) is Longitude
assert angle.wrap_angle == lon.wrap_angle
angle = lon[0]
assert type(angle) is Longitude
assert angle.wrap_angle == lon.wrap_angle
angle = lon[1:]
assert type(angle) is Longitude
assert angle.wrap_angle == lon.wrap_angle
# but not on calculations
angle = lon / 2.
assert np.all(angle == Angle(['5d', '44d']))
assert type(angle) is Angle
assert not hasattr(angle, 'wrap_angle')
angle = lon * 2. + 400 * u.deg
assert np.all(angle == Angle(['420d', '576d']))
assert type(angle) is Angle
# Test setting a mutable value and having it wrap
lon[1] = -10 * u.deg
assert np.all(lon == Angle(['10d', '350d']))
# Test wrapping and try hitting some edge cases
lon = Longitude(np.array([0, 0.5, 1.0, 1.5, 2.0]) * np.pi, unit=u.radian)
assert np.all(lon.degree == np.array([0., 90, 180, 270, 0]))
lon = Longitude(np.array([0, 0.5, 1.0, 1.5, 2.0]) * np.pi, unit=u.radian, wrap_angle='180d')
assert np.all(lon.degree == np.array([0., 90, -180, -90, 0]))
# Wrap on setting wrap_angle property (also test auto-conversion of wrap_angle to an Angle)
lon = Longitude(np.array([0, 0.5, 1.0, 1.5, 2.0]) * np.pi, unit=u.radian)
lon.wrap_angle = '180d'
assert np.all(lon.degree == np.array([0., 90, -180, -90, 0]))
lon = Longitude('460d')
assert lon == Angle('100d')
lon.wrap_angle = '90d'
assert lon == Angle('-260d')
# check that if we initialize a longitude with another longitude,
# wrap_angle is kept by default
lon2 = Longitude(lon)
assert lon2.wrap_angle == lon.wrap_angle
# but not if we explicitly set it
lon3 = Longitude(lon, wrap_angle='180d')
assert lon3.wrap_angle == 180 * u.deg
# check for problem reported in #2037 about Longitude initializing to -0
lon = Longitude(0, u.deg)
lonstr = lon.to_string()
assert not lonstr.startswith('-')
# also make sure dtype is correctly conserved
assert Longitude(0, u.deg, dtype=float).dtype == np.dtype(float)
assert Longitude(0, u.deg, dtype=int).dtype == np.dtype(int)
# Test errors when trying to interoperate with latitudes.
with pytest.raises(TypeError) as excinfo:
lat = Latitude(10, 'deg')
lon = Longitude(lat)
assert "A Longitude angle cannot be created from a Latitude angle" in str(excinfo)
with pytest.raises(TypeError) as excinfo:
lat = Latitude(10, 'deg')
lon = Longitude([20], 'deg')
lon[0] = lat
assert "A Latitude angle cannot be assigned to a Longitude angle" in str(excinfo)
# Check we can work around the Lat vs Long checks by casting explicitly to Angle.
lat = Latitude(10, 'deg')
lon = Longitude(Angle(lat))
assert lon.value == 10.0
# Check setitem.
lat = Latitude(10, 'deg')
lon = Longitude([20], 'deg')
lon[0] = Angle(lat)
assert lon.value[0] == 10.0
def test_wrap_at():
a = Angle([-20, 150, 350, 360] * u.deg)
assert np.all(a.wrap_at(360 * u.deg).degree == np.array([340., 150., 350., 0.]))
assert np.all(a.wrap_at(Angle(360, unit=u.deg)).degree == np.array([340., 150., 350., 0.]))
assert np.all(a.wrap_at('360d').degree == np.array([340., 150., 350., 0.]))
assert np.all(a.wrap_at('180d').degree == np.array([-20., 150., -10., 0.]))
assert np.all(a.wrap_at(np.pi * u.rad).degree == np.array([-20., 150., -10., 0.]))
# Test wrapping a scalar Angle
a = Angle('190d')
assert a.wrap_at('180d') == Angle('-170d')
a = Angle(np.arange(-1000.0, 1000.0, 0.125), unit=u.deg)
for wrap_angle in (270, 0.2, 0.0, 360.0, 500, -2000.125):
aw = a.wrap_at(wrap_angle * u.deg)
assert np.all(aw.degree >= wrap_angle - 360.0)
assert np.all(aw.degree < wrap_angle)
aw = a.to(u.rad).wrap_at(wrap_angle * u.deg)
assert np.all(aw.degree >= wrap_angle - 360.0)
assert np.all(aw.degree < wrap_angle)
def test_is_within_bounds():
a = Angle([-20, 150, 350] * u.deg)
assert a.is_within_bounds('0d', '360d') is False
assert a.is_within_bounds(None, '360d') is True
assert a.is_within_bounds(-30 * u.deg, None) is True
a = Angle('-20d')
assert a.is_within_bounds('0d', '360d') is False
assert a.is_within_bounds(None, '360d') is True
assert a.is_within_bounds(-30 * u.deg, None) is True
def test_angle_mismatched_unit():
a = Angle('+6h7m8s', unit=u.degree)
assert_allclose(a.value, 91.78333333333332)
def test_regression_formatting_negative():
# Regression test for a bug that caused:
#
# >>> Angle(-1., unit='deg').to_string()
# '-1d00m-0s'
assert Angle(-0., unit='deg').to_string() == '-0d00m00s'
assert Angle(-1., unit='deg').to_string() == '-1d00m00s'
assert Angle(-0., unit='hour').to_string() == '-0h00m00s'
assert Angle(-1., unit='hour').to_string() == '-1h00m00s'
def test_empty_sep():
a = Angle('05h04m31.93830s')
assert a.to_string(sep='', precision=2, pad=True) == '050431.94'
def test_create_tuple():
"""
Tests creation of an angle with a (d,m,s) or (h,m,s) tuple
"""
a1 = Angle((1, 30, 0), unit=u.degree)
assert a1.value == 1.5
a1 = Angle((1, 30, 0), unit=u.hourangle)
assert a1.value == 1.5
def test_list_of_quantities():
a1 = Angle([1*u.deg, 1*u.hourangle])
assert a1.unit == u.deg
assert_allclose(a1.value, [1, 15])
a2 = Angle([1*u.hourangle, 1*u.deg], u.deg)
assert a2.unit == u.deg
assert_allclose(a2.value, [15, 1])
def test_multiply_divide():
# Issue #2273
a1 = Angle([1, 2, 3], u.deg)
a2 = Angle([4, 5, 6], u.deg)
a3 = a1 * a2
assert_allclose(a3.value, [4, 10, 18])
assert a3.unit == (u.deg * u.deg)
a3 = a1 / a2
assert_allclose(a3.value, [.25, .4, .5])
assert a3.unit == u.dimensionless_unscaled
def test_mixed_string_and_quantity():
a1 = Angle(['1d', 1. * u.deg])
assert_array_equal(a1.value, [1., 1.])
assert a1.unit == u.deg
a2 = Angle(['1d', 1 * u.rad * np.pi, '3d'])
assert_array_equal(a2.value, [1., 180., 3.])
assert a2.unit == u.deg
def test_array_angle_tostring():
aobj = Angle([1, 2], u.deg)
assert aobj.to_string().dtype.kind == 'U'
assert np.all(aobj.to_string() == ['1d00m00s', '2d00m00s'])
def test_wrap_at_without_new():
"""
Regression test for subtle bugs from situations where an Angle is
created via numpy channels that don't do the standard __new__ but instead
depend on array_finalize to set state. Longitude is used because the
bug was in its _wrap_angle not getting initialized correctly
"""
l1 = Longitude([1]*u.deg)
l2 = Longitude([2]*u.deg)
l = np.concatenate([l1, l2])
assert l._wrap_angle is not None
def test__str__():
"""
Check the __str__ method used in printing the Angle
"""
# scalar angle
scangle = Angle('10.2345d')
strscangle = scangle.__str__()
assert strscangle == '10d14m04.2s'
# non-scalar array angles
arrangle = Angle(['10.2345d', '-20d'])
strarrangle = arrangle.__str__()
assert strarrangle == '[10d14m04.2s -20d00m00s]'
# summarizing for large arrays, ... should appear
bigarrangle = Angle(np.ones(10000), u.deg)
assert '...' in bigarrangle.__str__()
def test_repr_latex():
"""
Check the _repr_latex_ method, used primarily by IPython notebooks
"""
# try with both scalar
scangle = Angle(2.1, u.deg)
rlscangle = scangle._repr_latex_()
# and array angles
arrangle = Angle([1, 2.1], u.deg)
rlarrangle = arrangle._repr_latex_()
assert rlscangle == r'$2^\circ06{}^\prime00{}^{\prime\prime}$'
assert rlscangle.split('$')[1] in rlarrangle
# make sure the ... appears for large arrays
bigarrangle = Angle(np.ones(50000)/50000., u.deg)
assert '...' in bigarrangle._repr_latex_()
def test_angle_with_cds_units_enabled():
"""Regression test for #5350
Especially the example in
https://github.com/astropy/astropy/issues/5350#issuecomment-248770151
"""
from astropy.units import cds
# the problem is with the parser, so remove it temporarily
from astropy.coordinates.angle_utilities import _AngleParser
del _AngleParser._parser
with cds.enable():
Angle('5d')
del _AngleParser._parser
Angle('5d')
|
9bd200c28f962f8dd8bf4c809d3ca4824b60b83b3b006139e4354578096cc680 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Tests for the projected separation stuff
"""
import pytest
import numpy as np
from astropy.tests.helper import assert_quantity_allclose as assert_allclose
from astropy import units as u
from astropy.coordinates.builtin_frames import ICRS, FK5, Galactic
from astropy.coordinates import Angle, Distance
# lon1, lat1, lon2, lat2 in degrees
coords = [(1, 0, 0, 0),
(0, 1, 0, 0),
(0, 0, 1, 0),
(0, 0, 0, 1),
(0, 0, 10, 0),
(0, 0, 90, 0),
(0, 0, 180, 0),
(0, 45, 0, -45),
(0, 60, 0, -30),
(-135, -15, 45, 15),
(100, -89, -80, 89),
(0, 0, 0, 0),
(0, 0, 1. / 60., 1. / 60.)]
correct_seps = [1, 1, 1, 1, 10, 90, 180, 90, 90, 180, 180, 0,
0.023570225877234643]
correctness_margin = 2e-10
def test_angsep():
"""
Tests that the angular separation object also behaves correctly.
"""
from astropy.coordinates.angle_utilities import angular_separation
# check it both works with floats in radians, Quantities, or Angles
for conv in (np.deg2rad,
lambda x: u.Quantity(x, "deg"),
lambda x: Angle(x, "deg")):
for (lon1, lat1, lon2, lat2), corrsep in zip(coords, correct_seps):
angsep = angular_separation(conv(lon1), conv(lat1),
conv(lon2), conv(lat2))
assert np.fabs(angsep - conv(corrsep)) < conv(correctness_margin)
def test_fk5_seps():
"""
This tests if `separation` works for FK5 objects.
This is a regression test for github issue #891
"""
a = FK5(1.*u.deg, 1.*u.deg)
b = FK5(2.*u.deg, 2.*u.deg)
a.separation(b)
def test_proj_separations():
"""
Test angular separation functionality
"""
c1 = ICRS(ra=0*u.deg, dec=0*u.deg)
c2 = ICRS(ra=0*u.deg, dec=1*u.deg)
sep = c2.separation(c1)
# returns an Angle object
assert isinstance(sep, Angle)
assert sep.degree == 1
assert_allclose(sep.arcminute, 60.)
# these operations have ambiguous interpretations for points on a sphere
with pytest.raises(TypeError):
c1 + c2
with pytest.raises(TypeError):
c1 - c2
ngp = Galactic(l=0*u.degree, b=90*u.degree)
ncp = ICRS(ra=0*u.degree, dec=90*u.degree)
# if there is a defined conversion between the relevant coordinate systems,
# it will be automatically performed to get the right angular separation
assert_allclose(ncp.separation(ngp.transform_to(ICRS)).degree,
ncp.separation(ngp).degree)
# distance from the north galactic pole to celestial pole
assert_allclose(ncp.separation(ngp.transform_to(ICRS)).degree,
62.87174758503201)
def test_3d_separations():
"""
Test 3D separation functionality
"""
c1 = ICRS(ra=1*u.deg, dec=1*u.deg, distance=9*u.kpc)
c2 = ICRS(ra=1*u.deg, dec=1*u.deg, distance=10*u.kpc)
sep3d = c2.separation_3d(c1)
assert isinstance(sep3d, Distance)
assert_allclose(sep3d - 1*u.kpc, 0*u.kpc, atol=1e-12*u.kpc)
|
d3d32f6a21a48891f0aa4b0797a36a671addb1b75ff7277a77ef5ed3625fe164 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
This is the APE5 coordinates API document re-written to work as a series of test
functions.
Note that new tests for coordinates functionality should generally *not* be
added to this file - instead, add them to other appropriate test modules in
this package, like ``test_sky_coord.py``, ``test_frames.py``, or
``test_representation.py``. This file is instead meant mainly to keep track of
deviations from the original APE5 plan.
"""
import pytest
import numpy as np
from numpy import testing as npt
from astropy.tests.helper import raises, assert_quantity_allclose as assert_allclose
from astropy import units as u
from astropy import time
from astropy import coordinates as coords
from astropy.units import allclose
try:
import scipy # pylint: disable=W0611
except ImportError:
HAS_SCIPY = False
else:
HAS_SCIPY = True
def test_representations_api():
from astropy.coordinates.representation import SphericalRepresentation, \
UnitSphericalRepresentation, PhysicsSphericalRepresentation, \
CartesianRepresentation
from astropy.coordinates import Angle, Longitude, Latitude, Distance
# <-----------------Classes for representation of coordinate data-------------->
# These classes inherit from a common base class and internally contain Quantity
# objects, which are arrays (although they may act as scalars, like numpy's
# length-0 "arrays")
# They can be initialized with a variety of ways that make intuitive sense.
# Distance is optional.
UnitSphericalRepresentation(lon=8*u.hour, lat=5*u.deg)
UnitSphericalRepresentation(lon=8*u.hourangle, lat=5*u.deg)
SphericalRepresentation(lon=8*u.hourangle, lat=5*u.deg, distance=10*u.kpc)
# In the initial implementation, the lat/lon/distance arguments to the
# initializer must be in order. A *possible* future change will be to allow
# smarter guessing of the order. E.g. `Latitude` and `Longitude` objects can be
# given in any order.
UnitSphericalRepresentation(Longitude(8, u.hour), Latitude(5, u.deg))
SphericalRepresentation(Longitude(8, u.hour), Latitude(5, u.deg), Distance(10, u.kpc))
# Arrays of any of the inputs are fine
UnitSphericalRepresentation(lon=[8, 9]*u.hourangle, lat=[5, 6]*u.deg)
# Default is to copy arrays, but optionally, it can be a reference
UnitSphericalRepresentation(lon=[8, 9]*u.hourangle, lat=[5, 6]*u.deg, copy=False)
# strings are parsed by `Latitude` and `Longitude` constructors, so no need to
# implement parsing in the Representation classes
UnitSphericalRepresentation(lon=Angle('2h6m3.3s'), lat=Angle('0.1rad'))
# Or, you can give `Quantity`s with keywords, and they will be internally
# converted to Angle/Distance
c1 = SphericalRepresentation(lon=8*u.hourangle, lat=5*u.deg, distance=10*u.kpc)
# Can also give another representation object with the `reprobj` keyword.
c2 = SphericalRepresentation.from_representation(c1)
# distance, lat, and lon typically will just match in shape
SphericalRepresentation(lon=[8, 9]*u.hourangle, lat=[5, 6]*u.deg, distance=[10, 11]*u.kpc)
# if the inputs are not the same, if possible they will be broadcast following
# numpy's standard broadcasting rules.
c2 = SphericalRepresentation(lon=[8, 9]*u.hourangle, lat=[5, 6]*u.deg, distance=10*u.kpc)
assert len(c2.distance) == 2
# when they can't be broadcast, it is a ValueError (same as Numpy)
with raises(ValueError):
c2 = UnitSphericalRepresentation(lon=[8, 9, 10]*u.hourangle, lat=[5, 6]*u.deg)
# It's also possible to pass in scalar quantity lists with mixed units. These
# are converted to array quantities following the same rule as `Quantity`: all
# elements are converted to match the first element's units.
c2 = UnitSphericalRepresentation(lon=Angle([8*u.hourangle, 135*u.deg]),
lat=Angle([5*u.deg, (6*np.pi/180)*u.rad]))
assert c2.lat.unit == u.deg and c2.lon.unit == u.hourangle
npt.assert_almost_equal(c2.lon[1].value, 9)
# The Quantity initializer itself can also be used to force the unit even if the
# first element doesn't have the right unit
lon = u.Quantity([120*u.deg, 135*u.deg], u.hourangle)
lat = u.Quantity([(5*np.pi/180)*u.rad, 0.4*u.hourangle], u.deg)
c2 = UnitSphericalRepresentation(lon, lat)
# regardless of how input, the `lat` and `lon` come out as angle/distance
assert isinstance(c1.lat, Angle)
assert isinstance(c1.lat, Latitude) # `Latitude` is an `Angle` subclass
assert isinstance(c1.distance, Distance)
# but they are read-only, as representations are immutable once created
with raises(AttributeError):
c1.lat = Latitude(5, u.deg)
# Note that it is still possible to modify the array in-place, but this is not
# sanctioned by the API, as this would prevent things like caching.
c2.lat[:] = [0] * u.deg # possible, but NOT SUPPORTED
# To address the fact that there are various other conventions for how spherical
# coordinates are defined, other conventions can be included as new classes.
# Later there may be other conventions that we implement - for now just the
# physics convention, as it is one of the most common cases.
c3 = PhysicsSphericalRepresentation(phi=120*u.deg, theta=85*u.deg, r=3*u.kpc)
# first dimension must be length-3 if a lone `Quantity` is passed in.
c1 = CartesianRepresentation(np.random.randn(3, 100) * u.kpc)
assert c1.xyz.shape[0] == 3
assert c1.xyz.unit == u.kpc
assert c1.x.shape[0] == 100
assert c1.y.shape[0] == 100
assert c1.z.shape[0] == 100
# can also give each as separate keywords
CartesianRepresentation(x=np.random.randn(100)*u.kpc,
y=np.random.randn(100)*u.kpc,
z=np.random.randn(100)*u.kpc)
# if the units don't match but are all distances, they will automatically be
# converted to match `x`
xarr, yarr, zarr = np.random.randn(3, 100)
c1 = CartesianRepresentation(x=xarr*u.kpc, y=yarr*u.kpc, z=zarr*u.kpc)
c2 = CartesianRepresentation(x=xarr*u.kpc, y=yarr*u.kpc, z=zarr*u.pc)
assert c1.xyz.unit == c2.xyz.unit == u.kpc
assert_allclose((c1.z / 1000) - c2.z, 0*u.kpc, atol=1e-10*u.kpc)
# representations convert into other representations via `represent_as`
srep = SphericalRepresentation(lon=90*u.deg, lat=0*u.deg, distance=1*u.pc)
crep = srep.represent_as(CartesianRepresentation)
assert_allclose(crep.x, 0*u.pc, atol=1e-10*u.pc)
assert_allclose(crep.y, 1*u.pc, atol=1e-10*u.pc)
assert_allclose(crep.z, 0*u.pc, atol=1e-10*u.pc)
# The functions that actually do the conversion are defined via methods on the
# representation classes. This may later be expanded into a full registerable
# transform graph like the coordinate frames, but initially it will be a simpler
# method system
def test_frame_api():
from astropy.coordinates.representation import SphericalRepresentation, \
UnitSphericalRepresentation
from astropy.coordinates.builtin_frames import ICRS, FK5
# <--------------------Reference Frame/"Low-level" classes--------------------->
# The low-level classes have a dual role: they act as specifiers of coordinate
# frames and they *may* also contain data as one of the representation objects,
# in which case they are the actual coordinate objects themselves.
# They can always accept a representation as a first argument
icrs = ICRS(UnitSphericalRepresentation(lon=8*u.hour, lat=5*u.deg))
# which is stored as the `data` attribute
assert icrs.data.lat == 5*u.deg
assert icrs.data.lon == 8*u.hourangle
# Frames that require additional information like equinoxs or obstimes get them
# as keyword parameters to the frame constructor. Where sensible, defaults are
# used. E.g., FK5 is almost always J2000 equinox
fk5 = FK5(UnitSphericalRepresentation(lon=8*u.hour, lat=5*u.deg))
J2000 = time.Time('J2000')
fk5_2000 = FK5(UnitSphericalRepresentation(lon=8*u.hour, lat=5*u.deg), equinox=J2000)
assert fk5.equinox == fk5_2000.equinox
# the information required to specify the frame is immutable
J2001 = time.Time('J2001')
with raises(AttributeError):
fk5.equinox = J2001
# Similar for the representation data.
with raises(AttributeError):
fk5.data = UnitSphericalRepresentation(lon=8*u.hour, lat=5*u.deg)
# There is also a class-level attribute that lists the attributes needed to
# identify the frame. These include attributes like `equinox` shown above.
assert all(nm in ('equinox', 'obstime') for nm in fk5.get_frame_attr_names())
# the result of `get_frame_attr_names` is called for particularly in the
# high-level class (discussed below) to allow round-tripping between various
# frames. It is also part of the public API for other similar developer /
# advanced users' use.
# The actual position information is accessed via the representation objects
assert_allclose(icrs.represent_as(SphericalRepresentation).lat, 5*u.deg)
# shorthand for the above
assert_allclose(icrs.spherical.lat, 5*u.deg)
assert icrs.cartesian.z.value > 0
# Many frames have a "default" representation, the one in which they are
# conventionally described, often with a special name for some of the
# coordinates. E.g., most equatorial coordinate systems are spherical with RA and
# Dec. This works simply as a shorthand for the longer form above
assert_allclose(icrs.dec, 5*u.deg)
assert_allclose(fk5.ra, 8*u.hourangle)
assert icrs.representation_type == SphericalRepresentation
# low-level classes can also be initialized with names valid for that representation
# and frame:
icrs_2 = ICRS(ra=8*u.hour, dec=5*u.deg, distance=1*u.kpc)
assert_allclose(icrs.ra, icrs_2.ra)
# and these are taken as the default if keywords are not given:
# icrs_nokwarg = ICRS(8*u.hour, 5*u.deg, distance=1*u.kpc)
# assert icrs_nokwarg.ra == icrs_2.ra and icrs_nokwarg.dec == icrs_2.dec
# they also are capable of computing on-sky or 3d separations from each other,
# which will be a direct port of the existing methods:
coo1 = ICRS(ra=0*u.hour, dec=0*u.deg)
coo2 = ICRS(ra=0*u.hour, dec=1*u.deg)
# `separation` is the on-sky separation
assert coo1.separation(coo2).degree == 1.0
# while `separation_3d` includes the 3D distance information
coo3 = ICRS(ra=0*u.hour, dec=0*u.deg, distance=1*u.kpc)
coo4 = ICRS(ra=0*u.hour, dec=0*u.deg, distance=2*u.kpc)
assert coo3.separation_3d(coo4).kpc == 1.0
# The next example fails because `coo1` and `coo2` don't have distances
with raises(ValueError):
assert coo1.separation_3d(coo2).kpc == 1.0
# repr/str also shows info, with frame and data
# assert repr(fk5) == ''
def test_transform_api():
from astropy.coordinates.representation import UnitSphericalRepresentation
from astropy.coordinates.builtin_frames import ICRS, FK5
from astropy.coordinates.baseframe import frame_transform_graph, BaseCoordinateFrame
from astropy.coordinates.transformations import DynamicMatrixTransform
# <------------------------Transformations------------------------------------->
# Transformation functionality is the key to the whole scheme: they transform
# low-level classes from one frame to another.
# (used below but defined above in the API)
fk5 = FK5(ra=8*u.hour, dec=5*u.deg)
# If no data (or `None`) is given, the class acts as a specifier of a frame, but
# without any stored data.
J2001 = time.Time('J2001')
fk5_J2001_frame = FK5(equinox=J2001)
# if they do not have data, the string instead is the frame specification
assert repr(fk5_J2001_frame) == "<FK5 Frame (equinox=J2001.000)>"
# Note that, although a frame object is immutable and can't have data added, it
# can be used to create a new object that does have data by giving the
# `realize_frame` method a representation:
srep = UnitSphericalRepresentation(lon=8*u.hour, lat=5*u.deg)
fk5_j2001_with_data = fk5_J2001_frame.realize_frame(srep)
assert fk5_j2001_with_data.data is not None
# Now `fk5_j2001_with_data` is in the same frame as `fk5_J2001_frame`, but it
# is an actual low-level coordinate, rather than a frame without data.
# These frames are primarily useful for specifying what a coordinate should be
# transformed *into*, as they are used by the `transform_to` method
# E.g., this snippet precesses the point to the new equinox
newfk5 = fk5.transform_to(fk5_J2001_frame)
assert newfk5.equinox == J2001
# classes can also be given to `transform_to`, which then uses the defaults for
# the frame information:
samefk5 = fk5.transform_to(FK5)
# `fk5` was initialized using default `obstime` and `equinox`, so:
assert_allclose(samefk5.ra, fk5.ra, atol=1e-10*u.deg)
assert_allclose(samefk5.dec, fk5.dec, atol=1e-10*u.deg)
# transforming to a new frame necessarily loses framespec information if that
# information is not applicable to the new frame. This means transforms are not
# always round-trippable:
fk5_2 = FK5(ra=8*u.hour, dec=5*u.deg, equinox=J2001)
ic_trans = fk5_2.transform_to(ICRS)
# `ic_trans` does not have an `equinox`, so now when we transform back to FK5,
# it's a *different* RA and Dec
fk5_trans = ic_trans.transform_to(FK5)
assert not allclose(fk5_2.ra, fk5_trans.ra, rtol=0, atol=1e-10*u.deg)
# But if you explicitly give the right equinox, all is fine
fk5_trans_2 = fk5_2.transform_to(FK5(equinox=J2001))
assert_allclose(fk5_2.ra, fk5_trans_2.ra, rtol=0, atol=1e-10*u.deg)
# Trying to transforming a frame with no data is of course an error:
with raises(ValueError):
FK5(equinox=J2001).transform_to(ICRS)
# To actually define a new transformation, the same scheme as in the
# 0.2/0.3 coordinates framework can be re-used - a graph of transform functions
# connecting various coordinate classes together. The main changes are:
# 1) The transform functions now get the frame object they are transforming the
# current data into.
# 2) Frames with additional information need to have a way to transform between
# objects of the same class, but with different framespecinfo values
# An example transform function:
class SomeNewSystem(BaseCoordinateFrame):
pass
@frame_transform_graph.transform(DynamicMatrixTransform, SomeNewSystem, FK5)
def new_to_fk5(newobj, fk5frame):
ot = newobj.obstime
eq = fk5frame.equinox
# ... build a *cartesian* transform matrix using `eq` that transforms from
# the `newobj` frame as observed at `ot` to FK5 an equinox `eq`
matrix = np.eye(3)
return matrix
# Other options for transform functions include one that simply returns the new
# coordinate object, and one that returns a cartesian matrix but does *not*
# require `newobj` or `fk5frame` - this allows optimization of the transform.
def test_highlevel_api():
J2001 = time.Time('J2001')
# <--------------------------"High-level" class-------------------------------->
# The "high-level" class is intended to wrap the lower-level classes in such a
# way that they can be round-tripped, as well as providing a variety of
# convenience functionality. This document is not intended to show *all* of the
# possible high-level functionality, rather how the high-level classes are
# initialized and interact with the low-level classes
# this creates an object that contains an `ICRS` low-level class, initialized
# identically to the first ICRS example further up.
sc = coords.SkyCoord(coords.SphericalRepresentation(lon=8 * u.hour,
lat=5 * u.deg, distance=1 * u.kpc), frame='icrs')
# Other representations and `system` keywords delegate to the appropriate
# low-level class. The already-existing registry for user-defined coordinates
# will be used by `SkyCoordinate` to figure out what various the `system`
# keyword actually means.
sc = coords.SkyCoord(ra=8 * u.hour, dec=5 * u.deg, frame='icrs')
sc = coords.SkyCoord(l=120 * u.deg, b=5 * u.deg, frame='galactic')
# High-level classes can also be initialized directly from low-level objects
sc = coords.SkyCoord(coords.ICRS(ra=8 * u.hour, dec=5 * u.deg))
# The next example raises an error because the high-level class must always
# have position data.
with pytest.raises(ValueError):
sc = coords.SkyCoord(coords.FK5(equinox=J2001)) # raises ValueError
# similarly, the low-level object can always be accessed
# this is how it's supposed to look, but sometimes the numbers get rounded in
# funny ways
# assert repr(sc.frame) == '<ICRS Coordinate: ra=120.0 deg, dec=5.0 deg>'
rscf = repr(sc.frame)
assert rscf.startswith('<ICRS Coordinate: (ra, dec) in deg')
# and the string representation will be inherited from the low-level class.
# same deal, should loook like this, but different archituectures/ python
# versions may round the numbers differently
# assert repr(sc) == '<SkyCoord (ICRS): ra=120.0 deg, dec=5.0 deg>'
rsc = repr(sc)
assert rsc.startswith('<SkyCoord (ICRS): (ra, dec) in deg')
# Supports a variety of possible complex string formats
sc = coords.SkyCoord('8h00m00s +5d00m00.0s', frame='icrs')
# In the next example, the unit is only needed b/c units are ambiguous. In
# general, we *never* accept ambiguity
sc = coords.SkyCoord('8:00:00 +5:00:00.0', unit=(u.hour, u.deg), frame='icrs')
# The next one would yield length-2 array coordinates, because of the comma
sc = coords.SkyCoord(['8h 5d', '2°2′3″ 0.3rad'], frame='icrs')
# It should also interpret common designation styles as a coordinate
# NOT YET
# sc = coords.SkyCoord('SDSS J123456.89-012345.6', frame='icrs')
# but it should also be possible to provide formats for outputting to strings,
# similar to `Time`. This can be added right away or at a later date.
# transformation is done the same as for low-level classes, which it delegates to
sc_fk5_j2001 = sc.transform_to(coords.FK5(equinox=J2001))
assert sc_fk5_j2001.equinox == J2001
# The key difference is that the high-level class remembers frame information
# necessary for round-tripping, unlike the low-level classes:
sc1 = coords.SkyCoord(ra=8 * u.hour, dec=5 * u.deg, equinox=J2001, frame='fk5')
sc2 = sc1.transform_to('icrs')
# The next assertion succeeds, but it doesn't mean anything for ICRS, as ICRS
# isn't defined in terms of an equinox
assert sc2.equinox == J2001
# But it *is* necessary once we transform to FK5
sc3 = sc2.transform_to('fk5')
assert sc3.equinox == J2001
assert_allclose(sc1.ra, sc3.ra)
# `SkyCoord` will also include the attribute-style access that is in the
# v0.2/0.3 coordinate objects. This will *not* be in the low-level classes
sc = coords.SkyCoord(ra=8 * u.hour, dec=5 * u.deg, frame='icrs')
scgal = sc.galactic
assert str(scgal).startswith('<SkyCoord (Galactic): (l, b)')
# the existing `from_name` and `match_to_catalog_*` methods will be moved to the
# high-level class as convenience functionality.
# in remote-data test below!
# m31icrs = coords.SkyCoord.from_name('M31', frame='icrs')
# assert str(m31icrs) == '<SkyCoord (ICRS) RA=10.68471 deg, Dec=41.26875 deg>'
if HAS_SCIPY:
cat1 = coords.SkyCoord(ra=[1, 2]*u.hr, dec=[3, 4.01]*u.deg, distance=[5, 6]*u.kpc, frame='icrs')
cat2 = coords.SkyCoord(ra=[1, 2, 2.01]*u.hr, dec=[3, 4, 5]*u.deg, distance=[5, 200, 6]*u.kpc, frame='icrs')
idx1, sep2d1, dist3d1 = cat1.match_to_catalog_sky(cat2)
idx2, sep2d2, dist3d2 = cat1.match_to_catalog_3d(cat2)
assert np.any(idx1 != idx2)
# additional convenience functionality for the future should be added as methods
# on `SkyCoord`, *not* the low-level classes.
@pytest.mark.remote_data
def test_highlevel_api_remote():
m31icrs = coords.SkyCoord.from_name('M31', frame='icrs')
m31str = str(m31icrs)
assert m31str.startswith('<SkyCoord (ICRS): (ra, dec) in deg\n (')
assert m31str.endswith(')>')
assert '10.68' in m31str
assert '41.26' in m31str
# The above is essentially a replacement of the below, but tweaked so that
# small/moderate changes in what `from_name` returns don't cause the tests
# to fail
# assert str(m31icrs) == '<SkyCoord (ICRS): (ra, dec) in deg\n (10.6847083, 41.26875)>'
m31fk4 = coords.SkyCoord.from_name('M31', frame='fk4')
assert m31icrs.frame != m31fk4.frame
assert np.abs(m31icrs.ra - m31fk4.ra) > .5*u.deg
|
57e24537cccc844a4aa19359116536403faf676cb6e43bd26271e1fe4f2f3728 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Tests for putting velocity differentials into SkyCoord objects.
Note: the skyoffset velocity tests are in a different file, in
test_skyoffset_transformations.py
"""
import pytest
import numpy as np
from astropy import units as u
from astropy.tests.helper import assert_quantity_allclose
from astropy.coordinates import (SkyCoord, ICRS, SphericalRepresentation, SphericalDifferential,
SphericalCosLatDifferential, CartesianRepresentation,
CartesianDifferential, Galactic, PrecessedGeocentric)
try:
import scipy
HAS_SCIPY = True
except ImportError:
HAS_SCIPY = False
def test_creation_frameobjs():
i = ICRS(1*u.deg, 2*u.deg, pm_ra_cosdec=.2*u.mas/u.yr, pm_dec=.1*u.mas/u.yr)
sc = SkyCoord(i)
for attrnm in ['ra', 'dec', 'pm_ra_cosdec', 'pm_dec']:
assert_quantity_allclose(getattr(i, attrnm), getattr(sc, attrnm))
sc_nod = SkyCoord(ICRS(1*u.deg, 2*u.deg))
for attrnm in ['ra', 'dec']:
assert_quantity_allclose(getattr(sc, attrnm), getattr(sc_nod, attrnm))
def test_creation_attrs():
sc1 = SkyCoord(1*u.deg, 2*u.deg,
pm_ra_cosdec=.2*u.mas/u.yr, pm_dec=.1*u.mas/u.yr,
frame='fk5')
assert_quantity_allclose(sc1.ra, 1*u.deg)
assert_quantity_allclose(sc1.dec, 2*u.deg)
assert_quantity_allclose(sc1.pm_ra_cosdec, .2*u.arcsec/u.kyr)
assert_quantity_allclose(sc1.pm_dec, .1*u.arcsec/u.kyr)
sc2 = SkyCoord(1*u.deg, 2*u.deg,
pm_ra=.2*u.mas/u.yr, pm_dec=.1*u.mas/u.yr,
differential_type=SphericalDifferential)
assert_quantity_allclose(sc2.ra, 1*u.deg)
assert_quantity_allclose(sc2.dec, 2*u.deg)
assert_quantity_allclose(sc2.pm_ra, .2*u.arcsec/u.kyr)
assert_quantity_allclose(sc2.pm_dec, .1*u.arcsec/u.kyr)
sc3 = SkyCoord('1:2:3 4:5:6',
pm_ra_cosdec=.2*u.mas/u.yr, pm_dec=.1*u.mas/u.yr,
unit=(u.hour, u.deg))
assert_quantity_allclose(sc3.ra, 1*u.hourangle + 2*u.arcmin*15 + 3*u.arcsec*15)
assert_quantity_allclose(sc3.dec, 4*u.deg + 5*u.arcmin + 6*u.arcsec)
# might as well check with sillier units?
assert_quantity_allclose(sc3.pm_ra_cosdec, 1.2776637006616473e-07 * u.arcmin / u.fortnight)
assert_quantity_allclose(sc3.pm_dec, 6.388318503308237e-08 * u.arcmin / u.fortnight)
def test_creation_copy_basic():
i = ICRS(1*u.deg, 2*u.deg, pm_ra_cosdec=.2*u.mas/u.yr, pm_dec=.1*u.mas/u.yr)
sc = SkyCoord(i)
sc_cpy = SkyCoord(sc)
for attrnm in ['ra', 'dec', 'pm_ra_cosdec', 'pm_dec']:
assert_quantity_allclose(getattr(sc, attrnm), getattr(sc_cpy, attrnm))
def test_creation_copy_rediff():
sc = SkyCoord(1*u.deg, 2*u.deg,
pm_ra=.2*u.mas/u.yr, pm_dec=.1*u.mas/u.yr,
differential_type=SphericalDifferential)
sc_cpy = SkyCoord(sc)
for attrnm in ['ra', 'dec', 'pm_ra', 'pm_dec']:
assert_quantity_allclose(getattr(sc, attrnm), getattr(sc_cpy, attrnm))
sc_newdiff = SkyCoord(sc, differential_type=SphericalCosLatDifferential)
reprepr = sc.represent_as(SphericalRepresentation, SphericalCosLatDifferential)
assert_quantity_allclose(sc_newdiff.pm_ra_cosdec,
reprepr.differentials['s'].d_lon_coslat)
def test_creation_cartesian():
rep = CartesianRepresentation([10, 0., 0.]*u.pc)
dif = CartesianDifferential([0, 100, 0.]*u.pc/u.Myr)
rep = rep.with_differentials(dif)
c = SkyCoord(rep)
sdif = dif.represent_as(SphericalCosLatDifferential, rep)
assert_quantity_allclose(c.pm_ra_cosdec, sdif.d_lon_coslat)
def test_useful_error_missing():
sc_nod = SkyCoord(ICRS(1*u.deg, 2*u.deg))
try:
sc_nod.l
except AttributeError as e:
# this is double-checking the *normal* behavior
msg_l = e.args[0]
try:
sc_nod.pm_dec
except Exception as e:
msg_pm_dec = e.args[0]
assert "has no attribute" in msg_l
assert "has no associated differentials" in msg_pm_dec
# ----------------------Operations on SkyCoords w/ velocities-------------------
# define some fixtures to get baseline coordinates to try operations with
@pytest.fixture(scope="module", params=[(False, False),
(True, False),
(False, True),
(True, True)])
def sc(request):
incldist, inclrv = request.param
args = [1*u.deg, 2*u.deg]
kwargs = dict(pm_dec=1*u.mas/u.yr, pm_ra_cosdec=2*u.mas/u.yr)
if incldist:
kwargs['distance'] = 213.4*u.pc
if inclrv:
kwargs['radial_velocity'] = 61*u.km/u.s
return SkyCoord(*args, **kwargs)
@pytest.fixture(scope="module")
def scmany():
return SkyCoord(ICRS(ra=[1]*100*u.deg, dec=[2]*100*u.deg,
pm_ra_cosdec=np.random.randn(100)*u.mas/u.yr,
pm_dec=np.random.randn(100)*u.mas/u.yr,))
@pytest.fixture(scope="module")
def sc_for_sep():
return SkyCoord(1*u.deg, 2*u.deg,
pm_dec=1*u.mas/u.yr, pm_ra_cosdec=2*u.mas/u.yr)
def test_separation(sc, sc_for_sep):
sc.separation(sc_for_sep)
def test_accessors(sc, scmany):
sc.data.differentials['s']
sph = sc.spherical
gal = sc.galactic
if (sc.data.get_name().startswith('unit') and not
sc.data.differentials['s'].get_name().startswith('unit')):
# this xfail can be eliminated when issue #7028 is resolved
pytest.xfail('.velocity fails if there is an RV but not distance')
sc.velocity
assert isinstance(sph, SphericalRepresentation)
assert gal.data.differentials is not None
scmany[0]
sph = scmany.spherical
gal = scmany.galactic
assert isinstance(sph, SphericalRepresentation)
assert gal.data.differentials is not None
def test_transforms(sc):
trans = sc.transform_to('galactic')
assert isinstance(trans.frame, Galactic)
def test_transforms_diff(sc):
# note that arguably this *should* fail for the no-distance cases: 3D
# information is necessary to truly solve this, hence the xfail
if not sc.distance.unit.is_equivalent(u.m):
pytest.xfail('Should fail for no-distance cases')
else:
trans = sc.transform_to(PrecessedGeocentric(equinox='B1975'))
assert isinstance(trans.frame, PrecessedGeocentric)
@pytest.mark.skipif(str('not HAS_SCIPY'))
def test_matching(sc, scmany):
# just check that it works and yields something
idx, d2d, d3d = sc.match_to_catalog_sky(scmany)
def test_position_angle(sc, sc_for_sep):
sc.position_angle(sc_for_sep)
def test_constellations(sc):
const = sc.get_constellation()
assert const == 'Pisces'
def test_separation_3d_with_differentials():
c1 = SkyCoord(ra=138*u.deg, dec=-17*u.deg, distance=100*u.pc,
pm_ra_cosdec=5*u.mas/u.yr,
pm_dec=-7*u.mas/u.yr,
radial_velocity=160*u.km/u.s)
c2 = SkyCoord(ra=138*u.deg, dec=-17*u.deg, distance=105*u.pc,
pm_ra_cosdec=15*u.mas/u.yr,
pm_dec=-74*u.mas/u.yr,
radial_velocity=-60*u.km/u.s)
sep = c1.separation_3d(c2)
assert_quantity_allclose(sep, 5*u.pc)
|
fb1056a97735e83d00ab492c07da3c7a5d776ac2a89404845bc84cd5cabaebe1 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import numpy as np
from astropy import units as u
from astropy.utils import NumpyRNGContext
def randomly_sample_sphere(ntosample, randomseed=12345):
"""
Generates a set of spherical coordinates uniformly distributed over the
sphere in a way that gives the same answer for the same seed. Also
generates a random distance vector on [0, 1] (no units)
This simply returns (lon, lat, r) instead of a representation to avoid
failures due to the representation module.
"""
with NumpyRNGContext(randomseed):
lat = np.arcsin(np.random.rand(ntosample)*2-1)
lon = np.random.rand(ntosample)*np.pi*2
r = np.random.rand(ntosample)
return lon*u.rad, lat*u.rad, r
|
07b28d6c8c77ebc43e00b56bace51c4f06f5fdd4ced8a2d7ba35b15803101d3d | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import functools
import pytest
import numpy as np
from astropy import units as u
from astropy.coordinates import (PhysicsSphericalRepresentation, CartesianRepresentation,
CylindricalRepresentation, SphericalRepresentation,
UnitSphericalRepresentation, SphericalDifferential,
CartesianDifferential, UnitSphericalDifferential,
SphericalCosLatDifferential, UnitSphericalCosLatDifferential,
PhysicsSphericalDifferential, CylindricalDifferential,
RadialRepresentation, RadialDifferential, Longitude, Latitude)
from astropy.coordinates.representation import DIFFERENTIAL_CLASSES
from astropy.coordinates.angle_utilities import angular_separation
from astropy.tests.helper import assert_quantity_allclose, quantity_allclose
def assert_representation_allclose(actual, desired, rtol=1.e-7, atol=None,
**kwargs):
actual_xyz = actual.to_cartesian().get_xyz(xyz_axis=-1)
desired_xyz = desired.to_cartesian().get_xyz(xyz_axis=-1)
actual_xyz, desired_xyz = np.broadcast_arrays(actual_xyz, desired_xyz,
subok=True)
assert_quantity_allclose(actual_xyz, desired_xyz, rtol, atol, **kwargs)
def assert_differential_allclose(actual, desired, rtol=1.e-7, **kwargs):
assert actual.components == desired.components
for component in actual.components:
actual_c = getattr(actual, component)
atol = 1.e-10 * actual_c.unit
assert_quantity_allclose(actual_c, getattr(desired, component),
rtol, atol, **kwargs)
def representation_equal(first, second):
return functools.reduce(np.logical_and,
(getattr(first, component) ==
getattr(second, component)
for component in first.components))
class TestArithmetic():
def setup(self):
# Choose some specific coordinates, for which ``sum`` and ``dot``
# works out nicely.
self.lon = Longitude(np.arange(0, 12.1, 2), u.hourangle)
self.lat = Latitude(np.arange(-90, 91, 30), u.deg)
self.distance = [5., 12., 4., 2., 4., 12., 5.] * u.kpc
self.spherical = SphericalRepresentation(self.lon, self.lat,
self.distance)
self.unit_spherical = self.spherical.represent_as(
UnitSphericalRepresentation)
self.cartesian = self.spherical.to_cartesian()
def test_norm_spherical(self):
norm_s = self.spherical.norm()
assert isinstance(norm_s, u.Quantity)
# Just to be sure, test against getting object arrays.
assert norm_s.dtype.kind == 'f'
assert np.all(norm_s == self.distance)
@pytest.mark.parametrize('representation',
(PhysicsSphericalRepresentation,
CartesianRepresentation,
CylindricalRepresentation))
def test_norm(self, representation):
in_rep = self.spherical.represent_as(representation)
norm_rep = in_rep.norm()
assert isinstance(norm_rep, u.Quantity)
assert_quantity_allclose(norm_rep, self.distance)
def test_norm_unitspherical(self):
norm_rep = self.unit_spherical.norm()
assert norm_rep.unit == u.dimensionless_unscaled
assert np.all(norm_rep == 1. * u.dimensionless_unscaled)
@pytest.mark.parametrize('representation',
(SphericalRepresentation,
PhysicsSphericalRepresentation,
CartesianRepresentation,
CylindricalRepresentation,
UnitSphericalRepresentation))
def test_neg_pos(self, representation):
in_rep = self.cartesian.represent_as(representation)
pos_rep = +in_rep
assert type(pos_rep) is type(in_rep)
assert pos_rep is not in_rep
assert np.all(representation_equal(pos_rep, in_rep))
neg_rep = -in_rep
assert type(neg_rep) is type(in_rep)
assert np.all(neg_rep.norm() == in_rep.norm())
in_rep_xyz = in_rep.to_cartesian().xyz
assert_quantity_allclose(neg_rep.to_cartesian().xyz,
-in_rep_xyz, atol=1.e-10*in_rep_xyz.unit)
def test_mul_div_spherical(self):
s0 = self.spherical / (1. * u.Myr)
assert isinstance(s0, SphericalRepresentation)
assert s0.distance.dtype.kind == 'f'
assert np.all(s0.lon == self.spherical.lon)
assert np.all(s0.lat == self.spherical.lat)
assert np.all(s0.distance == self.distance / (1. * u.Myr))
s1 = (1./u.Myr) * self.spherical
assert isinstance(s1, SphericalRepresentation)
assert np.all(representation_equal(s1, s0))
s2 = self.spherical * np.array([[1.], [2.]])
assert isinstance(s2, SphericalRepresentation)
assert s2.shape == (2, self.spherical.shape[0])
assert np.all(s2.lon == self.spherical.lon)
assert np.all(s2.lat == self.spherical.lat)
assert np.all(s2.distance ==
self.spherical.distance * np.array([[1.], [2.]]))
s3 = np.array([[1.], [2.]]) * self.spherical
assert isinstance(s3, SphericalRepresentation)
assert np.all(representation_equal(s3, s2))
s4 = -self.spherical
assert isinstance(s4, SphericalRepresentation)
assert quantity_allclose(s4.to_cartesian().xyz,
-self.spherical.to_cartesian().xyz,
atol=1e-15*self.spherical.distance.unit)
assert np.all(s4.distance == self.spherical.distance)
s5 = +self.spherical
assert s5 is not self.spherical
assert np.all(representation_equal(s5, self.spherical))
@pytest.mark.parametrize('representation',
(PhysicsSphericalRepresentation,
CartesianRepresentation,
CylindricalRepresentation))
def test_mul_div(self, representation):
in_rep = self.spherical.represent_as(representation)
r1 = in_rep / (1. * u.Myr)
assert isinstance(r1, representation)
for component in in_rep.components:
in_rep_comp = getattr(in_rep, component)
r1_comp = getattr(r1, component)
if in_rep_comp.unit == self.distance.unit:
assert np.all(r1_comp == in_rep_comp / (1.*u.Myr))
else:
assert np.all(r1_comp == in_rep_comp)
r2 = np.array([[1.], [2.]]) * in_rep
assert isinstance(r2, representation)
assert r2.shape == (2, in_rep.shape[0])
assert_quantity_allclose(r2.norm(),
self.distance * np.array([[1.], [2.]]))
r3 = -in_rep
assert np.all(representation_equal(r3, in_rep * -1.))
with pytest.raises(TypeError):
in_rep * in_rep
with pytest.raises(TypeError):
dict() * in_rep
def test_mul_div_unit_spherical(self):
s1 = self.unit_spherical * self.distance
assert isinstance(s1, SphericalRepresentation)
assert np.all(s1.lon == self.unit_spherical.lon)
assert np.all(s1.lat == self.unit_spherical.lat)
assert np.all(s1.distance == self.spherical.distance)
s2 = self.unit_spherical / u.s
assert isinstance(s2, SphericalRepresentation)
assert np.all(s2.lon == self.unit_spherical.lon)
assert np.all(s2.lat == self.unit_spherical.lat)
assert np.all(s2.distance == 1./u.s)
u3 = -self.unit_spherical
assert isinstance(u3, UnitSphericalRepresentation)
assert_quantity_allclose(u3.lon, self.unit_spherical.lon + 180.*u.deg)
assert np.all(u3.lat == -self.unit_spherical.lat)
assert_quantity_allclose(u3.to_cartesian().xyz,
-self.unit_spherical.to_cartesian().xyz,
atol=1.e-10*u.dimensionless_unscaled)
u4 = +self.unit_spherical
assert isinstance(u4, UnitSphericalRepresentation)
assert u4 is not self.unit_spherical
assert np.all(representation_equal(u4, self.unit_spherical))
def test_add_sub_cartesian(self):
c1 = self.cartesian + self.cartesian
assert isinstance(c1, CartesianRepresentation)
assert c1.x.dtype.kind == 'f'
assert np.all(representation_equal(c1, 2. * self.cartesian))
with pytest.raises(TypeError):
self.cartesian + 10.*u.m
with pytest.raises(u.UnitsError):
self.cartesian + (self.cartesian / u.s)
c2 = self.cartesian - self.cartesian
assert isinstance(c2, CartesianRepresentation)
assert np.all(representation_equal(
c2, CartesianRepresentation(0.*u.m, 0.*u.m, 0.*u.m)))
c3 = self.cartesian - self.cartesian / 2.
assert isinstance(c3, CartesianRepresentation)
assert np.all(representation_equal(c3, self.cartesian / 2.))
@pytest.mark.parametrize('representation',
(PhysicsSphericalRepresentation,
SphericalRepresentation,
CylindricalRepresentation))
def test_add_sub(self, representation):
in_rep = self.cartesian.represent_as(representation)
r1 = in_rep + in_rep
assert isinstance(r1, representation)
expected = 2. * in_rep
for component in in_rep.components:
assert_quantity_allclose(getattr(r1, component),
getattr(expected, component))
with pytest.raises(TypeError):
10.*u.m + in_rep
with pytest.raises(u.UnitsError):
in_rep + (in_rep / u.s)
r2 = in_rep - in_rep
assert isinstance(r2, representation)
assert np.all(representation_equal(
r2.to_cartesian(), CartesianRepresentation(0.*u.m, 0.*u.m, 0.*u.m)))
r3 = in_rep - in_rep / 2.
assert isinstance(r3, representation)
expected = in_rep / 2.
assert_representation_allclose(r3, expected)
def test_add_sub_unit_spherical(self):
s1 = self.unit_spherical + self.unit_spherical
assert isinstance(s1, SphericalRepresentation)
expected = 2. * self.unit_spherical
for component in s1.components:
assert_quantity_allclose(getattr(s1, component),
getattr(expected, component))
with pytest.raises(TypeError):
10.*u.m - self.unit_spherical
with pytest.raises(u.UnitsError):
self.unit_spherical + (self.unit_spherical / u.s)
s2 = self.unit_spherical - self.unit_spherical / 2.
assert isinstance(s2, SphericalRepresentation)
expected = self.unit_spherical / 2.
for component in s2.components:
assert_quantity_allclose(getattr(s2, component),
getattr(expected, component))
@pytest.mark.parametrize('representation',
(CartesianRepresentation,
PhysicsSphericalRepresentation,
SphericalRepresentation,
CylindricalRepresentation))
def test_sum_mean(self, representation):
in_rep = self.spherical.represent_as(representation)
r_sum = in_rep.sum()
assert isinstance(r_sum, representation)
expected = SphericalRepresentation(
90. * u.deg, 0. * u.deg, 14. * u.kpc).represent_as(representation)
for component in expected.components:
exp_component = getattr(expected, component)
assert_quantity_allclose(getattr(r_sum, component),
exp_component,
atol=1e-10*exp_component.unit)
r_mean = in_rep.mean()
assert isinstance(r_mean, representation)
expected = expected / len(in_rep)
for component in expected.components:
exp_component = getattr(expected, component)
assert_quantity_allclose(getattr(r_mean, component),
exp_component,
atol=1e-10*exp_component.unit)
def test_sum_mean_unit_spherical(self):
s_sum = self.unit_spherical.sum()
assert isinstance(s_sum, SphericalRepresentation)
expected = SphericalRepresentation(
90. * u.deg, 0. * u.deg, 3. * u.dimensionless_unscaled)
for component in expected.components:
exp_component = getattr(expected, component)
assert_quantity_allclose(getattr(s_sum, component),
exp_component,
atol=1e-10*exp_component.unit)
s_mean = self.unit_spherical.mean()
assert isinstance(s_mean, SphericalRepresentation)
expected = expected / len(self.unit_spherical)
for component in expected.components:
exp_component = getattr(expected, component)
assert_quantity_allclose(getattr(s_mean, component),
exp_component,
atol=1e-10*exp_component.unit)
@pytest.mark.parametrize('representation',
(CartesianRepresentation,
PhysicsSphericalRepresentation,
SphericalRepresentation,
CylindricalRepresentation))
def test_dot(self, representation):
in_rep = self.cartesian.represent_as(representation)
r_dot_r = in_rep.dot(in_rep)
assert isinstance(r_dot_r, u.Quantity)
assert r_dot_r.shape == in_rep.shape
assert_quantity_allclose(np.sqrt(r_dot_r), self.distance)
r_dot_r_rev = in_rep.dot(in_rep[::-1])
assert isinstance(r_dot_r_rev, u.Quantity)
assert r_dot_r_rev.shape == in_rep.shape
expected = [-25., -126., 2., 4., 2., -126., -25.] * u.kpc**2
assert_quantity_allclose(r_dot_r_rev, expected)
for axis in 'xyz':
project = CartesianRepresentation(*(
(1. if axis == _axis else 0.) * u.dimensionless_unscaled
for _axis in 'xyz'))
assert_quantity_allclose(in_rep.dot(project),
getattr(self.cartesian, axis),
atol=1.*u.upc)
with pytest.raises(TypeError):
in_rep.dot(self.cartesian.xyz)
def test_dot_unit_spherical(self):
u_dot_u = self.unit_spherical.dot(self.unit_spherical)
assert isinstance(u_dot_u, u.Quantity)
assert u_dot_u.shape == self.unit_spherical.shape
assert_quantity_allclose(u_dot_u, 1.*u.dimensionless_unscaled)
cartesian = self.unit_spherical.to_cartesian()
for axis in 'xyz':
project = CartesianRepresentation(*(
(1. if axis == _axis else 0.) * u.dimensionless_unscaled
for _axis in 'xyz'))
assert_quantity_allclose(self.unit_spherical.dot(project),
getattr(cartesian, axis), atol=1.e-10)
@pytest.mark.parametrize('representation',
(CartesianRepresentation,
PhysicsSphericalRepresentation,
SphericalRepresentation,
CylindricalRepresentation))
def test_cross(self, representation):
in_rep = self.cartesian.represent_as(representation)
r_cross_r = in_rep.cross(in_rep)
assert isinstance(r_cross_r, representation)
assert_quantity_allclose(r_cross_r.norm(), 0.*u.kpc**2,
atol=1.*u.mpc**2)
r_cross_r_rev = in_rep.cross(in_rep[::-1])
sep = angular_separation(self.lon, self.lat,
self.lon[::-1], self.lat[::-1])
expected = self.distance * self.distance[::-1] * np.sin(sep)
assert_quantity_allclose(r_cross_r_rev.norm(), expected,
atol=1.*u.mpc**2)
unit_vectors = CartesianRepresentation(
[1., 0., 0.]*u.one,
[0., 1., 0.]*u.one,
[0., 0., 1.]*u.one)[:, np.newaxis]
r_cross_uv = in_rep.cross(unit_vectors)
assert r_cross_uv.shape == (3, 7)
assert_quantity_allclose(r_cross_uv.dot(unit_vectors), 0.*u.kpc,
atol=1.*u.upc)
assert_quantity_allclose(r_cross_uv.dot(in_rep), 0.*u.kpc**2,
atol=1.*u.mpc**2)
zeros = np.zeros(len(in_rep)) * u.kpc
expected = CartesianRepresentation(
u.Quantity((zeros, -self.cartesian.z, self.cartesian.y)),
u.Quantity((self.cartesian.z, zeros, -self.cartesian.x)),
u.Quantity((-self.cartesian.y, self.cartesian.x, zeros)))
# Comparison with spherical is hard since some distances are zero,
# implying the angles are undefined.
r_cross_uv_cartesian = r_cross_uv.to_cartesian()
assert_representation_allclose(r_cross_uv_cartesian,
expected, atol=1.*u.upc)
# A final check, with the side benefit of ensuring __div__ and norm
# work on multi-D representations.
r_cross_uv_by_distance = r_cross_uv / self.distance
uv_sph = unit_vectors.represent_as(UnitSphericalRepresentation)
sep = angular_separation(self.lon, self.lat, uv_sph.lon, uv_sph.lat)
assert_quantity_allclose(r_cross_uv_by_distance.norm(), np.sin(sep),
atol=1e-9)
with pytest.raises(TypeError):
in_rep.cross(self.cartesian.xyz)
def test_cross_unit_spherical(self):
u_cross_u = self.unit_spherical.cross(self.unit_spherical)
assert isinstance(u_cross_u, SphericalRepresentation)
assert_quantity_allclose(u_cross_u.norm(), 0.*u.one, atol=1.e-10*u.one)
u_cross_u_rev = self.unit_spherical.cross(self.unit_spherical[::-1])
assert isinstance(u_cross_u_rev, SphericalRepresentation)
sep = angular_separation(self.lon, self.lat,
self.lon[::-1], self.lat[::-1])
expected = np.sin(sep)
assert_quantity_allclose(u_cross_u_rev.norm(), expected,
atol=1.e-10*u.one)
class TestUnitVectorsAndScales():
@staticmethod
def check_unit_vectors(e):
for v in e.values():
assert type(v) is CartesianRepresentation
assert_quantity_allclose(v.norm(), 1. * u.one)
return e
@staticmethod
def check_scale_factors(sf, rep):
unit = rep.norm().unit
for c, f in sf.items():
assert type(f) is u.Quantity
assert (f.unit * getattr(rep, c).unit).is_equivalent(unit)
def test_spherical(self):
s = SphericalRepresentation(lon=[0., 6., 21.] * u.hourangle,
lat=[0., -30., 85.] * u.deg,
distance=[1, 2, 3] * u.kpc)
e = s.unit_vectors()
self.check_unit_vectors(e)
sf = s.scale_factors()
self.check_scale_factors(sf, s)
s_lon = s + s.distance * 1e-5 * np.cos(s.lat) * e['lon']
assert_quantity_allclose(s_lon.lon, s.lon + 1e-5*u.rad,
atol=1e-10*u.rad)
assert_quantity_allclose(s_lon.lat, s.lat, atol=1e-10*u.rad)
assert_quantity_allclose(s_lon.distance, s.distance)
s_lon2 = s + 1e-5 * u.radian * sf['lon'] * e['lon']
assert_representation_allclose(s_lon2, s_lon)
s_lat = s + s.distance * 1e-5 * e['lat']
assert_quantity_allclose(s_lat.lon, s.lon)
assert_quantity_allclose(s_lat.lat, s.lat + 1e-5*u.rad,
atol=1e-10*u.rad)
assert_quantity_allclose(s_lon.distance, s.distance)
s_lat2 = s + 1.e-5 * u.radian * sf['lat'] * e['lat']
assert_representation_allclose(s_lat2, s_lat)
s_distance = s + 1. * u.pc * e['distance']
assert_quantity_allclose(s_distance.lon, s.lon, atol=1e-10*u.rad)
assert_quantity_allclose(s_distance.lat, s.lat, atol=1e-10*u.rad)
assert_quantity_allclose(s_distance.distance, s.distance + 1.*u.pc)
s_distance2 = s + 1. * u.pc * sf['distance'] * e['distance']
assert_representation_allclose(s_distance2, s_distance)
def test_unit_spherical(self):
s = UnitSphericalRepresentation(lon=[0., 6., 21.] * u.hourangle,
lat=[0., -30., 85.] * u.deg)
e = s.unit_vectors()
self.check_unit_vectors(e)
sf = s.scale_factors()
self.check_scale_factors(sf, s)
s_lon = s + 1e-5 * np.cos(s.lat) * e['lon']
assert_quantity_allclose(s_lon.lon, s.lon + 1e-5*u.rad,
atol=1e-10*u.rad)
assert_quantity_allclose(s_lon.lat, s.lat, atol=1e-10*u.rad)
s_lon2 = s + 1e-5 * u.radian * sf['lon'] * e['lon']
assert_representation_allclose(s_lon2, s_lon)
s_lat = s + 1e-5 * e['lat']
assert_quantity_allclose(s_lat.lon, s.lon)
assert_quantity_allclose(s_lat.lat, s.lat + 1e-5*u.rad,
atol=1e-10*u.rad)
s_lat2 = s + 1.e-5 * u.radian * sf['lat'] * e['lat']
assert_representation_allclose(s_lat2, s_lat)
def test_radial(self):
r = RadialRepresentation(10.*u.kpc)
with pytest.raises(NotImplementedError):
r.unit_vectors()
sf = r.scale_factors()
assert np.all(sf['distance'] == 1.*u.one)
assert np.all(r.norm() == r.distance)
with pytest.raises(TypeError):
r + r
def test_physical_spherical(self):
s = PhysicsSphericalRepresentation(phi=[0., 6., 21.] * u.hourangle,
theta=[90., 120., 5.] * u.deg,
r=[1, 2, 3] * u.kpc)
e = s.unit_vectors()
self.check_unit_vectors(e)
sf = s.scale_factors()
self.check_scale_factors(sf, s)
s_phi = s + s.r * 1e-5 * np.sin(s.theta) * e['phi']
assert_quantity_allclose(s_phi.phi, s.phi + 1e-5*u.rad,
atol=1e-10*u.rad)
assert_quantity_allclose(s_phi.theta, s.theta, atol=1e-10*u.rad)
assert_quantity_allclose(s_phi.r, s.r)
s_phi2 = s + 1e-5 * u.radian * sf['phi'] * e['phi']
assert_representation_allclose(s_phi2, s_phi)
s_theta = s + s.r * 1e-5 * e['theta']
assert_quantity_allclose(s_theta.phi, s.phi)
assert_quantity_allclose(s_theta.theta, s.theta + 1e-5*u.rad,
atol=1e-10*u.rad)
assert_quantity_allclose(s_theta.r, s.r)
s_theta2 = s + 1.e-5 * u.radian * sf['theta'] * e['theta']
assert_representation_allclose(s_theta2, s_theta)
s_r = s + 1. * u.pc * e['r']
assert_quantity_allclose(s_r.phi, s.phi, atol=1e-10*u.rad)
assert_quantity_allclose(s_r.theta, s.theta, atol=1e-10*u.rad)
assert_quantity_allclose(s_r.r, s.r + 1.*u.pc)
s_r2 = s + 1. * u.pc * sf['r'] * e['r']
assert_representation_allclose(s_r2, s_r)
def test_cartesian(self):
s = CartesianRepresentation(x=[1, 2, 3] * u.pc,
y=[2, 3, 4] * u.Mpc,
z=[3, 4, 5] * u.kpc)
e = s.unit_vectors()
sf = s.scale_factors()
for v, expected in zip(e.values(), ([1., 0., 0.] * u.one,
[0., 1., 0.] * u.one,
[0., 0., 1.] * u.one)):
assert np.all(v.get_xyz(xyz_axis=-1) == expected)
for f in sf.values():
assert np.all(f == 1.*u.one)
def test_cylindrical(self):
s = CylindricalRepresentation(rho=[1, 2, 3] * u.pc,
phi=[0., 90., -45.] * u.deg,
z=[3, 4, 5] * u.kpc)
e = s.unit_vectors()
self.check_unit_vectors(e)
sf = s.scale_factors()
self.check_scale_factors(sf, s)
s_rho = s + 1. * u.pc * e['rho']
assert_quantity_allclose(s_rho.rho, s.rho + 1.*u.pc)
assert_quantity_allclose(s_rho.phi, s.phi)
assert_quantity_allclose(s_rho.z, s.z)
s_rho2 = s + 1. * u.pc * sf['rho'] * e['rho']
assert_representation_allclose(s_rho2, s_rho)
s_phi = s + s.rho * 1e-5 * e['phi']
assert_quantity_allclose(s_phi.rho, s.rho)
assert_quantity_allclose(s_phi.phi, s.phi + 1e-5*u.rad)
assert_quantity_allclose(s_phi.z, s.z)
s_phi2 = s + 1e-5 * u.radian * sf['phi'] * e['phi']
assert_representation_allclose(s_phi2, s_phi)
s_z = s + 1. * u.pc * e['z']
assert_quantity_allclose(s_z.rho, s.rho)
assert_quantity_allclose(s_z.phi, s.phi, atol=1e-10*u.rad)
assert_quantity_allclose(s_z.z, s.z + 1.*u.pc)
s_z2 = s + 1. * u.pc * sf['z'] * e['z']
assert_representation_allclose(s_z2, s_z)
@pytest.mark.parametrize('omit_coslat', [False, True], scope='class')
class TestSphericalDifferential():
# these test cases are subclassed for SphericalCosLatDifferential,
# hence some tests depend on omit_coslat.
def _setup(self, omit_coslat):
if omit_coslat:
self.SD_cls = SphericalCosLatDifferential
else:
self.SD_cls = SphericalDifferential
s = SphericalRepresentation(lon=[0., 6., 21.] * u.hourangle,
lat=[0., -30., 85.] * u.deg,
distance=[1, 2, 3] * u.kpc)
self.s = s
self.e = s.unit_vectors()
self.sf = s.scale_factors(omit_coslat=omit_coslat)
def test_name_coslat(self, omit_coslat):
self._setup(omit_coslat)
if omit_coslat:
assert self.SD_cls is SphericalCosLatDifferential
assert self.SD_cls.get_name() == 'sphericalcoslat'
else:
assert self.SD_cls is SphericalDifferential
assert self.SD_cls.get_name() == 'spherical'
assert self.SD_cls.get_name() in DIFFERENTIAL_CLASSES
def test_simple_differentials(self, omit_coslat):
self._setup(omit_coslat)
s, e, sf = self.s, self.e, self.sf
o_lon = self.SD_cls(1.*u.arcsec, 0.*u.arcsec, 0.*u.kpc)
o_lonc = o_lon.to_cartesian(base=s)
o_lon2 = self.SD_cls.from_cartesian(o_lonc, base=s)
assert_differential_allclose(o_lon, o_lon2)
# simple check by hand for first element.
# lat[0] is 0, so cos(lat) term doesn't matter.
assert_quantity_allclose(o_lonc[0].xyz,
[0., np.pi/180./3600., 0.]*u.kpc)
# check all using unit vectors and scale factors.
s_lon = s + 1.*u.arcsec * sf['lon'] * e['lon']
assert_representation_allclose(o_lonc, s_lon - s, atol=1*u.npc)
s_lon2 = s + o_lon
assert_representation_allclose(s_lon2, s_lon, atol=1*u.npc)
o_lat = self.SD_cls(0.*u.arcsec, 1.*u.arcsec, 0.*u.kpc)
o_latc = o_lat.to_cartesian(base=s)
assert_quantity_allclose(o_latc[0].xyz,
[0., 0., np.pi/180./3600.]*u.kpc,
atol=1.*u.npc)
s_lat = s + 1.*u.arcsec * sf['lat'] * e['lat']
assert_representation_allclose(o_latc, s_lat - s, atol=1*u.npc)
s_lat2 = s + o_lat
assert_representation_allclose(s_lat2, s_lat, atol=1*u.npc)
o_distance = self.SD_cls(0.*u.arcsec, 0.*u.arcsec, 1.*u.mpc)
o_distancec = o_distance.to_cartesian(base=s)
assert_quantity_allclose(o_distancec[0].xyz,
[1e-6, 0., 0.]*u.kpc, atol=1.*u.npc)
s_distance = s + 1.*u.mpc * sf['distance'] * e['distance']
assert_representation_allclose(o_distancec, s_distance - s,
atol=1*u.npc)
s_distance2 = s + o_distance
assert_representation_allclose(s_distance2, s_distance)
def test_differential_arithmetic(self, omit_coslat):
self._setup(omit_coslat)
s = self.s
o_lon = self.SD_cls(1.*u.arcsec, 0.*u.arcsec, 0.*u.kpc)
o_lon_by_2 = o_lon / 2.
assert_representation_allclose(o_lon_by_2.to_cartesian(s) * 2.,
o_lon.to_cartesian(s), atol=1e-10*u.kpc)
assert_representation_allclose(s + o_lon, s + 2 * o_lon_by_2,
atol=1e-10*u.kpc)
o_lon_rec = o_lon_by_2 + o_lon_by_2
assert_representation_allclose(s + o_lon, s + o_lon_rec,
atol=1e-10*u.kpc)
o_lon_0 = o_lon - o_lon
for c in o_lon_0.components:
assert np.all(getattr(o_lon_0, c) == 0.)
o_lon2 = self.SD_cls(1*u.mas/u.yr, 0*u.mas/u.yr, 0*u.km/u.s)
assert_quantity_allclose(o_lon2.norm(s)[0], 4.74*u.km/u.s,
atol=0.01*u.km/u.s)
assert_representation_allclose(o_lon2.to_cartesian(s) * 1000.*u.yr,
o_lon.to_cartesian(s), atol=1e-10*u.kpc)
s_off = s + o_lon
s_off2 = s + o_lon2 * 1000.*u.yr
assert_representation_allclose(s_off, s_off2, atol=1e-10*u.kpc)
factor = 1e5 * u.radian/u.arcsec
if not omit_coslat:
factor = factor / np.cos(s.lat)
s_off_big = s + o_lon * factor
assert_representation_allclose(
s_off_big, SphericalRepresentation(s.lon + 90.*u.deg, 0.*u.deg,
1e5*s.distance),
atol=5.*u.kpc)
o_lon3c = CartesianRepresentation(0., 4.74047, 0., unit=u.km/u.s)
o_lon3 = self.SD_cls.from_cartesian(o_lon3c, base=s)
expected0 = self.SD_cls(1.*u.mas/u.yr, 0.*u.mas/u.yr, 0.*u.km/u.s)
assert_differential_allclose(o_lon3[0], expected0)
s_off_big2 = s + o_lon3 * 1e5 * u.yr * u.radian/u.mas
assert_representation_allclose(
s_off_big2, SphericalRepresentation(90.*u.deg, 0.*u.deg,
1e5*u.kpc), atol=5.*u.kpc)
with pytest.raises(TypeError):
o_lon - s
with pytest.raises(TypeError):
s.to_cartesian() + o_lon
def test_differential_init_errors(self, omit_coslat):
self._setup(omit_coslat)
s = self.s
with pytest.raises(u.UnitsError):
self.SD_cls(1.*u.arcsec, 0., 0.)
with pytest.raises(TypeError):
self.SD_cls(1.*u.arcsec, 0.*u.arcsec, 0.*u.kpc,
False, False)
with pytest.raises(TypeError):
self.SD_cls(1.*u.arcsec, 0.*u.arcsec, 0.*u.kpc,
copy=False, d_lat=0.*u.arcsec)
with pytest.raises(TypeError):
self.SD_cls(1.*u.arcsec, 0.*u.arcsec, 0.*u.kpc,
copy=False, flying='circus')
with pytest.raises(ValueError):
self.SD_cls(np.ones(2)*u.arcsec,
np.zeros(3)*u.arcsec, np.zeros(2)*u.kpc)
with pytest.raises(u.UnitsError):
self.SD_cls(1.*u.arcsec, 1.*u.s, 0.*u.kpc)
with pytest.raises(u.UnitsError):
self.SD_cls(1.*u.kpc, 1.*u.arcsec, 0.*u.kpc)
o = self.SD_cls(1.*u.arcsec, 1.*u.arcsec, 0.*u.km/u.s)
with pytest.raises(u.UnitsError):
o.to_cartesian(s)
with pytest.raises(AttributeError):
o.d_lat = 0.*u.arcsec
with pytest.raises(AttributeError):
del o.d_lat
o = self.SD_cls(1.*u.arcsec, 1.*u.arcsec, 0.*u.km)
with pytest.raises(TypeError):
o.to_cartesian()
c = CartesianRepresentation(10., 0., 0., unit=u.km)
with pytest.raises(TypeError):
self.SD_cls.to_cartesian(c)
with pytest.raises(TypeError):
self.SD_cls.from_cartesian(c)
with pytest.raises(TypeError):
self.SD_cls.from_cartesian(c, SphericalRepresentation)
with pytest.raises(TypeError):
self.SD_cls.from_cartesian(c, c)
@pytest.mark.parametrize('omit_coslat', [False, True], scope='class')
class TestUnitSphericalDifferential():
def _setup(self, omit_coslat):
if omit_coslat:
self.USD_cls = UnitSphericalCosLatDifferential
else:
self.USD_cls = UnitSphericalDifferential
s = UnitSphericalRepresentation(lon=[0., 6., 21.] * u.hourangle,
lat=[0., -30., 85.] * u.deg)
self.s = s
self.e = s.unit_vectors()
self.sf = s.scale_factors(omit_coslat=omit_coslat)
def test_name_coslat(self, omit_coslat):
self._setup(omit_coslat)
if omit_coslat:
assert self.USD_cls is UnitSphericalCosLatDifferential
assert self.USD_cls.get_name() == 'unitsphericalcoslat'
else:
assert self.USD_cls is UnitSphericalDifferential
assert self.USD_cls.get_name() == 'unitspherical'
assert self.USD_cls.get_name() in DIFFERENTIAL_CLASSES
def test_simple_differentials(self, omit_coslat):
self._setup(omit_coslat)
s, e, sf = self.s, self.e, self.sf
o_lon = self.USD_cls(1.*u.arcsec, 0.*u.arcsec)
o_lonc = o_lon.to_cartesian(base=s)
o_lon2 = self.USD_cls.from_cartesian(o_lonc, base=s)
assert_differential_allclose(o_lon, o_lon2)
# simple check by hand for first element
# (lat[0]=0, so works for both normal and CosLat differential)
assert_quantity_allclose(o_lonc[0].xyz,
[0., np.pi/180./3600., 0.]*u.one)
# check all using unit vectors and scale factors.
s_lon = s + 1.*u.arcsec * sf['lon'] * e['lon']
assert type(s_lon) is SphericalRepresentation
assert_representation_allclose(o_lonc, s_lon - s, atol=1e-10*u.one)
s_lon2 = s + o_lon
assert_representation_allclose(s_lon2, s_lon, atol=1e-10*u.one)
o_lat = self.USD_cls(0.*u.arcsec, 1.*u.arcsec)
o_latc = o_lat.to_cartesian(base=s)
assert_quantity_allclose(o_latc[0].xyz,
[0., 0., np.pi/180./3600.]*u.one,
atol=1e-10*u.one)
s_lat = s + 1.*u.arcsec * sf['lat'] * e['lat']
assert type(s_lat) is SphericalRepresentation
assert_representation_allclose(o_latc, s_lat - s, atol=1e-10*u.one)
s_lat2 = s + o_lat
assert_representation_allclose(s_lat2, s_lat, atol=1e-10*u.one)
def test_differential_arithmetic(self, omit_coslat):
self._setup(omit_coslat)
s = self.s
o_lon = self.USD_cls(1.*u.arcsec, 0.*u.arcsec)
o_lon_by_2 = o_lon / 2.
assert type(o_lon_by_2) is self.USD_cls
assert_representation_allclose(o_lon_by_2.to_cartesian(s) * 2.,
o_lon.to_cartesian(s), atol=1e-10*u.one)
s_lon = s + o_lon
s_lon2 = s + 2 * o_lon_by_2
assert type(s_lon) is SphericalRepresentation
assert_representation_allclose(s_lon, s_lon2, atol=1e-10*u.one)
o_lon_rec = o_lon_by_2 + o_lon_by_2
assert type(o_lon_rec) is self.USD_cls
assert representation_equal(o_lon, o_lon_rec)
assert_representation_allclose(s + o_lon, s + o_lon_rec,
atol=1e-10*u.one)
o_lon_0 = o_lon - o_lon
assert type(o_lon_0) is self.USD_cls
for c in o_lon_0.components:
assert np.all(getattr(o_lon_0, c) == 0.)
o_lon2 = self.USD_cls(1.*u.mas/u.yr, 0.*u.mas/u.yr)
kks = u.km/u.kpc/u.s
assert_quantity_allclose(o_lon2.norm(s)[0], 4.74047*kks, atol=1e-4*kks)
assert_representation_allclose(o_lon2.to_cartesian(s) * 1000.*u.yr,
o_lon.to_cartesian(s), atol=1e-10*u.one)
s_off = s + o_lon
s_off2 = s + o_lon2 * 1000.*u.yr
assert_representation_allclose(s_off, s_off2, atol=1e-10*u.one)
factor = 1e5 * u.radian/u.arcsec
if not omit_coslat:
factor = factor / np.cos(s.lat)
s_off_big = s + o_lon * factor
assert_representation_allclose(
s_off_big, SphericalRepresentation(s.lon + 90.*u.deg,
0.*u.deg, 1e5),
atol=5.*u.one)
o_lon3c = CartesianRepresentation(0., 4.74047, 0., unit=kks)
# This looses information!!
o_lon3 = self.USD_cls.from_cartesian(o_lon3c, base=s)
expected0 = self.USD_cls(1.*u.mas/u.yr, 0.*u.mas/u.yr)
assert_differential_allclose(o_lon3[0], expected0)
# Part of motion kept.
part_kept = s.cross(CartesianRepresentation(0, 1, 0, unit=u.one)).norm()
assert_quantity_allclose(o_lon3.norm(s), 4.74047*part_kept*kks,
atol=1e-10*kks)
# (lat[0]=0, so works for both normal and CosLat differential)
s_off_big2 = s + o_lon3 * 1e5 * u.yr * u.radian/u.mas
expected0 = SphericalRepresentation(90.*u.deg, 0.*u.deg,
1e5*u.one)
assert_representation_allclose(s_off_big2[0], expected0, atol=5.*u.one)
def test_differential_init_errors(self, omit_coslat):
self._setup(omit_coslat)
with pytest.raises(u.UnitsError):
self.USD_cls(0.*u.deg, 10.*u.deg/u.yr)
class TestRadialDifferential():
def setup(self):
s = SphericalRepresentation(lon=[0., 6., 21.] * u.hourangle,
lat=[0., -30., 85.] * u.deg,
distance=[1, 2, 3] * u.kpc)
self.s = s
self.r = s.represent_as(RadialRepresentation)
self.e = s.unit_vectors()
self.sf = s.scale_factors()
def test_name(self):
assert RadialDifferential.get_name() == 'radial'
assert RadialDifferential.get_name() in DIFFERENTIAL_CLASSES
def test_simple_differentials(self):
r, s, e, sf = self.r, self.s, self.e, self.sf
o_distance = RadialDifferential(1.*u.mpc)
# Can be applied to RadialRepresentation, though not most useful.
r_distance = r + o_distance
assert_quantity_allclose(r_distance.distance,
r.distance + o_distance.d_distance)
r_distance2 = o_distance + r
assert_quantity_allclose(r_distance2.distance,
r.distance + o_distance.d_distance)
# More sense to apply it relative to spherical representation.
o_distancec = o_distance.to_cartesian(base=s)
assert_quantity_allclose(o_distancec[0].xyz,
[1e-6, 0., 0.]*u.kpc, atol=1.*u.npc)
o_recover = RadialDifferential.from_cartesian(o_distancec, base=s)
assert_quantity_allclose(o_recover.d_distance, o_distance.d_distance)
s_distance = s + 1.*u.mpc * sf['distance'] * e['distance']
assert_representation_allclose(o_distancec, s_distance - s,
atol=1*u.npc)
s_distance2 = s + o_distance
assert_representation_allclose(s_distance2, s_distance)
class TestPhysicsSphericalDifferential():
"""Test copied from SphericalDifferential, so less extensive."""
def setup(self):
s = PhysicsSphericalRepresentation(phi=[0., 90., 315.] * u.deg,
theta=[90., 120., 5.] * u.deg,
r=[1, 2, 3] * u.kpc)
self.s = s
self.e = s.unit_vectors()
self.sf = s.scale_factors()
def test_name(self):
assert PhysicsSphericalDifferential.get_name() == 'physicsspherical'
assert PhysicsSphericalDifferential.get_name() in DIFFERENTIAL_CLASSES
def test_simple_differentials(self):
s, e, sf = self.s, self.e, self.sf
o_phi = PhysicsSphericalDifferential(1*u.arcsec, 0*u.arcsec, 0*u.kpc)
o_phic = o_phi.to_cartesian(base=s)
o_phi2 = PhysicsSphericalDifferential.from_cartesian(o_phic, base=s)
assert_quantity_allclose(o_phi.d_phi, o_phi2.d_phi, atol=1.*u.narcsec)
assert_quantity_allclose(o_phi.d_theta, o_phi2.d_theta,
atol=1.*u.narcsec)
assert_quantity_allclose(o_phi.d_r, o_phi2.d_r, atol=1.*u.npc)
# simple check by hand for first element.
assert_quantity_allclose(o_phic[0].xyz,
[0., np.pi/180./3600., 0.]*u.kpc,
atol=1.*u.npc)
# check all using unit vectors and scale factors.
s_phi = s + 1.*u.arcsec * sf['phi'] * e['phi']
assert_representation_allclose(o_phic, s_phi - s, atol=1e-10*u.kpc)
o_theta = PhysicsSphericalDifferential(0*u.arcsec, 1*u.arcsec, 0*u.kpc)
o_thetac = o_theta.to_cartesian(base=s)
assert_quantity_allclose(o_thetac[0].xyz,
[0., 0., -np.pi/180./3600.]*u.kpc,
atol=1.*u.npc)
s_theta = s + 1.*u.arcsec * sf['theta'] * e['theta']
assert_representation_allclose(o_thetac, s_theta - s, atol=1e-10*u.kpc)
s_theta2 = s + o_theta
assert_representation_allclose(s_theta2, s_theta, atol=1e-10*u.kpc)
o_r = PhysicsSphericalDifferential(0*u.arcsec, 0*u.arcsec, 1*u.mpc)
o_rc = o_r.to_cartesian(base=s)
assert_quantity_allclose(o_rc[0].xyz, [1e-6, 0., 0.]*u.kpc,
atol=1.*u.npc)
s_r = s + 1.*u.mpc * sf['r'] * e['r']
assert_representation_allclose(o_rc, s_r - s, atol=1e-10*u.kpc)
s_r2 = s + o_r
assert_representation_allclose(s_r2, s_r)
def test_differential_init_errors(self):
with pytest.raises(u.UnitsError):
PhysicsSphericalDifferential(1.*u.arcsec, 0., 0.)
class TestCylindricalDifferential():
"""Test copied from SphericalDifferential, so less extensive."""
def setup(self):
s = CylindricalRepresentation(rho=[1, 2, 3] * u.kpc,
phi=[0., 90., 315.] * u.deg,
z=[3, 2, 1] * u.kpc)
self.s = s
self.e = s.unit_vectors()
self.sf = s.scale_factors()
def test_name(self):
assert CylindricalDifferential.get_name() == 'cylindrical'
assert CylindricalDifferential.get_name() in DIFFERENTIAL_CLASSES
def test_simple_differentials(self):
s, e, sf = self.s, self.e, self.sf
o_rho = CylindricalDifferential(1.*u.mpc, 0.*u.arcsec, 0.*u.kpc)
o_rhoc = o_rho.to_cartesian(base=s)
assert_quantity_allclose(o_rhoc[0].xyz, [1.e-6, 0., 0.]*u.kpc)
s_rho = s + 1.*u.mpc * sf['rho'] * e['rho']
assert_representation_allclose(o_rhoc, s_rho - s, atol=1e-10*u.kpc)
s_rho2 = s + o_rho
assert_representation_allclose(s_rho2, s_rho)
o_phi = CylindricalDifferential(0.*u.kpc, 1.*u.arcsec, 0.*u.kpc)
o_phic = o_phi.to_cartesian(base=s)
o_phi2 = CylindricalDifferential.from_cartesian(o_phic, base=s)
assert_quantity_allclose(o_phi.d_rho, o_phi2.d_rho, atol=1.*u.npc)
assert_quantity_allclose(o_phi.d_phi, o_phi2.d_phi, atol=1.*u.narcsec)
assert_quantity_allclose(o_phi.d_z, o_phi2.d_z, atol=1.*u.npc)
# simple check by hand for first element.
assert_quantity_allclose(o_phic[0].xyz,
[0., np.pi/180./3600., 0.]*u.kpc)
# check all using unit vectors and scale factors.
s_phi = s + 1.*u.arcsec * sf['phi'] * e['phi']
assert_representation_allclose(o_phic, s_phi - s, atol=1e-10*u.kpc)
o_z = CylindricalDifferential(0.*u.kpc, 0.*u.arcsec, 1.*u.mpc)
o_zc = o_z.to_cartesian(base=s)
assert_quantity_allclose(o_zc[0].xyz, [0., 0., 1.e-6]*u.kpc)
s_z = s + 1.*u.mpc * sf['z'] * e['z']
assert_representation_allclose(o_zc, s_z - s, atol=1e-10*u.kpc)
s_z2 = s + o_z
assert_representation_allclose(s_z2, s_z)
def test_differential_init_errors(self):
with pytest.raises(u.UnitsError):
CylindricalDifferential(1.*u.pc, 1.*u.arcsec, 3.*u.km/u.s)
class TestCartesianDifferential():
"""Test copied from SphericalDifferential, so less extensive."""
def setup(self):
s = CartesianRepresentation(x=[1, 2, 3] * u.kpc,
y=[2, 3, 1] * u.kpc,
z=[3, 1, 2] * u.kpc)
self.s = s
self.e = s.unit_vectors()
self.sf = s.scale_factors()
def test_name(self):
assert CartesianDifferential.get_name() == 'cartesian'
assert CartesianDifferential.get_name() in DIFFERENTIAL_CLASSES
def test_simple_differentials(self):
s, e, sf = self.s, self.e, self.sf
for d, differential in ( # test different inits while we're at it.
('x', CartesianDifferential(1.*u.pc, 0.*u.pc, 0.*u.pc)),
('y', CartesianDifferential([0., 1., 0.], unit=u.pc)),
('z', CartesianDifferential(np.array([[0., 0., 1.]]) * u.pc,
xyz_axis=1))):
o_c = differential.to_cartesian(base=s)
o_c2 = differential.to_cartesian()
assert np.all(representation_equal(o_c, o_c2))
assert all(np.all(getattr(differential, 'd_'+c) == getattr(o_c, c))
for c in ('x', 'y', 'z'))
differential2 = CartesianDifferential.from_cartesian(o_c)
assert np.all(representation_equal(differential2, differential))
differential3 = CartesianDifferential.from_cartesian(o_c, base=o_c)
assert np.all(representation_equal(differential3, differential))
s_off = s + 1.*u.pc * sf[d] * e[d]
assert_representation_allclose(o_c, s_off - s, atol=1e-10*u.kpc)
s_off2 = s + differential
assert_representation_allclose(s_off2, s_off)
def test_init_failures(self):
with pytest.raises(ValueError):
CartesianDifferential(1.*u.kpc/u.s, 2.*u.kpc)
with pytest.raises(u.UnitsError):
CartesianDifferential(1.*u.kpc/u.s, 2.*u.kpc, 3.*u.kpc)
with pytest.raises(ValueError):
CartesianDifferential(1.*u.kpc, 2.*u.kpc, 3.*u.kpc, xyz_axis=1)
class TestDifferentialConversion():
def setup(self):
self.s = SphericalRepresentation(lon=[0., 6., 21.] * u.hourangle,
lat=[0., -30., 85.] * u.deg,
distance=[1, 2, 3] * u.kpc)
@pytest.mark.parametrize('sd_cls', [SphericalDifferential,
SphericalCosLatDifferential])
def test_represent_as_own_class(self, sd_cls):
so = sd_cls(1.*u.deg, 2.*u.deg, 0.1*u.kpc)
so2 = so.represent_as(sd_cls)
assert so2 is so
def test_represent_other_coslat(self):
s = self.s
coslat = np.cos(s.lat)
so = SphericalDifferential(1.*u.deg, 2.*u.deg, 0.1*u.kpc)
so_coslat = so.represent_as(SphericalCosLatDifferential, base=s)
assert_quantity_allclose(so.d_lon * coslat,
so_coslat.d_lon_coslat)
so2 = so_coslat.represent_as(SphericalDifferential, base=s)
assert np.all(representation_equal(so2, so))
so3 = SphericalDifferential.from_representation(so_coslat, base=s)
assert np.all(representation_equal(so3, so))
so_coslat2 = SphericalCosLatDifferential.from_representation(so, base=s)
assert np.all(representation_equal(so_coslat2, so_coslat))
# Also test UnitSpherical
us = s.represent_as(UnitSphericalRepresentation)
uo = so.represent_as(UnitSphericalDifferential)
uo_coslat = so.represent_as(UnitSphericalCosLatDifferential, base=s)
assert_quantity_allclose(uo.d_lon * coslat,
uo_coslat.d_lon_coslat)
uo2 = uo_coslat.represent_as(UnitSphericalDifferential, base=us)
assert np.all(representation_equal(uo2, uo))
uo3 = UnitSphericalDifferential.from_representation(uo_coslat, base=us)
assert np.all(representation_equal(uo3, uo))
uo_coslat2 = UnitSphericalCosLatDifferential.from_representation(
uo, base=us)
assert np.all(representation_equal(uo_coslat2, uo_coslat))
uo_coslat3 = uo.represent_as(UnitSphericalCosLatDifferential, base=us)
assert np.all(representation_equal(uo_coslat3, uo_coslat))
@pytest.mark.parametrize('sd_cls', [SphericalDifferential,
SphericalCosLatDifferential])
@pytest.mark.parametrize('r_cls', (SphericalRepresentation,
UnitSphericalRepresentation,
PhysicsSphericalRepresentation,
CylindricalRepresentation))
def test_represent_regular_class(self, sd_cls, r_cls):
so = sd_cls(1.*u.deg, 2.*u.deg, 0.1*u.kpc)
r = so.represent_as(r_cls, base=self.s)
c = so.to_cartesian(self.s)
r_check = c.represent_as(r_cls)
assert np.all(representation_equal(r, r_check))
so2 = sd_cls.from_representation(r, base=self.s)
so3 = sd_cls.from_cartesian(r.to_cartesian(), self.s)
assert np.all(representation_equal(so2, so3))
@pytest.mark.parametrize('sd_cls', [SphericalDifferential,
SphericalCosLatDifferential])
def test_convert_physics(self, sd_cls):
# Conversion needs no base for SphericalDifferential, but does
# need one (to get the latitude) for SphericalCosLatDifferential.
if sd_cls is SphericalDifferential:
usd_cls = UnitSphericalDifferential
base_s = base_u = base_p = None
else:
usd_cls = UnitSphericalCosLatDifferential
base_s = self.s[1]
base_u = base_s.represent_as(UnitSphericalRepresentation)
base_p = base_s.represent_as(PhysicsSphericalRepresentation)
so = sd_cls(1.*u.deg, 2.*u.deg, 0.1*u.kpc)
po = so.represent_as(PhysicsSphericalDifferential, base=base_s)
so2 = sd_cls.from_representation(po, base=base_s)
assert_differential_allclose(so, so2)
po2 = PhysicsSphericalDifferential.from_representation(so, base=base_p)
assert_differential_allclose(po, po2)
so3 = po.represent_as(sd_cls, base=base_p)
assert_differential_allclose(so, so3)
s = self.s
p = s.represent_as(PhysicsSphericalRepresentation)
cso = so.to_cartesian(s[1])
cpo = po.to_cartesian(p[1])
assert_representation_allclose(cso, cpo)
assert_representation_allclose(s[1] + so, p[1] + po)
po2 = so.represent_as(PhysicsSphericalDifferential,
base=None if base_s is None else s)
assert_representation_allclose(s + so, p + po2)
suo = usd_cls.from_representation(so)
puo = usd_cls.from_representation(po, base=base_u)
assert_differential_allclose(suo, puo)
suo2 = so.represent_as(usd_cls)
puo2 = po.represent_as(usd_cls, base=base_p)
assert_differential_allclose(suo2, puo2)
assert_differential_allclose(puo, puo2)
sro = RadialDifferential.from_representation(so)
pro = RadialDifferential.from_representation(po)
assert representation_equal(sro, pro)
sro2 = so.represent_as(RadialDifferential)
pro2 = po.represent_as(RadialDifferential)
assert representation_equal(sro2, pro2)
assert representation_equal(pro, pro2)
@pytest.mark.parametrize(
('sd_cls', 'usd_cls'),
[(SphericalDifferential, UnitSphericalDifferential),
(SphericalCosLatDifferential, UnitSphericalCosLatDifferential)])
def test_convert_unit_spherical_radial(self, sd_cls, usd_cls):
s = self.s
us = s.represent_as(UnitSphericalRepresentation)
rs = s.represent_as(RadialRepresentation)
assert_representation_allclose(rs * us, s)
uo = usd_cls(2.*u.deg, 1.*u.deg)
so = uo.represent_as(sd_cls, base=s)
assert_quantity_allclose(so.d_distance, 0.*u.kpc, atol=1.*u.npc)
uo2 = so.represent_as(usd_cls)
assert_representation_allclose(uo.to_cartesian(us),
uo2.to_cartesian(us))
so1 = sd_cls(2.*u.deg, 1.*u.deg, 5.*u.pc)
uo_r = so1.represent_as(usd_cls)
ro_r = so1.represent_as(RadialDifferential)
assert np.all(representation_equal(uo_r, uo))
assert np.all(representation_equal(ro_r, RadialDifferential(5.*u.pc)))
@pytest.mark.parametrize('sd_cls', [SphericalDifferential,
SphericalCosLatDifferential])
def test_convert_cylindrial(self, sd_cls):
s = self.s
so = sd_cls(1.*u.deg, 2.*u.deg, 0.1*u.kpc)
cyo = so.represent_as(CylindricalDifferential, base=s)
cy = s.represent_as(CylindricalRepresentation)
so1 = cyo.represent_as(sd_cls, base=cy)
assert_representation_allclose(so.to_cartesian(s),
so1.to_cartesian(s))
cyo2 = CylindricalDifferential.from_representation(so, base=cy)
assert_representation_allclose(cyo2.to_cartesian(base=cy),
cyo.to_cartesian(base=cy))
so2 = sd_cls.from_representation(cyo2, base=s)
assert_representation_allclose(so.to_cartesian(s),
so2.to_cartesian(s))
@pytest.mark.parametrize('sd_cls', [SphericalDifferential,
SphericalCosLatDifferential])
def test_combinations(self, sd_cls):
if sd_cls is SphericalDifferential:
uo = UnitSphericalDifferential(2.*u.deg, 1.*u.deg)
uo_d_lon = uo.d_lon
else:
uo = UnitSphericalCosLatDifferential(2.*u.deg, 1.*u.deg)
uo_d_lon = uo.d_lon_coslat
ro = RadialDifferential(1.*u.mpc)
so1 = uo + ro
so1c = sd_cls(uo_d_lon, uo.d_lat, ro.d_distance)
assert np.all(representation_equal(so1, so1c))
so2 = uo - ro
so2c = sd_cls(uo_d_lon, uo.d_lat, -ro.d_distance)
assert np.all(representation_equal(so2, so2c))
so3 = so2 + ro
so3c = sd_cls(uo_d_lon, uo.d_lat, 0.*u.kpc)
assert np.all(representation_equal(so3, so3c))
so4 = so1 + ro
so4c = sd_cls(uo_d_lon, uo.d_lat, 2*ro.d_distance)
assert np.all(representation_equal(so4, so4c))
so5 = so1 - uo
so5c = sd_cls(0*u.deg, 0.*u.deg, ro.d_distance)
assert np.all(representation_equal(so5, so5c))
assert_representation_allclose(self.s + (uo+ro), self.s+so1)
@pytest.mark.parametrize('rep,dif', [
[CartesianRepresentation([1, 2, 3]*u.kpc),
CartesianDifferential([.1, .2, .3]*u.km/u.s)],
[SphericalRepresentation(90*u.deg, 0.*u.deg, 14.*u.kpc),
SphericalDifferential(1.*u.deg, 2.*u.deg, 0.1*u.kpc)]
])
def test_arithmetic_with_differentials_fail(rep, dif):
rep = rep.with_differentials(dif)
with pytest.raises(TypeError):
rep + rep
with pytest.raises(TypeError):
rep - rep
with pytest.raises(TypeError):
rep * rep
with pytest.raises(TypeError):
rep / rep
with pytest.raises(TypeError):
10. * rep
with pytest.raises(TypeError):
rep / 10.
with pytest.raises(TypeError):
-rep
|
2be805ad35f8f1f4b12935fe2fb0e1273022ec47e20acbbc824988112141a228 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import warnings
import pytest
import numpy as np
from numpy import testing as npt
from astropy import units as u
from astropy.time import Time
from astropy.coordinates.builtin_frames import ICRS, AltAz
from astropy.coordinates.builtin_frames.utils import get_jd12
from astropy.coordinates import EarthLocation
from astropy.coordinates import SkyCoord
from astropy.tests.helper import catch_warnings
from astropy import _erfa as erfa
from astropy.utils import iers
from .utils import randomly_sample_sphere
# These fixtures are used in test_iau_fullstack
@pytest.fixture(scope="function")
def fullstack_icrs():
ra, dec, _ = randomly_sample_sphere(1000)
return ICRS(ra=ra, dec=dec)
@pytest.fixture(scope="function")
def fullstack_fiducial_altaz(fullstack_icrs):
altazframe = AltAz(location=EarthLocation(lat=0*u.deg, lon=0*u.deg, height=0*u.m),
obstime=Time('J2000'))
with warnings.catch_warnings(): # Ignore remote_data warning
warnings.simplefilter('ignore')
result = fullstack_icrs.transform_to(altazframe)
return result
@pytest.fixture(scope="function", params=['J2000.1', 'J2010'])
def fullstack_times(request):
return Time(request.param)
@pytest.fixture(scope="function", params=[(0, 0, 0), (23, 0, 0), (-70, 0, 0), (0, 100, 0), (23, 0, 3000)])
def fullstack_locations(request):
return EarthLocation(lat=request.param[0]*u.deg, lon=request.param[0]*u.deg,
height=request.param[0]*u.m)
@pytest.fixture(scope="function",
params=[(0*u.bar, 0*u.deg_C, 0, 1*u.micron),
(1*u.bar, 0*u.deg_C, 0*u.one, 1*u.micron),
(1*u.bar, 10*u.deg_C, 0, 1*u.micron),
(1*u.bar, 0*u.deg_C, 50*u.percent, 1*u.micron),
(1*u.bar, 0*u.deg_C, 0, 21*u.cm)])
def fullstack_obsconditions(request):
return request.param
def _erfa_check(ira, idec, astrom):
"""
This function does the same thing the astropy layer is supposed to do, but
all in erfa
"""
cra, cdec = erfa.atciq(ira, idec, 0, 0, 0, 0, astrom)
az, zen, ha, odec, ora = erfa.atioq(cra, cdec, astrom)
alt = np.pi/2-zen
cra2, cdec2 = erfa.atoiq('A', az, zen, astrom)
ira2, idec2 = erfa.aticq(cra2, cdec2, astrom)
dct = locals()
del dct['astrom']
return dct
@pytest.mark.remote_data
def test_iau_fullstack(fullstack_icrs, fullstack_fiducial_altaz,
fullstack_times, fullstack_locations,
fullstack_obsconditions):
"""
Test the full transform from ICRS <-> AltAz
"""
# create the altaz frame
altazframe = AltAz(obstime=fullstack_times, location=fullstack_locations,
pressure=fullstack_obsconditions[0],
temperature=fullstack_obsconditions[1],
relative_humidity=fullstack_obsconditions[2],
obswl=fullstack_obsconditions[3])
aacoo = fullstack_icrs.transform_to(altazframe)
# compare aacoo to the fiducial AltAz - should always be different
assert np.all(np.abs(aacoo.alt - fullstack_fiducial_altaz.alt) > 50*u.milliarcsecond)
assert np.all(np.abs(aacoo.az - fullstack_fiducial_altaz.az) > 50*u.milliarcsecond)
# if the refraction correction is included, we *only* do the comparisons
# where altitude >5 degrees. The SOFA guides imply that below 5 is where
# where accuracy gets more problematic, and testing reveals that alt<~0
# gives garbage round-tripping, and <10 can give ~1 arcsec uncertainty
if fullstack_obsconditions[0].value == 0:
# but if there is no refraction correction, check everything
msk = slice(None)
tol = 5*u.microarcsecond
else:
msk = aacoo.alt > 5*u.deg
# most of them aren't this bad, but some of those at low alt are offset
# this much. For alt > 10, this is always better than 100 masec
tol = 750*u.milliarcsecond
# now make sure the full stack round-tripping works
icrs2 = aacoo.transform_to(ICRS)
adras = np.abs(fullstack_icrs.ra - icrs2.ra)[msk]
addecs = np.abs(fullstack_icrs.dec - icrs2.dec)[msk]
assert np.all(adras < tol), 'largest RA change is {0} mas, > {1}'.format(np.max(adras.arcsec*1000), tol)
assert np.all(addecs < tol), 'largest Dec change is {0} mas, > {1}'.format(np.max(addecs.arcsec*1000), tol)
# check that we're consistent with the ERFA alt/az result
xp, yp = u.Quantity(iers.IERS_Auto.open().pm_xy(fullstack_times)).to_value(u.radian)
lon = fullstack_locations.geodetic[0].to_value(u.radian)
lat = fullstack_locations.geodetic[1].to_value(u.radian)
height = fullstack_locations.geodetic[2].to_value(u.m)
jd1, jd2 = get_jd12(fullstack_times, 'utc')
pressure = fullstack_obsconditions[0].to_value(u.hPa)
temperature = fullstack_obsconditions[1].to_value(u.deg_C)
# Relative humidity can be a quantity or a number.
relative_humidity = u.Quantity(fullstack_obsconditions[2], u.one).value
obswl = fullstack_obsconditions[3].to_value(u.micron)
astrom, eo = erfa.apco13(jd1, jd2,
fullstack_times.delta_ut1_utc,
lon, lat, height,
xp, yp,
pressure, temperature, relative_humidity,
obswl)
erfadct = _erfa_check(fullstack_icrs.ra.rad, fullstack_icrs.dec.rad, astrom)
npt.assert_allclose(erfadct['alt'], aacoo.alt.radian, atol=1e-7)
npt.assert_allclose(erfadct['az'], aacoo.az.radian, atol=1e-7)
@pytest.mark.remote_data
def test_fiducial_roudtrip(fullstack_icrs, fullstack_fiducial_altaz):
"""
Test the full transform from ICRS <-> AltAz
"""
aacoo = fullstack_icrs.transform_to(fullstack_fiducial_altaz)
# make sure the round-tripping works
icrs2 = aacoo.transform_to(ICRS)
npt.assert_allclose(fullstack_icrs.ra.deg, icrs2.ra.deg)
npt.assert_allclose(fullstack_icrs.dec.deg, icrs2.dec.deg)
def test_future_altaz():
"""
While this does test the full stack, it is mostly meant to check that a
warning is raised when attempting to get to AltAz in the future (beyond
IERS tables)
"""
from astropy.utils.exceptions import AstropyWarning
# this is an ugly hack to get the warning to show up even if it has already
# appeared
from astropy.coordinates.builtin_frames import utils
if hasattr(utils, '__warningregistry__'):
utils.__warningregistry__.clear()
with catch_warnings() as found_warnings:
location = EarthLocation(lat=0*u.deg, lon=0*u.deg)
t = Time('J2161')
SkyCoord(1*u.deg, 2*u.deg).transform_to(AltAz(location=location, obstime=t))
# check that these message(s) appear among any other warnings. If tests are run with
# --remote-data then the IERS table will be an instance of IERS_Auto which is
# assured of being "fresh". In this case getting times outside the range of the
# table does not raise an exception. Only if using IERS_B (which happens without
# --remote-data, i.e. for all CI testing) do we expect another warning.
messages_to_find = ["Tried to get polar motions for times after IERS data is valid."]
if isinstance(iers.IERS_Auto.iers_table, iers.IERS_B):
messages_to_find.append("(some) times are outside of range covered by IERS table.")
messages_found = [False for _ in messages_to_find]
for w in found_warnings:
if issubclass(w.category, AstropyWarning):
for i, message_to_find in enumerate(messages_to_find):
if message_to_find in str(w.message):
messages_found[i] = True
assert all(messages_found)
|
16ddb2911b2f5af710e9a883354939736e3cae8208dbb44ff16b2b4d3aaa0210 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Test replacements for ERFA functions atciqz and aticq."""
from itertools import product
import pytest
from astropy.tests.helper import assert_quantity_allclose as assert_allclose
from astropy.time import Time
from astropy import _erfa as erfa
from .utils import randomly_sample_sphere
from astropy.coordinates.builtin_frames.utils import get_jd12, atciqz, aticq
times = [Time("2014-06-25T00:00"), Time(["2014-06-25T00:00", "2014-09-24"])]
ra, dec, _ = randomly_sample_sphere(2)
positions = ((ra[0], dec[0]), (ra, dec))
spacetimes = product(times, positions)
@pytest.mark.parametrize('st', spacetimes)
def test_atciqz_aticq(st):
"""Check replacements against erfa versions for consistency."""
t, pos = st
jd1, jd2 = get_jd12(t, 'tdb')
astrom, _ = erfa.apci13(jd1, jd2)
ra, dec = pos
ra = ra.value
dec = dec.value
assert_allclose(erfa.atciqz(ra, dec, astrom), atciqz(ra, dec, astrom))
assert_allclose(erfa.aticq(ra, dec, astrom), aticq(ra, dec, astrom))
|
bee8bf24f6a55e9ac8a952336c8baf99bb18b1755c816b83059428b49a87c4f0 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import numpy as np
from numpy.testing import assert_allclose, assert_array_equal
from astropy import units as u
from astropy.coordinates.matrix_utilities import rotation_matrix, angle_axis
def test_rotation_matrix():
assert_array_equal(rotation_matrix(0*u.deg, 'x'), np.eye(3))
assert_allclose(rotation_matrix(90*u.deg, 'y'), [[0, 0, -1],
[0, 1, 0],
[1, 0, 0]], atol=1e-12)
assert_allclose(rotation_matrix(-90*u.deg, 'z'), [[0, -1, 0],
[1, 0, 0],
[0, 0, 1]], atol=1e-12)
assert_allclose(rotation_matrix(45*u.deg, 'x'),
rotation_matrix(45*u.deg, [1, 0, 0]))
assert_allclose(rotation_matrix(125*u.deg, 'y'),
rotation_matrix(125*u.deg, [0, 1, 0]))
assert_allclose(rotation_matrix(-30*u.deg, 'z'),
rotation_matrix(-30*u.deg, [0, 0, 1]))
assert_allclose(np.dot(rotation_matrix(180*u.deg, [1, 1, 0]), [1, 0, 0]),
[0, 1, 0], atol=1e-12)
# make sure it also works for very small angles
assert_allclose(rotation_matrix(0.000001*u.deg, 'x'),
rotation_matrix(0.000001*u.deg, [1, 0, 0]))
def test_angle_axis():
m1 = rotation_matrix(35*u.deg, 'x')
an1, ax1 = angle_axis(m1)
assert an1 - 35*u.deg < 1e-10*u.deg
assert_allclose(ax1, [1, 0, 0])
m2 = rotation_matrix(-89*u.deg, [1, 1, 0])
an2, ax2 = angle_axis(m2)
assert an2 - 89*u.deg < 1e-10*u.deg
assert_allclose(ax2, [-2**-0.5, -2**-0.5, 0])
|
57898674f611ec7769552755720385adc9af687e1f45f7120354c74e0d563fee | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Regression tests for coordinates-related bugs that don't have an obvious other
place to live
"""
import io
import copy
import pytest
import numpy as np
from astropy import units as u
from astropy.coordinates import (AltAz, EarthLocation, SkyCoord, get_sun, ICRS,
GeocentricMeanEcliptic, Longitude, Latitude, GCRS, HCRS, CIRS,
get_moon, FK4, FK4NoETerms, BaseCoordinateFrame, ITRS,
QuantityAttribute, UnitSphericalRepresentation,
SphericalRepresentation, CartesianRepresentation,
FunctionTransform)
from astropy.coordinates.sites import get_builtin_sites
from astropy.time import Time
from astropy.utils import iers
from astropy.table import Table
from astropy.tests.helper import assert_quantity_allclose, catch_warnings
from .test_matching import HAS_SCIPY, OLDER_SCIPY
from astropy.units import allclose as quantity_allclose
try:
import yaml # pylint: disable=W0611
HAS_YAML = True
except ImportError:
HAS_YAML = False
def test_regression_5085():
"""
PR #5085 was put in place to fix the following issue.
Issue: https://github.com/astropy/astropy/issues/5069
At root was the transformation of Ecliptic coordinates with
non-scalar times.
"""
# Note: for regression test, we need to be sure that we use UTC for the
# epoch, even though more properly that should be TT; but the "expected"
# values were calculated using that.
j2000 = Time('J2000', scale='utc')
times = Time(["2015-08-28 03:30", "2015-09-05 10:30", "2015-09-15 18:35"])
latitudes = Latitude([3.9807075, -5.00733806, 1.69539491]*u.deg)
longitudes = Longitude([311.79678613, 72.86626741, 199.58698226]*u.deg)
distances = u.Quantity([0.00243266, 0.0025424, 0.00271296]*u.au)
coo = GeocentricMeanEcliptic(lat=latitudes,
lon=longitudes,
distance=distances, obstime=times, equinox=times)
# expected result
ras = Longitude([310.50095400, 314.67109920, 319.56507428]*u.deg)
decs = Latitude([-18.25190443, -17.1556676, -15.71616522]*u.deg)
distances = u.Quantity([1.78309901, 1.710874, 1.61326649]*u.au)
expected_result = GCRS(ra=ras, dec=decs,
distance=distances, obstime=j2000).cartesian.xyz
actual_result = coo.transform_to(GCRS(obstime=j2000)).cartesian.xyz
assert_quantity_allclose(expected_result, actual_result)
@pytest.mark.remote_data
def test_regression_3920():
"""
Issue: https://github.com/astropy/astropy/issues/3920
"""
loc = EarthLocation.from_geodetic(0*u.deg, 0*u.deg, 0)
time = Time('2010-1-1')
aa = AltAz(location=loc, obstime=time)
sc = SkyCoord(10*u.deg, 3*u.deg)
assert sc.transform_to(aa).shape == tuple()
# That part makes sense: the input is a scalar so the output is too
sc2 = SkyCoord(10*u.deg, 3*u.deg, 1*u.AU)
assert sc2.transform_to(aa).shape == tuple()
# in 3920 that assert fails, because the shape is (1,)
# check that the same behavior occurs even if transform is from low-level classes
icoo = ICRS(sc.data)
icoo2 = ICRS(sc2.data)
assert icoo.transform_to(aa).shape == tuple()
assert icoo2.transform_to(aa).shape == tuple()
@pytest.mark.remote_data
def test_regression_3938():
"""
Issue: https://github.com/astropy/astropy/issues/3938
"""
# Set up list of targets - we don't use `from_name` here to avoid
# remote_data requirements, but it does the same thing
# vega = SkyCoord.from_name('Vega')
vega = SkyCoord(279.23473479*u.deg, 38.78368896*u.deg)
# capella = SkyCoord.from_name('Capella')
capella = SkyCoord(79.17232794*u.deg, 45.99799147*u.deg)
# sirius = SkyCoord.from_name('Sirius')
sirius = SkyCoord(101.28715533*u.deg, -16.71611586*u.deg)
targets = [vega, capella, sirius]
# Feed list of targets into SkyCoord
combined_coords = SkyCoord(targets)
# Set up AltAz frame
time = Time('2012-01-01 00:00:00')
location = EarthLocation('10d', '45d', 0)
aa = AltAz(location=location, obstime=time)
combined_coords.transform_to(aa)
# in 3938 the above yields ``UnitConversionError: '' (dimensionless) and 'pc' (length) are not convertible``
def test_regression_3998():
"""
Issue: https://github.com/astropy/astropy/issues/3998
"""
time = Time('2012-01-01 00:00:00')
assert time.isscalar
sun = get_sun(time)
assert sun.isscalar
# in 3998, the above yields False - `sun` is a length-1 vector
assert sun.obstime is time
@pytest.mark.remote_data
def test_regression_4033():
"""
Issue: https://github.com/astropy/astropy/issues/4033
"""
# alb = SkyCoord.from_name('Albireo')
alb = SkyCoord(292.68033548*u.deg, 27.95968007*u.deg)
alb_wdist = SkyCoord(alb, distance=133*u.pc)
# de = SkyCoord.from_name('Deneb')
de = SkyCoord(310.35797975*u.deg, 45.28033881*u.deg)
de_wdist = SkyCoord(de, distance=802*u.pc)
aa = AltAz(location=EarthLocation(lat=45*u.deg, lon=0*u.deg), obstime='2010-1-1')
deaa = de.transform_to(aa)
albaa = alb.transform_to(aa)
alb_wdistaa = alb_wdist.transform_to(aa)
de_wdistaa = de_wdist.transform_to(aa)
# these work fine
sepnod = deaa.separation(albaa)
sepwd = deaa.separation(alb_wdistaa)
assert_quantity_allclose(sepnod, 22.2862*u.deg, rtol=1e-6)
assert_quantity_allclose(sepwd, 22.2862*u.deg, rtol=1e-6)
# parallax should be present when distance added
assert np.abs(sepnod - sepwd) > 1*u.marcsec
# in 4033, the following fail with a recursion error
assert_quantity_allclose(de_wdistaa.separation(alb_wdistaa), 22.2862*u.deg, rtol=1e-3)
assert_quantity_allclose(alb_wdistaa.separation(deaa), 22.2862*u.deg, rtol=1e-3)
@pytest.mark.skipif(not HAS_SCIPY, reason='No Scipy')
@pytest.mark.skipif(OLDER_SCIPY, reason='Scipy too old')
def test_regression_4082():
"""
Issue: https://github.com/astropy/astropy/issues/4082
"""
from astropy.coordinates import search_around_sky, search_around_3d
cat = SkyCoord([10.076, 10.00455], [18.54746, 18.54896], unit='deg')
search_around_sky(cat[0:1], cat, seplimit=u.arcsec * 60, storekdtree=False)
# in the issue, this raises a TypeError
# also check 3d for good measure, although it's not really affected by this bug directly
cat3d = SkyCoord([10.076, 10.00455]*u.deg, [18.54746, 18.54896]*u.deg, distance=[0.1, 1.5]*u.kpc)
search_around_3d(cat3d[0:1], cat3d, 1*u.kpc, storekdtree=False)
def test_regression_4210():
"""
Issue: https://github.com/astropy/astropy/issues/4210
Related PR with actual change: https://github.com/astropy/astropy/pull/4211
"""
crd = SkyCoord(0*u.deg, 0*u.deg, distance=1*u.AU)
ecl = crd.geocentricmeanecliptic
# bug was that "lambda", which at the time was the name of the geocentric
# ecliptic longitude, is a reserved keyword. So this just makes sure the
# new name is are all valid
ecl.lon
# and for good measure, check the other ecliptic systems are all the same
# names for their attributes
from astropy.coordinates.builtin_frames import ecliptic
for frame_name in ecliptic.__all__:
eclcls = getattr(ecliptic, frame_name)
eclobj = eclcls(1*u.deg, 2*u.deg, 3*u.AU)
eclobj.lat
eclobj.lon
eclobj.distance
def test_regression_futuretimes_4302():
"""
Checks that an error is not raised for future times not covered by IERS
tables (at least in a simple transform like CIRS->ITRS that simply requires
the UTC<->UT1 conversion).
Relevant comment: https://github.com/astropy/astropy/pull/4302#discussion_r44836531
"""
from astropy.utils.exceptions import AstropyWarning
# this is an ugly hack to get the warning to show up even if it has already
# appeared
from astropy.coordinates.builtin_frames import utils
if hasattr(utils, '__warningregistry__'):
utils.__warningregistry__.clear()
with catch_warnings() as found_warnings:
future_time = Time('2511-5-1')
c = CIRS(1*u.deg, 2*u.deg, obstime=future_time)
c.transform_to(ITRS(obstime=future_time))
if not isinstance(iers.IERS_Auto.iers_table, iers.IERS_Auto):
saw_iers_warnings = False
for w in found_warnings:
if issubclass(w.category, AstropyWarning):
if '(some) times are outside of range covered by IERS table' in str(w.message):
saw_iers_warnings = True
break
assert saw_iers_warnings, 'Never saw IERS warning'
def test_regression_4996():
# this part is the actual regression test
deltat = np.linspace(-12, 12, 1000)*u.hour
times = Time('2012-7-13 00:00:00') + deltat
suncoo = get_sun(times)
assert suncoo.shape == (len(times),)
# and this is an additional test to make sure more complex arrays work
times2 = Time('2012-7-13 00:00:00') + deltat.reshape(10, 20, 5)
suncoo2 = get_sun(times2)
assert suncoo2.shape == times2.shape
# this is intentionally not allclose - they should be *exactly* the same
assert np.all(suncoo.ra.ravel() == suncoo2.ra.ravel())
def test_regression_4293():
"""Really just an extra test on FK4 no e, after finding that the units
were not always taken correctly. This test is against explicitly doing
the transformations on pp170 of Explanatory Supplement to the Astronomical
Almanac (Seidelmann, 2005).
See https://github.com/astropy/astropy/pull/4293#issuecomment-234973086
"""
# Check all over sky, but avoiding poles (note that FK4 did not ignore
# e terms within 10∘ of the poles... see p170 of explan.supp.).
ra, dec = np.meshgrid(np.arange(0, 359, 45), np.arange(-80, 81, 40))
fk4 = FK4(ra.ravel() * u.deg, dec.ravel() * u.deg)
Dc = -0.065838*u.arcsec
Dd = +0.335299*u.arcsec
# Dc * tan(obliquity), as given on p.170
Dctano = -0.028553*u.arcsec
fk4noe_dec = (fk4.dec - (Dd*np.cos(fk4.ra) -
Dc*np.sin(fk4.ra))*np.sin(fk4.dec) -
Dctano*np.cos(fk4.dec))
fk4noe_ra = fk4.ra - (Dc*np.cos(fk4.ra) +
Dd*np.sin(fk4.ra)) / np.cos(fk4.dec)
fk4noe = fk4.transform_to(FK4NoETerms)
# Tolerance here just set to how well the coordinates match, which is much
# better than the claimed accuracy of <1 mas for this first-order in
# v_earth/c approximation.
# Interestingly, if one divides by np.cos(fk4noe_dec) in the ra correction,
# the match becomes good to 2 μas.
assert_quantity_allclose(fk4noe.ra, fk4noe_ra, atol=11.*u.uas, rtol=0)
assert_quantity_allclose(fk4noe.dec, fk4noe_dec, atol=3.*u.uas, rtol=0)
@pytest.mark.remote_data
def test_regression_4926():
times = Time('2010-01-1') + np.arange(20)*u.day
green = get_builtin_sites()['greenwich']
# this is the regression test
moon = get_moon(times, green)
# this is an additional test to make sure the GCRS->ICRS transform works for complex shapes
moon.transform_to(ICRS())
# and some others to increase coverage of transforms
moon.transform_to(HCRS(obstime="J2000"))
moon.transform_to(HCRS(obstime=times))
def test_regression_5209():
"check that distances are not lost on SkyCoord init"
time = Time('2015-01-01')
moon = get_moon(time)
new_coord = SkyCoord([moon])
assert_quantity_allclose(new_coord[0].distance, moon.distance)
@pytest.mark.remote_data
def test_regression_5133():
N = 1000
np.random.seed(12345)
lon = np.random.uniform(-10, 10, N) * u.deg
lat = np.random.uniform(50, 52, N) * u.deg
alt = np.random.uniform(0, 10., N) * u.km
time = Time('2010-1-1')
objects = EarthLocation.from_geodetic(lon, lat, height=alt)
itrs_coo = objects.get_itrs(time)
homes = [EarthLocation.from_geodetic(lon=-1 * u.deg, lat=52 * u.deg, height=h)
for h in (0, 1000, 10000)*u.km]
altaz_frames = [AltAz(obstime=time, location=h) for h in homes]
altaz_coos = [itrs_coo.transform_to(f) for f in altaz_frames]
# they should all be different
for coo in altaz_coos[1:]:
assert not quantity_allclose(coo.az, coo.az[0])
assert not quantity_allclose(coo.alt, coo.alt[0])
@pytest.mark.remote_data
def test_itrs_vals_5133():
time = Time('2010-1-1')
el = EarthLocation.from_geodetic(lon=20*u.deg, lat=45*u.deg, height=0*u.km)
lons = [20, 30, 20]*u.deg
lats = [44, 45, 45]*u.deg
alts = [0, 0, 10]*u.km
coos = [EarthLocation.from_geodetic(lon, lat, height=alt).get_itrs(time)
for lon, lat, alt in zip(lons, lats, alts)]
aaf = AltAz(obstime=time, location=el)
aacs = [coo.transform_to(aaf) for coo in coos]
assert all([coo.isscalar for coo in aacs])
# the ~1 arcsec tolerance is b/c aberration makes it not exact
assert_quantity_allclose(aacs[0].az, 180*u.deg, atol=1*u.arcsec)
assert aacs[0].alt < 0*u.deg
assert aacs[0].distance > 50*u.km
# it should *not* actually be 90 degrees, b/c constant latitude is not
# straight east anywhere except the equator... but should be close-ish
assert_quantity_allclose(aacs[1].az, 90*u.deg, atol=5*u.deg)
assert aacs[1].alt < 0*u.deg
assert aacs[1].distance > 50*u.km
assert_quantity_allclose(aacs[2].alt, 90*u.deg, atol=1*u.arcsec)
assert_quantity_allclose(aacs[2].distance, 10*u.km)
@pytest.mark.remote_data
def test_regression_simple_5133():
t = Time('J2010')
obj = EarthLocation(-1*u.deg, 52*u.deg, height=[100., 0.]*u.km)
home = EarthLocation(-1*u.deg, 52*u.deg, height=10.*u.km)
aa = obj.get_itrs(t).transform_to(AltAz(obstime=t, location=home))
# az is more-or-less undefined for straight up or down
assert_quantity_allclose(aa.alt, [90, -90]*u.deg, rtol=1e-5)
assert_quantity_allclose(aa.distance, [90, 10]*u.km)
def test_regression_5743():
sc = SkyCoord([5, 10], [20, 30], unit=u.deg,
obstime=['2017-01-01T00:00', '2017-01-01T00:10'])
assert sc[0].obstime.shape == tuple()
@pytest.mark.remote_data
def test_regression_5889_5890():
# ensure we can represent all Representations and transform to ND frames
greenwich = EarthLocation(
*u.Quantity([3980608.90246817, -102.47522911, 4966861.27310067],
unit=u.m))
times = Time("2017-03-20T12:00:00") + np.linspace(-2, 2, 3)*u.hour
moon = get_moon(times, location=greenwich)
targets = SkyCoord([350.7*u.deg, 260.7*u.deg], [18.4*u.deg, 22.4*u.deg])
targs2d = targets[:, np.newaxis]
targs2d.transform_to(moon)
def test_regression_6236():
# sunpy changes its representation upon initialisation of a frame,
# including via `realize_frame`. Ensure this works.
class MyFrame(BaseCoordinateFrame):
default_representation = CartesianRepresentation
my_attr = QuantityAttribute(default=0, unit=u.m)
class MySpecialFrame(MyFrame):
def __init__(self, *args, **kwargs):
_rep_kwarg = kwargs.get('representation_type', None)
super().__init__(*args, **kwargs)
if not _rep_kwarg:
self.representation_type = self.default_representation
self._data = self.data.represent_as(self.representation_type)
rep1 = UnitSphericalRepresentation([0., 1]*u.deg, [2., 3.]*u.deg)
rep2 = SphericalRepresentation([10., 11]*u.deg, [12., 13.]*u.deg,
[14., 15.]*u.kpc)
mf1 = MyFrame(rep1, my_attr=1.*u.km)
mf2 = mf1.realize_frame(rep2)
# Normally, data is stored as is, but the representation gets set to a
# default, even if a different representation instance was passed in.
# realize_frame should do the same. Just in case, check attrs are passed.
assert mf1.data is rep1
assert mf2.data is rep2
assert mf1.representation_type is CartesianRepresentation
assert mf2.representation_type is CartesianRepresentation
assert mf2.my_attr == mf1.my_attr
# It should be independent of whether I set the reprensentation explicitly
mf3 = MyFrame(rep1, my_attr=1.*u.km, representation_type='unitspherical')
mf4 = mf3.realize_frame(rep2)
assert mf3.data is rep1
assert mf4.data is rep2
assert mf3.representation_type is UnitSphericalRepresentation
assert mf4.representation_type is CartesianRepresentation
assert mf4.my_attr == mf3.my_attr
# This should be enough to help sunpy, but just to be sure, a test
# even closer to what is done there, i.e., transform the representation.
msf1 = MySpecialFrame(rep1, my_attr=1.*u.km)
msf2 = msf1.realize_frame(rep2)
assert msf1.data is not rep1 # Gets transformed to Cartesian.
assert msf2.data is not rep2
assert type(msf1.data) is CartesianRepresentation
assert type(msf2.data) is CartesianRepresentation
assert msf1.representation_type is CartesianRepresentation
assert msf2.representation_type is CartesianRepresentation
assert msf2.my_attr == msf1.my_attr
# And finally a test where the input is not transformed.
msf3 = MySpecialFrame(rep1, my_attr=1.*u.km,
representation_type='unitspherical')
msf4 = msf3.realize_frame(rep2)
assert msf3.data is rep1
assert msf4.data is not rep2
assert msf3.representation_type is UnitSphericalRepresentation
assert msf4.representation_type is CartesianRepresentation
assert msf4.my_attr == msf3.my_attr
@pytest.mark.skipif(not HAS_SCIPY, reason='No Scipy')
@pytest.mark.skipif(OLDER_SCIPY, reason='Scipy too old')
def test_regression_6347():
sc1 = SkyCoord([1, 2]*u.deg, [3, 4]*u.deg)
sc2 = SkyCoord([1.1, 2.1]*u.deg, [3.1, 4.1]*u.deg)
sc0 = sc1[:0]
idx1_10, idx2_10, d2d_10, d3d_10 = sc1.search_around_sky(sc2, 10*u.arcmin)
idx1_1, idx2_1, d2d_1, d3d_1 = sc1.search_around_sky(sc2, 1*u.arcmin)
idx1_0, idx2_0, d2d_0, d3d_0 = sc0.search_around_sky(sc2, 10*u.arcmin)
assert len(d2d_10) == 2
assert len(d2d_0) == 0
assert type(d2d_0) is type(d2d_10)
assert len(d2d_1) == 0
assert type(d2d_1) is type(d2d_10)
@pytest.mark.skipif(not HAS_SCIPY, reason='No Scipy')
@pytest.mark.skipif(OLDER_SCIPY, reason='Scipy too old')
def test_regression_6347_3d():
sc1 = SkyCoord([1, 2]*u.deg, [3, 4]*u.deg, [5, 6]*u.kpc)
sc2 = SkyCoord([1, 2]*u.deg, [3, 4]*u.deg, [5.1, 6.1]*u.kpc)
sc0 = sc1[:0]
idx1_10, idx2_10, d2d_10, d3d_10 = sc1.search_around_3d(sc2, 500*u.pc)
idx1_1, idx2_1, d2d_1, d3d_1 = sc1.search_around_3d(sc2, 50*u.pc)
idx1_0, idx2_0, d2d_0, d3d_0 = sc0.search_around_3d(sc2, 500*u.pc)
assert len(d2d_10) > 0
assert len(d2d_0) == 0
assert type(d2d_0) is type(d2d_10)
assert len(d2d_1) == 0
assert type(d2d_1) is type(d2d_10)
def test_regression_6300():
"""Check that importing old frame attribute names from astropy.coordinates
still works. See comments at end of #6300
"""
from astropy.utils.exceptions import AstropyDeprecationWarning
from astropy.coordinates import CartesianRepresentation
from astropy.coordinates import (TimeFrameAttribute, QuantityFrameAttribute,
CartesianRepresentationFrameAttribute)
with catch_warnings() as found_warnings:
attr = TimeFrameAttribute(default=Time("J2000"))
for w in found_warnings:
if issubclass(w.category, AstropyDeprecationWarning):
break
else:
assert False, "Deprecation warning not raised"
with catch_warnings() as found_warnings:
attr = QuantityFrameAttribute(default=5*u.km)
for w in found_warnings:
if issubclass(w.category, AstropyDeprecationWarning):
break
else:
assert False, "Deprecation warning not raised"
with catch_warnings() as found_warnings:
attr = CartesianRepresentationFrameAttribute(
default=CartesianRepresentation([5,6,7]*u.kpc))
for w in found_warnings:
if issubclass(w.category, AstropyDeprecationWarning):
break
else:
assert False, "Deprecation warning not raised"
@pytest.mark.remote_data
def test_gcrs_itrs_cartesian_repr():
# issue 6436: transformation failed if coordinate representation was
# Cartesian
gcrs = GCRS(CartesianRepresentation((859.07256, -4137.20368, 5295.56871),
unit='km'), representation_type='cartesian')
gcrs.transform_to(ITRS)
@pytest.mark.skipif('not HAS_YAML')
def test_regression_6446():
# this succeeds even before 6446:
sc1 = SkyCoord([1, 2], [3, 4], unit='deg')
t1 = Table([sc1])
sio1 = io.StringIO()
t1.write(sio1, format='ascii.ecsv')
# but this fails due to the 6446 bug
c1 = SkyCoord(1, 3, unit='deg')
c2 = SkyCoord(2, 4, unit='deg')
sc2 = SkyCoord([c1, c2])
t2 = Table([sc2])
sio2 = io.StringIO()
t2.write(sio2, format='ascii.ecsv')
assert sio1.getvalue() == sio2.getvalue()
def test_regression_6448():
"""
This tests the more narrow problem reported in 6446 that 6448 is meant to
fix. `test_regression_6446` also covers this, but this test is provided
so that this is still tested even if YAML isn't installed.
"""
sc1 = SkyCoord([1, 2], [3, 4], unit='deg')
# this should always succeed even prior to 6448
assert sc1.galcen_v_sun is None
c1 = SkyCoord(1, 3, unit='deg')
c2 = SkyCoord(2, 4, unit='deg')
sc2 = SkyCoord([c1, c2])
# without 6448 this fails
assert sc2.galcen_v_sun is None
def test_regression_6597():
frame_name = 'galactic'
c1 = SkyCoord(1, 3, unit='deg', frame=frame_name)
c2 = SkyCoord(2, 4, unit='deg', frame=frame_name)
sc1 = SkyCoord([c1, c2])
assert sc1.frame.name == frame_name
def test_regression_6597_2():
"""
This tests the more subtle flaw that #6597 indirectly uncovered: that even
in the case that the frames are ra/dec, they still might be the wrong *kind*
"""
frame = FK4(equinox='J1949')
c1 = SkyCoord(1, 3, unit='deg', frame=frame)
c2 = SkyCoord(2, 4, unit='deg', frame=frame)
sc1 = SkyCoord([c1, c2])
assert sc1.frame.name == frame.name
@pytest.mark.remote_data
def test_regression_6697():
"""
Test for regression of a bug in get_gcrs_posvel that introduced errors at the 1m/s level.
Comparison data is derived from calculation in PINT
https://github.com/nanograv/PINT/blob/master/pint/erfautils.py
"""
pint_vels = CartesianRepresentation(*(348.63632871, -212.31704928, -0.60154936), unit=u.m/u.s)
location = EarthLocation(*(5327448.9957829, -1718665.73869569, 3051566.90295403), unit=u.m)
t = Time(2458036.161966612, format='jd')
obsgeopos, obsgeovel = location.get_gcrs_posvel(t)
delta = (obsgeovel-pint_vels).norm()
assert delta < 1*u.cm/u.s
def test_regression_8138():
sc = SkyCoord(1*u.deg, 2*u.deg)
newframe = GCRS()
sc2 = sc.transform_to(newframe)
assert newframe.is_equivalent_frame(sc2.frame)
def test_regression_8276():
from astropy.coordinates import baseframe
with pytest.raises(TypeError) as excinfo:
class MyFrame(BaseCoordinateFrame):
a = QuantityAttribute(unit=u.m)
# note that the remainder of this with clause does not get executed
# because an exception is raised here. A future PR is planned to
# allow the default to be left off, after which the rest of this
# test will get executed, so it is being left in place. See
# https://github.com/astropy/astropy/pull/8300 for more info
# we save the transform graph so that it doesn't acidentally mess with other tests
old_transform_graph = baseframe.frame_transform_graph
try:
baseframe.frame_transform_graph = copy.copy(baseframe.frame_transform_graph)
# as reported in 8276, this fails right here because registering the
# transform tries to create a frame attribute
@baseframe.frame_transform_graph.transform(FunctionTransform, MyFrame, AltAz)
def trans(my_frame_coord, altaz_frame):
pass
# should also be able to *create* the Frame at this point
MyFrame()
finally:
baseframe.frame_transform_graph = old_transform_graph
assert "missing 1 required positional argument: 'default'" in str(excinfo.value)
|
c597a5ff79722db1dd69c07d97a2b5764a331626652308789207ea1878a76c4b | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import pytest
import numpy as np
from numpy import testing as npt
from astropy.tests.helper import assert_quantity_allclose as assert_allclose
from astropy import units as u
from astropy.utils import minversion
from astropy.coordinates import matching
"""
These are the tests for coordinate matching.
Note that this requires scipy.
"""
try:
import scipy
HAS_SCIPY = True
except ImportError:
HAS_SCIPY = False
if HAS_SCIPY and minversion(scipy, '0.12.0', inclusive=False):
OLDER_SCIPY = False
else:
OLDER_SCIPY = True
@pytest.mark.skipif(str('not HAS_SCIPY'))
def test_matching_function():
from astropy.coordinates import ICRS
from astropy.coordinates.matching import match_coordinates_3d
# this only uses match_coordinates_3d because that's the actual implementation
cmatch = ICRS([4, 2.1]*u.degree, [0, 0]*u.degree)
ccatalog = ICRS([1, 2, 3, 4]*u.degree, [0, 0, 0, 0]*u.degree)
idx, d2d, d3d = match_coordinates_3d(cmatch, ccatalog)
npt.assert_array_equal(idx, [3, 1])
npt.assert_array_almost_equal(d2d.degree, [0, 0.1])
assert d3d.value[0] == 0
idx, d2d, d3d = match_coordinates_3d(cmatch, ccatalog, nthneighbor=2)
assert np.all(idx == 2)
npt.assert_array_almost_equal(d2d.degree, [1, 0.9])
npt.assert_array_less(d3d.value, 0.02)
@pytest.mark.skipif(str('not HAS_SCIPY'))
def test_matching_function_3d_and_sky():
from astropy.coordinates import ICRS
from astropy.coordinates.matching import match_coordinates_3d, match_coordinates_sky
cmatch = ICRS([4, 2.1]*u.degree, [0, 0]*u.degree, distance=[1, 5] * u.kpc)
ccatalog = ICRS([1, 2, 3, 4]*u.degree, [0, 0, 0, 0]*u.degree, distance=[1, 1, 1, 5] * u.kpc)
idx, d2d, d3d = match_coordinates_3d(cmatch, ccatalog)
npt.assert_array_equal(idx, [2, 3])
assert_allclose(d2d, [1, 1.9] * u.deg)
assert np.abs(d3d[0].to_value(u.kpc) - np.radians(1)) < 1e-6
assert np.abs(d3d[1].to_value(u.kpc) - 5*np.radians(1.9)) < 1e-5
idx, d2d, d3d = match_coordinates_sky(cmatch, ccatalog)
npt.assert_array_equal(idx, [3, 1])
assert_allclose(d2d, [0, 0.1] * u.deg)
assert_allclose(d3d, [4, 4.0000019] * u.kpc)
@pytest.mark.parametrize('functocheck, args, defaultkdtname, bothsaved',
[(matching.match_coordinates_3d, [], 'kdtree_3d', False),
(matching.match_coordinates_sky, [], 'kdtree_sky', False),
(matching.search_around_3d, [1*u.kpc], 'kdtree_3d', True),
(matching.search_around_sky, [1*u.deg], 'kdtree_sky', False)
])
@pytest.mark.skipif(str('not HAS_SCIPY'))
def test_kdtree_storage(functocheck, args, defaultkdtname, bothsaved):
from astropy.coordinates import ICRS
def make_scs():
cmatch = ICRS([4, 2.1]*u.degree, [0, 0]*u.degree, distance=[1, 2]*u.kpc)
ccatalog = ICRS([1, 2, 3, 4]*u.degree, [0, 0, 0, 0]*u.degree, distance=[1, 2, 3, 4]*u.kpc)
return cmatch, ccatalog
cmatch, ccatalog = make_scs()
functocheck(cmatch, ccatalog, *args, storekdtree=False)
assert 'kdtree' not in ccatalog.cache
assert defaultkdtname not in ccatalog.cache
cmatch, ccatalog = make_scs()
functocheck(cmatch, ccatalog, *args)
assert defaultkdtname in ccatalog.cache
assert 'kdtree' not in ccatalog.cache
cmatch, ccatalog = make_scs()
functocheck(cmatch, ccatalog, *args, storekdtree=True)
assert 'kdtree' in ccatalog.cache
assert defaultkdtname not in ccatalog.cache
cmatch, ccatalog = make_scs()
assert 'tislit_cheese' not in ccatalog.cache
functocheck(cmatch, ccatalog, *args, storekdtree='tislit_cheese')
assert 'tislit_cheese' in ccatalog.cache
assert defaultkdtname not in ccatalog.cache
assert 'kdtree' not in ccatalog.cache
if bothsaved:
assert 'tislit_cheese' in cmatch.cache
assert defaultkdtname not in cmatch.cache
assert 'kdtree' not in cmatch.cache
else:
assert 'tislit_cheese' not in cmatch.cache
# now a bit of a hacky trick to make sure it at least tries to *use* it
ccatalog.cache['tislit_cheese'] = 1
cmatch.cache['tislit_cheese'] = 1
with pytest.raises(TypeError) as e:
functocheck(cmatch, ccatalog, *args, storekdtree='tislit_cheese')
assert 'KD' in e.value.args[0]
@pytest.mark.skipif(str('not HAS_SCIPY'))
def test_python_kdtree(monkeypatch):
from astropy.coordinates import ICRS
cmatch = ICRS([4, 2.1]*u.degree, [0, 0]*u.degree, distance=[1, 2]*u.kpc)
ccatalog = ICRS([1, 2, 3, 4]*u.degree, [0, 0, 0, 0]*u.degree, distance=[1, 2, 3, 4]*u.kpc)
monkeypatch.delattr("scipy.spatial.cKDTree")
with pytest.warns(UserWarning, match='C-based KD tree not found'):
matching.match_coordinates_sky(cmatch, ccatalog)
@pytest.mark.skipif(str('not HAS_SCIPY'))
def test_matching_method():
from astropy.coordinates import ICRS, SkyCoord
from astropy.utils import NumpyRNGContext
from astropy.coordinates.matching import match_coordinates_3d, match_coordinates_sky
with NumpyRNGContext(987654321):
cmatch = ICRS(np.random.rand(20) * 360.*u.degree,
(np.random.rand(20) * 180. - 90.)*u.degree)
ccatalog = ICRS(np.random.rand(100) * 360. * u.degree,
(np.random.rand(100) * 180. - 90.)*u.degree)
idx1, d2d1, d3d1 = SkyCoord(cmatch).match_to_catalog_3d(ccatalog)
idx2, d2d2, d3d2 = match_coordinates_3d(cmatch, ccatalog)
npt.assert_array_equal(idx1, idx2)
assert_allclose(d2d1, d2d2)
assert_allclose(d3d1, d3d2)
# should be the same as above because there's no distance, but just make sure this method works
idx1, d2d1, d3d1 = SkyCoord(cmatch).match_to_catalog_sky(ccatalog)
idx2, d2d2, d3d2 = match_coordinates_sky(cmatch, ccatalog)
npt.assert_array_equal(idx1, idx2)
assert_allclose(d2d1, d2d2)
assert_allclose(d3d1, d3d2)
assert len(idx1) == len(d2d1) == len(d3d1) == 20
@pytest.mark.skipif(str('not HAS_SCIPY'))
@pytest.mark.skipif(str('OLDER_SCIPY'))
def test_search_around():
from astropy.coordinates import ICRS, SkyCoord
from astropy.coordinates.matching import search_around_sky, search_around_3d
coo1 = ICRS([4, 2.1]*u.degree, [0, 0]*u.degree, distance=[1, 5] * u.kpc)
coo2 = ICRS([1, 2, 3, 4]*u.degree, [0, 0, 0, 0]*u.degree, distance=[1, 1, 1, 5] * u.kpc)
idx1_1deg, idx2_1deg, d2d_1deg, d3d_1deg = search_around_sky(coo1, coo2, 1.01*u.deg)
idx1_0p05deg, idx2_0p05deg, d2d_0p05deg, d3d_0p05deg = search_around_sky(coo1, coo2, 0.05*u.deg)
assert list(zip(idx1_1deg, idx2_1deg)) == [(0, 2), (0, 3), (1, 1), (1, 2)]
assert d2d_1deg[0] == 1.0*u.deg
assert_allclose(d2d_1deg, [1, 0, .1, .9]*u.deg)
assert list(zip(idx1_0p05deg, idx2_0p05deg)) == [(0, 3)]
idx1_1kpc, idx2_1kpc, d2d_1kpc, d3d_1kpc = search_around_3d(coo1, coo2, 1*u.kpc)
idx1_sm, idx2_sm, d2d_sm, d3d_sm = search_around_3d(coo1, coo2, 0.05*u.kpc)
assert list(zip(idx1_1kpc, idx2_1kpc)) == [(0, 0), (0, 1), (0, 2), (1, 3)]
assert list(zip(idx1_sm, idx2_sm)) == [(0, 1), (0, 2)]
assert_allclose(d2d_sm, [2, 1]*u.deg)
# Test for the non-matches, #4877
coo1 = ICRS([4.1, 2.1]*u.degree, [0, 0]*u.degree, distance=[1, 5] * u.kpc)
idx1, idx2, d2d, d3d = search_around_sky(coo1, coo2, 1*u.arcsec)
assert idx1.size == idx2.size == d2d.size == d3d.size == 0
assert idx1.dtype == idx2.dtype == np.int
assert d2d.unit == u.deg
assert d3d.unit == u.kpc
idx1, idx2, d2d, d3d = search_around_3d(coo1, coo2, 1*u.m)
assert idx1.size == idx2.size == d2d.size == d3d.size == 0
assert idx1.dtype == idx2.dtype == np.int
assert d2d.unit == u.deg
assert d3d.unit == u.kpc
# Test when one or both of the coordinate arrays is empty, #4875
empty = ICRS(ra=[] * u.degree, dec=[] * u.degree, distance=[] * u.kpc)
idx1, idx2, d2d, d3d = search_around_sky(empty, coo2, 1*u.arcsec)
assert idx1.size == idx2.size == d2d.size == d3d.size == 0
assert idx1.dtype == idx2.dtype == np.int
assert d2d.unit == u.deg
assert d3d.unit == u.kpc
idx1, idx2, d2d, d3d = search_around_sky(coo1, empty, 1*u.arcsec)
assert idx1.size == idx2.size == d2d.size == d3d.size == 0
assert idx1.dtype == idx2.dtype == np.int
assert d2d.unit == u.deg
assert d3d.unit == u.kpc
empty = ICRS(ra=[] * u.degree, dec=[] * u.degree, distance=[] * u.kpc)
idx1, idx2, d2d, d3d = search_around_sky(empty, empty[:], 1*u.arcsec)
assert idx1.size == idx2.size == d2d.size == d3d.size == 0
assert idx1.dtype == idx2.dtype == np.int
assert d2d.unit == u.deg
assert d3d.unit == u.kpc
idx1, idx2, d2d, d3d = search_around_3d(empty, coo2, 1*u.m)
assert idx1.size == idx2.size == d2d.size == d3d.size == 0
assert idx1.dtype == idx2.dtype == np.int
assert d2d.unit == u.deg
assert d3d.unit == u.kpc
idx1, idx2, d2d, d3d = search_around_3d(coo1, empty, 1*u.m)
assert idx1.size == idx2.size == d2d.size == d3d.size == 0
assert idx1.dtype == idx2.dtype == np.int
assert d2d.unit == u.deg
assert d3d.unit == u.kpc
idx1, idx2, d2d, d3d = search_around_3d(empty, empty[:], 1*u.m)
assert idx1.size == idx2.size == d2d.size == d3d.size == 0
assert idx1.dtype == idx2.dtype == np.int
assert d2d.unit == u.deg
assert d3d.unit == u.kpc
# Test that input without distance units results in a
# 'dimensionless_unscaled' unit
cempty = SkyCoord(ra=[], dec=[], unit=u.deg)
idx1, idx2, d2d, d3d = search_around_3d(cempty, cempty[:], 1*u.m)
assert d2d.unit == u.deg
assert d3d.unit == u.dimensionless_unscaled
idx1, idx2, d2d, d3d = search_around_sky(cempty, cempty[:], 1*u.m)
assert d2d.unit == u.deg
assert d3d.unit == u.dimensionless_unscaled
@pytest.mark.skipif(str('not HAS_SCIPY'))
@pytest.mark.skipif(str('OLDER_SCIPY'))
def test_search_around_scalar():
from astropy.coordinates import SkyCoord, Angle
cat = SkyCoord([1, 2, 3], [-30, 45, 8], unit="deg")
target = SkyCoord('1.1 -30.1', unit="deg")
with pytest.raises(ValueError) as excinfo:
cat.search_around_sky(target, Angle('2d'))
# make sure the error message is *specific* to search_around_sky rather than
# generic as reported in #3359
assert 'search_around_sky' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
cat.search_around_3d(target, Angle('2d'))
assert 'search_around_3d' in str(excinfo.value)
@pytest.mark.skipif(str('not HAS_SCIPY'))
@pytest.mark.skipif(str('OLDER_SCIPY'))
def test_match_catalog_empty():
from astropy.coordinates import SkyCoord
sc1 = SkyCoord(1, 2, unit="deg")
cat0 = SkyCoord([], [], unit="deg")
cat1 = SkyCoord([1.1], [2.1], unit="deg")
cat2 = SkyCoord([1.1, 3], [2.1, 5], unit="deg")
sc1.match_to_catalog_sky(cat2)
sc1.match_to_catalog_3d(cat2)
sc1.match_to_catalog_sky(cat1)
sc1.match_to_catalog_3d(cat1)
with pytest.raises(ValueError) as excinfo:
sc1.match_to_catalog_sky(cat1[0])
assert 'catalog' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
sc1.match_to_catalog_3d(cat1[0])
assert 'catalog' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
sc1.match_to_catalog_sky(cat0)
assert 'catalog' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
sc1.match_to_catalog_3d(cat0)
assert 'catalog' in str(excinfo.value)
|
ef9b7cea8bb6b05dd9c74ce22a5c155c1faf118a6a36581d55db8d1883c670e8 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import pytest
import numpy as np
from numpy import testing as npt
from astropy import units as u
from astropy.time import Time
from astropy.tests.helper import assert_quantity_allclose as assert_allclose
from astropy.coordinates import (Angle, ICRS, FK4, FK5, Galactic, SkyCoord,
CartesianRepresentation)
from astropy.coordinates.angle_utilities import dms_to_degrees, hms_to_hours
def test_angle_arrays():
"""
Test arrays values with Angle objects.
"""
# Tests incomplete
a1 = Angle([0, 45, 90, 180, 270, 360, 720.], unit=u.degree)
npt.assert_almost_equal([0., 45., 90., 180., 270., 360., 720.], a1.value)
a2 = Angle(np.array([-90, -45, 0, 45, 90, 180, 270, 360]), unit=u.degree)
npt.assert_almost_equal([-90, -45, 0, 45, 90, 180, 270, 360],
a2.value)
a3 = Angle(["12 degrees", "3 hours", "5 deg", "4rad"])
npt.assert_almost_equal([12., 45., 5., 229.18311805],
a3.value)
assert a3.unit == u.degree
a4 = Angle(["12 degrees", "3 hours", "5 deg", "4rad"], u.radian)
npt.assert_almost_equal(a4.degree, a3.value)
assert a4.unit == u.radian
a5 = Angle([0, 45, 90, 180, 270, 360], unit=u.degree)
a6 = a5.sum()
npt.assert_almost_equal(a6.value, 945.0)
assert a6.unit is u.degree
with pytest.raises(TypeError):
# Arrays where the elements are Angle objects are not supported -- it's
# really tricky to do correctly, if at all, due to the possibility of
# nesting.
a7 = Angle([a1, a2, a3], unit=u.degree)
a8 = Angle(["04:02:02", "03:02:01", "06:02:01"], unit=u.degree)
npt.assert_almost_equal(a8.value, [4.03388889, 3.03361111, 6.03361111])
a9 = Angle(np.array(["04:02:02", "03:02:01", "06:02:01"]), unit=u.degree)
npt.assert_almost_equal(a9.value, a8.value)
with pytest.raises(u.UnitsError):
a10 = Angle(["04:02:02", "03:02:01", "06:02:01"])
def test_dms():
a1 = Angle([0, 45.5, -45.5], unit=u.degree)
d, m, s = a1.dms
npt.assert_almost_equal(d, [0, 45, -45])
npt.assert_almost_equal(m, [0, 30, -30])
npt.assert_almost_equal(s, [0, 0, -0])
dms = a1.dms
degrees = dms_to_degrees(*dms)
npt.assert_almost_equal(a1.degree, degrees)
a2 = Angle(dms, unit=u.degree)
npt.assert_almost_equal(a2.radian, a1.radian)
def test_hms():
a1 = Angle([0, 11.5, -11.5], unit=u.hour)
h, m, s = a1.hms
npt.assert_almost_equal(h, [0, 11, -11])
npt.assert_almost_equal(m, [0, 30, -30])
npt.assert_almost_equal(s, [0, 0, -0])
hms = a1.hms
hours = hms_to_hours(*hms)
npt.assert_almost_equal(a1.hour, hours)
a2 = Angle(hms, unit=u.hour)
npt.assert_almost_equal(a2.radian, a1.radian)
def test_array_coordinates_creation():
"""
Test creating coordinates from arrays.
"""
c = ICRS(np.array([1, 2])*u.deg, np.array([3, 4])*u.deg)
assert not c.ra.isscalar
with pytest.raises(ValueError):
c = ICRS(np.array([1, 2])*u.deg, np.array([3, 4, 5])*u.deg)
with pytest.raises(ValueError):
c = ICRS(np.array([1, 2, 4, 5])*u.deg, np.array([[3, 4], [5, 6]])*u.deg)
# make sure cartesian initialization also works
cart = CartesianRepresentation(x=[1., 2.]*u.kpc, y=[3., 4.]*u.kpc, z=[5., 6.]*u.kpc)
c = ICRS(cart)
# also ensure strings can be arrays
c = SkyCoord(['1d0m0s', '2h02m00.3s'], ['3d', '4d'])
# but invalid strings cannot
with pytest.raises(ValueError):
c = SkyCoord(Angle(['10m0s', '2h02m00.3s']), Angle(['3d', '4d']))
with pytest.raises(ValueError):
c = SkyCoord(Angle(['1d0m0s', '2h02m00.3s']), Angle(['3x', '4d']))
def test_array_coordinates_distances():
"""
Test creating coordinates from arrays and distances.
"""
# correct way
ICRS(ra=np.array([1, 2])*u.deg, dec=np.array([3, 4])*u.deg, distance=[.1, .2] * u.kpc)
with pytest.raises(ValueError):
# scalar distance and mismatched array coordinates
ICRS(ra=np.array([1, 2, 3])*u.deg, dec=np.array([[3, 4], [5, 6]])*u.deg, distance=2. * u.kpc)
with pytest.raises(ValueError):
# more distance values than coordinates
ICRS(ra=np.array([1, 2])*u.deg, dec=np.array([3, 4])*u.deg, distance=[.1, .2, 3.] * u.kpc)
@pytest.mark.parametrize(('arrshape', 'distance'), [((2, ), None), ((4, 2, 5), None), ((4, 2, 5), 2 * u.kpc)])
def test_array_coordinates_transformations(arrshape, distance):
"""
Test transformation on coordinates with array content (first length-2 1D, then a 3D array)
"""
# M31 coordinates from test_transformations
raarr = np.ones(arrshape) * 10.6847929
decarr = np.ones(arrshape) * 41.2690650
if distance is not None:
distance = np.ones(arrshape) * distance
print(raarr, decarr, distance)
c = ICRS(ra=raarr*u.deg, dec=decarr*u.deg, distance=distance)
g = c.transform_to(Galactic)
assert g.l.shape == arrshape
npt.assert_array_almost_equal(g.l.degree, 121.17440967)
npt.assert_array_almost_equal(g.b.degree, -21.57299631)
if distance is not None:
assert g.distance.unit == c.distance.unit
# now make sure round-tripping works through FK5
c2 = c.transform_to(FK5).transform_to(ICRS)
npt.assert_array_almost_equal(c.ra.radian, c2.ra.radian)
npt.assert_array_almost_equal(c.dec.radian, c2.dec.radian)
assert c2.ra.shape == arrshape
if distance is not None:
assert c2.distance.unit == c.distance.unit
# also make sure it's possible to get to FK4, which uses a direct transform function.
fk4 = c.transform_to(FK4)
npt.assert_array_almost_equal(fk4.ra.degree, 10.0004, decimal=4)
npt.assert_array_almost_equal(fk4.dec.degree, 40.9953, decimal=4)
assert fk4.ra.shape == arrshape
if distance is not None:
assert fk4.distance.unit == c.distance.unit
# now check the reverse transforms run
cfk4 = fk4.transform_to(ICRS)
assert cfk4.ra.shape == arrshape
def test_array_precession():
"""
Ensures that FK5 coordinates as arrays precess their equinoxes
"""
j2000 = Time('J2000')
j1975 = Time('J1975')
fk5 = FK5([1, 1.1]*u.radian, [0.5, 0.6]*u.radian)
assert fk5.equinox.jyear == j2000.jyear
fk5_2 = fk5.transform_to(FK5(equinox=j1975))
assert fk5_2.equinox.jyear == j1975.jyear
npt.assert_array_less(0.05, np.abs(fk5.ra.degree - fk5_2.ra.degree))
npt.assert_array_less(0.05, np.abs(fk5.dec.degree - fk5_2.dec.degree))
def test_array_separation():
c1 = ICRS([0, 0]*u.deg, [0, 0]*u.deg)
c2 = ICRS([1, 2]*u.deg, [0, 0]*u.deg)
npt.assert_array_almost_equal(c1.separation(c2).degree, [1, 2])
c3 = ICRS([0, 3.]*u.deg, [0., 0]*u.deg, distance=[1, 1.] * u.kpc)
c4 = ICRS([1, 1.]*u.deg, [0., 0]*u.deg, distance=[1, 1.] * u.kpc)
# the 3-1 separation should be twice the 0-1 separation, but not *exactly* the same
sep = c3.separation_3d(c4)
sepdiff = sep[1] - (2 * sep[0])
assert abs(sepdiff.value) < 1e-5
assert sepdiff != 0
def test_array_indexing():
ra = np.linspace(0, 360, 10)
dec = np.linspace(-90, 90, 10)
j1975 = Time(1975, format='jyear')
c1 = FK5(ra*u.deg, dec*u.deg, equinox=j1975)
c2 = c1[4]
assert c2.ra.degree == 160
assert c2.dec.degree == -10
c3 = c1[2:5]
assert_allclose(c3.ra, [80, 120, 160] * u.deg)
assert_allclose(c3.dec, [-50, -30, -10] * u.deg)
c4 = c1[np.array([2, 5, 8])]
assert_allclose(c4.ra, [80, 200, 320] * u.deg)
assert_allclose(c4.dec, [-50, 10, 70] * u.deg)
# now make sure the equinox is preserved
assert c2.equinox == c1.equinox
assert c3.equinox == c1.equinox
assert c4.equinox == c1.equinox
def test_array_len():
input_length = [1, 5]
for length in input_length:
ra = np.linspace(0, 360, length)
dec = np.linspace(0, 90, length)
c = ICRS(ra*u.deg, dec*u.deg)
assert len(c) == length
assert c.shape == (length,)
with pytest.raises(TypeError):
c = ICRS(0*u.deg, 0*u.deg)
len(c)
assert c.shape == tuple()
def test_array_eq():
c1 = ICRS([1, 2]*u.deg, [3, 4]*u.deg)
c2 = ICRS([1, 2]*u.deg, [3, 5]*u.deg)
c3 = ICRS([1, 3]*u.deg, [3, 4]*u.deg)
c4 = ICRS([1, 2]*u.deg, [3, 4.2]*u.deg)
assert c1 == c1
assert c1 != c2
assert c1 != c3
assert c1 != c4
|
46cf8f4ff04c32c667f8fb55834dae7ce2e40b79c1fcc1c9cc8edb6c80784e79 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from copy import deepcopy
from collections import OrderedDict
import pytest
import numpy as np
from numpy.testing import assert_allclose
from astropy import units as u
from astropy.tests.helper import (assert_quantity_allclose as
assert_allclose_quantity, catch_warnings)
from astropy.utils import isiterable
from astropy.utils.compat import NUMPY_LT_1_14
from astropy.utils.exceptions import AstropyDeprecationWarning
from astropy.coordinates.angles import Longitude, Latitude, Angle
from astropy.coordinates.distances import Distance
from astropy.coordinates.representation import (REPRESENTATION_CLASSES,
DIFFERENTIAL_CLASSES,
BaseRepresentation,
SphericalRepresentation,
UnitSphericalRepresentation,
SphericalCosLatDifferential,
CartesianRepresentation,
CylindricalRepresentation,
PhysicsSphericalRepresentation,
CartesianDifferential,
SphericalDifferential,
_combine_xyz)
# Preserve the original REPRESENTATION_CLASSES dict so that importing
# the test file doesn't add a persistent test subclass (LogDRepresentation)
def setup_function(func):
func.REPRESENTATION_CLASSES_ORIG = deepcopy(REPRESENTATION_CLASSES)
def teardown_function(func):
REPRESENTATION_CLASSES.clear()
REPRESENTATION_CLASSES.update(func.REPRESENTATION_CLASSES_ORIG)
class TestSphericalRepresentation:
def test_name(self):
assert SphericalRepresentation.get_name() == 'spherical'
assert SphericalRepresentation.get_name() in REPRESENTATION_CLASSES
def test_empty_init(self):
with pytest.raises(TypeError) as exc:
s = SphericalRepresentation()
def test_init_quantity(self):
s3 = SphericalRepresentation(lon=8 * u.hourangle, lat=5 * u.deg, distance=10 * u.kpc)
assert s3.lon == 8. * u.hourangle
assert s3.lat == 5. * u.deg
assert s3.distance == 10 * u.kpc
assert isinstance(s3.lon, Longitude)
assert isinstance(s3.lat, Latitude)
assert isinstance(s3.distance, Distance)
def test_init_lonlat(self):
s2 = SphericalRepresentation(Longitude(8, u.hour),
Latitude(5, u.deg),
Distance(10, u.kpc))
assert s2.lon == 8. * u.hourangle
assert s2.lat == 5. * u.deg
assert s2.distance == 10. * u.kpc
assert isinstance(s2.lon, Longitude)
assert isinstance(s2.lat, Latitude)
assert isinstance(s2.distance, Distance)
# also test that wrap_angle is preserved
s3 = SphericalRepresentation(Longitude(-90, u.degree,
wrap_angle=180*u.degree),
Latitude(-45, u.degree),
Distance(1., u.Rsun))
assert s3.lon == -90. * u.degree
assert s3.lon.wrap_angle == 180 * u.degree
def test_init_array(self):
s1 = SphericalRepresentation(lon=[8, 9] * u.hourangle,
lat=[5, 6] * u.deg,
distance=[1, 2] * u.kpc)
assert_allclose(s1.lon.degree, [120, 135])
assert_allclose(s1.lat.degree, [5, 6])
assert_allclose(s1.distance.kpc, [1, 2])
assert isinstance(s1.lon, Longitude)
assert isinstance(s1.lat, Latitude)
assert isinstance(s1.distance, Distance)
def test_init_array_nocopy(self):
lon = Longitude([8, 9] * u.hourangle)
lat = Latitude([5, 6] * u.deg)
distance = Distance([1, 2] * u.kpc)
s1 = SphericalRepresentation(lon=lon, lat=lat, distance=distance, copy=False)
lon[:] = [1, 2] * u.rad
lat[:] = [3, 4] * u.arcmin
distance[:] = [8, 9] * u.Mpc
assert_allclose_quantity(lon, s1.lon)
assert_allclose_quantity(lat, s1.lat)
assert_allclose_quantity(distance, s1.distance)
def test_init_float32_array(self):
"""Regression test against #2983"""
lon = Longitude(np.float32([1., 2.]), u.degree)
lat = Latitude(np.float32([3., 4.]), u.degree)
s1 = UnitSphericalRepresentation(lon=lon, lat=lat, copy=False)
assert s1.lon.dtype == np.float32
assert s1.lat.dtype == np.float32
assert s1._values['lon'].dtype == np.float32
assert s1._values['lat'].dtype == np.float32
def test_reprobj(self):
s1 = SphericalRepresentation(lon=8 * u.hourangle, lat=5 * u.deg, distance=10 * u.kpc)
s2 = SphericalRepresentation.from_representation(s1)
assert_allclose_quantity(s2.lon, 8. * u.hourangle)
assert_allclose_quantity(s2.lat, 5. * u.deg)
assert_allclose_quantity(s2.distance, 10 * u.kpc)
def test_broadcasting(self):
s1 = SphericalRepresentation(lon=[8, 9] * u.hourangle,
lat=[5, 6] * u.deg,
distance=10 * u.kpc)
assert_allclose_quantity(s1.lon, [120, 135] * u.degree)
assert_allclose_quantity(s1.lat, [5, 6] * u.degree)
assert_allclose_quantity(s1.distance, [10, 10] * u.kpc)
def test_broadcasting_mismatch(self):
with pytest.raises(ValueError) as exc:
s1 = SphericalRepresentation(lon=[8, 9, 10] * u.hourangle,
lat=[5, 6] * u.deg,
distance=[1, 2] * u.kpc)
assert exc.value.args[0] == "Input parameters lon, lat, and distance cannot be broadcast"
def test_readonly(self):
s1 = SphericalRepresentation(lon=8 * u.hourangle,
lat=5 * u.deg,
distance=1. * u.kpc)
with pytest.raises(AttributeError):
s1.lon = 1. * u.deg
with pytest.raises(AttributeError):
s1.lat = 1. * u.deg
with pytest.raises(AttributeError):
s1.distance = 1. * u.kpc
def test_getitem_len_iterable(self):
s = SphericalRepresentation(lon=np.arange(10) * u.deg,
lat=-np.arange(10) * u.deg,
distance=1 * u.kpc)
s_slc = s[2:8:2]
assert_allclose_quantity(s_slc.lon, [2, 4, 6] * u.deg)
assert_allclose_quantity(s_slc.lat, [-2, -4, -6] * u.deg)
assert_allclose_quantity(s_slc.distance, [1, 1, 1] * u.kpc)
assert len(s) == 10
assert isiterable(s)
def test_getitem_len_iterable_scalar(self):
s = SphericalRepresentation(lon=1 * u.deg,
lat=-2 * u.deg,
distance=3 * u.kpc)
with pytest.raises(TypeError):
s_slc = s[0]
with pytest.raises(TypeError):
len(s)
assert not isiterable(s)
def test_nan_distance(self):
""" This is a regression test: calling represent_as() and passing in the
same class as the object shouldn't round-trip through cartesian.
"""
sph = SphericalRepresentation(1*u.deg, 2*u.deg, np.nan*u.kpc)
new_sph = sph.represent_as(SphericalRepresentation)
assert_allclose_quantity(new_sph.lon, sph.lon)
assert_allclose_quantity(new_sph.lat, sph.lat)
dif = SphericalCosLatDifferential(1*u.mas/u.yr, 2*u.mas/u.yr,
3*u.km/u.s)
sph = sph.with_differentials(dif)
new_sph = sph.represent_as(SphericalRepresentation)
assert_allclose_quantity(new_sph.lon, sph.lon)
assert_allclose_quantity(new_sph.lat, sph.lat)
class TestUnitSphericalRepresentation:
def test_name(self):
assert UnitSphericalRepresentation.get_name() == 'unitspherical'
assert UnitSphericalRepresentation.get_name() in REPRESENTATION_CLASSES
def test_empty_init(self):
with pytest.raises(TypeError) as exc:
s = UnitSphericalRepresentation()
def test_init_quantity(self):
s3 = UnitSphericalRepresentation(lon=8 * u.hourangle, lat=5 * u.deg)
assert s3.lon == 8. * u.hourangle
assert s3.lat == 5. * u.deg
assert isinstance(s3.lon, Longitude)
assert isinstance(s3.lat, Latitude)
def test_init_lonlat(self):
s2 = UnitSphericalRepresentation(Longitude(8, u.hour),
Latitude(5, u.deg))
assert s2.lon == 8. * u.hourangle
assert s2.lat == 5. * u.deg
assert isinstance(s2.lon, Longitude)
assert isinstance(s2.lat, Latitude)
def test_init_array(self):
s1 = UnitSphericalRepresentation(lon=[8, 9] * u.hourangle,
lat=[5, 6] * u.deg)
assert_allclose(s1.lon.degree, [120, 135])
assert_allclose(s1.lat.degree, [5, 6])
assert isinstance(s1.lon, Longitude)
assert isinstance(s1.lat, Latitude)
def test_init_array_nocopy(self):
lon = Longitude([8, 9] * u.hourangle)
lat = Latitude([5, 6] * u.deg)
s1 = UnitSphericalRepresentation(lon=lon, lat=lat, copy=False)
lon[:] = [1, 2] * u.rad
lat[:] = [3, 4] * u.arcmin
assert_allclose_quantity(lon, s1.lon)
assert_allclose_quantity(lat, s1.lat)
def test_reprobj(self):
s1 = UnitSphericalRepresentation(lon=8 * u.hourangle, lat=5 * u.deg)
s2 = UnitSphericalRepresentation.from_representation(s1)
assert_allclose_quantity(s2.lon, 8. * u.hourangle)
assert_allclose_quantity(s2.lat, 5. * u.deg)
def test_broadcasting(self):
s1 = UnitSphericalRepresentation(lon=[8, 9] * u.hourangle,
lat=[5, 6] * u.deg)
assert_allclose_quantity(s1.lon, [120, 135] * u.degree)
assert_allclose_quantity(s1.lat, [5, 6] * u.degree)
def test_broadcasting_mismatch(self):
with pytest.raises(ValueError) as exc:
s1 = UnitSphericalRepresentation(lon=[8, 9, 10] * u.hourangle,
lat=[5, 6] * u.deg)
assert exc.value.args[0] == "Input parameters lon and lat cannot be broadcast"
def test_readonly(self):
s1 = UnitSphericalRepresentation(lon=8 * u.hourangle,
lat=5 * u.deg)
with pytest.raises(AttributeError):
s1.lon = 1. * u.deg
with pytest.raises(AttributeError):
s1.lat = 1. * u.deg
def test_getitem(self):
s = UnitSphericalRepresentation(lon=np.arange(10) * u.deg,
lat=-np.arange(10) * u.deg)
s_slc = s[2:8:2]
assert_allclose_quantity(s_slc.lon, [2, 4, 6] * u.deg)
assert_allclose_quantity(s_slc.lat, [-2, -4, -6] * u.deg)
def test_getitem_scalar(self):
s = UnitSphericalRepresentation(lon=1 * u.deg,
lat=-2 * u.deg)
with pytest.raises(TypeError):
s_slc = s[0]
class TestPhysicsSphericalRepresentation:
def test_name(self):
assert PhysicsSphericalRepresentation.get_name() == 'physicsspherical'
assert PhysicsSphericalRepresentation.get_name() in REPRESENTATION_CLASSES
def test_empty_init(self):
with pytest.raises(TypeError) as exc:
s = PhysicsSphericalRepresentation()
def test_init_quantity(self):
s3 = PhysicsSphericalRepresentation(phi=8 * u.hourangle, theta=5 * u.deg, r=10 * u.kpc)
assert s3.phi == 8. * u.hourangle
assert s3.theta == 5. * u.deg
assert s3.r == 10 * u.kpc
assert isinstance(s3.phi, Angle)
assert isinstance(s3.theta, Angle)
assert isinstance(s3.r, Distance)
def test_init_phitheta(self):
s2 = PhysicsSphericalRepresentation(Angle(8, u.hour),
Angle(5, u.deg),
Distance(10, u.kpc))
assert s2.phi == 8. * u.hourangle
assert s2.theta == 5. * u.deg
assert s2.r == 10. * u.kpc
assert isinstance(s2.phi, Angle)
assert isinstance(s2.theta, Angle)
assert isinstance(s2.r, Distance)
def test_init_array(self):
s1 = PhysicsSphericalRepresentation(phi=[8, 9] * u.hourangle,
theta=[5, 6] * u.deg,
r=[1, 2] * u.kpc)
assert_allclose(s1.phi.degree, [120, 135])
assert_allclose(s1.theta.degree, [5, 6])
assert_allclose(s1.r.kpc, [1, 2])
assert isinstance(s1.phi, Angle)
assert isinstance(s1.theta, Angle)
assert isinstance(s1.r, Distance)
def test_init_array_nocopy(self):
phi = Angle([8, 9] * u.hourangle)
theta = Angle([5, 6] * u.deg)
r = Distance([1, 2] * u.kpc)
s1 = PhysicsSphericalRepresentation(phi=phi, theta=theta, r=r, copy=False)
phi[:] = [1, 2] * u.rad
theta[:] = [3, 4] * u.arcmin
r[:] = [8, 9] * u.Mpc
assert_allclose_quantity(phi, s1.phi)
assert_allclose_quantity(theta, s1.theta)
assert_allclose_quantity(r, s1.r)
def test_reprobj(self):
s1 = PhysicsSphericalRepresentation(phi=8 * u.hourangle, theta=5 * u.deg, r=10 * u.kpc)
s2 = PhysicsSphericalRepresentation.from_representation(s1)
assert_allclose_quantity(s2.phi, 8. * u.hourangle)
assert_allclose_quantity(s2.theta, 5. * u.deg)
assert_allclose_quantity(s2.r, 10 * u.kpc)
def test_broadcasting(self):
s1 = PhysicsSphericalRepresentation(phi=[8, 9] * u.hourangle,
theta=[5, 6] * u.deg,
r=10 * u.kpc)
assert_allclose_quantity(s1.phi, [120, 135] * u.degree)
assert_allclose_quantity(s1.theta, [5, 6] * u.degree)
assert_allclose_quantity(s1.r, [10, 10] * u.kpc)
def test_broadcasting_mismatch(self):
with pytest.raises(ValueError) as exc:
s1 = PhysicsSphericalRepresentation(phi=[8, 9, 10] * u.hourangle,
theta=[5, 6] * u.deg,
r=[1, 2] * u.kpc)
assert exc.value.args[0] == "Input parameters phi, theta, and r cannot be broadcast"
def test_readonly(self):
s1 = PhysicsSphericalRepresentation(phi=[8, 9] * u.hourangle,
theta=[5, 6] * u.deg,
r=[10, 20] * u.kpc)
with pytest.raises(AttributeError):
s1.phi = 1. * u.deg
with pytest.raises(AttributeError):
s1.theta = 1. * u.deg
with pytest.raises(AttributeError):
s1.r = 1. * u.kpc
def test_getitem(self):
s = PhysicsSphericalRepresentation(phi=np.arange(10) * u.deg,
theta=np.arange(5, 15) * u.deg,
r=1 * u.kpc)
s_slc = s[2:8:2]
assert_allclose_quantity(s_slc.phi, [2, 4, 6] * u.deg)
assert_allclose_quantity(s_slc.theta, [7, 9, 11] * u.deg)
assert_allclose_quantity(s_slc.r, [1, 1, 1] * u.kpc)
def test_getitem_scalar(self):
s = PhysicsSphericalRepresentation(phi=1 * u.deg,
theta=2 * u.deg,
r=3 * u.kpc)
with pytest.raises(TypeError):
s_slc = s[0]
class TestCartesianRepresentation:
def test_name(self):
assert CartesianRepresentation.get_name() == 'cartesian'
assert CartesianRepresentation.get_name() in REPRESENTATION_CLASSES
def test_empty_init(self):
with pytest.raises(TypeError) as exc:
s = CartesianRepresentation()
def test_init_quantity(self):
s1 = CartesianRepresentation(x=1 * u.kpc, y=2 * u.kpc, z=3 * u.kpc)
assert s1.x.unit is u.kpc
assert s1.y.unit is u.kpc
assert s1.z.unit is u.kpc
assert_allclose(s1.x.value, 1)
assert_allclose(s1.y.value, 2)
assert_allclose(s1.z.value, 3)
def test_init_singleunit(self):
s1 = CartesianRepresentation(x=1, y=2, z=3, unit=u.kpc)
assert s1.x.unit is u.kpc
assert s1.y.unit is u.kpc
assert s1.z.unit is u.kpc
assert_allclose(s1.x.value, 1)
assert_allclose(s1.y.value, 2)
assert_allclose(s1.z.value, 3)
def test_init_array(self):
s1 = CartesianRepresentation(x=[1, 2, 3] * u.pc,
y=[2, 3, 4] * u.Mpc,
z=[3, 4, 5] * u.kpc)
assert s1.x.unit is u.pc
assert s1.y.unit is u.Mpc
assert s1.z.unit is u.kpc
assert_allclose(s1.x.value, [1, 2, 3])
assert_allclose(s1.y.value, [2, 3, 4])
assert_allclose(s1.z.value, [3, 4, 5])
def test_init_one_array(self):
s1 = CartesianRepresentation(x=[1, 2, 3] * u.pc)
assert s1.x.unit is u.pc
assert s1.y.unit is u.pc
assert s1.z.unit is u.pc
assert_allclose(s1.x.value, 1)
assert_allclose(s1.y.value, 2)
assert_allclose(s1.z.value, 3)
r = np.arange(27.).reshape(3, 3, 3) * u.kpc
s2 = CartesianRepresentation(r, xyz_axis=0)
assert s2.shape == (3, 3)
assert s2.x.unit == u.kpc
assert np.all(s2.x == r[0])
assert np.all(s2.xyz == r)
assert np.all(s2.get_xyz(xyz_axis=0) == r)
s3 = CartesianRepresentation(r, xyz_axis=1)
assert s3.shape == (3, 3)
assert np.all(s3.x == r[:, 0])
assert np.all(s3.y == r[:, 1])
assert np.all(s3.z == r[:, 2])
assert np.all(s3.get_xyz(xyz_axis=1) == r)
s4 = CartesianRepresentation(r, xyz_axis=2)
assert s4.shape == (3, 3)
assert np.all(s4.x == r[:, :, 0])
assert np.all(s4.get_xyz(xyz_axis=2) == r)
s5 = CartesianRepresentation(r, unit=u.pc)
assert s5.x.unit == u.pc
assert np.all(s5.xyz == r)
s6 = CartesianRepresentation(r.value, unit=u.pc, xyz_axis=2)
assert s6.x.unit == u.pc
assert np.all(s6.get_xyz(xyz_axis=2).value == r.value)
def test_init_one_array_size_fail(self):
with pytest.raises(ValueError) as exc:
CartesianRepresentation(x=[1, 2, 3, 4] * u.pc)
assert exc.value.args[0].startswith("too many values to unpack")
def test_init_xyz_but_more_than_one_array_fail(self):
with pytest.raises(ValueError) as exc:
CartesianRepresentation(x=[1, 2, 3] * u.pc, y=[2, 3, 4] * u.pc,
z=[3, 4, 5] * u.pc, xyz_axis=0)
assert 'xyz_axis should only be set' in str(exc)
def test_init_one_array_yz_fail(self):
with pytest.raises(ValueError) as exc:
CartesianRepresentation(x=[1, 2, 3, 4] * u.pc, y=[1, 2] * u.pc)
assert exc.value.args[0] == ("x, y, and z are required to instantiate "
"CartesianRepresentation")
def test_init_array_nocopy(self):
x = [8, 9, 10] * u.pc
y = [5, 6, 7] * u.Mpc
z = [2, 3, 4] * u.kpc
s1 = CartesianRepresentation(x=x, y=y, z=z, copy=False)
x[:] = [1, 2, 3] * u.kpc
y[:] = [9, 9, 8] * u.kpc
z[:] = [1, 2, 1] * u.kpc
assert_allclose_quantity(x, s1.x)
assert_allclose_quantity(y, s1.y)
assert_allclose_quantity(z, s1.z)
def test_xyz_is_view_if_possible(self):
xyz = np.arange(1., 10.).reshape(3, 3)
s1 = CartesianRepresentation(xyz, unit=u.kpc, copy=False)
s1_xyz = s1.xyz
assert s1_xyz.value[0, 0] == 1.
xyz[0, 0] = 0.
assert s1.x[0] == 0.
assert s1_xyz.value[0, 0] == 0.
# Not possible: we don't check that tuples are from the same array
xyz = np.arange(1., 10.).reshape(3, 3)
s2 = CartesianRepresentation(*xyz, unit=u.kpc, copy=False)
s2_xyz = s2.xyz
assert s2_xyz.value[0, 0] == 1.
xyz[0, 0] = 0.
assert s2.x[0] == 0.
assert s2_xyz.value[0, 0] == 1.
def test_reprobj(self):
s1 = CartesianRepresentation(x=1 * u.kpc, y=2 * u.kpc, z=3 * u.kpc)
s2 = CartesianRepresentation.from_representation(s1)
assert s2.x == 1 * u.kpc
assert s2.y == 2 * u.kpc
assert s2.z == 3 * u.kpc
def test_broadcasting(self):
s1 = CartesianRepresentation(x=[1, 2] * u.kpc, y=[3, 4] * u.kpc, z=5 * u.kpc)
assert s1.x.unit == u.kpc
assert s1.y.unit == u.kpc
assert s1.z.unit == u.kpc
assert_allclose(s1.x.value, [1, 2])
assert_allclose(s1.y.value, [3, 4])
assert_allclose(s1.z.value, [5, 5])
def test_broadcasting_mismatch(self):
with pytest.raises(ValueError) as exc:
s1 = CartesianRepresentation(x=[1, 2] * u.kpc, y=[3, 4] * u.kpc, z=[5, 6, 7] * u.kpc)
assert exc.value.args[0] == "Input parameters x, y, and z cannot be broadcast"
def test_readonly(self):
s1 = CartesianRepresentation(x=1 * u.kpc, y=2 * u.kpc, z=3 * u.kpc)
with pytest.raises(AttributeError):
s1.x = 1. * u.kpc
with pytest.raises(AttributeError):
s1.y = 1. * u.kpc
with pytest.raises(AttributeError):
s1.z = 1. * u.kpc
def test_xyz(self):
s1 = CartesianRepresentation(x=1 * u.kpc, y=2 * u.kpc, z=3 * u.kpc)
assert isinstance(s1.xyz, u.Quantity)
assert s1.xyz.unit is u.kpc
assert_allclose(s1.xyz.value, [1, 2, 3])
def test_unit_mismatch(self):
q_len = u.Quantity([1], u.km)
q_nonlen = u.Quantity([1], u.kg)
with pytest.raises(u.UnitsError) as exc:
s1 = CartesianRepresentation(x=q_nonlen, y=q_len, z=q_len)
assert exc.value.args[0] == "x, y, and z should have matching physical types"
with pytest.raises(u.UnitsError) as exc:
s1 = CartesianRepresentation(x=q_len, y=q_nonlen, z=q_len)
assert exc.value.args[0] == "x, y, and z should have matching physical types"
with pytest.raises(u.UnitsError) as exc:
s1 = CartesianRepresentation(x=q_len, y=q_len, z=q_nonlen)
assert exc.value.args[0] == "x, y, and z should have matching physical types"
def test_unit_non_length(self):
s1 = CartesianRepresentation(x=1 * u.kg, y=2 * u.kg, z=3 * u.kg)
s2 = CartesianRepresentation(x=1 * u.km / u.s, y=2 * u.km / u.s, z=3 * u.km / u.s)
banana = u.def_unit('banana')
s3 = CartesianRepresentation(x=1 * banana, y=2 * banana, z=3 * banana)
def test_getitem(self):
s = CartesianRepresentation(x=np.arange(10) * u.m,
y=-np.arange(10) * u.m,
z=3 * u.km)
s_slc = s[2:8:2]
assert_allclose_quantity(s_slc.x, [2, 4, 6] * u.m)
assert_allclose_quantity(s_slc.y, [-2, -4, -6] * u.m)
assert_allclose_quantity(s_slc.z, [3, 3, 3] * u.km)
def test_getitem_scalar(self):
s = CartesianRepresentation(x=1 * u.m,
y=-2 * u.m,
z=3 * u.km)
with pytest.raises(TypeError):
s_slc = s[0]
def test_transform(self):
s1 = CartesianRepresentation(x=[1, 2] * u.kpc, y=[3, 4] * u.kpc, z=[5, 6] * u.kpc)
matrix = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
s2 = s1.transform(matrix)
assert_allclose(s2.x.value, [1 * 1 + 2 * 3 + 3 * 5, 1 * 2 + 2 * 4 + 3 * 6])
assert_allclose(s2.y.value, [4 * 1 + 5 * 3 + 6 * 5, 4 * 2 + 5 * 4 + 6 * 6])
assert_allclose(s2.z.value, [7 * 1 + 8 * 3 + 9 * 5, 7 * 2 + 8 * 4 + 9 * 6])
assert s2.x.unit is u.kpc
assert s2.y.unit is u.kpc
assert s2.z.unit is u.kpc
class TestCylindricalRepresentation:
def test_name(self):
assert CylindricalRepresentation.get_name() == 'cylindrical'
assert CylindricalRepresentation.get_name() in REPRESENTATION_CLASSES
def test_empty_init(self):
with pytest.raises(TypeError) as exc:
s = CylindricalRepresentation()
def test_init_quantity(self):
s1 = CylindricalRepresentation(rho=1 * u.kpc, phi=2 * u.deg, z=3 * u.kpc)
assert s1.rho.unit is u.kpc
assert s1.phi.unit is u.deg
assert s1.z.unit is u.kpc
assert_allclose(s1.rho.value, 1)
assert_allclose(s1.phi.value, 2)
assert_allclose(s1.z.value, 3)
def test_init_array(self):
s1 = CylindricalRepresentation(rho=[1, 2, 3] * u.pc,
phi=[2, 3, 4] * u.deg,
z=[3, 4, 5] * u.kpc)
assert s1.rho.unit is u.pc
assert s1.phi.unit is u.deg
assert s1.z.unit is u.kpc
assert_allclose(s1.rho.value, [1, 2, 3])
assert_allclose(s1.phi.value, [2, 3, 4])
assert_allclose(s1.z.value, [3, 4, 5])
def test_init_array_nocopy(self):
rho = [8, 9, 10] * u.pc
phi = [5, 6, 7] * u.deg
z = [2, 3, 4] * u.kpc
s1 = CylindricalRepresentation(rho=rho, phi=phi, z=z, copy=False)
rho[:] = [9, 2, 3] * u.kpc
phi[:] = [1, 2, 3] * u.arcmin
z[:] = [-2, 3, 8] * u.kpc
assert_allclose_quantity(rho, s1.rho)
assert_allclose_quantity(phi, s1.phi)
assert_allclose_quantity(z, s1.z)
def test_reprobj(self):
s1 = CylindricalRepresentation(rho=1 * u.kpc, phi=2 * u.deg, z=3 * u.kpc)
s2 = CylindricalRepresentation.from_representation(s1)
assert s2.rho == 1 * u.kpc
assert s2.phi == 2 * u.deg
assert s2.z == 3 * u.kpc
def test_broadcasting(self):
s1 = CylindricalRepresentation(rho=[1, 2] * u.kpc, phi=[3, 4] * u.deg, z=5 * u.kpc)
assert s1.rho.unit == u.kpc
assert s1.phi.unit == u.deg
assert s1.z.unit == u.kpc
assert_allclose(s1.rho.value, [1, 2])
assert_allclose(s1.phi.value, [3, 4])
assert_allclose(s1.z.value, [5, 5])
def test_broadcasting_mismatch(self):
with pytest.raises(ValueError) as exc:
s1 = CylindricalRepresentation(rho=[1, 2] * u.kpc, phi=[3, 4] * u.deg, z=[5, 6, 7] * u.kpc)
assert exc.value.args[0] == "Input parameters rho, phi, and z cannot be broadcast"
def test_readonly(self):
s1 = CylindricalRepresentation(rho=1 * u.kpc,
phi=20 * u.deg,
z=3 * u.kpc)
with pytest.raises(AttributeError):
s1.rho = 1. * u.kpc
with pytest.raises(AttributeError):
s1.phi = 20 * u.deg
with pytest.raises(AttributeError):
s1.z = 1. * u.kpc
def unit_mismatch(self):
q_len = u.Quantity([1], u.kpc)
q_nonlen = u.Quantity([1], u.kg)
with pytest.raises(u.UnitsError) as exc:
s1 = CylindricalRepresentation(rho=q_nonlen, phi=10 * u.deg, z=q_len)
assert exc.value.args[0] == "rho and z should have matching physical types"
with pytest.raises(u.UnitsError) as exc:
s1 = CylindricalRepresentation(rho=q_len, phi=10 * u.deg, z=q_nonlen)
assert exc.value.args[0] == "rho and z should have matching physical types"
def test_getitem(self):
s = CylindricalRepresentation(rho=np.arange(10) * u.pc,
phi=-np.arange(10) * u.deg,
z=1 * u.kpc)
s_slc = s[2:8:2]
assert_allclose_quantity(s_slc.rho, [2, 4, 6] * u.pc)
assert_allclose_quantity(s_slc.phi, [-2, -4, -6] * u.deg)
assert_allclose_quantity(s_slc.z, [1, 1, 1] * u.kpc)
def test_getitem_scalar(self):
s = CylindricalRepresentation(rho=1 * u.pc,
phi=-2 * u.deg,
z=3 * u.kpc)
with pytest.raises(TypeError):
s_slc = s[0]
def test_cartesian_spherical_roundtrip():
s1 = CartesianRepresentation(x=[1, 2000.] * u.kpc,
y=[3000., 4.] * u.pc,
z=[5., 6000.] * u.pc)
s2 = SphericalRepresentation.from_representation(s1)
s3 = CartesianRepresentation.from_representation(s2)
s4 = SphericalRepresentation.from_representation(s3)
assert_allclose_quantity(s1.x, s3.x)
assert_allclose_quantity(s1.y, s3.y)
assert_allclose_quantity(s1.z, s3.z)
assert_allclose_quantity(s2.lon, s4.lon)
assert_allclose_quantity(s2.lat, s4.lat)
assert_allclose_quantity(s2.distance, s4.distance)
def test_cartesian_physics_spherical_roundtrip():
s1 = CartesianRepresentation(x=[1, 2000.] * u.kpc,
y=[3000., 4.] * u.pc,
z=[5., 6000.] * u.pc)
s2 = PhysicsSphericalRepresentation.from_representation(s1)
s3 = CartesianRepresentation.from_representation(s2)
s4 = PhysicsSphericalRepresentation.from_representation(s3)
assert_allclose_quantity(s1.x, s3.x)
assert_allclose_quantity(s1.y, s3.y)
assert_allclose_quantity(s1.z, s3.z)
assert_allclose_quantity(s2.phi, s4.phi)
assert_allclose_quantity(s2.theta, s4.theta)
assert_allclose_quantity(s2.r, s4.r)
def test_spherical_physics_spherical_roundtrip():
s1 = SphericalRepresentation(lon=3 * u.deg, lat=4 * u.deg, distance=3 * u.kpc)
s2 = PhysicsSphericalRepresentation.from_representation(s1)
s3 = SphericalRepresentation.from_representation(s2)
s4 = PhysicsSphericalRepresentation.from_representation(s3)
assert_allclose_quantity(s1.lon, s3.lon)
assert_allclose_quantity(s1.lat, s3.lat)
assert_allclose_quantity(s1.distance, s3.distance)
assert_allclose_quantity(s2.phi, s4.phi)
assert_allclose_quantity(s2.theta, s4.theta)
assert_allclose_quantity(s2.r, s4.r)
assert_allclose_quantity(s1.lon, s4.phi)
assert_allclose_quantity(s1.lat, 90. * u.deg - s4.theta)
assert_allclose_quantity(s1.distance, s4.r)
def test_cartesian_cylindrical_roundtrip():
s1 = CartesianRepresentation(x=np.array([1., 2000.]) * u.kpc,
y=np.array([3000., 4.]) * u.pc,
z=np.array([5., 600.]) * u.cm)
s2 = CylindricalRepresentation.from_representation(s1)
s3 = CartesianRepresentation.from_representation(s2)
s4 = CylindricalRepresentation.from_representation(s3)
assert_allclose_quantity(s1.x, s3.x)
assert_allclose_quantity(s1.y, s3.y)
assert_allclose_quantity(s1.z, s3.z)
assert_allclose_quantity(s2.rho, s4.rho)
assert_allclose_quantity(s2.phi, s4.phi)
assert_allclose_quantity(s2.z, s4.z)
def test_unit_spherical_roundtrip():
s1 = UnitSphericalRepresentation(lon=[10., 30.] * u.deg,
lat=[5., 6.] * u.arcmin)
s2 = CartesianRepresentation.from_representation(s1)
s3 = SphericalRepresentation.from_representation(s2)
s4 = UnitSphericalRepresentation.from_representation(s3)
assert_allclose_quantity(s1.lon, s4.lon)
assert_allclose_quantity(s1.lat, s4.lat)
def test_no_unnecessary_copies():
s1 = UnitSphericalRepresentation(lon=[10., 30.] * u.deg,
lat=[5., 6.] * u.arcmin)
s2 = s1.represent_as(UnitSphericalRepresentation)
assert s2 is s1
assert np.may_share_memory(s1.lon, s2.lon)
assert np.may_share_memory(s1.lat, s2.lat)
s3 = s1.represent_as(SphericalRepresentation)
assert np.may_share_memory(s1.lon, s3.lon)
assert np.may_share_memory(s1.lat, s3.lat)
s4 = s1.represent_as(CartesianRepresentation)
s5 = s4.represent_as(CylindricalRepresentation)
assert np.may_share_memory(s5.z, s4.z)
def test_representation_repr():
r1 = SphericalRepresentation(lon=1 * u.deg, lat=2.5 * u.deg, distance=1 * u.kpc)
assert repr(r1) == ('<SphericalRepresentation (lon, lat, distance) in (deg, deg, kpc)\n'
' ({})>').format(' 1., 2.5, 1.' if NUMPY_LT_1_14
else '1., 2.5, 1.')
r2 = CartesianRepresentation(x=1 * u.kpc, y=2 * u.kpc, z=3 * u.kpc)
assert repr(r2) == ('<CartesianRepresentation (x, y, z) in kpc\n'
' ({})>').format(' 1., 2., 3.' if NUMPY_LT_1_14
else '1., 2., 3.')
r3 = CartesianRepresentation(x=[1, 2, 3] * u.kpc, y=4 * u.kpc, z=[9, 10, 11] * u.kpc)
if NUMPY_LT_1_14:
assert repr(r3) == ('<CartesianRepresentation (x, y, z) in kpc\n'
' [( 1., 4., 9.), ( 2., 4., 10.), ( 3., 4., 11.)]>')
else:
assert repr(r3) == ('<CartesianRepresentation (x, y, z) in kpc\n'
' [(1., 4., 9.), (2., 4., 10.), (3., 4., 11.)]>')
def test_representation_repr_multi_d():
"""Regression test for #5889."""
cr = CartesianRepresentation(np.arange(27).reshape(3, 3, 3), unit='m')
if NUMPY_LT_1_14:
assert repr(cr) == (
'<CartesianRepresentation (x, y, z) in m\n'
' [[( 0., 9., 18.), ( 1., 10., 19.), ( 2., 11., 20.)],\n'
' [( 3., 12., 21.), ( 4., 13., 22.), ( 5., 14., 23.)],\n'
' [( 6., 15., 24.), ( 7., 16., 25.), ( 8., 17., 26.)]]>')
else:
assert repr(cr) == (
'<CartesianRepresentation (x, y, z) in m\n'
' [[(0., 9., 18.), (1., 10., 19.), (2., 11., 20.)],\n'
' [(3., 12., 21.), (4., 13., 22.), (5., 14., 23.)],\n'
' [(6., 15., 24.), (7., 16., 25.), (8., 17., 26.)]]>')
# This was broken before.
if NUMPY_LT_1_14:
assert repr(cr.T) == (
'<CartesianRepresentation (x, y, z) in m\n'
' [[( 0., 9., 18.), ( 3., 12., 21.), ( 6., 15., 24.)],\n'
' [( 1., 10., 19.), ( 4., 13., 22.), ( 7., 16., 25.)],\n'
' [( 2., 11., 20.), ( 5., 14., 23.), ( 8., 17., 26.)]]>')
else:
assert repr(cr.T) == (
'<CartesianRepresentation (x, y, z) in m\n'
' [[(0., 9., 18.), (3., 12., 21.), (6., 15., 24.)],\n'
' [(1., 10., 19.), (4., 13., 22.), (7., 16., 25.)],\n'
' [(2., 11., 20.), (5., 14., 23.), (8., 17., 26.)]]>')
def test_representation_str():
r1 = SphericalRepresentation(lon=1 * u.deg, lat=2.5 * u.deg, distance=1 * u.kpc)
assert str(r1) == ('( 1., 2.5, 1.) (deg, deg, kpc)' if NUMPY_LT_1_14 else
'(1., 2.5, 1.) (deg, deg, kpc)')
r2 = CartesianRepresentation(x=1 * u.kpc, y=2 * u.kpc, z=3 * u.kpc)
assert str(r2) == ('( 1., 2., 3.) kpc' if NUMPY_LT_1_14 else
'(1., 2., 3.) kpc')
r3 = CartesianRepresentation(x=[1, 2, 3] * u.kpc, y=4 * u.kpc, z=[9, 10, 11] * u.kpc)
assert str(r3) == ('[( 1., 4., 9.), ( 2., 4., 10.), ( 3., 4., 11.)] kpc'
if NUMPY_LT_1_14 else
'[(1., 4., 9.), (2., 4., 10.), (3., 4., 11.)] kpc')
def test_representation_str_multi_d():
"""Regression test for #5889."""
cr = CartesianRepresentation(np.arange(27).reshape(3, 3, 3), unit='m')
if NUMPY_LT_1_14:
assert str(cr) == (
'[[( 0., 9., 18.), ( 1., 10., 19.), ( 2., 11., 20.)],\n'
' [( 3., 12., 21.), ( 4., 13., 22.), ( 5., 14., 23.)],\n'
' [( 6., 15., 24.), ( 7., 16., 25.), ( 8., 17., 26.)]] m')
else:
assert str(cr) == (
'[[(0., 9., 18.), (1., 10., 19.), (2., 11., 20.)],\n'
' [(3., 12., 21.), (4., 13., 22.), (5., 14., 23.)],\n'
' [(6., 15., 24.), (7., 16., 25.), (8., 17., 26.)]] m')
# This was broken before.
if NUMPY_LT_1_14:
assert str(cr.T) == (
'[[( 0., 9., 18.), ( 3., 12., 21.), ( 6., 15., 24.)],\n'
' [( 1., 10., 19.), ( 4., 13., 22.), ( 7., 16., 25.)],\n'
' [( 2., 11., 20.), ( 5., 14., 23.), ( 8., 17., 26.)]] m')
else:
assert str(cr.T) == (
'[[(0., 9., 18.), (3., 12., 21.), (6., 15., 24.)],\n'
' [(1., 10., 19.), (4., 13., 22.), (7., 16., 25.)],\n'
' [(2., 11., 20.), (5., 14., 23.), (8., 17., 26.)]] m')
@pytest.mark.remote_data
def test_subclass_representation():
from astropy.coordinates.builtin_frames import ICRS
class Longitude180(Longitude):
def __new__(cls, angle, unit=None, wrap_angle=180 * u.deg, **kwargs):
self = super().__new__(cls, angle, unit=unit, wrap_angle=wrap_angle,
**kwargs)
return self
class SphericalWrap180Representation(SphericalRepresentation):
attr_classes = OrderedDict([('lon', Longitude180),
('lat', Latitude),
('distance', u.Quantity)])
class ICRSWrap180(ICRS):
frame_specific_representation_info = ICRS._frame_specific_representation_info.copy()
frame_specific_representation_info[SphericalWrap180Representation] = \
frame_specific_representation_info[SphericalRepresentation]
default_representation = SphericalWrap180Representation
c = ICRSWrap180(ra=-1 * u.deg, dec=-2 * u.deg, distance=1 * u.m)
assert c.ra.value == -1
assert c.ra.unit is u.deg
assert c.dec.value == -2
assert c.dec.unit is u.deg
def test_minimal_subclass():
# Basically to check what we document works;
# see doc/coordinates/representations.rst
class LogDRepresentation(BaseRepresentation):
attr_classes = OrderedDict([('lon', Longitude),
('lat', Latitude),
('logd', u.Dex)])
def to_cartesian(self):
d = self.logd.physical
x = d * np.cos(self.lat) * np.cos(self.lon)
y = d * np.cos(self.lat) * np.sin(self.lon)
z = d * np.sin(self.lat)
return CartesianRepresentation(x=x, y=y, z=z, copy=False)
@classmethod
def from_cartesian(cls, cart):
s = np.hypot(cart.x, cart.y)
r = np.hypot(s, cart.z)
lon = np.arctan2(cart.y, cart.x)
lat = np.arctan2(cart.z, s)
return cls(lon=lon, lat=lat, logd=u.Dex(r), copy=False)
ld1 = LogDRepresentation(90.*u.deg, 0.*u.deg, 1.*u.dex(u.kpc))
ld2 = LogDRepresentation(lon=90.*u.deg, lat=0.*u.deg, logd=1.*u.dex(u.kpc))
assert np.all(ld1.lon == ld2.lon)
assert np.all(ld1.lat == ld2.lat)
assert np.all(ld1.logd == ld2.logd)
c = ld1.to_cartesian()
assert_allclose_quantity(c.xyz, [0., 10., 0.] * u.kpc, atol=1.*u.npc)
ld3 = LogDRepresentation.from_cartesian(c)
assert np.all(ld3.lon == ld2.lon)
assert np.all(ld3.lat == ld2.lat)
assert np.all(ld3.logd == ld2.logd)
s = ld1.represent_as(SphericalRepresentation)
assert_allclose_quantity(s.lon, ld1.lon)
assert_allclose_quantity(s.distance, 10.*u.kpc)
assert_allclose_quantity(s.lat, ld1.lat)
with pytest.raises(TypeError):
LogDRepresentation(0.*u.deg, 1.*u.deg)
with pytest.raises(TypeError):
LogDRepresentation(0.*u.deg, 1.*u.deg, 1.*u.dex(u.kpc), lon=1.*u.deg)
with pytest.raises(TypeError):
LogDRepresentation(0.*u.deg, 1.*u.deg, 1.*u.dex(u.kpc), True, False)
with pytest.raises(TypeError):
LogDRepresentation(0.*u.deg, 1.*u.deg, 1.*u.dex(u.kpc), foo='bar')
with pytest.raises(ValueError):
# check we cannot redefine an existing class.
class LogDRepresentation(BaseRepresentation):
attr_classes = OrderedDict([('lon', Longitude),
('lat', Latitude),
('logr', u.Dex)])
def test_combine_xyz():
x, y, z = np.arange(27).reshape(3, 9) * u.kpc
xyz = _combine_xyz(x, y, z, xyz_axis=0)
assert xyz.shape == (3, 9)
assert np.all(xyz[0] == x)
assert np.all(xyz[1] == y)
assert np.all(xyz[2] == z)
x, y, z = np.arange(27).reshape(3, 3, 3) * u.kpc
xyz = _combine_xyz(x, y, z, xyz_axis=0)
assert xyz.ndim == 3
assert np.all(xyz[0] == x)
assert np.all(xyz[1] == y)
assert np.all(xyz[2] == z)
xyz = _combine_xyz(x, y, z, xyz_axis=1)
assert xyz.ndim == 3
assert np.all(xyz[:, 0] == x)
assert np.all(xyz[:, 1] == y)
assert np.all(xyz[:, 2] == z)
xyz = _combine_xyz(x, y, z, xyz_axis=-1)
assert xyz.ndim == 3
assert np.all(xyz[..., 0] == x)
assert np.all(xyz[..., 1] == y)
assert np.all(xyz[..., 2] == z)
class TestCartesianRepresentationWithDifferential:
def test_init_differential(self):
diff = CartesianDifferential(d_x=1 * u.km/u.s,
d_y=2 * u.km/u.s,
d_z=3 * u.km/u.s)
# Check that a single differential gets turned into a 1-item dict.
s1 = CartesianRepresentation(x=1 * u.kpc, y=2 * u.kpc, z=3 * u.kpc,
differentials=diff)
assert s1.x.unit is u.kpc
assert s1.y.unit is u.kpc
assert s1.z.unit is u.kpc
assert len(s1.differentials) == 1
assert s1.differentials['s'] is diff
# can also pass in an explicit dictionary
s1 = CartesianRepresentation(x=1 * u.kpc, y=2 * u.kpc, z=3 * u.kpc,
differentials={'s': diff})
assert len(s1.differentials) == 1
assert s1.differentials['s'] is diff
# using the wrong key will cause it to fail
with pytest.raises(ValueError):
s1 = CartesianRepresentation(x=1 * u.kpc, y=2 * u.kpc, z=3 * u.kpc,
differentials={'1 / s2': diff})
# make sure other kwargs are handled properly
s1 = CartesianRepresentation(x=1, y=2, z=3,
differentials=diff, copy=False, unit=u.kpc)
assert len(s1.differentials) == 1
assert s1.differentials['s'] is diff
with pytest.raises(TypeError): # invalid type passed to differentials
CartesianRepresentation(x=1 * u.kpc, y=2 * u.kpc, z=3 * u.kpc,
differentials='garmonbozia')
# make sure differentials can't accept differentials
with pytest.raises(TypeError):
CartesianDifferential(d_x=1 * u.km/u.s, d_y=2 * u.km/u.s,
d_z=3 * u.km/u.s, differentials=diff)
def test_init_differential_compatible(self):
# TODO: more extensive checking of this
# should fail - representation and differential not compatible
diff = SphericalDifferential(d_lon=1 * u.mas/u.yr,
d_lat=2 * u.mas/u.yr,
d_distance=3 * u.km/u.s)
with pytest.raises(TypeError):
CartesianRepresentation(x=1 * u.kpc, y=2 * u.kpc, z=3 * u.kpc,
differentials=diff)
# should succeed - representation and differential are compatible
diff = SphericalCosLatDifferential(d_lon_coslat=1 * u.mas/u.yr,
d_lat=2 * u.mas/u.yr,
d_distance=3 * u.km/u.s)
r1 = SphericalRepresentation(lon=15*u.deg, lat=21*u.deg,
distance=1*u.pc,
differentials=diff)
def test_init_differential_multiple_equivalent_keys(self):
d1 = CartesianDifferential(*[1, 2, 3] * u.km/u.s)
d2 = CartesianDifferential(*[4, 5, 6] * u.km/u.s)
# verify that the check against expected_unit validates against passing
# in two different but equivalent keys
with pytest.raises(ValueError):
r1 = CartesianRepresentation(x=1 * u.kpc, y=2 * u.kpc, z=3 * u.kpc,
differentials={'s': d1, 'yr': d2})
def test_init_array_broadcasting(self):
arr1 = np.arange(8).reshape(4, 2) * u.km/u.s
diff = CartesianDifferential(d_x=arr1, d_y=arr1, d_z=arr1)
# shapes aren't compatible
arr2 = np.arange(27).reshape(3, 9) * u.kpc
with pytest.raises(ValueError):
rep = CartesianRepresentation(x=arr2, y=arr2, z=arr2,
differentials=diff)
arr2 = np.arange(8).reshape(4, 2) * u.kpc
rep = CartesianRepresentation(x=arr2, y=arr2, z=arr2,
differentials=diff)
assert rep.x.unit is u.kpc
assert rep.y.unit is u.kpc
assert rep.z.unit is u.kpc
assert len(rep.differentials) == 1
assert rep.differentials['s'] is diff
assert rep.xyz.shape == rep.differentials['s'].d_xyz.shape
def test_reprobj(self):
# should succeed - representation and differential are compatible
diff = SphericalCosLatDifferential(d_lon_coslat=1 * u.mas/u.yr,
d_lat=2 * u.mas/u.yr,
d_distance=3 * u.km/u.s)
r1 = SphericalRepresentation(lon=15*u.deg, lat=21*u.deg,
distance=1*u.pc,
differentials=diff)
r2 = CartesianRepresentation.from_representation(r1)
assert r2.get_name() == 'cartesian'
assert not r2.differentials
def test_readonly(self):
s1 = CartesianRepresentation(x=1 * u.kpc, y=2 * u.kpc, z=3 * u.kpc)
with pytest.raises(AttributeError): # attribute is not settable
s1.differentials = 'thing'
def test_represent_as(self):
diff = CartesianDifferential(d_x=1 * u.km/u.s,
d_y=2 * u.km/u.s,
d_z=3 * u.km/u.s)
rep1 = CartesianRepresentation(x=1 * u.kpc, y=2 * u.kpc, z=3 * u.kpc,
differentials=diff)
# Only change the representation, drop the differential
new_rep = rep1.represent_as(SphericalRepresentation)
assert new_rep.get_name() == 'spherical'
assert not new_rep.differentials # dropped
# Pass in separate classes for representation, differential
new_rep = rep1.represent_as(SphericalRepresentation,
SphericalCosLatDifferential)
assert new_rep.get_name() == 'spherical'
assert new_rep.differentials['s'].get_name() == 'sphericalcoslat'
# Pass in a dictionary for the differential classes
new_rep = rep1.represent_as(SphericalRepresentation,
{'s': SphericalCosLatDifferential})
assert new_rep.get_name() == 'spherical'
assert new_rep.differentials['s'].get_name() == 'sphericalcoslat'
# make sure represent_as() passes through the differentials
for name in REPRESENTATION_CLASSES:
if name == 'radial':
# TODO: Converting a CartesianDifferential to a
# RadialDifferential fails, even on `master`
continue
new_rep = rep1.represent_as(REPRESENTATION_CLASSES[name],
DIFFERENTIAL_CLASSES[name])
assert new_rep.get_name() == name
assert len(new_rep.differentials) == 1
assert new_rep.differentials['s'].get_name() == name
with pytest.raises(ValueError) as excinfo:
rep1.represent_as('name')
assert 'use frame object' in str(excinfo.value)
def test_getitem(self):
d = CartesianDifferential(d_x=np.arange(10) * u.m/u.s,
d_y=-np.arange(10) * u.m/u.s,
d_z=1. * u.m/u.s)
s = CartesianRepresentation(x=np.arange(10) * u.m,
y=-np.arange(10) * u.m,
z=3 * u.km,
differentials=d)
s_slc = s[2:8:2]
s_dif = s_slc.differentials['s']
assert_allclose_quantity(s_slc.x, [2, 4, 6] * u.m)
assert_allclose_quantity(s_slc.y, [-2, -4, -6] * u.m)
assert_allclose_quantity(s_slc.z, [3, 3, 3] * u.km)
assert_allclose_quantity(s_dif.d_x, [2, 4, 6] * u.m/u.s)
assert_allclose_quantity(s_dif.d_y, [-2, -4, -6] * u.m/u.s)
assert_allclose_quantity(s_dif.d_z, [1, 1, 1] * u.m/u.s)
def test_transform(self):
d1 = CartesianDifferential(d_x=[1, 2] * u.km/u.s,
d_y=[3, 4] * u.km/u.s,
d_z=[5, 6] * u.km/u.s)
r1 = CartesianRepresentation(x=[1, 2] * u.kpc,
y=[3, 4] * u.kpc,
z=[5, 6] * u.kpc,
differentials=d1)
matrix = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
r2 = r1.transform(matrix)
d2 = r2.differentials['s']
assert_allclose_quantity(d2.d_x, [22., 28]*u.km/u.s)
assert_allclose_quantity(d2.d_y, [49, 64]*u.km/u.s)
assert_allclose_quantity(d2.d_z, [76, 100.]*u.km/u.s)
def test_with_differentials(self):
# make sure with_differential correctly creates a new copy with the same
# differential
cr = CartesianRepresentation([1, 2, 3]*u.kpc)
diff = CartesianDifferential([.1, .2, .3]*u.km/u.s)
cr2 = cr.with_differentials(diff)
assert cr.differentials != cr2.differentials
assert cr2.differentials['s'] is diff
# make sure it works even if a differential is present already
diff2 = CartesianDifferential([.1, .2, .3]*u.m/u.s)
cr3 = CartesianRepresentation([1, 2, 3]*u.kpc, differentials=diff)
cr4 = cr3.with_differentials(diff2)
assert cr4.differentials['s'] != cr3.differentials['s']
assert cr4.differentials['s'] == diff2
# also ensure a *scalar* differential will works
cr5 = cr.with_differentials(diff)
assert len(cr5.differentials) == 1
assert cr5.differentials['s'] == diff
# make sure we don't update the original representation's dict
d1 = CartesianDifferential(*np.random.random((3, 5)), unit=u.km/u.s)
d2 = CartesianDifferential(*np.random.random((3, 5)), unit=u.km/u.s**2)
r1 = CartesianRepresentation(*np.random.random((3, 5)), unit=u.pc,
differentials=d1)
r2 = r1.with_differentials(d2)
assert r1.differentials['s'] is r2.differentials['s']
assert 's2' not in r1.differentials
assert 's2' in r2.differentials
def test_repr_with_differentials():
diff = CartesianDifferential([.1, .2, .3]*u.km/u.s)
cr = CartesianRepresentation([1, 2, 3]*u.kpc, differentials=diff)
assert "has differentials w.r.t.: 's'" in repr(cr)
def test_to_cartesian():
"""
Test that to_cartesian drops the differential.
"""
sd = SphericalDifferential(d_lat=1*u.deg, d_lon=2*u.deg, d_distance=10*u.m)
sr = SphericalRepresentation(lat=1*u.deg, lon=2*u.deg, distance=10*u.m,
differentials=sd)
cart = sr.to_cartesian()
assert cart.get_name() == 'cartesian'
assert not cart.differentials
def test_recommended_units_deprecation():
sr = SphericalRepresentation(lat=1*u.deg, lon=2*u.deg, distance=10*u.m)
with catch_warnings(AstropyDeprecationWarning) as w:
sr.recommended_units
assert 'recommended_units' in str(w[0].message)
with catch_warnings(AstropyDeprecationWarning) as w:
class MyClass(SphericalRepresentation):
attr_classes = SphericalRepresentation.attr_classes
recommended_units = {}
assert 'recommended_units' in str(w[0].message)
@pytest.fixture
def unitphysics():
"""
This fixture is used
"""
had_unit = False
if hasattr(PhysicsSphericalRepresentation, '_unit_representation'):
orig = PhysicsSphericalRepresentation._unit_representation
had_unit = True
class UnitPhysicsSphericalRepresentation(BaseRepresentation):
attr_classes = OrderedDict([('phi', Angle),
('theta', Angle)])
def __init__(self, phi, theta, differentials=None, copy=True):
super().__init__(phi, theta, copy=copy, differentials=differentials)
# Wrap/validate phi/theta
if copy:
self._phi = self._phi.wrap_at(360 * u.deg)
else:
# necessary because the above version of `wrap_at` has to be a copy
self._phi.wrap_at(360 * u.deg, inplace=True)
if np.any(self._theta < 0.*u.deg) or np.any(self._theta > 180.*u.deg):
raise ValueError('Inclination angle(s) must be within '
'0 deg <= angle <= 180 deg, '
'got {0}'.format(theta.to(u.degree)))
@property
def phi(self):
return self._phi
@property
def theta(self):
return self._theta
def unit_vectors(self):
sinphi, cosphi = np.sin(self.phi), np.cos(self.phi)
sintheta, costheta = np.sin(self.theta), np.cos(self.theta)
return OrderedDict(
(('phi', CartesianRepresentation(-sinphi, cosphi, 0., copy=False)),
('theta', CartesianRepresentation(costheta*cosphi,
costheta*sinphi,
-sintheta, copy=False))))
def scale_factors(self):
sintheta = np.sin(self.theta)
l = np.broadcast_to(1.*u.one, self.shape, subok=True)
return OrderedDict((('phi', sintheta),
('theta', l)))
def to_cartesian(self):
x = np.sin(self.theta) * np.cos(self.phi)
y = np.sin(self.theta) * np.sin(self.phi)
z = np.cos(self.theta)
return CartesianRepresentation(x=x, y=y, z=z, copy=False)
@classmethod
def from_cartesian(cls, cart):
"""
Converts 3D rectangular cartesian coordinates to spherical polar
coordinates.
"""
s = np.hypot(cart.x, cart.y)
phi = np.arctan2(cart.y, cart.x)
theta = np.arctan2(s, cart.z)
return cls(phi=phi, theta=theta, copy=False)
def norm(self):
return u.Quantity(np.ones(self.shape), u.dimensionless_unscaled,
copy=False)
PhysicsSphericalRepresentation._unit_representation = UnitPhysicsSphericalRepresentation
yield UnitPhysicsSphericalRepresentation
if had_unit:
PhysicsSphericalRepresentation._unit_representation = orig
else:
del PhysicsSphericalRepresentation._unit_representation
# remove from the module-level representations, if present
REPRESENTATION_CLASSES.pop(UnitPhysicsSphericalRepresentation.get_name(), None)
def test_unitphysics(unitphysics):
obj = unitphysics(phi=0*u.deg, theta=10*u.deg)
objkw = unitphysics(phi=0*u.deg, theta=10*u.deg)
assert objkw.phi == obj.phi
assert objkw.theta == obj.theta
asphys = obj.represent_as(PhysicsSphericalRepresentation)
assert asphys.phi == obj.phi
assert asphys.theta == obj.theta
assert_allclose_quantity(asphys.r, 1*u.dimensionless_unscaled)
assph = obj.represent_as(SphericalRepresentation)
assert assph.lon == obj.phi
assert assph.lat == 80*u.deg
assert_allclose_quantity(assph.distance, 1*u.dimensionless_unscaled)
def test_distance_warning(recwarn):
SphericalRepresentation(1*u.deg, 2*u.deg, 1*u.kpc)
with pytest.raises(ValueError) as excinfo:
SphericalRepresentation(1*u.deg, 2*u.deg, -1*u.kpc)
assert 'Distance must be >= 0' in str(excinfo.value)
# second check is because the "originating" ValueError says the above,
# while the representation one includes the below
assert 'you must explicitly pass' in str(excinfo.value)
|
410abf39e64dbe32b666d2003917f9a1b96d3f95c5084b30bef16b9ede0bcc4b | # Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Accuracy tests for GCRS coordinate transformations, primarily to/from AltAz.
"""
import pytest
import numpy as np
from astropy import units as u
from astropy.tests.helper import (assert_quantity_allclose as assert_allclose)
from astropy.time import Time
from astropy.coordinates import (EarthLocation, get_sun, ICRS, GCRS, CIRS, ITRS, AltAz,
PrecessedGeocentric, CartesianRepresentation, SkyCoord,
SphericalRepresentation, UnitSphericalRepresentation,
HCRS, HeliocentricMeanEcliptic)
from astropy._erfa import epv00
from .utils import randomly_sample_sphere
from astropy.coordinates.builtin_frames.utils import get_jd12
from astropy.coordinates import solar_system_ephemeris
from astropy.units import allclose
try:
import jplephem # pylint: disable=W0611
except ImportError:
HAS_JPLEPHEM = False
else:
HAS_JPLEPHEM = True
def test_icrs_cirs():
"""
Check a few cases of ICRS<->CIRS for consistency.
Also includes the CIRS<->CIRS transforms at different times, as those go
through ICRS
"""
ra, dec, dist = randomly_sample_sphere(200)
inod = ICRS(ra=ra, dec=dec)
iwd = ICRS(ra=ra, dec=dec, distance=dist*u.pc)
cframe1 = CIRS()
cirsnod = inod.transform_to(cframe1) # uses the default time
# first do a round-tripping test
inod2 = cirsnod.transform_to(ICRS)
assert_allclose(inod.ra, inod2.ra)
assert_allclose(inod.dec, inod2.dec)
# now check that a different time yields different answers
cframe2 = CIRS(obstime=Time('J2005'))
cirsnod2 = inod.transform_to(cframe2)
assert not allclose(cirsnod.ra, cirsnod2.ra, rtol=1e-8)
assert not allclose(cirsnod.dec, cirsnod2.dec, rtol=1e-8)
# parallax effects should be included, so with and w/o distance should be different
cirswd = iwd.transform_to(cframe1)
assert not allclose(cirswd.ra, cirsnod.ra, rtol=1e-8)
assert not allclose(cirswd.dec, cirsnod.dec, rtol=1e-8)
# and the distance should transform at least somehow
assert not allclose(cirswd.distance, iwd.distance, rtol=1e-8)
# now check that the cirs self-transform works as expected
cirsnod3 = cirsnod.transform_to(cframe1) # should be a no-op
assert_allclose(cirsnod.ra, cirsnod3.ra)
assert_allclose(cirsnod.dec, cirsnod3.dec)
cirsnod4 = cirsnod.transform_to(cframe2) # should be different
assert not allclose(cirsnod4.ra, cirsnod.ra, rtol=1e-8)
assert not allclose(cirsnod4.dec, cirsnod.dec, rtol=1e-8)
cirsnod5 = cirsnod4.transform_to(cframe1) # should be back to the same
assert_allclose(cirsnod.ra, cirsnod5.ra)
assert_allclose(cirsnod.dec, cirsnod5.dec)
ra, dec, dist = randomly_sample_sphere(200)
icrs_coords = [ICRS(ra=ra, dec=dec), ICRS(ra=ra, dec=dec, distance=dist*u.pc)]
gcrs_frames = [GCRS(), GCRS(obstime=Time('J2005'))]
@pytest.mark.parametrize('icoo', icrs_coords)
def test_icrs_gcrs(icoo):
"""
Check ICRS<->GCRS for consistency
"""
gcrscoo = icoo.transform_to(gcrs_frames[0]) # uses the default time
# first do a round-tripping test
icoo2 = gcrscoo.transform_to(ICRS)
assert_allclose(icoo.distance, icoo2.distance)
assert_allclose(icoo.ra, icoo2.ra)
assert_allclose(icoo.dec, icoo2.dec)
assert isinstance(icoo2.data, icoo.data.__class__)
# now check that a different time yields different answers
gcrscoo2 = icoo.transform_to(gcrs_frames[1])
assert not allclose(gcrscoo.ra, gcrscoo2.ra, rtol=1e-8, atol=1e-10*u.deg)
assert not allclose(gcrscoo.dec, gcrscoo2.dec, rtol=1e-8, atol=1e-10*u.deg)
# now check that the cirs self-transform works as expected
gcrscoo3 = gcrscoo.transform_to(gcrs_frames[0]) # should be a no-op
assert_allclose(gcrscoo.ra, gcrscoo3.ra)
assert_allclose(gcrscoo.dec, gcrscoo3.dec)
gcrscoo4 = gcrscoo.transform_to(gcrs_frames[1]) # should be different
assert not allclose(gcrscoo4.ra, gcrscoo.ra, rtol=1e-8, atol=1e-10*u.deg)
assert not allclose(gcrscoo4.dec, gcrscoo.dec, rtol=1e-8, atol=1e-10*u.deg)
gcrscoo5 = gcrscoo4.transform_to(gcrs_frames[0]) # should be back to the same
assert_allclose(gcrscoo.ra, gcrscoo5.ra, rtol=1e-8, atol=1e-10*u.deg)
assert_allclose(gcrscoo.dec, gcrscoo5.dec, rtol=1e-8, atol=1e-10*u.deg)
# also make sure that a GCRS with a different geoloc/geovel gets a different answer
# roughly a moon-like frame
gframe3 = GCRS(obsgeoloc=[385000., 0, 0]*u.km, obsgeovel=[1, 0, 0]*u.km/u.s)
gcrscoo6 = icoo.transform_to(gframe3) # should be different
assert not allclose(gcrscoo.ra, gcrscoo6.ra, rtol=1e-8, atol=1e-10*u.deg)
assert not allclose(gcrscoo.dec, gcrscoo6.dec, rtol=1e-8, atol=1e-10*u.deg)
icooviag3 = gcrscoo6.transform_to(ICRS) # and now back to the original
assert_allclose(icoo.ra, icooviag3.ra)
assert_allclose(icoo.dec, icooviag3.dec)
@pytest.mark.parametrize('gframe', gcrs_frames)
def test_icrs_gcrs_dist_diff(gframe):
"""
Check that with and without distance give different ICRS<->GCRS answers
"""
gcrsnod = icrs_coords[0].transform_to(gframe)
gcrswd = icrs_coords[1].transform_to(gframe)
# parallax effects should be included, so with and w/o distance should be different
assert not allclose(gcrswd.ra, gcrsnod.ra, rtol=1e-8, atol=1e-10*u.deg)
assert not allclose(gcrswd.dec, gcrsnod.dec, rtol=1e-8, atol=1e-10*u.deg)
# and the distance should transform at least somehow
assert not allclose(gcrswd.distance, icrs_coords[1].distance, rtol=1e-8,
atol=1e-10*u.pc)
@pytest.mark.remote_data
def test_cirs_to_altaz():
"""
Check the basic CIRS<->AltAz transforms. More thorough checks implicitly
happen in `test_iau_fullstack`
"""
from astropy.coordinates import EarthLocation
ra, dec, dist = randomly_sample_sphere(200)
cirs = CIRS(ra=ra, dec=dec, obstime='J2000')
crepr = SphericalRepresentation(lon=ra, lat=dec, distance=dist)
cirscart = CIRS(crepr, obstime=cirs.obstime, representation_type=CartesianRepresentation)
loc = EarthLocation(lat=0*u.deg, lon=0*u.deg, height=0*u.m)
altazframe = AltAz(location=loc, obstime=Time('J2005'))
cirs2 = cirs.transform_to(altazframe).transform_to(cirs)
cirs3 = cirscart.transform_to(altazframe).transform_to(cirs)
# check round-tripping
assert_allclose(cirs.ra, cirs2.ra)
assert_allclose(cirs.dec, cirs2.dec)
assert_allclose(cirs.ra, cirs3.ra)
assert_allclose(cirs.dec, cirs3.dec)
@pytest.mark.remote_data
def test_gcrs_itrs():
"""
Check basic GCRS<->ITRS transforms for round-tripping.
"""
ra, dec, _ = randomly_sample_sphere(200)
gcrs = GCRS(ra=ra, dec=dec, obstime='J2000')
gcrs6 = GCRS(ra=ra, dec=dec, obstime='J2006')
gcrs2 = gcrs.transform_to(ITRS).transform_to(gcrs)
gcrs6_2 = gcrs6.transform_to(ITRS).transform_to(gcrs)
assert_allclose(gcrs.ra, gcrs2.ra)
assert_allclose(gcrs.dec, gcrs2.dec)
assert not allclose(gcrs.ra, gcrs6_2.ra)
assert not allclose(gcrs.dec, gcrs6_2.dec)
# also try with the cartesian representation
gcrsc = gcrs.realize_frame(gcrs.data)
gcrsc.representation_type = CartesianRepresentation
gcrsc2 = gcrsc.transform_to(ITRS).transform_to(gcrsc)
assert_allclose(gcrsc.spherical.lon.deg, gcrsc2.ra.deg)
assert_allclose(gcrsc.spherical.lat, gcrsc2.dec)
@pytest.mark.remote_data
def test_cirs_itrs():
"""
Check basic CIRS<->ITRS transforms for round-tripping.
"""
ra, dec, _ = randomly_sample_sphere(200)
cirs = CIRS(ra=ra, dec=dec, obstime='J2000')
cirs6 = CIRS(ra=ra, dec=dec, obstime='J2006')
cirs2 = cirs.transform_to(ITRS).transform_to(cirs)
cirs6_2 = cirs6.transform_to(ITRS).transform_to(cirs) # different obstime
# just check round-tripping
assert_allclose(cirs.ra, cirs2.ra)
assert_allclose(cirs.dec, cirs2.dec)
assert not allclose(cirs.ra, cirs6_2.ra)
assert not allclose(cirs.dec, cirs6_2.dec)
@pytest.mark.remote_data
def test_gcrs_cirs():
"""
Check GCRS<->CIRS transforms for round-tripping. More complicated than the
above two because it's multi-hop
"""
ra, dec, _ = randomly_sample_sphere(200)
gcrs = GCRS(ra=ra, dec=dec, obstime='J2000')
gcrs6 = GCRS(ra=ra, dec=dec, obstime='J2006')
gcrs2 = gcrs.transform_to(CIRS).transform_to(gcrs)
gcrs6_2 = gcrs6.transform_to(CIRS).transform_to(gcrs)
assert_allclose(gcrs.ra, gcrs2.ra)
assert_allclose(gcrs.dec, gcrs2.dec)
assert not allclose(gcrs.ra, gcrs6_2.ra)
assert not allclose(gcrs.dec, gcrs6_2.dec)
# now try explicit intermediate pathways and ensure they're all consistent
gcrs3 = gcrs.transform_to(ITRS).transform_to(CIRS).transform_to(ITRS).transform_to(gcrs)
assert_allclose(gcrs.ra, gcrs3.ra)
assert_allclose(gcrs.dec, gcrs3.dec)
gcrs4 = gcrs.transform_to(ICRS).transform_to(CIRS).transform_to(ICRS).transform_to(gcrs)
assert_allclose(gcrs.ra, gcrs4.ra)
assert_allclose(gcrs.dec, gcrs4.dec)
@pytest.mark.remote_data
def test_gcrs_altaz():
"""
Check GCRS<->AltAz transforms for round-tripping. Has multiple paths
"""
from astropy.coordinates import EarthLocation
ra, dec, _ = randomly_sample_sphere(1)
gcrs = GCRS(ra=ra[0], dec=dec[0], obstime='J2000')
# check array times sure N-d arrays work
times = Time(np.linspace(2456293.25, 2456657.25, 51) * u.day,
format='jd')
loc = EarthLocation(lon=10 * u.deg, lat=80. * u.deg)
aaframe = AltAz(obstime=times, location=loc)
aa1 = gcrs.transform_to(aaframe)
aa2 = gcrs.transform_to(ICRS).transform_to(CIRS).transform_to(aaframe)
aa3 = gcrs.transform_to(ITRS).transform_to(CIRS).transform_to(aaframe)
# make sure they're all consistent
assert_allclose(aa1.alt, aa2.alt)
assert_allclose(aa1.az, aa2.az)
assert_allclose(aa1.alt, aa3.alt)
assert_allclose(aa1.az, aa3.az)
@pytest.mark.remote_data
def test_precessed_geocentric():
assert PrecessedGeocentric().equinox.jd == Time('J2000').jd
gcrs_coo = GCRS(180*u.deg, 2*u.deg, distance=10000*u.km)
pgeo_coo = gcrs_coo.transform_to(PrecessedGeocentric)
assert np.abs(gcrs_coo.ra - pgeo_coo.ra) > 10*u.marcsec
assert np.abs(gcrs_coo.dec - pgeo_coo.dec) > 10*u.marcsec
assert_allclose(gcrs_coo.distance, pgeo_coo.distance)
gcrs_roundtrip = pgeo_coo.transform_to(GCRS)
assert_allclose(gcrs_coo.ra, gcrs_roundtrip.ra)
assert_allclose(gcrs_coo.dec, gcrs_roundtrip.dec)
assert_allclose(gcrs_coo.distance, gcrs_roundtrip.distance)
pgeo_coo2 = gcrs_coo.transform_to(PrecessedGeocentric(equinox='B1850'))
assert np.abs(gcrs_coo.ra - pgeo_coo2.ra) > 1.5*u.deg
assert np.abs(gcrs_coo.dec - pgeo_coo2.dec) > 0.5*u.deg
assert_allclose(gcrs_coo.distance, pgeo_coo2.distance)
gcrs2_roundtrip = pgeo_coo2.transform_to(GCRS)
assert_allclose(gcrs_coo.ra, gcrs2_roundtrip.ra)
assert_allclose(gcrs_coo.dec, gcrs2_roundtrip.dec)
assert_allclose(gcrs_coo.distance, gcrs2_roundtrip.distance)
# shared by parametrized tests below. Some use the whole AltAz, others use just obstime
totest_frames = [AltAz(location=EarthLocation(-90*u.deg, 65*u.deg),
obstime=Time('J2000')), # J2000 is often a default so this might work when others don't
AltAz(location=EarthLocation(120*u.deg, -35*u.deg),
obstime=Time('J2000')),
AltAz(location=EarthLocation(-90*u.deg, 65*u.deg),
obstime=Time('2014-01-01 00:00:00')),
AltAz(location=EarthLocation(-90*u.deg, 65*u.deg),
obstime=Time('2014-08-01 08:00:00')),
AltAz(location=EarthLocation(120*u.deg, -35*u.deg),
obstime=Time('2014-01-01 00:00:00'))
]
MOONDIST = 385000*u.km # approximate moon semi-major orbit axis of moon
MOONDIST_CART = CartesianRepresentation(3**-0.5*MOONDIST, 3**-0.5*MOONDIST, 3**-0.5*MOONDIST)
EARTHECC = 0.017 + 0.005 # roughly earth orbital eccentricity, but with an added tolerance
@pytest.mark.remote_data
@pytest.mark.parametrize('testframe', totest_frames)
def test_gcrs_altaz_sunish(testframe):
"""
Sanity-check that the sun is at a reasonable distance from any altaz
"""
sun = get_sun(testframe.obstime)
assert sun.frame.name == 'gcrs'
# the .to(u.au) is not necessary, it just makes the asserts on failure more readable
assert (EARTHECC - 1)*u.au < sun.distance.to(u.au) < (EARTHECC + 1)*u.au
sunaa = sun.transform_to(testframe)
assert (EARTHECC - 1)*u.au < sunaa.distance.to(u.au) < (EARTHECC + 1)*u.au
@pytest.mark.remote_data
@pytest.mark.parametrize('testframe', totest_frames)
def test_gcrs_altaz_moonish(testframe):
"""
Sanity-check that an object resembling the moon goes to the right place with
a GCRS->AltAz transformation
"""
moon = GCRS(MOONDIST_CART, obstime=testframe.obstime)
moonaa = moon.transform_to(testframe)
# now check that the distance change is similar to earth radius
assert 1000*u.km < np.abs(moonaa.distance - moon.distance).to(u.au) < 7000*u.km
# now check that it round-trips
moon2 = moonaa.transform_to(moon)
assert_allclose(moon.cartesian.xyz, moon2.cartesian.xyz)
# also should add checks that the alt/az are different for different earth locations
@pytest.mark.remote_data
@pytest.mark.parametrize('testframe', totest_frames)
def test_gcrs_altaz_bothroutes(testframe):
"""
Repeat of both the moonish and sunish tests above to make sure the two
routes through the coordinate graph are consistent with each other
"""
sun = get_sun(testframe.obstime)
sunaa_viaicrs = sun.transform_to(ICRS).transform_to(testframe)
sunaa_viaitrs = sun.transform_to(ITRS(obstime=testframe.obstime)).transform_to(testframe)
moon = GCRS(MOONDIST_CART, obstime=testframe.obstime)
moonaa_viaicrs = moon.transform_to(ICRS).transform_to(testframe)
moonaa_viaitrs = moon.transform_to(ITRS(obstime=testframe.obstime)).transform_to(testframe)
assert_allclose(sunaa_viaicrs.cartesian.xyz, sunaa_viaitrs.cartesian.xyz)
assert_allclose(moonaa_viaicrs.cartesian.xyz, moonaa_viaitrs.cartesian.xyz)
@pytest.mark.remote_data
@pytest.mark.parametrize('testframe', totest_frames)
def test_cirs_altaz_moonish(testframe):
"""
Sanity-check that an object resembling the moon goes to the right place with
a CIRS<->AltAz transformation
"""
moon = CIRS(MOONDIST_CART, obstime=testframe.obstime)
moonaa = moon.transform_to(testframe)
assert 1000*u.km < np.abs(moonaa.distance - moon.distance).to(u.km) < 7000*u.km
# now check that it round-trips
moon2 = moonaa.transform_to(moon)
assert_allclose(moon.cartesian.xyz, moon2.cartesian.xyz)
@pytest.mark.remote_data
@pytest.mark.parametrize('testframe', totest_frames)
def test_cirs_altaz_nodist(testframe):
"""
Check that a UnitSphericalRepresentation coordinate round-trips for the
CIRS<->AltAz transformation.
"""
coo0 = CIRS(UnitSphericalRepresentation(10*u.deg, 20*u.deg), obstime=testframe.obstime)
# check that it round-trips
coo1 = coo0.transform_to(testframe).transform_to(coo0)
assert_allclose(coo0.cartesian.xyz, coo1.cartesian.xyz)
@pytest.mark.parametrize('testframe', totest_frames)
def test_cirs_icrs_moonish(testframe):
"""
check that something like the moon goes to about the right distance from the
ICRS origin when starting from CIRS
"""
moonish = CIRS(MOONDIST_CART, obstime=testframe.obstime)
moonicrs = moonish.transform_to(ICRS)
assert 0.97*u.au < moonicrs.distance < 1.03*u.au
@pytest.mark.parametrize('testframe', totest_frames)
def test_gcrs_icrs_moonish(testframe):
"""
check that something like the moon goes to about the right distance from the
ICRS origin when starting from GCRS
"""
moonish = GCRS(MOONDIST_CART, obstime=testframe.obstime)
moonicrs = moonish.transform_to(ICRS)
assert 0.97*u.au < moonicrs.distance < 1.03*u.au
@pytest.mark.remote_data
@pytest.mark.parametrize('testframe', totest_frames)
def test_icrs_gcrscirs_sunish(testframe):
"""
check that the ICRS barycenter goes to about the right distance from various
~geocentric frames (other than testframe)
"""
# slight offset to avoid divide-by-zero errors
icrs = ICRS(0*u.deg, 0*u.deg, distance=10*u.km)
gcrs = icrs.transform_to(GCRS(obstime=testframe.obstime))
assert (EARTHECC - 1)*u.au < gcrs.distance.to(u.au) < (EARTHECC + 1)*u.au
cirs = icrs.transform_to(CIRS(obstime=testframe.obstime))
assert (EARTHECC - 1)*u.au < cirs.distance.to(u.au) < (EARTHECC + 1)*u.au
itrs = icrs.transform_to(ITRS(obstime=testframe.obstime))
assert (EARTHECC - 1)*u.au < itrs.spherical.distance.to(u.au) < (EARTHECC + 1)*u.au
@pytest.mark.remote_data
@pytest.mark.parametrize('testframe', totest_frames)
def test_icrs_altaz_moonish(testframe):
"""
Check that something expressed in *ICRS* as being moon-like goes to the
right AltAz distance
"""
# we use epv00 instead of get_sun because get_sun includes aberration
earth_pv_helio, earth_pv_bary = epv00(*get_jd12(testframe.obstime, 'tdb'))
earth_icrs_xyz = earth_pv_bary[0]*u.au
moonoffset = [0, 0, MOONDIST.value]*MOONDIST.unit
moonish_icrs = ICRS(CartesianRepresentation(earth_icrs_xyz + moonoffset))
moonaa = moonish_icrs.transform_to(testframe)
# now check that the distance change is similar to earth radius
assert 1000*u.km < np.abs(moonaa.distance - MOONDIST).to(u.au) < 7000*u.km
def test_gcrs_self_transform_closeby():
"""
Tests GCRS self transform for objects which are nearby and thus
have reasonable parallax.
Moon positions were originally created using JPL DE432s ephemeris.
The two lunar positions (one geocentric, one at a defined location)
are created via a transformation from ICRS to two different GCRS frames.
We test that the GCRS-GCRS self transform can correctly map one GCRS
frame onto the other.
"""
t = Time("2014-12-25T07:00")
moon_geocentric = SkyCoord(GCRS(318.10579159*u.deg,
-11.65281165*u.deg,
365042.64880308*u.km, obstime=t))
# this is the location of the Moon as seen from La Palma
obsgeoloc = [-5592982.59658935, -63054.1948592, 3059763.90102216]*u.m
obsgeovel = [4.59798494, -407.84677071, 0.]*u.m/u.s
moon_lapalma = SkyCoord(GCRS(318.7048445*u.deg,
-11.98761996*u.deg,
369722.8231031*u.km,
obstime=t,
obsgeoloc=obsgeoloc,
obsgeovel=obsgeovel))
transformed = moon_geocentric.transform_to(moon_lapalma.frame)
delta = transformed.separation_3d(moon_lapalma)
assert_allclose(delta, 0.0*u.m, atol=1*u.m)
@pytest.mark.remote_data
@pytest.mark.skipif('not HAS_JPLEPHEM')
def test_ephemerides():
"""
We test that using different ephemerides gives very similar results
for transformations
"""
t = Time("2014-12-25T07:00")
moon = SkyCoord(GCRS(318.10579159*u.deg,
-11.65281165*u.deg,
365042.64880308*u.km, obstime=t))
icrs_frame = ICRS()
hcrs_frame = HCRS(obstime=t)
ecl_frame = HeliocentricMeanEcliptic(equinox=t)
cirs_frame = CIRS(obstime=t)
moon_icrs_builtin = moon.transform_to(icrs_frame)
moon_hcrs_builtin = moon.transform_to(hcrs_frame)
moon_helioecl_builtin = moon.transform_to(ecl_frame)
moon_cirs_builtin = moon.transform_to(cirs_frame)
with solar_system_ephemeris.set('jpl'):
moon_icrs_jpl = moon.transform_to(icrs_frame)
moon_hcrs_jpl = moon.transform_to(hcrs_frame)
moon_helioecl_jpl = moon.transform_to(ecl_frame)
moon_cirs_jpl = moon.transform_to(cirs_frame)
# most transformations should differ by an amount which is
# non-zero but of order milliarcsecs
sep_icrs = moon_icrs_builtin.separation(moon_icrs_jpl)
sep_hcrs = moon_hcrs_builtin.separation(moon_hcrs_jpl)
sep_helioecl = moon_helioecl_builtin.separation(moon_helioecl_jpl)
sep_cirs = moon_cirs_builtin.separation(moon_cirs_jpl)
assert_allclose([sep_icrs, sep_hcrs, sep_helioecl], 0.0*u.deg, atol=10*u.mas)
assert all(sep > 10*u.microarcsecond for sep in (sep_icrs, sep_hcrs, sep_helioecl))
# CIRS should be the same
assert_allclose(sep_cirs, 0.0*u.deg, atol=1*u.microarcsecond)
|
2976bb3171c8545b787bbd1e20804525d966bb393f060481026d5ce2146410b6 |
import pytest
from astropy.tests.helper import assert_quantity_allclose
from astropy.units import allclose as quantity_allclose
from astropy import units as u
from astropy.coordinates import Longitude, Latitude, EarthLocation
from astropy.coordinates.sites import get_builtin_sites, get_downloaded_sites, SiteRegistry
def test_builtin_sites():
reg = get_builtin_sites()
greenwich = reg['greenwich']
lon, lat, el = greenwich.to_geodetic()
assert_quantity_allclose(lon, Longitude('0:0:0', unit=u.deg),
atol=10*u.arcsec)
assert_quantity_allclose(lat, Latitude('51:28:40', unit=u.deg),
atol=1*u.arcsec)
assert_quantity_allclose(el, 46*u.m, atol=1*u.m)
names = reg.names
assert 'greenwich' in names
assert 'example_site' in names
with pytest.raises(KeyError) as exc:
reg['nonexistent site']
assert exc.value.args[0] == "Site 'nonexistent site' not in database. Use the 'names' attribute to see available sites."
@pytest.mark.remote_data(source='astropy')
def test_online_sites():
reg = get_downloaded_sites()
keck = reg['keck']
lon, lat, el = keck.to_geodetic()
assert_quantity_allclose(lon, -Longitude('155:28.7', unit=u.deg),
atol=0.001*u.deg)
assert_quantity_allclose(lat, Latitude('19:49.7', unit=u.deg),
atol=0.001*u.deg)
assert_quantity_allclose(el, 4160*u.m, atol=1*u.m)
names = reg.names
assert 'keck' in names
assert 'ctio' in names
with pytest.raises(KeyError) as exc:
reg['nonexistent site']
assert exc.value.args[0] == "Site 'nonexistent site' not in database. Use the 'names' attribute to see available sites."
with pytest.raises(KeyError) as exc:
reg['kec']
assert exc.value.args[0] == "Site 'kec' not in database. Use the 'names' attribute to see available sites. Did you mean one of: 'keck'?'"
@pytest.mark.remote_data(source='astropy')
# this will *try* the online so we have to make it remote_data, even though it
# could fall back on the non-remote version
def test_EarthLocation_basic():
greenwichel = EarthLocation.of_site('greenwich')
lon, lat, el = greenwichel.to_geodetic()
assert_quantity_allclose(lon, Longitude('0:0:0', unit=u.deg),
atol=10*u.arcsec)
assert_quantity_allclose(lat, Latitude('51:28:40', unit=u.deg),
atol=1*u.arcsec)
assert_quantity_allclose(el, 46*u.m, atol=1*u.m)
names = EarthLocation.get_site_names()
assert 'greenwich' in names
assert 'example_site' in names
with pytest.raises(KeyError) as exc:
EarthLocation.of_site('nonexistent site')
assert exc.value.args[0] == "Site 'nonexistent site' not in database. Use EarthLocation.get_site_names to see available sites."
def test_EarthLocation_state_offline():
EarthLocation._site_registry = None
EarthLocation._get_site_registry(force_builtin=True)
assert EarthLocation._site_registry is not None
oldreg = EarthLocation._site_registry
newreg = EarthLocation._get_site_registry()
assert oldreg is newreg
newreg = EarthLocation._get_site_registry(force_builtin=True)
assert oldreg is not newreg
@pytest.mark.remote_data(source='astropy')
def test_EarthLocation_state_online():
EarthLocation._site_registry = None
EarthLocation._get_site_registry(force_download=True)
assert EarthLocation._site_registry is not None
oldreg = EarthLocation._site_registry
newreg = EarthLocation._get_site_registry()
assert oldreg is newreg
newreg = EarthLocation._get_site_registry(force_download=True)
assert oldreg is not newreg
def test_registry():
reg = SiteRegistry()
assert len(reg.names) == 0
names = ['sitea', 'site A']
loc = EarthLocation.from_geodetic(lat=1*u.deg, lon=2*u.deg, height=3*u.km)
reg.add_site(names, loc)
assert len(reg.names) == 2
loc1 = reg['SIteA']
assert loc1 is loc
loc2 = reg['sIte a']
assert loc2 is loc
def test_non_EarthLocation():
"""
A regression test for a typo bug pointed out at the bottom of
https://github.com/astropy/astropy/pull/4042
"""
class EarthLocation2(EarthLocation):
pass
# This lets keeps us from needing to do remote_data
# note that this does *not* mess up the registry for EarthLocation because
# registry is cached on a per-class basis
EarthLocation2._get_site_registry(force_builtin=True)
el2 = EarthLocation2.of_site('greenwich')
assert type(el2) is EarthLocation2
assert el2.info.name == 'Royal Observatory Greenwich'
def check_builtin_matches_remote(download_url=True):
"""
This function checks that the builtin sites registry is consistent with the
remote registry (or a registry at some other location).
Note that current this is *not* run by the testing suite (because it
doesn't start with "test", and is instead meant to be used as a check
before merging changes in astropy-data)
"""
builtin_registry = EarthLocation._get_site_registry(force_builtin=True)
dl_registry = EarthLocation._get_site_registry(force_download=download_url)
in_dl = {}
matches = {}
for name in builtin_registry.names:
in_dl[name] = name in dl_registry
if in_dl[name]:
matches[name] = quantity_allclose(builtin_registry[name], dl_registry[name])
else:
matches[name] = False
if not all(matches.values()):
# this makes sure we actually see which don't match
print("In builtin registry but not in download:")
for name in in_dl:
if not in_dl[name]:
print(' ', name)
print("In both but not the same value:")
for name in matches:
if not matches[name] and in_dl[name]:
print(' ', name, 'builtin:', builtin_registry[name], 'download:', dl_registry[name])
assert False, "Builtin and download registry aren't consistent - failures printed to stdout"
def test_meta_present():
reg = get_builtin_sites()
greenwich = reg['greenwich']
assert greenwich.info.meta['source'] == ('Ordnance Survey via '
'http://gpsinformation.net/main/greenwich.htm and UNESCO')
|
a2566171fd967f88960a2ff609fc783300925deb2827dd7a520567d8d9ebcda1 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Tests for miscellaneous functionality in the `funcs` module
"""
import pytest
import numpy as np
from numpy import testing as npt
from astropy import units as u
from astropy.time import Time
from astropy._erfa import ErfaWarning
def test_sun():
"""
Test that `get_sun` works and it behaves roughly as it should (in GCRS)
"""
from astropy.coordinates.funcs import get_sun
northern_summer_solstice = Time('2010-6-21')
northern_winter_solstice = Time('2010-12-21')
equinox_1 = Time('2010-3-21')
equinox_2 = Time('2010-9-21')
gcrs1 = get_sun(equinox_1)
assert np.abs(gcrs1.dec.deg) < 1
gcrs2 = get_sun(Time([northern_summer_solstice, equinox_2, northern_winter_solstice]))
assert np.all(np.abs(gcrs2.dec - [23.5, 0, -23.5]*u.deg) < 1*u.deg)
def test_constellations(recwarn):
from astropy.coordinates import ICRS, FK5, SkyCoord
from astropy.coordinates.funcs import get_constellation
inuma = ICRS(9*u.hour, 65*u.deg)
n_prewarn = len(recwarn)
res = get_constellation(inuma)
res_short = get_constellation(inuma, short_name=True)
assert len(recwarn) == n_prewarn # neither version should not make warnings
assert res == 'Ursa Major'
assert res_short == 'UMa'
assert isinstance(res, str) or getattr(res, 'shape', None) == tuple()
# these are taken from the ReadMe for Roman 1987
ras = [9, 23.5, 5.12, 9.4555, 12.8888, 15.6687, 19, 6.2222]
decs = [65, -20, 9.12, -19.9, 22, -12.1234, -40, -81.1234]
shortnames = ['UMa', 'Aqr', 'Ori', 'Hya', 'Com', 'Lib', 'CrA', 'Men']
testcoos = FK5(ras*u.hour, decs*u.deg, equinox='B1950')
npt.assert_equal(get_constellation(testcoos, short_name=True), shortnames)
# test on a SkyCoord, *and* test Boötes, which is special in that it has a
# non-ASCII character
bootest = SkyCoord(15*u.hour, 30*u.deg, frame='icrs')
boores = get_constellation(bootest)
assert boores == u'Boötes'
assert isinstance(boores, str) or getattr(boores, 'shape', None) == tuple()
def test_concatenate():
from astropy.coordinates import FK5, SkyCoord, ICRS
from astropy.coordinates.funcs import concatenate
# Just positions
fk5 = FK5(1*u.deg, 2*u.deg)
sc = SkyCoord(3*u.deg, 4*u.deg, frame='fk5')
res = concatenate([fk5, sc])
np.testing.assert_allclose(res.ra, [1, 3]*u.deg)
np.testing.assert_allclose(res.dec, [2, 4]*u.deg)
with pytest.raises(TypeError):
concatenate(fk5)
with pytest.raises(TypeError):
concatenate(1*u.deg)
# positions and velocities
fr = ICRS(ra=10*u.deg, dec=11.*u.deg,
pm_ra_cosdec=12*u.mas/u.yr,
pm_dec=13*u.mas/u.yr)
sc = SkyCoord(ra=20*u.deg, dec=21.*u.deg,
pm_ra_cosdec=22*u.mas/u.yr,
pm_dec=23*u.mas/u.yr)
res = concatenate([fr, sc])
with pytest.raises(ValueError):
concatenate([fr, fk5])
fr2 = ICRS(ra=10*u.deg, dec=11.*u.deg)
with pytest.raises(ValueError):
concatenate([fr, fr2])
def test_concatenate_representations():
from astropy.coordinates.funcs import concatenate_representations
from astropy.coordinates import representation as r
reps = [r.CartesianRepresentation([1, 2, 3.]*u.kpc),
r.SphericalRepresentation(lon=1*u.deg, lat=2.*u.deg,
distance=10*u.pc),
r.UnitSphericalRepresentation(lon=1*u.deg, lat=2.*u.deg),
r.CartesianRepresentation(np.ones((3, 100)) * u.kpc),
r.CartesianRepresentation(np.ones((3, 16, 8)) * u.kpc)]
reps.append(reps[0].with_differentials(
r.CartesianDifferential([1, 2, 3.] * u.km/u.s)))
reps.append(reps[1].with_differentials(
r.SphericalCosLatDifferential(1*u.mas/u.yr, 2*u.mas/u.yr, 3*u.km/u.s)))
reps.append(reps[2].with_differentials(
r.SphericalCosLatDifferential(1*u.mas/u.yr, 2*u.mas/u.yr, 3*u.km/u.s)))
reps.append(reps[2].with_differentials(
r.UnitSphericalCosLatDifferential(1*u.mas/u.yr, 2*u.mas/u.yr)))
reps.append(reps[2].with_differentials(
{'s': r.RadialDifferential(1*u.km/u.s)}))
reps.append(reps[3].with_differentials(
r.CartesianDifferential(*np.ones((3, 100)) * u.km/u.s)))
reps.append(reps[4].with_differentials(
r.CartesianDifferential(*np.ones((3, 16, 8)) * u.km/u.s)))
# Test that combining all of the above with itself succeeds
for rep in reps:
if not rep.shape:
expected_shape = (2, )
else:
expected_shape = (2 * rep.shape[0], ) + rep.shape[1:]
tmp = concatenate_representations((rep, rep))
assert tmp.shape == expected_shape
if 's' in rep.differentials:
assert tmp.differentials['s'].shape == expected_shape
# Try combining 4, just for something different
for rep in reps:
if not rep.shape:
expected_shape = (4, )
else:
expected_shape = (4 * rep.shape[0], ) + rep.shape[1:]
tmp = concatenate_representations((rep, rep, rep, rep))
assert tmp.shape == expected_shape
if 's' in rep.differentials:
assert tmp.differentials['s'].shape == expected_shape
# Test that combining pairs fails
with pytest.raises(TypeError):
concatenate_representations((reps[0], reps[1]))
with pytest.raises(ValueError):
concatenate_representations((reps[0], reps[5]))
# Check that passing in a single object fails
with pytest.raises(TypeError):
concatenate_representations(reps[0])
|
72af72ee93e8138e36465ded5445638304897b59a4aed0ece8cfbd7ae44da7b8 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Tests for the SkyCoord class. Note that there are also SkyCoord tests in
test_api_ape5.py
"""
import copy
import pytest
import numpy as np
import numpy.testing as npt
from astropy import units as u
from astropy.tests.helper import assert_quantity_allclose as assert_allclose
from astropy.coordinates.representation import REPRESENTATION_CLASSES
from astropy.coordinates import (ICRS, FK4, FK5, Galactic, SkyCoord, Angle,
SphericalRepresentation, CartesianRepresentation,
UnitSphericalRepresentation, AltAz,
BaseCoordinateFrame, Attribute,
frame_transform_graph, RepresentationMapping)
from astropy.coordinates import Latitude, EarthLocation
from astropy.time import Time
from astropy.utils import minversion, isiterable
from astropy.utils.compat import NUMPY_LT_1_14
from astropy.units import allclose as quantity_allclose
from astropy.io import fits
from astropy.wcs import WCS
RA = 1.0 * u.deg
DEC = 2.0 * u.deg
C_ICRS = ICRS(RA, DEC)
C_FK5 = C_ICRS.transform_to(FK5)
J2001 = Time('J2001')
def allclose(a, b, rtol=0.0, atol=None):
if atol is None:
atol = 1.e-8 * getattr(a, 'unit', 1.)
return quantity_allclose(a, b, rtol, atol)
try:
import scipy
HAS_SCIPY = True
except ImportError:
HAS_SCIPY = False
if HAS_SCIPY and minversion(scipy, '0.12.0', inclusive=False):
OLDER_SCIPY = False
else:
OLDER_SCIPY = True
def test_transform_to():
for frame in (FK5, FK5(equinox=Time('J1975.0')),
FK4, FK4(equinox=Time('J1975.0')),
SkyCoord(RA, DEC, frame='fk4', equinox='J1980')):
c_frame = C_ICRS.transform_to(frame)
s_icrs = SkyCoord(RA, DEC, frame='icrs')
s_frame = s_icrs.transform_to(frame)
assert allclose(c_frame.ra, s_frame.ra)
assert allclose(c_frame.dec, s_frame.dec)
assert allclose(c_frame.distance, s_frame.distance)
# set up for parametrized test
rt_sets = []
rt_frames = [ICRS, FK4, FK5, Galactic]
for rt_frame0 in rt_frames:
for rt_frame1 in rt_frames:
for equinox0 in (None, 'J1975.0'):
for obstime0 in (None, 'J1980.0'):
for equinox1 in (None, 'J1975.0'):
for obstime1 in (None, 'J1980.0'):
rt_sets.append((rt_frame0, rt_frame1,
equinox0, equinox1,
obstime0, obstime1))
rt_args = ('frame0', 'frame1', 'equinox0', 'equinox1', 'obstime0', 'obstime1')
@pytest.mark.parametrize(rt_args, rt_sets)
def test_round_tripping(frame0, frame1, equinox0, equinox1, obstime0, obstime1):
"""
Test round tripping out and back using transform_to in every combination.
"""
attrs0 = {'equinox': equinox0, 'obstime': obstime0}
attrs1 = {'equinox': equinox1, 'obstime': obstime1}
# Remove None values
attrs0 = dict((k, v) for k, v in attrs0.items() if v is not None)
attrs1 = dict((k, v) for k, v in attrs1.items() if v is not None)
# Go out and back
sc = SkyCoord(RA, DEC, frame=frame0, **attrs0)
# Keep only frame attributes for frame1
attrs1 = dict((attr, val) for attr, val in attrs1.items()
if attr in frame1.get_frame_attr_names())
sc2 = sc.transform_to(frame1(**attrs1))
# When coming back only keep frame0 attributes for transform_to
attrs0 = dict((attr, val) for attr, val in attrs0.items()
if attr in frame0.get_frame_attr_names())
# also, if any are None, fill in with defaults
for attrnm in frame0.get_frame_attr_names():
if attrs0.get(attrnm, None) is None:
if attrnm == 'obstime' and frame0.get_frame_attr_names()[attrnm] is None:
if 'equinox' in attrs0:
attrs0[attrnm] = attrs0['equinox']
else:
attrs0[attrnm] = frame0.get_frame_attr_names()[attrnm]
sc_rt = sc2.transform_to(frame0(**attrs0))
if frame0 is Galactic:
assert allclose(sc.l, sc_rt.l)
assert allclose(sc.b, sc_rt.b)
else:
assert allclose(sc.ra, sc_rt.ra)
assert allclose(sc.dec, sc_rt.dec)
if equinox0:
assert type(sc.equinox) is Time and sc.equinox == sc_rt.equinox
if obstime0:
assert type(sc.obstime) is Time and sc.obstime == sc_rt.obstime
def test_coord_init_string():
"""
Spherical or Cartesian represenation input coordinates.
"""
sc = SkyCoord('1d 2d')
assert allclose(sc.ra, 1 * u.deg)
assert allclose(sc.dec, 2 * u.deg)
sc = SkyCoord('1d', '2d')
assert allclose(sc.ra, 1 * u.deg)
assert allclose(sc.dec, 2 * u.deg)
sc = SkyCoord('1°2′3″', '2°3′4″')
assert allclose(sc.ra, Angle('1°2′3″'))
assert allclose(sc.dec, Angle('2°3′4″'))
sc = SkyCoord('1°2′3″ 2°3′4″')
assert allclose(sc.ra, Angle('1°2′3″'))
assert allclose(sc.dec, Angle('2°3′4″'))
with pytest.raises(ValueError) as err:
SkyCoord('1d 2d 3d')
assert "Cannot parse first argument data" in str(err)
sc1 = SkyCoord('8 00 00 +5 00 00.0', unit=(u.hour, u.deg), frame='icrs')
assert isinstance(sc1, SkyCoord)
assert allclose(sc1.ra, Angle(120 * u.deg))
assert allclose(sc1.dec, Angle(5 * u.deg))
sc11 = SkyCoord('8h00m00s+5d00m00.0s', unit=(u.hour, u.deg), frame='icrs')
assert isinstance(sc11, SkyCoord)
assert allclose(sc1.ra, Angle(120 * u.deg))
assert allclose(sc1.dec, Angle(5 * u.deg))
sc2 = SkyCoord('8 00 -5 00 00.0', unit=(u.hour, u.deg), frame='icrs')
assert isinstance(sc2, SkyCoord)
assert allclose(sc2.ra, Angle(120 * u.deg))
assert allclose(sc2.dec, Angle(-5 * u.deg))
sc3 = SkyCoord('8 00 -5 00.6', unit=(u.hour, u.deg), frame='icrs')
assert isinstance(sc3, SkyCoord)
assert allclose(sc3.ra, Angle(120 * u.deg))
assert allclose(sc3.dec, Angle(-5.01 * u.deg))
sc4 = SkyCoord('J080000.00-050036.00', unit=(u.hour, u.deg), frame='icrs')
assert isinstance(sc4, SkyCoord)
assert allclose(sc4.ra, Angle(120 * u.deg))
assert allclose(sc4.dec, Angle(-5.01 * u.deg))
sc41 = SkyCoord('J080000+050036', unit=(u.hour, u.deg), frame='icrs')
assert isinstance(sc41, SkyCoord)
assert allclose(sc41.ra, Angle(120 * u.deg))
assert allclose(sc41.dec, Angle(+5.01 * u.deg))
sc5 = SkyCoord('8h00.6m -5d00.6m', unit=(u.hour, u.deg), frame='icrs')
assert isinstance(sc5, SkyCoord)
assert allclose(sc5.ra, Angle(120.15 * u.deg))
assert allclose(sc5.dec, Angle(-5.01 * u.deg))
sc6 = SkyCoord('8h00.6m -5d00.6m', unit=(u.hour, u.deg), frame='fk4')
assert isinstance(sc6, SkyCoord)
assert allclose(sc6.ra, Angle(120.15 * u.deg))
assert allclose(sc6.dec, Angle(-5.01 * u.deg))
sc61 = SkyCoord('8h00.6m-5d00.6m', unit=(u.hour, u.deg), frame='fk4')
assert isinstance(sc61, SkyCoord)
assert allclose(sc6.ra, Angle(120.15 * u.deg))
assert allclose(sc6.dec, Angle(-5.01 * u.deg))
sc61 = SkyCoord('8h00.6-5d00.6', unit=(u.hour, u.deg), frame='fk4')
assert isinstance(sc61, SkyCoord)
assert allclose(sc6.ra, Angle(120.15 * u.deg))
assert allclose(sc6.dec, Angle(-5.01 * u.deg))
sc7 = SkyCoord("J1874221.60+122421.6", unit=u.deg)
assert isinstance(sc7, SkyCoord)
assert allclose(sc7.ra, Angle(187.706 * u.deg))
assert allclose(sc7.dec, Angle(12.406 * u.deg))
with pytest.raises(ValueError):
SkyCoord('8 00 -5 00.6', unit=(u.deg, u.deg), frame='galactic')
def test_coord_init_unit():
"""
Test variations of the unit keyword.
"""
for unit in ('deg', 'deg,deg', ' deg , deg ', u.deg, (u.deg, u.deg),
np.array(['deg', 'deg'])):
sc = SkyCoord(1, 2, unit=unit)
assert allclose(sc.ra, Angle(1 * u.deg))
assert allclose(sc.dec, Angle(2 * u.deg))
for unit in ('hourangle', 'hourangle,hourangle', ' hourangle , hourangle ',
u.hourangle, [u.hourangle, u.hourangle]):
sc = SkyCoord(1, 2, unit=unit)
assert allclose(sc.ra, Angle(15 * u.deg))
assert allclose(sc.dec, Angle(30 * u.deg))
for unit in ('hourangle,deg', (u.hourangle, u.deg)):
sc = SkyCoord(1, 2, unit=unit)
assert allclose(sc.ra, Angle(15 * u.deg))
assert allclose(sc.dec, Angle(2 * u.deg))
for unit in ('deg,deg,deg,deg', [u.deg, u.deg, u.deg, u.deg], None):
with pytest.raises(ValueError) as err:
SkyCoord(1, 2, unit=unit)
assert 'Unit keyword must have one to three unit values' in str(err)
for unit in ('m', (u.m, u.deg), ''):
with pytest.raises(u.UnitsError) as err:
SkyCoord(1, 2, unit=unit)
def test_coord_init_list():
"""
Spherical or Cartesian representation input coordinates.
"""
sc = SkyCoord([('1d', '2d'),
(1 * u.deg, 2 * u.deg),
'1d 2d',
('1°', '2°'),
'1° 2°'], unit='deg')
assert allclose(sc.ra, Angle('1d'))
assert allclose(sc.dec, Angle('2d'))
with pytest.raises(ValueError) as err:
SkyCoord(['1d 2d 3d'])
assert "Cannot parse first argument data" in str(err)
with pytest.raises(ValueError) as err:
SkyCoord([('1d', '2d', '3d')])
assert "Cannot parse first argument data" in str(err)
sc = SkyCoord([1 * u.deg, 1 * u.deg], [2 * u.deg, 2 * u.deg])
assert allclose(sc.ra, Angle('1d'))
assert allclose(sc.dec, Angle('2d'))
with pytest.raises(ValueError) as err:
SkyCoord([1 * u.deg, 2 * u.deg]) # this list is taken as RA w/ missing dec
assert "One or more elements of input sequence does not have a length" in str(err)
def test_coord_init_array():
"""
Input in the form of a list array or numpy array
"""
for a in (['1 2', '3 4'],
[['1', '2'], ['3', '4']],
[[1, 2], [3, 4]]):
sc = SkyCoord(a, unit='deg')
assert allclose(sc.ra - [1, 3] * u.deg, 0 * u.deg)
assert allclose(sc.dec - [2, 4] * u.deg, 0 * u.deg)
sc = SkyCoord(np.array(a), unit='deg')
assert allclose(sc.ra - [1, 3] * u.deg, 0 * u.deg)
assert allclose(sc.dec - [2, 4] * u.deg, 0 * u.deg)
def test_coord_init_representation():
"""
Spherical or Cartesian represenation input coordinates.
"""
coord = SphericalRepresentation(lon=8 * u.deg, lat=5 * u.deg, distance=1 * u.kpc)
sc = SkyCoord(coord, frame='icrs')
assert allclose(sc.ra, coord.lon)
assert allclose(sc.dec, coord.lat)
assert allclose(sc.distance, coord.distance)
with pytest.raises(ValueError) as err:
SkyCoord(coord, frame='icrs', ra='1d')
assert "conflicts with keyword argument 'ra'" in str(err)
coord = CartesianRepresentation(1 * u.one, 2 * u.one, 3 * u.one)
sc = SkyCoord(coord, frame='icrs')
sc_cart = sc.represent_as(CartesianRepresentation)
assert allclose(sc_cart.x, 1.0)
assert allclose(sc_cart.y, 2.0)
assert allclose(sc_cart.z, 3.0)
def test_frame_init():
"""
Different ways of providing the frame.
"""
sc = SkyCoord(RA, DEC, frame='icrs')
assert sc.frame.name == 'icrs'
sc = SkyCoord(RA, DEC, frame=ICRS)
assert sc.frame.name == 'icrs'
sc = SkyCoord(sc)
assert sc.frame.name == 'icrs'
sc = SkyCoord(C_ICRS)
assert sc.frame.name == 'icrs'
SkyCoord(C_ICRS, frame='icrs')
assert sc.frame.name == 'icrs'
with pytest.raises(ValueError) as err:
SkyCoord(C_ICRS, frame='galactic')
assert 'Cannot override frame=' in str(err)
def test_attr_inheritance():
"""
When initializing from an existing coord the representation attrs like
equinox should be inherited to the SkyCoord. If there is a conflict
then raise an exception.
"""
sc = SkyCoord(1, 2, frame='icrs', unit='deg', equinox='J1999', obstime='J2001')
sc2 = SkyCoord(sc)
assert sc2.equinox == sc.equinox
assert sc2.obstime == sc.obstime
assert allclose(sc2.ra, sc.ra)
assert allclose(sc2.dec, sc.dec)
assert allclose(sc2.distance, sc.distance)
sc2 = SkyCoord(sc.frame) # Doesn't have equinox there so we get FK4 defaults
assert sc2.equinox != sc.equinox
assert sc2.obstime != sc.obstime
assert allclose(sc2.ra, sc.ra)
assert allclose(sc2.dec, sc.dec)
assert allclose(sc2.distance, sc.distance)
sc = SkyCoord(1, 2, frame='fk4', unit='deg', equinox='J1999', obstime='J2001')
sc2 = SkyCoord(sc)
assert sc2.equinox == sc.equinox
assert sc2.obstime == sc.obstime
assert allclose(sc2.ra, sc.ra)
assert allclose(sc2.dec, sc.dec)
assert allclose(sc2.distance, sc.distance)
sc2 = SkyCoord(sc.frame) # sc.frame has equinox, obstime
assert sc2.equinox == sc.equinox
assert sc2.obstime == sc.obstime
assert allclose(sc2.ra, sc.ra)
assert allclose(sc2.dec, sc.dec)
assert allclose(sc2.distance, sc.distance)
def test_attr_conflicts():
"""
Check conflicts resolution between coordinate attributes and init kwargs.
"""
sc = SkyCoord(1, 2, frame='icrs', unit='deg', equinox='J1999', obstime='J2001')
# OK if attrs both specified but with identical values
SkyCoord(sc, equinox='J1999', obstime='J2001')
# OK because sc.frame doesn't have obstime
SkyCoord(sc.frame, equinox='J1999', obstime='J2100')
# Not OK if attrs don't match
with pytest.raises(ValueError) as err:
SkyCoord(sc, equinox='J1999', obstime='J2002')
assert "Coordinate attribute 'obstime'=" in str(err)
# Same game but with fk4 which has equinox and obstime frame attrs
sc = SkyCoord(1, 2, frame='fk4', unit='deg', equinox='J1999', obstime='J2001')
# OK if attrs both specified but with identical values
SkyCoord(sc, equinox='J1999', obstime='J2001')
# Not OK if SkyCoord attrs don't match
with pytest.raises(ValueError) as err:
SkyCoord(sc, equinox='J1999', obstime='J2002')
assert "Frame attribute 'obstime' has conflicting" in str(err)
# Not OK because sc.frame has different attrs
with pytest.raises(ValueError) as err:
SkyCoord(sc.frame, equinox='J1999', obstime='J2002')
assert "Frame attribute 'obstime' has conflicting" in str(err)
def test_frame_attr_getattr():
"""
When accessing frame attributes like equinox, the value should come
from self.frame when that object has the relevant attribute, otherwise
from self.
"""
sc = SkyCoord(1, 2, frame='icrs', unit='deg', equinox='J1999', obstime='J2001')
assert sc.equinox == 'J1999' # Just the raw value (not validated)
assert sc.obstime == 'J2001'
sc = SkyCoord(1, 2, frame='fk4', unit='deg', equinox='J1999', obstime='J2001')
assert sc.equinox == Time('J1999') # Coming from the self.frame object
assert sc.obstime == Time('J2001')
sc = SkyCoord(1, 2, frame='fk4', unit='deg', equinox='J1999')
assert sc.equinox == Time('J1999')
assert sc.obstime == Time('J1999')
def test_to_string():
"""
Basic testing of converting SkyCoord to strings. This just tests
for a single input coordinate and and 1-element list. It does not
test the underlying `Angle.to_string` method itself.
"""
coord = '1h2m3s 1d2m3s'
for wrap in (lambda x: x, lambda x: [x]):
sc = SkyCoord(wrap(coord))
assert sc.to_string() == wrap('15.5125 1.03417')
assert sc.to_string('dms') == wrap('15d30m45s 1d02m03s')
assert sc.to_string('hmsdms') == wrap('01h02m03s +01d02m03s')
with_kwargs = sc.to_string('hmsdms', precision=3, pad=True, alwayssign=True)
assert with_kwargs == wrap('+01h02m03.000s +01d02m03.000s')
def test_seps():
sc1 = SkyCoord(0 * u.deg, 1 * u.deg, frame='icrs')
sc2 = SkyCoord(0 * u.deg, 2 * u.deg, frame='icrs')
sep = sc1.separation(sc2)
assert (sep - 1 * u.deg)/u.deg < 1e-10
with pytest.raises(ValueError):
sc1.separation_3d(sc2)
sc3 = SkyCoord(1 * u.deg, 1 * u.deg, distance=1 * u.kpc, frame='icrs')
sc4 = SkyCoord(1 * u.deg, 1 * u.deg, distance=2 * u.kpc, frame='icrs')
sep3d = sc3.separation_3d(sc4)
assert sep3d == 1 * u.kpc
def test_repr():
sc1 = SkyCoord(0 * u.deg, 1 * u.deg, frame='icrs')
sc2 = SkyCoord(1 * u.deg, 1 * u.deg, frame='icrs', distance=1 * u.kpc)
assert repr(sc1) == ('<SkyCoord (ICRS): (ra, dec) in deg\n'
' ({})>').format(' 0., 1.' if NUMPY_LT_1_14 else
'0., 1.')
assert repr(sc2) == ('<SkyCoord (ICRS): (ra, dec, distance) in (deg, deg, kpc)\n'
' ({})>').format(' 1., 1., 1.' if NUMPY_LT_1_14
else '1., 1., 1.')
sc3 = SkyCoord(0.25 * u.deg, [1, 2.5] * u.deg, frame='icrs')
assert repr(sc3).startswith('<SkyCoord (ICRS): (ra, dec) in deg\n')
sc_default = SkyCoord(0 * u.deg, 1 * u.deg)
assert repr(sc_default) == ('<SkyCoord (ICRS): (ra, dec) in deg\n'
' ({})>').format(' 0., 1.' if NUMPY_LT_1_14
else '0., 1.')
@pytest.mark.remote_data
def test_repr_altaz():
sc2 = SkyCoord(1 * u.deg, 1 * u.deg, frame='icrs', distance=1 * u.kpc)
loc = EarthLocation(-2309223 * u.m, -3695529 * u.m, -4641767 * u.m)
time = Time('2005-03-21 00:00:00')
sc4 = sc2.transform_to(AltAz(location=loc, obstime=time))
assert repr(sc4).startswith("<SkyCoord (AltAz: obstime=2005-03-21 00:00:00.000, "
"location=(-2309223., -3695529., "
"-4641767.) m, pressure=0.0 hPa, "
"temperature=0.0 deg_C, relative_humidity=0.0, "
"obswl=1.0 micron): (az, alt, distance) in "
"(deg, deg, m)\n")
def test_ops():
"""
Tests miscellaneous operations like `len`
"""
sc = SkyCoord(0 * u.deg, 1 * u.deg, frame='icrs')
sc_arr = SkyCoord(0 * u.deg, [1, 2] * u.deg, frame='icrs')
sc_empty = SkyCoord([] * u.deg, [] * u.deg, frame='icrs')
assert sc.isscalar
assert not sc_arr.isscalar
assert not sc_empty.isscalar
with pytest.raises(TypeError):
len(sc)
assert len(sc_arr) == 2
assert len(sc_empty) == 0
assert bool(sc)
assert bool(sc_arr)
assert not bool(sc_empty)
assert sc_arr[0].isscalar
assert len(sc_arr[:1]) == 1
# A scalar shouldn't be indexable
with pytest.raises(TypeError):
sc[0:]
# but it should be possible to just get an item
sc_item = sc[()]
assert sc_item.shape == ()
# and to turn it into an array
sc_1d = sc[np.newaxis]
assert sc_1d.shape == (1,)
with pytest.raises(TypeError):
iter(sc)
assert not isiterable(sc)
assert isiterable(sc_arr)
assert isiterable(sc_empty)
it = iter(sc_arr)
assert next(it).dec == sc_arr[0].dec
assert next(it).dec == sc_arr[1].dec
with pytest.raises(StopIteration):
next(it)
def test_none_transform():
"""
Ensure that transforming from a SkyCoord with no frame provided works like
ICRS
"""
sc = SkyCoord(0 * u.deg, 1 * u.deg)
sc_arr = SkyCoord(0 * u.deg, [1, 2] * u.deg)
sc2 = sc.transform_to(ICRS)
assert sc.ra == sc2.ra and sc.dec == sc2.dec
sc5 = sc.transform_to('fk5')
assert sc5.ra == sc2.transform_to('fk5').ra
sc_arr2 = sc_arr.transform_to(ICRS)
sc_arr5 = sc_arr.transform_to('fk5')
npt.assert_array_equal(sc_arr5.ra, sc_arr2.transform_to('fk5').ra)
def test_position_angle():
c1 = SkyCoord(0*u.deg, 0*u.deg)
c2 = SkyCoord(1*u.deg, 0*u.deg)
assert_allclose(c1.position_angle(c2) - 90.0 * u.deg, 0*u.deg)
c3 = SkyCoord(1*u.deg, 0.1*u.deg)
assert c1.position_angle(c3) < 90*u.deg
c4 = SkyCoord(0*u.deg, 1*u.deg)
assert_allclose(c1.position_angle(c4), 0*u.deg)
carr1 = SkyCoord(0*u.deg, [0, 1, 2]*u.deg)
carr2 = SkyCoord([-1, -2, -3]*u.deg, [0.1, 1.1, 2.1]*u.deg)
res = carr1.position_angle(carr2)
assert res.shape == (3,)
assert np.all(res < 360*u.degree)
assert np.all(res > 270*u.degree)
cicrs = SkyCoord(0*u.deg, 0*u.deg, frame='icrs')
cfk5 = SkyCoord(1*u.deg, 0*u.deg, frame='fk5')
# because of the frame transform, it's just a *bit* more than 90 degrees
assert cicrs.position_angle(cfk5) > 90.0 * u.deg
assert cicrs.position_angle(cfk5) < 91.0 * u.deg
def test_position_angle_directly():
"""Regression check for #3800: position_angle should accept floats."""
from astropy.coordinates.angle_utilities import position_angle
result = position_angle(10., 20., 10., 20.)
assert result.unit is u.radian
assert result.value == 0.
def test_sep_pa_equivalence():
"""Regression check for bug in #5702.
PA and separation from object 1 to 2 should be consistent with those
from 2 to 1
"""
cfk5 = SkyCoord(1*u.deg, 0*u.deg, frame='fk5')
cfk5B1950 = SkyCoord(1*u.deg, 0*u.deg, frame='fk5', equinox='B1950')
# test with both default and explicit equinox #5722 and #3106
sep_forward = cfk5.separation(cfk5B1950)
sep_backward = cfk5B1950.separation(cfk5)
assert sep_forward != 0 and sep_backward != 0
assert_allclose(sep_forward, sep_backward)
posang_forward = cfk5.position_angle(cfk5B1950)
posang_backward = cfk5B1950.position_angle(cfk5)
assert posang_forward != 0 and posang_backward != 0
assert 179 < (posang_forward - posang_backward).wrap_at(360*u.deg).degree < 181
dcfk5 = SkyCoord(1*u.deg, 0*u.deg, frame='fk5', distance=1*u.pc)
dcfk5B1950 = SkyCoord(1*u.deg, 0*u.deg, frame='fk5', equinox='B1950',
distance=1.*u.pc)
sep3d_forward = dcfk5.separation_3d(dcfk5B1950)
sep3d_backward = dcfk5B1950.separation_3d(dcfk5)
assert sep3d_forward != 0 and sep3d_backward != 0
assert_allclose(sep3d_forward, sep3d_backward)
def test_directional_offset_by():
# Round-trip tests: where is sc2 from sc1?
# Use those offsets from sc1 and verify you get to sc2.
npoints = 7 # How many points when doing vectors of SkyCoords
for sc1 in [SkyCoord(0*u.deg,-90*u.deg), # South pole
SkyCoord(0 * u.deg, 90 * u.deg), # North pole
SkyCoord(1*u.deg,2*u.deg),
SkyCoord(np.linspace(0,359,npoints),np.linspace(-90, 90,npoints),
unit=u.deg, frame='fk4'),
SkyCoord(np.linspace(359,0,npoints),np.linspace(-90, 90,npoints),
unit=u.deg, frame='icrs'),
SkyCoord(np.linspace(-3,3,npoints),np.linspace(-90, 90,npoints),
unit=(u.rad, u.deg), frame='barycentricmeanecliptic')]:
for sc2 in [SkyCoord(5*u.deg,10*u.deg),
SkyCoord(np.linspace(0, 359, npoints), np.linspace(-90, 90, npoints),
unit=u.deg, frame='galactic')]:
# Find the displacement from sc1 to sc2,
posang = sc1.position_angle(sc2)
sep = sc1.separation(sc2)
# then do the offset from sc1 and verify that you are at sc2
sc2a = sc1.directional_offset_by(position_angle=posang, separation=sep)
assert np.max(np.abs(sc2.separation(sc2a).arcsec)) < 1e-3
# Specific test cases
# Go over the North pole a little way, and
# over the South pole a long way, to get to same spot
sc1 = SkyCoord(0*u.deg, 89*u.deg)
for posang,sep in [(0*u.deg, 2*u.deg), (180*u.deg, 358*u.deg)]:
sc2 = sc1.directional_offset_by(posang, sep)
assert allclose([sc2.ra.degree, sc2.dec.degree], [180, 89])
# Go twice as far to ensure that dec is actually changing
# and that >360deg is supported
sc2 = sc1.directional_offset_by(posang, 2*sep)
assert allclose([sc2.ra.degree, sc2.dec.degree], [180, 87])
# Verify that a separation of 180 deg in any direction gets to the antipode
# and 360 deg returns to start
sc1 = SkyCoord(10*u.deg, 47*u.deg)
for posang in np.linspace(0, 377, npoints):
sc2 = sc1.directional_offset_by(posang, 180*u.deg)
assert allclose([sc2.ra.degree, sc2.dec.degree], [190, -47])
sc2 = sc1.directional_offset_by(posang, 360*u.deg)
assert allclose([sc2.ra.degree, sc2.dec.degree], [10, 47])
# Verify that a 90 degree posang, which means East
# corresponds to an increase in RA, by ~separation/cos(dec) and
# a slight convergence to equator
sc1 = SkyCoord(10*u.deg, 60*u.deg)
sc2 = sc1.directional_offset_by(90*u.deg, 1.0*u.deg)
assert 11.9 < sc2.ra.degree < 12.0
assert 59.9 < sc2.dec.degree < 60.0
def test_table_to_coord():
"""
Checks "end-to-end" use of `Table` with `SkyCoord` - the `Quantity`
initializer is the intermediary that translate the table columns into
something coordinates understands.
(Regression test for #1762 )
"""
from astropy.table import Table, Column
t = Table()
t.add_column(Column(data=[1, 2, 3], name='ra', unit=u.deg))
t.add_column(Column(data=[4, 5, 6], name='dec', unit=u.deg))
c = SkyCoord(t['ra'], t['dec'])
assert allclose(c.ra.to(u.deg), [1, 2, 3] * u.deg)
assert allclose(c.dec.to(u.deg), [4, 5, 6] * u.deg)
def assert_quantities_allclose(coord, q1s, attrs):
"""
Compare two tuples of quantities. This assumes that the values in q1 are of
order(1) and uses atol=1e-13, rtol=0. It also asserts that the units of the
two quantities are the *same*, in order to check that the representation
output has the expected units.
"""
q2s = [getattr(coord, attr) for attr in attrs]
assert len(q1s) == len(q2s)
for q1, q2 in zip(q1s, q2s):
assert q1.shape == q2.shape
assert allclose(q1, q2, rtol=0, atol=1e-13 * q1.unit)
# Sets of inputs corresponding to Galactic frame
base_unit_attr_sets = [
('spherical', u.karcsec, u.karcsec, u.kpc, Latitude, 'l', 'b', 'distance'),
('unitspherical', u.karcsec, u.karcsec, None, Latitude, 'l', 'b', None),
('physicsspherical', u.karcsec, u.karcsec, u.kpc, Angle, 'phi', 'theta', 'r'),
('cartesian', u.km, u.km, u.km, u.Quantity, 'u', 'v', 'w'),
('cylindrical', u.km, u.karcsec, u.km, Angle, 'rho', 'phi', 'z')
]
units_attr_sets = []
for base_unit_attr_set in base_unit_attr_sets:
repr_name = base_unit_attr_set[0]
for representation in (repr_name, REPRESENTATION_CLASSES[repr_name]):
for c1, c2, c3 in ((1, 2, 3), ([1], [2], [3])):
for arrayify in True, False:
if arrayify:
c1 = np.array(c1)
c2 = np.array(c2)
c3 = np.array(c3)
units_attr_sets.append(base_unit_attr_set + (representation, c1, c2, c3))
units_attr_args = ('repr_name', 'unit1', 'unit2', 'unit3', 'cls2', 'attr1', 'attr2', 'attr3', 'representation', 'c1', 'c2', 'c3')
@pytest.mark.parametrize(units_attr_args,
[x for x in units_attr_sets if x[0] != 'unitspherical'])
def test_skycoord_three_components(repr_name, unit1, unit2, unit3, cls2, attr1, attr2, attr3,
representation, c1, c2, c3):
"""
Tests positional inputs using components (COMP1, COMP2, COMP3)
and various representations. Use weird units and Galactic frame.
"""
sc = SkyCoord(c1, c2, c3, unit=(unit1, unit2, unit3),
representation_type=representation,
frame=Galactic)
assert_quantities_allclose(sc, (c1*unit1, c2*unit2, c3*unit3),
(attr1, attr2, attr3))
sc = SkyCoord(1000*c1*u.Unit(unit1/1000), cls2(c2, unit=unit2),
1000*c3*u.Unit(unit3/1000), frame=Galactic,
unit=(unit1, unit2, unit3), representation_type=representation)
assert_quantities_allclose(sc, (c1*unit1, c2*unit2, c3*unit3),
(attr1, attr2, attr3))
kwargs = {attr3: c3}
sc = SkyCoord(c1, c2, unit=(unit1, unit2, unit3),
frame=Galactic,
representation_type=representation, **kwargs)
assert_quantities_allclose(sc, (c1*unit1, c2*unit2, c3*unit3),
(attr1, attr2, attr3))
kwargs = {attr1: c1, attr2: c2, attr3: c3}
sc = SkyCoord(frame=Galactic, unit=(unit1, unit2, unit3),
representation_type=representation, **kwargs)
assert_quantities_allclose(sc, (c1*unit1, c2*unit2, c3*unit3),
(attr1, attr2, attr3))
@pytest.mark.parametrize(units_attr_args,
[x for x in units_attr_sets
if x[0] in ('spherical', 'unitspherical')])
def test_skycoord_spherical_two_components(repr_name, unit1, unit2, unit3, cls2,
attr1, attr2, attr3, representation, c1, c2, c3):
"""
Tests positional inputs using components (COMP1, COMP2) for spherical
representations. Use weird units and Galactic frame.
"""
sc = SkyCoord(c1, c2, unit=(unit1, unit2), frame=Galactic,
representation_type=representation)
assert_quantities_allclose(sc, (c1*unit1, c2*unit2),
(attr1, attr2))
sc = SkyCoord(1000*c1*u.Unit(unit1/1000), cls2(c2, unit=unit2),
frame=Galactic,
unit=(unit1, unit2, unit3), representation_type=representation)
assert_quantities_allclose(sc, (c1*unit1, c2*unit2),
(attr1, attr2))
kwargs = {attr1: c1, attr2: c2}
sc = SkyCoord(frame=Galactic, unit=(unit1, unit2),
representation_type=representation, **kwargs)
assert_quantities_allclose(sc, (c1*unit1, c2*unit2),
(attr1, attr2))
@pytest.mark.parametrize(units_attr_args,
[x for x in units_attr_sets if x[0] != 'unitspherical'])
def test_galactic_three_components(repr_name, unit1, unit2, unit3, cls2, attr1, attr2, attr3,
representation, c1, c2, c3):
"""
Tests positional inputs using components (COMP1, COMP2, COMP3)
and various representations. Use weird units and Galactic frame.
"""
sc = Galactic(1000*c1*u.Unit(unit1/1000), cls2(c2, unit=unit2),
1000*c3*u.Unit(unit3/1000), representation_type=representation)
assert_quantities_allclose(sc, (c1*unit1, c2*unit2, c3*unit3),
(attr1, attr2, attr3))
kwargs = {attr3: c3*unit3}
sc = Galactic(c1*unit1, c2*unit2,
representation_type=representation, **kwargs)
assert_quantities_allclose(sc, (c1*unit1, c2*unit2, c3*unit3),
(attr1, attr2, attr3))
kwargs = {attr1: c1*unit1, attr2: c2*unit2, attr3: c3*unit3}
sc = Galactic(representation_type=representation, **kwargs)
assert_quantities_allclose(sc, (c1*unit1, c2*unit2, c3*unit3),
(attr1, attr2, attr3))
@pytest.mark.parametrize(units_attr_args,
[x for x in units_attr_sets
if x[0] in ('spherical', 'unitspherical')])
def test_galactic_spherical_two_components(repr_name, unit1, unit2, unit3, cls2,
attr1, attr2, attr3, representation, c1, c2, c3):
"""
Tests positional inputs using components (COMP1, COMP2) for spherical
representations. Use weird units and Galactic frame.
"""
sc = Galactic(1000*c1*u.Unit(unit1/1000), cls2(c2, unit=unit2), representation_type=representation)
assert_quantities_allclose(sc, (c1*unit1, c2*unit2), (attr1, attr2))
sc = Galactic(c1*unit1, c2*unit2, representation_type=representation)
assert_quantities_allclose(sc, (c1*unit1, c2*unit2), (attr1, attr2))
kwargs = {attr1: c1*unit1, attr2: c2*unit2}
sc = Galactic(representation_type=representation, **kwargs)
assert_quantities_allclose(sc, (c1*unit1, c2*unit2), (attr1, attr2))
@pytest.mark.parametrize(('repr_name', 'unit1', 'unit2', 'unit3', 'cls2', 'attr1', 'attr2', 'attr3'),
[x for x in base_unit_attr_sets if x[0] != 'unitspherical'])
def test_skycoord_coordinate_input(repr_name, unit1, unit2, unit3, cls2, attr1, attr2, attr3):
c1, c2, c3 = 1, 2, 3
sc = SkyCoord([(c1, c2, c3)], unit=(unit1, unit2, unit3), representation_type=repr_name,
frame='galactic')
assert_quantities_allclose(sc, ([c1]*unit1, [c2]*unit2, [c3]*unit3), (attr1, attr2, attr3))
c1, c2, c3 = 1*unit1, 2*unit2, 3*unit3
sc = SkyCoord([(c1, c2, c3)], representation_type=repr_name, frame='galactic')
assert_quantities_allclose(sc, ([1]*unit1, [2]*unit2, [3]*unit3), (attr1, attr2, attr3))
def test_skycoord_string_coordinate_input():
sc = SkyCoord('01 02 03 +02 03 04', unit='deg', representation_type='unitspherical')
assert_quantities_allclose(sc, (Angle('01:02:03', unit='deg'),
Angle('02:03:04', unit='deg')),
('ra', 'dec'))
sc = SkyCoord(['01 02 03 +02 03 04'], unit='deg', representation_type='unitspherical')
assert_quantities_allclose(sc, (Angle(['01:02:03'], unit='deg'),
Angle(['02:03:04'], unit='deg')),
('ra', 'dec'))
def test_units():
sc = SkyCoord(1, 2, 3, unit='m', representation_type='cartesian') # All get meters
assert sc.x.unit is u.m
assert sc.y.unit is u.m
assert sc.z.unit is u.m
sc = SkyCoord(1, 2*u.km, 3, unit='m', representation_type='cartesian') # All get u.m
assert sc.x.unit is u.m
assert sc.y.unit is u.m
assert sc.z.unit is u.m
sc = SkyCoord(1, 2, 3, unit=u.m, representation_type='cartesian') # All get u.m
assert sc.x.unit is u.m
assert sc.y.unit is u.m
assert sc.z.unit is u.m
sc = SkyCoord(1, 2, 3, unit='m, km, pc', representation_type='cartesian')
assert_quantities_allclose(sc, (1*u.m, 2*u.km, 3*u.pc), ('x', 'y', 'z'))
with pytest.raises(u.UnitsError) as err:
SkyCoord(1, 2, 3, unit=(u.m, u.m), representation_type='cartesian')
assert 'should have matching physical types' in str(err)
SkyCoord(1, 2, 3, unit=(u.m, u.km, u.pc), representation_type='cartesian')
assert_quantities_allclose(sc, (1*u.m, 2*u.km, 3*u.pc), ('x', 'y', 'z'))
@pytest.mark.xfail
def test_units_known_fail():
# should fail but doesn't => corner case oddity
with pytest.raises(u.UnitsError):
SkyCoord(1, 2, 3, unit=u.deg, representation_type='spherical')
def test_nodata_failure():
with pytest.raises(ValueError):
SkyCoord()
@pytest.mark.parametrize(('mode', 'origin'), [('wcs', 0),
('all', 0),
('all', 1)])
def test_wcs_methods(mode, origin):
from astropy.wcs import WCS
from astropy.utils.data import get_pkg_data_contents
from astropy.wcs.utils import pixel_to_skycoord
header = get_pkg_data_contents('../../wcs/tests/data/maps/1904-66_TAN.hdr', encoding='binary')
wcs = WCS(header)
ref = SkyCoord(0.1 * u.deg, -89. * u.deg, frame='icrs')
xp, yp = ref.to_pixel(wcs, mode=mode, origin=origin)
# WCS is in FK5 so we need to transform back to ICRS
new = pixel_to_skycoord(xp, yp, wcs, mode=mode, origin=origin).transform_to('icrs')
assert_allclose(new.ra.degree, ref.ra.degree)
assert_allclose(new.dec.degree, ref.dec.degree)
# also try to round-trip with `from_pixel`
scnew = SkyCoord.from_pixel(xp, yp, wcs, mode=mode, origin=origin).transform_to('icrs')
assert_allclose(scnew.ra.degree, ref.ra.degree)
assert_allclose(scnew.dec.degree, ref.dec.degree)
# Also make sure the right type comes out
class SkyCoord2(SkyCoord):
pass
scnew2 = SkyCoord2.from_pixel(xp, yp, wcs, mode=mode, origin=origin)
assert scnew.__class__ is SkyCoord
assert scnew2.__class__ is SkyCoord2
def test_frame_attr_transform_inherit():
"""
Test that frame attributes get inherited as expected during transform.
Driven by #3106.
"""
c = SkyCoord(1 * u.deg, 2 * u.deg, frame=FK5)
c2 = c.transform_to(FK4)
assert c2.equinox.value == 'B1950.000'
assert c2.obstime.value == 'B1950.000'
c2 = c.transform_to(FK4(equinox='J1975', obstime='J1980'))
assert c2.equinox.value == 'J1975.000'
assert c2.obstime.value == 'J1980.000'
c = SkyCoord(1 * u.deg, 2 * u.deg, frame=FK4)
c2 = c.transform_to(FK5)
assert c2.equinox.value == 'J2000.000'
assert c2.obstime is None
c = SkyCoord(1 * u.deg, 2 * u.deg, frame=FK4, obstime='J1980')
c2 = c.transform_to(FK5)
assert c2.equinox.value == 'J2000.000'
assert c2.obstime.value == 'J1980.000'
c = SkyCoord(1 * u.deg, 2 * u.deg, frame=FK4, equinox='J1975', obstime='J1980')
c2 = c.transform_to(FK5)
assert c2.equinox.value == 'J1975.000'
assert c2.obstime.value == 'J1980.000'
c2 = c.transform_to(FK5(equinox='J1990'))
assert c2.equinox.value == 'J1990.000'
assert c2.obstime.value == 'J1980.000'
# The work-around for #5722
c = SkyCoord(1 * u.deg, 2 * u.deg, frame='fk5')
c1 = SkyCoord(1 * u.deg, 2 * u.deg, frame='fk5', equinox='B1950.000')
c2 = c1.transform_to(c)
assert not c2.is_equivalent_frame(c) # counterintuitive, but documented
assert c2.equinox.value == 'B1950.000'
c3 = c1.transform_to(c, merge_attributes=False)
assert c3.equinox.value == 'J2000.000'
assert c3.is_equivalent_frame(c)
def test_deepcopy():
c1 = SkyCoord(1 * u.deg, 2 * u.deg)
c2 = copy.copy(c1)
c3 = copy.deepcopy(c1)
c4 = SkyCoord([1, 2] * u.m, [2, 3] * u.m, [3, 4] * u.m, representation_type='cartesian', frame='fk5',
obstime='J1999.9', equinox='J1988.8')
c5 = copy.deepcopy(c4)
assert np.all(c5.x == c4.x) # and y and z
assert c5.frame.name == c4.frame.name
assert c5.obstime == c4.obstime
assert c5.equinox == c4.equinox
assert c5.representation_type == c4.representation_type
def test_no_copy():
c1 = SkyCoord(np.arange(10.) * u.hourangle, np.arange(20., 30.) * u.deg)
c2 = SkyCoord(c1, copy=False)
# Note: c1.ra and c2.ra will *not* share memory, as these are recalculated
# to be in "preferred" units. See discussion in #4883.
assert np.may_share_memory(c1.data.lon, c2.data.lon)
c3 = SkyCoord(c1, copy=True)
assert not np.may_share_memory(c1.data.lon, c3.data.lon)
def test_immutable():
c1 = SkyCoord(1 * u.deg, 2 * u.deg)
with pytest.raises(AttributeError):
c1.ra = 3.0
c1.foo = 42
assert c1.foo == 42
@pytest.mark.skipif(str('not HAS_SCIPY'))
@pytest.mark.skipif(str('OLDER_SCIPY'))
def test_search_around():
"""
Test the search_around_* methods
Here we don't actually test the values are right, just that the methods of
SkyCoord work. The accuracy tests are in ``test_matching.py``
"""
from astropy.utils import NumpyRNGContext
with NumpyRNGContext(987654321):
sc1 = SkyCoord(np.random.rand(20) * 360.*u.degree,
(np.random.rand(20) * 180. - 90.)*u.degree)
sc2 = SkyCoord(np.random.rand(100) * 360. * u.degree,
(np.random.rand(100) * 180. - 90.)*u.degree)
sc1ds = SkyCoord(ra=sc1.ra, dec=sc1.dec, distance=np.random.rand(20)*u.kpc)
sc2ds = SkyCoord(ra=sc2.ra, dec=sc2.dec, distance=np.random.rand(100)*u.kpc)
idx1_sky, idx2_sky, d2d_sky, d3d_sky = sc1.search_around_sky(sc2, 10*u.deg)
idx1_3d, idx2_3d, d2d_3d, d3d_3d = sc1ds.search_around_3d(sc2ds, 250*u.pc)
def test_init_with_frame_instance_keyword():
# Frame instance
c1 = SkyCoord(3 * u.deg, 4 * u.deg,
frame=FK5(equinox='J2010'))
assert c1.equinox == Time('J2010')
# Frame instance with data (data gets ignored)
c2 = SkyCoord(3 * u.deg, 4 * u.deg,
frame=FK5(1. * u.deg, 2 * u.deg,
equinox='J2010'))
assert c2.equinox == Time('J2010')
assert allclose(c2.ra.degree, 3)
assert allclose(c2.dec.degree, 4)
# SkyCoord instance
c3 = SkyCoord(3 * u.deg, 4 * u.deg, frame=c1)
assert c3.equinox == Time('J2010')
# Check duplicate arguments
with pytest.raises(ValueError) as err:
c = SkyCoord(3 * u.deg, 4 * u.deg, frame=FK5(equinox='J2010'), equinox='J2001')
assert "Cannot specify frame attribute 'equinox'" in str(err)
def test_guess_from_table():
from astropy.table import Table, Column
from astropy.utils import NumpyRNGContext
tab = Table()
with NumpyRNGContext(987654321):
tab.add_column(Column(data=np.random.rand(1000), unit='deg', name='RA[J2000]'))
tab.add_column(Column(data=np.random.rand(1000), unit='deg', name='DEC[J2000]'))
sc = SkyCoord.guess_from_table(tab)
npt.assert_array_equal(sc.ra.deg, tab['RA[J2000]'])
npt.assert_array_equal(sc.dec.deg, tab['DEC[J2000]'])
# try without units in the table
tab['RA[J2000]'].unit = None
tab['DEC[J2000]'].unit = None
# should fail if not given explicitly
with pytest.raises(u.UnitsError):
sc2 = SkyCoord.guess_from_table(tab)
# but should work if provided
sc2 = SkyCoord.guess_from_table(tab, unit=u.deg)
npt.assert_array_equal(sc.ra.deg, tab['RA[J2000]'])
npt.assert_array_equal(sc.dec.deg, tab['DEC[J2000]'])
# should fail if two options are available - ambiguity bad!
tab.add_column(Column(data=np.random.rand(1000), name='RA_J1900'))
with pytest.raises(ValueError) as excinfo:
sc3 = SkyCoord.guess_from_table(tab, unit=u.deg)
assert 'J1900' in excinfo.value.args[0] and 'J2000' in excinfo.value.args[0]
# should also fail if user specifies something already in the table, but
# should succeed even if the user has to give one of the components
tab.remove_column('RA_J1900')
with pytest.raises(ValueError):
sc3 = SkyCoord.guess_from_table(tab, ra=tab['RA[J2000]'], unit=u.deg)
oldra = tab['RA[J2000]']
tab.remove_column('RA[J2000]')
sc3 = SkyCoord.guess_from_table(tab, ra=oldra, unit=u.deg)
npt.assert_array_equal(sc3.ra.deg, oldra)
npt.assert_array_equal(sc3.dec.deg, tab['DEC[J2000]'])
# check a few non-ICRS/spherical systems
x, y, z = np.arange(3).reshape(3, 1) * u.pc
l, b = np.arange(2).reshape(2, 1) * u.deg
tabcart = Table([x, y, z], names=('x', 'y', 'z'))
tabgal = Table([b, l], names=('b', 'l'))
sc_cart = SkyCoord.guess_from_table(tabcart, representation_type='cartesian')
npt.assert_array_equal(sc_cart.x, x)
npt.assert_array_equal(sc_cart.y, y)
npt.assert_array_equal(sc_cart.z, z)
sc_gal = SkyCoord.guess_from_table(tabgal, frame='galactic')
npt.assert_array_equal(sc_gal.l, l)
npt.assert_array_equal(sc_gal.b, b)
# also try some column names that *end* with the attribute name
tabgal['b'].name = 'gal_b'
tabgal['l'].name = 'gal_l'
SkyCoord.guess_from_table(tabgal, frame='galactic')
tabgal['gal_b'].name = 'blob'
tabgal['gal_l'].name = 'central'
with pytest.raises(ValueError):
SkyCoord.guess_from_table(tabgal, frame='galactic')
def test_skycoord_list_creation():
"""
Test that SkyCoord can be created in a reasonable way with lists of SkyCoords
(regression for #2702)
"""
sc = SkyCoord(ra=[1, 2, 3]*u.deg, dec=[4, 5, 6]*u.deg)
sc0 = sc[0]
sc2 = sc[2]
scnew = SkyCoord([sc0, sc2])
assert np.all(scnew.ra == [1, 3]*u.deg)
assert np.all(scnew.dec == [4, 6]*u.deg)
# also check ranges
sc01 = sc[:2]
scnew2 = SkyCoord([sc01, sc2])
assert np.all(scnew2.ra == sc.ra)
assert np.all(scnew2.dec == sc.dec)
# now try with a mix of skycoord, frame, and repr objects
frobj = ICRS(2*u.deg, 5*u.deg)
reprobj = UnitSphericalRepresentation(3*u.deg, 6*u.deg)
scnew3 = SkyCoord([sc0, frobj, reprobj])
assert np.all(scnew3.ra == sc.ra)
assert np.all(scnew3.dec == sc.dec)
# should *fail* if different frame attributes or types are passed in
scfk5_j2000 = SkyCoord(1*u.deg, 4*u.deg, frame='fk5')
with pytest.raises(ValueError):
SkyCoord([sc0, scfk5_j2000])
scfk5_j2010 = SkyCoord(1*u.deg, 4*u.deg, frame='fk5', equinox='J2010')
with pytest.raises(ValueError):
SkyCoord([scfk5_j2000, scfk5_j2010])
# but they should inherit if they're all consistent
scfk5_2_j2010 = SkyCoord(2*u.deg, 5*u.deg, frame='fk5', equinox='J2010')
scfk5_3_j2010 = SkyCoord(3*u.deg, 6*u.deg, frame='fk5', equinox='J2010')
scnew4 = SkyCoord([scfk5_j2010, scfk5_2_j2010, scfk5_3_j2010])
assert np.all(scnew4.ra == sc.ra)
assert np.all(scnew4.dec == sc.dec)
assert scnew4.equinox == Time('J2010')
def test_nd_skycoord_to_string():
c = SkyCoord(np.ones((2, 2)), 1, unit=('deg', 'deg'))
ts = c.to_string()
assert np.all(ts.shape == c.shape)
assert np.all(ts == u'1 1')
def test_equiv_skycoord():
sci1 = SkyCoord(1*u.deg, 2*u.deg, frame='icrs')
sci2 = SkyCoord(1*u.deg, 3*u.deg, frame='icrs')
assert sci1.is_equivalent_frame(sci1)
assert sci1.is_equivalent_frame(sci2)
assert sci1.is_equivalent_frame(ICRS())
assert not sci1.is_equivalent_frame(FK5())
with pytest.raises(TypeError):
sci1.is_equivalent_frame(10)
scf1 = SkyCoord(1*u.deg, 2*u.deg, frame='fk5')
scf2 = SkyCoord(1*u.deg, 2*u.deg, frame='fk5', equinox='J2005')
# obstime is *not* an FK5 attribute, but we still want scf1 and scf3 to come
# to come out different because they're part of SkyCoord
scf3 = SkyCoord(1*u.deg, 2*u.deg, frame='fk5', obstime='J2005')
assert scf1.is_equivalent_frame(scf1)
assert not scf1.is_equivalent_frame(sci1)
assert scf1.is_equivalent_frame(FK5())
assert not scf1.is_equivalent_frame(scf2)
assert scf2.is_equivalent_frame(FK5(equinox='J2005'))
assert not scf3.is_equivalent_frame(scf1)
assert not scf3.is_equivalent_frame(FK5(equinox='J2005'))
def test_constellations():
# the actual test for accuracy is in test_funcs - this is just meant to make
# sure we get sensible answers
sc = SkyCoord(135*u.deg, 65*u.deg)
assert sc.get_constellation() == 'Ursa Major'
assert sc.get_constellation(short_name=True) == 'UMa'
scs = SkyCoord([135]*2*u.deg, [65]*2*u.deg)
npt.assert_equal(scs.get_constellation(), ['Ursa Major']*2)
npt.assert_equal(scs.get_constellation(short_name=True), ['UMa']*2)
@pytest.mark.remote_data
def test_constellations_with_nameresolve():
assert SkyCoord.from_name('And I').get_constellation(short_name=True) == 'And'
# you'd think "And ..." should be in Andromeda. But you'd be wrong.
assert SkyCoord.from_name('And VI').get_constellation() == 'Pegasus'
# maybe it's because And VI isn't really a galaxy?
assert SkyCoord.from_name('And XXII').get_constellation() == 'Pisces'
assert SkyCoord.from_name('And XXX').get_constellation() == 'Cassiopeia'
# ok maybe not
# ok, but at least some of the others do make sense...
assert SkyCoord.from_name('Coma Cluster').get_constellation(short_name=True) == 'Com'
assert SkyCoord.from_name('Orion Nebula').get_constellation() == 'Orion'
assert SkyCoord.from_name('Triangulum Galaxy').get_constellation() == 'Triangulum'
def test_getitem_representation():
"""
Make sure current representation survives __getitem__ even if different
from data representation.
"""
sc = SkyCoord([1, 1] * u.deg, [2, 2] * u.deg)
sc.representation_type = 'cartesian'
assert sc[0].representation_type is CartesianRepresentation
def test_spherical_offsets():
i00 = SkyCoord(0*u.arcmin, 0*u.arcmin, frame='icrs')
i01 = SkyCoord(0*u.arcmin, 1*u.arcmin, frame='icrs')
i10 = SkyCoord(1*u.arcmin, 0*u.arcmin, frame='icrs')
i11 = SkyCoord(1*u.arcmin, 1*u.arcmin, frame='icrs')
i22 = SkyCoord(2*u.arcmin, 2*u.arcmin, frame='icrs')
dra, ddec = i00.spherical_offsets_to(i01)
assert_allclose(dra, 0*u.arcmin)
assert_allclose(ddec, 1*u.arcmin)
dra, ddec = i00.spherical_offsets_to(i10)
assert_allclose(dra, 1*u.arcmin)
assert_allclose(ddec, 0*u.arcmin)
dra, ddec = i10.spherical_offsets_to(i01)
assert_allclose(dra, -1*u.arcmin)
assert_allclose(ddec, 1*u.arcmin)
dra, ddec = i11.spherical_offsets_to(i22)
assert_allclose(ddec, 1*u.arcmin)
assert 0*u.arcmin < dra < 1*u.arcmin
fk5 = SkyCoord(0*u.arcmin, 0*u.arcmin, frame='fk5')
with pytest.raises(ValueError):
# different frames should fail
i00.spherical_offsets_to(fk5)
i1deg = ICRS(1*u.deg, 1*u.deg)
dra, ddec = i00.spherical_offsets_to(i1deg)
assert_allclose(dra, 1*u.deg)
assert_allclose(ddec, 1*u.deg)
# make sure an abbreviated array-based version of the above also works
i00s = SkyCoord([0]*4*u.arcmin, [0]*4*u.arcmin, frame='icrs')
i01s = SkyCoord([0]*4*u.arcmin, np.arange(4)*u.arcmin, frame='icrs')
dra, ddec = i00s.spherical_offsets_to(i01s)
assert_allclose(dra, 0*u.arcmin)
assert_allclose(ddec, np.arange(4)*u.arcmin)
def test_frame_attr_changes():
"""
This tests the case where a frame is added with a new frame attribute after
a SkyCoord has been created. This is necessary because SkyCoords get the
attributes set at creation time, but the set of attributes can change as
frames are added or removed from the transform graph. This makes sure that
everything continues to work consistently.
"""
sc_before = SkyCoord(1*u.deg, 2*u.deg, frame='icrs')
assert 'fakeattr' not in dir(sc_before)
class FakeFrame(BaseCoordinateFrame):
fakeattr = Attribute()
# doesn't matter what this does as long as it just puts the frame in the
# transform graph
transset = (ICRS, FakeFrame, lambda c, f: c)
frame_transform_graph.add_transform(*transset)
try:
assert 'fakeattr' in dir(sc_before)
assert sc_before.fakeattr is None
sc_after1 = SkyCoord(1*u.deg, 2*u.deg, frame='icrs')
assert 'fakeattr' in dir(sc_after1)
assert sc_after1.fakeattr is None
sc_after2 = SkyCoord(1*u.deg, 2*u.deg, frame='icrs', fakeattr=1)
assert sc_after2.fakeattr == 1
finally:
frame_transform_graph.remove_transform(*transset)
assert 'fakeattr' not in dir(sc_before)
assert 'fakeattr' not in dir(sc_after1)
assert 'fakeattr' not in dir(sc_after2)
def test_cache_clear_sc():
from astropy.coordinates import SkyCoord
i = SkyCoord(1*u.deg, 2*u.deg)
# Add an in frame units version of the rep to the cache.
repr(i)
assert len(i.cache['representation']) == 2
i.cache.clear()
assert len(i.cache['representation']) == 0
def test_set_attribute_exceptions():
"""Ensure no attrbute for any frame can be set directly.
Though it is fine if the current frame does not have it."""
sc = SkyCoord(1.*u.deg, 2.*u.deg, frame='fk5')
assert hasattr(sc.frame, 'equinox')
with pytest.raises(AttributeError):
sc.equinox = 'B1950'
assert sc.relative_humidity is None
sc.relative_humidity = 0.5
assert sc.relative_humidity == 0.5
assert not hasattr(sc.frame, 'relative_humidity')
def test_extra_attributes():
"""Ensure any extra attributes are dealt with correctly.
Regression test against #5743.
"""
obstime_string = ['2017-01-01T00:00', '2017-01-01T00:10']
obstime = Time(obstime_string)
sc = SkyCoord([5, 10], [20, 30], unit=u.deg, obstime=obstime_string)
assert not hasattr(sc.frame, 'obstime')
assert type(sc.obstime) is Time
assert sc.obstime.shape == (2,)
assert np.all(sc.obstime == obstime)
# ensure equivalency still works for more than one obstime.
assert sc.is_equivalent_frame(sc)
sc_1 = sc[1]
assert sc_1.obstime == obstime[1]
# Transforming to FK4 should use sc.obstime.
sc_fk4 = sc.transform_to('fk4')
assert np.all(sc_fk4.frame.obstime == obstime)
# And transforming back should not loose it.
sc2 = sc_fk4.transform_to('icrs')
assert not hasattr(sc2.frame, 'obstime')
assert np.all(sc2.obstime == obstime)
# Ensure obstime get taken from the SkyCoord if passed in directly.
# (regression test for #5749).
sc3 = SkyCoord([0., 1.], [2., 3.], unit='deg', frame=sc)
assert np.all(sc3.obstime == obstime)
# Finally, check that we can delete such attributes.
del sc3.obstime
assert sc3.obstime is None
def test_apply_space_motion():
# use this 12 year period because it's a multiple of 4 to avoid the quirks
# of leap years while having 2 leap seconds in it
t1 = Time('2000-01-01T00:00')
t2 = Time('2012-01-01T00:00')
# Check a very simple case first:
frame = ICRS(ra=10.*u.deg, dec=0*u.deg,
distance=10.*u.pc,
pm_ra_cosdec=0.1*u.deg/u.yr,
pm_dec=0*u.mas/u.yr,
radial_velocity=0*u.km/u.s)
# Cases that should work (just testing input for now):
c1 = SkyCoord(frame, obstime=t1, pressure=101*u.kPa)
applied1 = c1.apply_space_motion(new_obstime=t2)
applied2 = c1.apply_space_motion(dt=12*u.year)
assert isinstance(applied1.frame, c1.frame.__class__)
assert isinstance(applied2.frame, c1.frame.__class__)
assert_allclose(applied1.ra, applied2.ra)
assert_allclose(applied1.pm_ra, applied2.pm_ra)
assert_allclose(applied1.dec, applied2.dec)
assert_allclose(applied1.distance, applied2.distance)
# ensure any frame attributes that were there before get passed through
assert applied1.pressure == c1.pressure
# there were 2 leap seconds between 2000 and 2010, so the difference in
# the two forms of time evolution should be ~2 sec
adt = np.abs(applied2.obstime - applied1.obstime)
assert 1.9*u.second < adt.to(u.second) < 2.1*u.second
c2 = SkyCoord(frame)
applied3 = c2.apply_space_motion(dt=6*u.year)
assert isinstance(applied3.frame, c1.frame.__class__)
assert applied3.obstime is None
# this should *not* be .6 deg due to space-motion on a sphere, but it
# should be fairly close
assert 0.5*u.deg < applied3.ra-c1.ra < .7*u.deg
# the two cases should only match somewhat due to it being space motion, but
# they should be at least this close
assert quantity_allclose(applied1.ra-c1.ra, (applied3.ra-c1.ra)*2, atol=1e-3*u.deg)
# but *not* this close
assert not quantity_allclose(applied1.ra-c1.ra, (applied3.ra-c1.ra)*2, atol=1e-4*u.deg)
with pytest.raises(ValueError):
c2.apply_space_motion(new_obstime=t2)
def test_custom_frame_skycoord():
# also regression check for the case from #7069
class BlahBleeBlopFrame(BaseCoordinateFrame):
default_representation = SphericalRepresentation
# without a differential, SkyCoord creation fails
# default_differential = SphericalDifferential
_frame_specific_representation_info = {
'spherical': [
RepresentationMapping('lon', 'lon', 'recommended'),
RepresentationMapping('lat', 'lat', 'recommended'),
RepresentationMapping('distance', 'radius', 'recommended')
]
}
SkyCoord(lat=1*u.deg, lon=2*u.deg, frame=BlahBleeBlopFrame)
def test_user_friendly_pm_error():
"""
This checks that a more user-friendly error message is raised for the user
if they pass, e.g., pm_ra instead of pm_ra_cosdec
"""
with pytest.raises(ValueError) as e:
SkyCoord(ra=150*u.deg, dec=-11*u.deg,
pm_ra=100*u.mas/u.yr, pm_dec=10*u.mas/u.yr)
assert 'pm_ra_cosdec' in str(e.value)
with pytest.raises(ValueError) as e:
SkyCoord(l=150*u.deg, b=-11*u.deg,
pm_l=100*u.mas/u.yr, pm_b=10*u.mas/u.yr,
frame='galactic')
assert 'pm_l_cosb' in str(e.value)
# The special error should not turn on here:
with pytest.raises(ValueError) as e:
SkyCoord(x=1*u.pc, y=2*u.pc, z=3*u.pc,
pm_ra=100*u.mas/u.yr, pm_dec=10*u.mas/u.yr,
representation_type='cartesian')
assert 'pm_ra_cosdec' not in str(e.value)
def test_contained_by():
"""
Test Skycoord.contained(wcs,image)
"""
header = """
WCSAXES = 2 / Number of coordinate axes
CRPIX1 = 1045.0 / Pixel coordinate of reference point
CRPIX2 = 1001.0 / Pixel coordinate of reference point
PC1_1 = -0.00556448550786 / Coordinate transformation matrix element
PC1_2 = -0.001042120133257 / Coordinate transformation matrix element
PC2_1 = 0.001181477028705 / Coordinate transformation matrix element
PC2_2 = -0.005590809742987 / Coordinate transformation matrix element
CDELT1 = 1.0 / [deg] Coordinate increment at reference point
CDELT2 = 1.0 / [deg] Coordinate increment at reference point
CUNIT1 = 'deg' / Units of coordinate increment and value
CUNIT2 = 'deg' / Units of coordinate increment and value
CTYPE1 = 'RA---TAN' / TAN (gnomonic) projection + SIP distortions
CTYPE2 = 'DEC--TAN' / TAN (gnomonic) projection + SIP distortions
CRVAL1 = 250.34971683647 / [deg] Coordinate value at reference point
CRVAL2 = 2.2808772582495 / [deg] Coordinate value at reference point
LONPOLE = 180.0 / [deg] Native longitude of celestial pole
LATPOLE = 2.2808772582495 / [deg] Native latitude of celestial pole
RADESYS = 'ICRS' / Equatorial coordinate system
MJD-OBS = 58612.339199259 / [d] MJD of observation matching DATE-OBS
DATE-OBS= '2019-05-09T08:08:26.816Z' / ISO-8601 observation date matching MJD-OB
NAXIS = 2 / NAXIS
NAXIS1 = 2136 / length of first array dimension
NAXIS2 = 2078 / length of second array dimension
"""
header = fits.Header.fromstring(header.strip(),'\n')
test_wcs = WCS(header)
coord = SkyCoord(254,2,unit='deg')
assert coord.contained_by(test_wcs) == True
coord = SkyCoord(240,2,unit='deg')
assert coord.contained_by(test_wcs) == False
img = np.zeros((2136,2078))
coord = SkyCoord(250,2,unit='deg')
assert coord.contained_by(test_wcs, img) == True
coord = SkyCoord(240,2,unit='deg')
assert coord.contained_by(test_wcs, img) == False
ra = np.array([254.2, 254.1])
dec = np.array([2, 12.1])
coords = SkyCoord(ra, dec, unit='deg')
assert np.all(test_wcs.footprint_contains(coords) == np.array([True, False]))
def test_none_differential_type():
"""
This is a regression test for #8021
"""
from astropy.coordinates import BaseCoordinateFrame
class MockHeliographicStonyhurst(BaseCoordinateFrame):
default_representation = SphericalRepresentation
frame_specific_representation_info = {
SphericalRepresentation: [RepresentationMapping(reprname='lon',
framename='lon',
defaultunit=u.deg),
RepresentationMapping(reprname='lat',
framename='lat',
defaultunit=u.deg),
RepresentationMapping(reprname='distance',
framename='radius',
defaultunit=None)]
}
fr = MockHeliographicStonyhurst(lon=1*u.deg, lat=2*u.deg, radius=10*u.au)
SkyCoord(0*u.deg, fr.lat, fr.radius, frame=fr) # this was the failure
|
831dfab77182343cce01647046e2616478a0e54b784b99356712d603cdc3876a | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
This includes tests for the Distance class and related calculations
"""
import pytest
import numpy as np
from numpy import testing as npt
from astropy import units as u
from astropy.units import allclose as quantity_allclose
from astropy.coordinates import Longitude, Latitude, Distance, CartesianRepresentation
from astropy.coordinates.builtin_frames import ICRS, Galactic
from astropy.tests.helper import catch_warnings
from astropy.utils.exceptions import AstropyWarning
try:
import scipy # pylint: disable=W0611
except ImportError:
HAS_SCIPY = False
else:
HAS_SCIPY = True
def test_distances():
"""
Tests functionality for Coordinate class distances and cartesian
transformations.
"""
'''
Distances can also be specified, and allow for a full 3D definition of a
coordinate.
'''
# try all the different ways to initialize a Distance
distance = Distance(12, u.parsec)
Distance(40, unit=u.au)
Distance(value=5, unit=u.kpc)
# need to provide a unit
with pytest.raises(u.UnitsError):
Distance(12)
# standard units are pre-defined
npt.assert_allclose(distance.lyr, 39.138765325702551)
npt.assert_allclose(distance.km, 370281309776063.0)
# Coordinate objects can be assigned a distance object, giving them a full
# 3D position
c = Galactic(l=158.558650*u.degree, b=-43.350066*u.degree,
distance=Distance(12, u.parsec))
# or initialize distances via redshifts - this is actually tested in the
# function below that checks for scipy. This is kept here as an example
# c.distance = Distance(z=0.2) # uses current cosmology
# with whatever your preferred cosmology may be
# c.distance = Distance(z=0.2, cosmology=WMAP5)
# Coordinate objects can be initialized with a distance using special
# syntax
c1 = Galactic(l=158.558650*u.deg, b=-43.350066*u.deg, distance=12 * u.kpc)
# Coordinate objects can be instantiated with cartesian coordinates
# Internally they will immediately be converted to two angles + a distance
cart = CartesianRepresentation(x=2 * u.pc, y=4 * u.pc, z=8 * u.pc)
c2 = Galactic(cart)
sep12 = c1.separation_3d(c2)
# returns a *3d* distance between the c1 and c2 coordinates
# not that this does *not*
assert isinstance(sep12, Distance)
npt.assert_allclose(sep12.pc, 12005.784163916317, 10)
'''
All spherical coordinate systems with distances can be converted to
cartesian coordinates.
'''
cartrep2 = c2.cartesian
assert isinstance(cartrep2.x, u.Quantity)
npt.assert_allclose(cartrep2.x.value, 2)
npt.assert_allclose(cartrep2.y.value, 4)
npt.assert_allclose(cartrep2.z.value, 8)
# with no distance, the unit sphere is assumed when converting to cartesian
c3 = Galactic(l=158.558650*u.degree, b=-43.350066*u.degree, distance=None)
unitcart = c3.cartesian
npt.assert_allclose(((unitcart.x**2 + unitcart.y**2 +
unitcart.z**2)**0.5).value, 1.0)
# TODO: choose between these when CartesianRepresentation gets a definite
# decision on whether or not it gets __add__
#
# CartesianRepresentation objects can be added and subtracted, which are
# vector/elementwise they can also be given as arguments to a coordinate
# system
# csum = ICRS(c1.cartesian + c2.cartesian)
csumrep = CartesianRepresentation(c1.cartesian.xyz + c2.cartesian.xyz)
csum = ICRS(csumrep)
npt.assert_allclose(csumrep.x.value, -8.12016610185)
npt.assert_allclose(csumrep.y.value, 3.19380597435)
npt.assert_allclose(csumrep.z.value, -8.2294483707)
npt.assert_allclose(csum.ra.degree, 158.529401774)
npt.assert_allclose(csum.dec.degree, -43.3235825777)
npt.assert_allclose(csum.distance.kpc, 11.9942200501)
@pytest.mark.skipif(str('not HAS_SCIPY'))
def test_distances_scipy():
"""
The distance-related tests that require scipy due to the cosmology
module needing scipy integration routines
"""
from astropy.cosmology import WMAP5
# try different ways to initialize a Distance
d4 = Distance(z=0.23) # uses default cosmology - as of writing, WMAP7
npt.assert_allclose(d4.z, 0.23, rtol=1e-8)
d5 = Distance(z=0.23, cosmology=WMAP5)
npt.assert_allclose(d5.compute_z(WMAP5), 0.23, rtol=1e-8)
d6 = Distance(z=0.23, cosmology=WMAP5, unit=u.km)
npt.assert_allclose(d6.value, 3.5417046898762366e+22)
with pytest.raises(ValueError):
Distance(cosmology=WMAP5, unit=u.km)
with pytest.raises(ValueError):
Distance()
def test_distance_change():
ra = Longitude("4:08:15.162342", unit=u.hour)
dec = Latitude("-41:08:15.162342", unit=u.degree)
c1 = ICRS(ra, dec, Distance(1, unit=u.kpc))
oldx = c1.cartesian.x.value
assert (oldx - 0.35284083171901953) < 1e-10
# first make sure distances are immutible
with pytest.raises(AttributeError):
c1.distance = Distance(2, unit=u.kpc)
# now x should increase with a bigger distance increases
c2 = ICRS(ra, dec, Distance(2, unit=u.kpc))
assert c2.cartesian.x.value == oldx * 2
def test_distance_is_quantity():
"""
test that distance behaves like a proper quantity
"""
Distance(2 * u.kpc)
d = Distance([2, 3.1], u.kpc)
assert d.shape == (2,)
a = d.view(np.ndarray)
q = d.view(u.Quantity)
a[0] = 1.2
q.value[1] = 5.4
assert d[0].value == 1.2
assert d[1].value == 5.4
q = u.Quantity(d, copy=True)
q.value[1] = 0
assert q.value[1] == 0
assert d.value[1] != 0
# regression test against #2261
d = Distance([2 * u.kpc, 250. * u.pc])
assert d.unit is u.kpc
assert np.all(d.value == np.array([2., 0.25]))
def test_distmod():
d = Distance(10, u.pc)
assert d.distmod.value == 0
d = Distance(distmod=20)
assert d.distmod.value == 20
assert d.kpc == 100
d = Distance(distmod=-1., unit=u.au)
npt.assert_allclose(d.value, 1301442.9440836983)
with pytest.raises(ValueError):
d = Distance(value=d, distmod=20)
with pytest.raises(ValueError):
d = Distance(z=.23, distmod=20)
# check the Mpc/kpc/pc behavior
assert Distance(distmod=1).unit == u.pc
assert Distance(distmod=11).unit == u.kpc
assert Distance(distmod=26).unit == u.Mpc
assert Distance(distmod=-21).unit == u.AU
# if an array, uses the mean of the log of the distances
assert Distance(distmod=[1, 11, 26]).unit == u.kpc
def test_parallax():
d = Distance(parallax=1*u.arcsecond)
assert d.pc == 1.
with pytest.raises(ValueError):
d = Distance(15*u.pc, parallax=20*u.milliarcsecond)
with pytest.raises(ValueError):
d = Distance(parallax=20*u.milliarcsecond, distmod=20)
# array
plx = [1, 10, 100.]*u.mas
d = Distance(parallax=plx)
assert quantity_allclose(d.pc, [1000., 100., 10.])
assert quantity_allclose(plx, d.parallax)
# check behavior for negative parallax
with pytest.raises(ValueError):
Distance(parallax=-1 * u.mas)
with pytest.raises(ValueError):
Distance(parallax=[10, 1, -1] * u.mas)
with catch_warnings(AstropyWarning) as w:
Distance(parallax=-1 * u.mas, allow_negative=True)
assert len(w) > 0
with catch_warnings(AstropyWarning) as w:
Distance(parallax=[10, 1, -1] * u.mas, allow_negative=True)
assert len(w) > 0
def test_distance_in_coordinates():
"""
test that distances can be created from quantities and that cartesian
representations come out right
"""
ra = Longitude("4:08:15.162342", unit=u.hour)
dec = Latitude("-41:08:15.162342", unit=u.degree)
coo = ICRS(ra, dec, distance=2*u.kpc)
cart = coo.cartesian
assert isinstance(cart.xyz, u.Quantity)
def test_negative_distance():
""" Test optional kwarg allow_negative """
with pytest.raises(ValueError):
Distance([-2, 3.1], u.kpc)
with pytest.raises(ValueError):
Distance([-2, -3.1], u.kpc)
with pytest.raises(ValueError):
Distance(-2, u.kpc)
d = Distance(-2, u.kpc, allow_negative=True)
assert d.value == -2
def test_distance_comparison():
"""Ensure comparisons of distances work (#2206, #2250)"""
a = Distance(15*u.kpc)
b = Distance(15*u.kpc)
assert a == b
c = Distance(1.*u.Mpc)
assert a < c
def test_distance_to_quantity_when_not_units_of_length():
"""Any operation that leaves units other than those of length
should turn a distance into a quantity (#2206, #2250)"""
d = Distance(15*u.kpc)
twice = 2.*d
assert isinstance(twice, Distance)
area = 4.*np.pi*d**2
assert area.unit.is_equivalent(u.m**2)
assert not isinstance(area, Distance)
assert type(area) is u.Quantity
|
852a4bc04414c5b2bbbf25ca09a2a353cbdb386516f952830b889a634e4c4782 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Test initialization of angles not already covered by the API tests"""
import pickle
import pytest
import numpy as np
from astropy.coordinates.earth import EarthLocation, ELLIPSOIDS
from astropy.coordinates.angles import Longitude, Latitude
from astropy.units import allclose as quantity_allclose
from astropy import units as u
from astropy.time import Time
from astropy import constants
from astropy.coordinates.name_resolve import NameResolveError
def allclose_m14(a, b, rtol=1.e-14, atol=None):
if atol is None:
atol = 1.e-14 * getattr(a, 'unit', 1)
return quantity_allclose(a, b, rtol, atol)
def allclose_m8(a, b, rtol=1.e-8, atol=None):
if atol is None:
atol = 1.e-8 * getattr(a, 'unit', 1)
return quantity_allclose(a, b, rtol, atol)
def isclose_m14(val, ref):
return np.array([allclose_m14(v, r) for (v, r) in zip(val, ref)])
def isclose_m8(val, ref):
return np.array([allclose_m8(v, r) for (v, r) in zip(val, ref)])
def vvd(val, valok, dval, func, test, status):
"""Mimic routine of erfa/src/t_erfa_c.c (to help copy & paste)"""
assert quantity_allclose(val, valok * val.unit, atol=dval * val.unit)
def test_gc2gd():
"""Test that we reproduce erfa/src/t_erfa_c.c t_gc2gd"""
x, y, z = (2e6, 3e6, 5.244e6)
status = 0 # help for copy & paste of vvd
location = EarthLocation.from_geocentric(x, y, z, u.m)
e, p, h = location.to_geodetic('WGS84')
e, p, h = e.to(u.radian), p.to(u.radian), h.to(u.m)
vvd(e, 0.98279372324732907, 1e-14, "eraGc2gd", "e2", status)
vvd(p, 0.97160184820607853, 1e-14, "eraGc2gd", "p2", status)
vvd(h, 331.41731754844348, 1e-8, "eraGc2gd", "h2", status)
e, p, h = location.to_geodetic('GRS80')
e, p, h = e.to(u.radian), p.to(u.radian), h.to(u.m)
vvd(e, 0.98279372324732907, 1e-14, "eraGc2gd", "e2", status)
vvd(p, 0.97160184820607853, 1e-14, "eraGc2gd", "p2", status)
vvd(h, 331.41731754844348, 1e-8, "eraGc2gd", "h2", status)
e, p, h = location.to_geodetic('WGS72')
e, p, h = e.to(u.radian), p.to(u.radian), h.to(u.m)
vvd(e, 0.98279372324732907, 1e-14, "eraGc2gd", "e3", status)
vvd(p, 0.97160181811015119, 1e-14, "eraGc2gd", "p3", status)
vvd(h, 333.27707261303181, 1e-8, "eraGc2gd", "h3", status)
def test_gd2gc():
"""Test that we reproduce erfa/src/t_erfa_c.c t_gd2gc"""
e = 3.1 * u.rad
p = -0.5 * u.rad
h = 2500.0 * u.m
status = 0 # help for copy & paste of vvd
location = EarthLocation.from_geodetic(e, p, h, ellipsoid='WGS84')
xyz = tuple(v.to(u.m) for v in location.to_geocentric())
vvd(xyz[0], -5599000.5577049947, 1e-7, "eraGd2gc", "0/1", status)
vvd(xyz[1], 233011.67223479203, 1e-7, "eraGd2gc", "1/1", status)
vvd(xyz[2], -3040909.4706983363, 1e-7, "eraGd2gc", "2/1", status)
location = EarthLocation.from_geodetic(e, p, h, ellipsoid='GRS80')
xyz = tuple(v.to(u.m) for v in location.to_geocentric())
vvd(xyz[0], -5599000.5577260984, 1e-7, "eraGd2gc", "0/2", status)
vvd(xyz[1], 233011.6722356703, 1e-7, "eraGd2gc", "1/2", status)
vvd(xyz[2], -3040909.4706095476, 1e-7, "eraGd2gc", "2/2", status)
location = EarthLocation.from_geodetic(e, p, h, ellipsoid='WGS72')
xyz = tuple(v.to(u.m) for v in location.to_geocentric())
vvd(xyz[0], -5598998.7626301490, 1e-7, "eraGd2gc", "0/3", status)
vvd(xyz[1], 233011.5975297822, 1e-7, "eraGd2gc", "1/3", status)
vvd(xyz[2], -3040908.6861467111, 1e-7, "eraGd2gc", "2/3", status)
class TestInput():
def setup(self):
self.lon = Longitude([0., 45., 90., 135., 180., -180, -90, -45], u.deg,
wrap_angle=180*u.deg)
self.lat = Latitude([+0., 30., 60., +90., -90., -60., -30., 0.], u.deg)
self.h = u.Quantity([0.1, 0.5, 1.0, -0.5, -1.0, +4.2, -11., -.1], u.m)
self.location = EarthLocation.from_geodetic(self.lon, self.lat, self.h)
self.x, self.y, self.z = self.location.to_geocentric()
def test_default_ellipsoid(self):
assert self.location.ellipsoid == EarthLocation._ellipsoid
def test_geo_attributes(self):
assert all(np.all(_1 == _2)
for _1, _2 in zip(self.location.geodetic,
self.location.to_geodetic()))
assert all(np.all(_1 == _2)
for _1, _2 in zip(self.location.geocentric,
self.location.to_geocentric()))
def test_attribute_classes(self):
"""Test that attribute classes are correct (and not EarthLocation)"""
assert type(self.location.x) is u.Quantity
assert type(self.location.y) is u.Quantity
assert type(self.location.z) is u.Quantity
assert type(self.location.lon) is Longitude
assert type(self.location.lat) is Latitude
assert type(self.location.height) is u.Quantity
def test_input(self):
"""Check input is parsed correctly"""
# units of length should be assumed geocentric
geocentric = EarthLocation(self.x, self.y, self.z)
assert np.all(geocentric == self.location)
geocentric2 = EarthLocation(self.x.value, self.y.value, self.z.value,
self.x.unit)
assert np.all(geocentric2 == self.location)
geodetic = EarthLocation(self.lon, self.lat, self.h)
assert np.all(geodetic == self.location)
geodetic2 = EarthLocation(self.lon.to_value(u.degree),
self.lat.to_value(u.degree),
self.h.to_value(u.m))
assert np.all(geodetic2 == self.location)
geodetic3 = EarthLocation(self.lon, self.lat)
assert allclose_m14(geodetic3.lon.value,
self.location.lon.value)
assert allclose_m14(geodetic3.lat.value,
self.location.lat.value)
assert not np.any(isclose_m14(geodetic3.height.value,
self.location.height.value))
geodetic4 = EarthLocation(self.lon, self.lat, self.h[-1])
assert allclose_m14(geodetic4.lon.value,
self.location.lon.value)
assert allclose_m14(geodetic4.lat.value,
self.location.lat.value)
assert allclose_m14(geodetic4.height[-1].value,
self.location.height[-1].value)
assert not np.any(isclose_m14(geodetic4.height[:-1].value,
self.location.height[:-1].value))
# check length unit preservation
geocentric5 = EarthLocation(self.x, self.y, self.z, u.pc)
assert geocentric5.unit is u.pc
assert geocentric5.x.unit is u.pc
assert geocentric5.height.unit is u.pc
assert allclose_m14(geocentric5.x.to_value(self.x.unit), self.x.value)
geodetic5 = EarthLocation(self.lon, self.lat, self.h.to(u.pc))
assert geodetic5.unit is u.pc
assert geodetic5.x.unit is u.pc
assert geodetic5.height.unit is u.pc
assert allclose_m14(geodetic5.x.to_value(self.x.unit), self.x.value)
def test_invalid_input(self):
"""Check invalid input raises exception"""
# incomprehensible by either raises TypeError
with pytest.raises(TypeError):
EarthLocation(self.lon, self.y, self.z)
# wrong units
with pytest.raises(u.UnitsError):
EarthLocation.from_geocentric(self.lon, self.lat, self.lat)
# inconsistent units
with pytest.raises(u.UnitsError):
EarthLocation.from_geocentric(self.h, self.lon, self.lat)
# floats without a unit
with pytest.raises(TypeError):
EarthLocation.from_geocentric(self.x.value, self.y.value,
self.z.value)
# inconsistent shape
with pytest.raises(ValueError):
EarthLocation.from_geocentric(self.x, self.y, self.z[:5])
# inconsistent units
with pytest.raises(u.UnitsError):
EarthLocation.from_geodetic(self.x, self.y, self.z)
# inconsistent shape
with pytest.raises(ValueError):
EarthLocation.from_geodetic(self.lon, self.lat, self.h[:5])
def test_slicing(self):
# test on WGS72 location, so we can check the ellipsoid is passed on
locwgs72 = EarthLocation.from_geodetic(self.lon, self.lat, self.h,
ellipsoid='WGS72')
loc_slice1 = locwgs72[4]
assert isinstance(loc_slice1, EarthLocation)
assert loc_slice1.unit is locwgs72.unit
assert loc_slice1.ellipsoid == locwgs72.ellipsoid == 'WGS72'
assert not loc_slice1.shape
with pytest.raises(TypeError):
loc_slice1[0]
with pytest.raises(IndexError):
len(loc_slice1)
loc_slice2 = locwgs72[4:6]
assert isinstance(loc_slice2, EarthLocation)
assert len(loc_slice2) == 2
assert loc_slice2.unit is locwgs72.unit
assert loc_slice2.ellipsoid == locwgs72.ellipsoid
assert loc_slice2.shape == (2,)
loc_x = locwgs72['x']
assert type(loc_x) is u.Quantity
assert loc_x.shape == locwgs72.shape
assert loc_x.unit is locwgs72.unit
def test_invalid_ellipsoid(self):
# unknown ellipsoid
with pytest.raises(ValueError):
EarthLocation.from_geodetic(self.lon, self.lat, self.h,
ellipsoid='foo')
with pytest.raises(TypeError):
EarthLocation(self.lon, self.lat, self.h, ellipsoid='foo')
with pytest.raises(ValueError):
self.location.ellipsoid = 'foo'
with pytest.raises(ValueError):
self.location.to_geodetic('foo')
@pytest.mark.parametrize('ellipsoid', ELLIPSOIDS)
def test_ellipsoid(self, ellipsoid):
"""Test that different ellipsoids are understood, and differ"""
# check that heights differ for different ellipsoids
# need different tolerance, since heights are relative to ~6000 km
lon, lat, h = self.location.to_geodetic(ellipsoid)
if ellipsoid == self.location.ellipsoid:
assert allclose_m8(h.value, self.h.value)
else:
# Some heights are very similar for some; some lon, lat identical.
assert not np.all(isclose_m8(h.value, self.h.value))
# given lon, lat, height, check that x,y,z differ
location = EarthLocation.from_geodetic(self.lon, self.lat, self.h,
ellipsoid=ellipsoid)
if ellipsoid == self.location.ellipsoid:
assert allclose_m14(location.z.value, self.z.value)
else:
assert not np.all(isclose_m14(location.z.value, self.z.value))
def test_to_value(self):
loc = self.location
loc_ndarray = loc.view(np.ndarray)
assert np.all(loc.value == loc_ndarray)
loc2 = self.location.to(u.km)
loc2_ndarray = np.empty_like(loc_ndarray)
for coo in 'x', 'y', 'z':
loc2_ndarray[coo] = loc_ndarray[coo] / 1000.
assert np.all(loc2.value == loc2_ndarray)
loc2_value = self.location.to_value(u.km)
assert np.all(loc2_value == loc2_ndarray)
def test_pickling():
"""Regression test against #4304."""
el = EarthLocation(0.*u.m, 6000*u.km, 6000*u.km)
s = pickle.dumps(el)
el2 = pickle.loads(s)
assert el == el2
def test_repr_latex():
"""
Regression test for issue #4542
"""
somelocation = EarthLocation(lon='149:3:57.9', lat='-31:16:37.3')
somelocation._repr_latex_()
somelocation2 = EarthLocation(lon=[1., 2.]*u.deg, lat=[-1., 9.]*u.deg)
somelocation2._repr_latex_()
@pytest.mark.remote_data
# TODO: this parametrize should include a second option with a valid Google API
# key. For example, we should make an API key for Astropy, and add it to Travis
# as an environment variable (for security).
@pytest.mark.parametrize('google_api_key', [None])
def test_of_address(google_api_key):
NYC_lon = -74.0 * u.deg
NYC_lat = 40.7 * u.deg
# ~10 km tolerance to address difference between OpenStreetMap and Google
# for "New York, NY". This doesn't matter in practice because this test is
# only used to verify that the query succeeded, not that the returned
# position is precise.
NYC_tol = 0.1 * u.deg
# just a location
try:
loc = EarthLocation.of_address("New York, NY")
except NameResolveError as e:
# API limit might surface even here in Travis CI.
if 'unknown failure with' not in str(e):
pytest.xfail(str(e))
else:
assert quantity_allclose(loc.lat, NYC_lat, atol=NYC_tol)
assert quantity_allclose(loc.lon, NYC_lon, atol=NYC_tol)
assert np.allclose(loc.height.value, 0.)
# Put this one here as buffer to get around Google map API limit per sec.
# no match: This always raises NameResolveError
with pytest.raises(NameResolveError):
EarthLocation.of_address("lkjasdflkja")
if google_api_key is not None:
# a location and height
try:
loc = EarthLocation.of_address("New York, NY", get_height=True)
except NameResolveError as e:
# Buffer above sometimes insufficient to get around API limit but
# we also do not want to drag things out with time.sleep(0.195),
# where 0.195 was empirically determined on some physical machine.
pytest.xfail(str(e))
else:
assert quantity_allclose(loc.lat, NYC_lat, atol=NYC_tol)
assert quantity_allclose(loc.lon, NYC_lon, atol=NYC_tol)
assert quantity_allclose(loc.height, 10.438*u.meter, atol=1.*u.cm)
def test_geodetic_tuple():
lat = 2*u.deg
lon = 10*u.deg
height = 100*u.m
el = EarthLocation.from_geodetic(lat=lat, lon=lon, height=height)
res1 = el.to_geodetic()
res2 = el.geodetic
assert res1.lat == res2.lat and quantity_allclose(res1.lat, lat)
assert res1.lon == res2.lon and quantity_allclose(res1.lon, lon)
assert res1.height == res2.height and quantity_allclose(res1.height, height)
def test_gravitational_redshift():
someloc = EarthLocation(lon=-87.7*u.deg, lat=37*u.deg)
sometime = Time('2017-8-21 18:26:40')
zg0 = someloc.gravitational_redshift(sometime)
# should be of order ~few mm/s change per week
zg_week = someloc.gravitational_redshift(sometime + 7 * u.day)
assert 1.*u.mm/u.s < abs(zg_week - zg0) < 1*u.cm/u.s
# ~cm/s over a half-year
zg_halfyear = someloc.gravitational_redshift(sometime + 0.5 * u.yr)
assert 1*u.cm/u.s < abs(zg_halfyear - zg0) < 1*u.dm/u.s
# but when back to the same time in a year, should be tenths of mm
# even over decades
zg_year = someloc.gravitational_redshift(sometime - 20 * u.year)
assert .1*u.mm/u.s < abs(zg_year - zg0) < 1*u.mm/u.s
# Check mass adjustments.
# If Jupiter and the moon are ignored, effect should be off by ~ .5 mm/s
masses = {'sun': constants.G*constants.M_sun,
'jupiter': 0*constants.G*u.kg,
'moon': 0*constants.G*u.kg}
zg_moonjup = someloc.gravitational_redshift(sometime, masses=masses)
assert .1*u.mm/u.s < abs(zg_moonjup - zg0) < 1*u.mm/u.s
# Check that simply not including the bodies gives the same result.
assert zg_moonjup == someloc.gravitational_redshift(sometime,
bodies=('sun',))
# And that earth can be given, even not as last argument
assert zg_moonjup == someloc.gravitational_redshift(
sometime, bodies=('earth', 'sun',))
# If the earth is also ignored, effect should be off by ~ 20 cm/s
# This also tests the conversion of kg to gravitational units.
masses['earth'] = 0*u.kg
zg_moonjupearth = someloc.gravitational_redshift(sometime, masses=masses)
assert 1*u.dm/u.s < abs(zg_moonjupearth - zg0) < 1*u.m/u.s
# If all masses are zero, redshift should be 0 as well.
masses['sun'] = 0*u.kg
assert someloc.gravitational_redshift(sometime, masses=masses) == 0
with pytest.raises(KeyError):
someloc.gravitational_redshift(sometime, bodies=('saturn',))
with pytest.raises(u.UnitsError):
masses = {'sun': constants.G*constants.M_sun,
'jupiter': constants.G*constants.M_jup,
'moon': 1*u.km, # wrong units!
'earth': constants.G*constants.M_earth}
someloc.gravitational_redshift(sometime, masses=masses)
|
39ceb0e296fac30d0beb9fc9aa50fcb9c2ecb7e6df01b79522197859ecf95812 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import pytest
import numpy as np
from astropy.units import allclose as quantity_allclose
from astropy import units as u
from astropy import constants
from astropy.time import Time
from astropy.coordinates.builtin_frames import ICRS, AltAz, LSR, GCRS, Galactic, FK5
from astropy.coordinates.baseframe import frame_transform_graph
from astropy.coordinates.sites import get_builtin_sites
from astropy.coordinates import (TimeAttribute,
FunctionTransformWithFiniteDifference, get_sun,
CartesianRepresentation, SphericalRepresentation,
CartesianDifferential, SphericalDifferential,
DynamicMatrixTransform)
J2000 = Time('J2000')
@pytest.mark.parametrize("dt, symmetric", [(1*u.second, True),
(1*u.year, True),
(1*u.second, False),
(1*u.year, False)])
def test_faux_lsr(dt, symmetric):
class LSR2(LSR):
obstime = TimeAttribute(default=J2000)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference,
ICRS, LSR2, finite_difference_dt=dt,
symmetric_finite_difference=symmetric)
def icrs_to_lsr(icrs_coo, lsr_frame):
dt = lsr_frame.obstime - J2000
offset = lsr_frame.v_bary * dt.to(u.second)
return lsr_frame.realize_frame(icrs_coo.data.without_differentials() + offset)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference,
LSR2, ICRS, finite_difference_dt=dt,
symmetric_finite_difference=symmetric)
def lsr_to_icrs(lsr_coo, icrs_frame):
dt = lsr_coo.obstime - J2000
offset = lsr_coo.v_bary * dt.to(u.second)
return icrs_frame.realize_frame(lsr_coo.data - offset)
ic = ICRS(ra=12.3*u.deg, dec=45.6*u.deg, distance=7.8*u.au,
pm_ra_cosdec=0*u.marcsec/u.yr, pm_dec=0*u.marcsec/u.yr,
radial_velocity=0*u.km/u.s)
lsrc = ic.transform_to(LSR2())
assert quantity_allclose(ic.cartesian.xyz, lsrc.cartesian.xyz)
idiff = ic.cartesian.differentials['s']
ldiff = lsrc.cartesian.differentials['s']
change = (ldiff.d_xyz - idiff.d_xyz).to(u.km/u.s)
totchange = np.sum(change**2)**0.5
assert quantity_allclose(totchange, np.sum(lsrc.v_bary.d_xyz**2)**0.5)
ic2 = ICRS(ra=120.3*u.deg, dec=45.6*u.deg, distance=7.8*u.au,
pm_ra_cosdec=0*u.marcsec/u.yr, pm_dec=10*u.marcsec/u.yr,
radial_velocity=1000*u.km/u.s)
lsrc2 = ic2.transform_to(LSR2())
ic2_roundtrip = lsrc2.transform_to(ICRS)
tot = np.sum(lsrc2.cartesian.differentials['s'].d_xyz**2)**0.5
assert np.abs(tot.to('km/s') - 1000*u.km/u.s) < 20*u.km/u.s
assert quantity_allclose(ic2.cartesian.xyz,
ic2_roundtrip.cartesian.xyz)
def test_faux_fk5_galactic():
from astropy.coordinates.builtin_frames.galactic_transforms import fk5_to_gal, _gal_to_fk5
class Galactic2(Galactic):
pass
dt = 1000*u.s
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference,
FK5, Galactic2, finite_difference_dt=dt,
symmetric_finite_difference=True,
finite_difference_frameattr_name=None)
def fk5_to_gal2(fk5_coo, gal_frame):
trans = DynamicMatrixTransform(fk5_to_gal, FK5, Galactic2)
return trans(fk5_coo, gal_frame)
@frame_transform_graph.transform(FunctionTransformWithFiniteDifference,
Galactic2, ICRS, finite_difference_dt=dt,
symmetric_finite_difference=True,
finite_difference_frameattr_name=None)
def gal2_to_fk5(gal_coo, fk5_frame):
trans = DynamicMatrixTransform(_gal_to_fk5, Galactic2, FK5)
return trans(gal_coo, fk5_frame)
c1 = FK5(ra=150*u.deg, dec=-17*u.deg, radial_velocity=83*u.km/u.s,
pm_ra_cosdec=-41*u.mas/u.yr, pm_dec=16*u.mas/u.yr,
distance=150*u.pc)
c2 = c1.transform_to(Galactic2)
c3 = c1.transform_to(Galactic)
# compare the matrix and finite-difference calculations
assert quantity_allclose(c2.pm_l_cosb, c3.pm_l_cosb, rtol=1e-4)
assert quantity_allclose(c2.pm_b, c3.pm_b, rtol=1e-4)
def test_gcrs_diffs():
time = Time('2017-01-01')
gf = GCRS(obstime=time)
sung = get_sun(time) # should have very little vhelio
# qtr-year off sun location should be the direction of ~ maximal vhelio
qtrsung = get_sun(time-.25*u.year)
# now we use those essentially as directions where the velocities should
# be either maximal or minimal - with or perpendiculat to Earh's orbit
msungr = CartesianRepresentation(-sung.cartesian.xyz).represent_as(SphericalRepresentation)
suni = ICRS(ra=msungr.lon, dec=msungr.lat, distance=100*u.au,
pm_ra_cosdec=0*u.marcsec/u.yr, pm_dec=0*u.marcsec/u.yr,
radial_velocity=0*u.km/u.s)
qtrsuni = ICRS(ra=qtrsung.ra, dec=qtrsung.dec, distance=100*u.au,
pm_ra_cosdec=0*u.marcsec/u.yr, pm_dec=0*u.marcsec/u.yr,
radial_velocity=0*u.km/u.s)
# Now we transform those parallel- and perpendicular-to Earth's orbit
# directions to GCRS, which should shift the velocity to either include
# the Earth's velocity vector, or not (for parallel and perpendicular,
# respectively).
sung = suni.transform_to(gf)
qtrsung = qtrsuni.transform_to(gf)
# should be high along the ecliptic-not-sun sun axis and
# low along the sun axis
assert np.abs(qtrsung.radial_velocity) > 30*u.km/u.s
assert np.abs(qtrsung.radial_velocity) < 40*u.km/u.s
assert np.abs(sung.radial_velocity) < 1*u.km/u.s
suni2 = sung.transform_to(ICRS)
assert np.all(np.abs(suni2.data.differentials['s'].d_xyz) < 3e-5*u.km/u.s)
qtrisun2 = qtrsung.transform_to(ICRS)
assert np.all(np.abs(qtrisun2.data.differentials['s'].d_xyz) < 3e-5*u.km/u.s)
@pytest.mark.remote_data
def test_altaz_diffs():
time = Time('J2015') + np.linspace(-1, 1, 1000)*u.day
loc = get_builtin_sites()['greenwich']
aa = AltAz(obstime=time, location=loc)
icoo = ICRS(np.zeros_like(time)*u.deg, 10*u.deg, 100*u.au,
pm_ra_cosdec=np.zeros_like(time)*u.marcsec/u.yr,
pm_dec=0*u.marcsec/u.yr,
radial_velocity=0*u.km/u.s)
acoo = icoo.transform_to(aa)
# Make sure the change in radial velocity over ~2 days isn't too much
# more than the rotation speed of the Earth - some excess is expected
# because the orbit also shifts the RV, but it should be pretty small
# over this short a time.
assert np.ptp(acoo.radial_velocity)/2 < (2*np.pi*constants.R_earth/u.day)*1.2 # MAGIC NUMBER
cdiff = acoo.data.differentials['s'].represent_as(CartesianDifferential,
acoo.data)
# The "total" velocity should be > c, because the *tangential* velocity
# isn't a True velocity, but rather an induced velocity due to the Earth's
# rotation at a distance of 100 AU
assert np.all(np.sum(cdiff.d_xyz**2, axis=0)**0.5 > constants.c)
_xfail = pytest.mark.xfail
@pytest.mark.parametrize('distance', [1000*u.au,
10*u.pc,
pytest.param(10*u.kpc, marks=_xfail),
pytest.param(100*u.kpc, marks=_xfail)])
# TODO: make these not fail when the
# finite-difference numerical stability
# is improved
def test_numerical_limits(distance):
"""
Tests the numerical stability of the default settings for the finite
difference transformation calculation. This is *known* to fail for at
>~1kpc, but this may be improved in future versions.
"""
time = Time('J2017') + np.linspace(-.5, .5, 100)*u.year
icoo = ICRS(ra=0*u.deg, dec=10*u.deg, distance=distance,
pm_ra_cosdec=0*u.marcsec/u.yr, pm_dec=0*u.marcsec/u.yr,
radial_velocity=0*u.km/u.s)
gcoo = icoo.transform_to(GCRS(obstime=time))
rv = gcoo.radial_velocity.to('km/s')
# if its a lot bigger than this - ~the maximal velocity shift along
# the direction above with a small allowance for noise - finite-difference
# rounding errors have ruined the calculation
assert np.ptp(rv) < 65*u.km/u.s
def diff_info_plot(frame, time):
"""
Useful for plotting a frame with multiple times. *Not* used in the testing
suite per se, but extremely useful for interactive plotting of results from
tests in this module.
"""
from matplotlib import pyplot as plt
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(20, 12))
ax1.plot_date(time.plot_date, frame.data.differentials['s'].d_xyz.to(u.km/u.s).T, fmt='-')
ax1.legend(['x', 'y', 'z'])
ax2.plot_date(time.plot_date, np.sum(frame.data.differentials['s'].d_xyz.to(u.km/u.s)**2, axis=0)**0.5, fmt='-')
ax2.set_title('total')
sd = frame.data.differentials['s'].represent_as(SphericalDifferential, frame.data)
ax3.plot_date(time.plot_date, sd.d_distance.to(u.km/u.s), fmt='-')
ax3.set_title('radial')
ax4.plot_date(time.plot_date, sd.d_lat.to(u.marcsec/u.yr), fmt='-', label='lat')
ax4.plot_date(time.plot_date, sd.d_lon.to(u.marcsec/u.yr), fmt='-', label='lon')
return fig
|
6a615c64c491f8e87b02fea94ee92a737060b0034fdeacf114c41b9a9cc6ef4d | """
This series of functions are used to generate the reference CSV files
used by the accuracy tests. Running this as a comand-line script will
generate them all.
"""
import os
import numpy as np
from astropy.table import Table, Column
def ref_fk4_no_e_fk4(fnout='fk4_no_e_fk4.csv'):
"""
Accuracy tests for the FK4 (with no E-terms of aberration) to/from FK4
conversion, with arbitrary equinoxes and epoch of observation.
"""
import starlink.Ast as Ast
np.random.seed(12345)
N = 200
# Sample uniformly on the unit sphere. These will be either the FK4
# coordinates for the transformation to FK5, or the FK5 coordinates for the
# transformation to FK4.
ra = np.random.uniform(0., 360., N)
dec = np.degrees(np.arcsin(np.random.uniform(-1., 1., N)))
# Generate random observation epoch and equinoxes
obstime = ["B{0:7.2f}".format(x) for x in np.random.uniform(1950., 2000., N)]
ra_fk4ne, dec_fk4ne = [], []
ra_fk4, dec_fk4 = [], []
for i in range(N):
# Set up frames for AST
frame_fk4ne = Ast.SkyFrame('System=FK4-NO-E,Epoch={epoch},Equinox=B1950'.format(epoch=obstime[i]))
frame_fk4 = Ast.SkyFrame('System=FK4,Epoch={epoch},Equinox=B1950'.format(epoch=obstime[i]))
# FK4 to FK4 (no E-terms)
frameset = frame_fk4.convert(frame_fk4ne)
coords = np.degrees(frameset.tran([[np.radians(ra[i])], [np.radians(dec[i])]]))
ra_fk4ne.append(coords[0, 0])
dec_fk4ne.append(coords[1, 0])
# FK4 (no E-terms) to FK4
frameset = frame_fk4ne.convert(frame_fk4)
coords = np.degrees(frameset.tran([[np.radians(ra[i])], [np.radians(dec[i])]]))
ra_fk4.append(coords[0, 0])
dec_fk4.append(coords[1, 0])
# Write out table to a CSV file
t = Table()
t.add_column(Column(name='obstime', data=obstime))
t.add_column(Column(name='ra_in', data=ra))
t.add_column(Column(name='dec_in', data=dec))
t.add_column(Column(name='ra_fk4ne', data=ra_fk4ne))
t.add_column(Column(name='dec_fk4ne', data=dec_fk4ne))
t.add_column(Column(name='ra_fk4', data=ra_fk4))
t.add_column(Column(name='dec_fk4', data=dec_fk4))
f = open(os.path.join('data', fnout), 'wb')
f.write("# This file was generated with the {0} script, and the reference "
"values were computed using AST\n".format(os.path.basename(__file__)))
t.write(f, format='ascii', delimiter=',')
def ref_fk4_no_e_fk5(fnout='fk4_no_e_fk5.csv'):
"""
Accuracy tests for the FK4 (with no E-terms of aberration) to/from FK5
conversion, with arbitrary equinoxes and epoch of observation.
"""
import starlink.Ast as Ast
np.random.seed(12345)
N = 200
# Sample uniformly on the unit sphere. These will be either the FK4
# coordinates for the transformation to FK5, or the FK5 coordinates for the
# transformation to FK4.
ra = np.random.uniform(0., 360., N)
dec = np.degrees(np.arcsin(np.random.uniform(-1., 1., N)))
# Generate random observation epoch and equinoxes
obstime = ["B{0:7.2f}".format(x) for x in np.random.uniform(1950., 2000., N)]
equinox_fk4 = ["B{0:7.2f}".format(x) for x in np.random.uniform(1925., 1975., N)]
equinox_fk5 = ["J{0:7.2f}".format(x) for x in np.random.uniform(1975., 2025., N)]
ra_fk4, dec_fk4 = [], []
ra_fk5, dec_fk5 = [], []
for i in range(N):
# Set up frames for AST
frame_fk4 = Ast.SkyFrame('System=FK4-NO-E,Epoch={epoch},Equinox={equinox_fk4}'.format(epoch=obstime[i], equinox_fk4=equinox_fk4[i]))
frame_fk5 = Ast.SkyFrame('System=FK5,Epoch={epoch},Equinox={equinox_fk5}'.format(epoch=obstime[i], equinox_fk5=equinox_fk5[i]))
# FK4 to FK5
frameset = frame_fk4.convert(frame_fk5)
coords = np.degrees(frameset.tran([[np.radians(ra[i])], [np.radians(dec[i])]]))
ra_fk5.append(coords[0, 0])
dec_fk5.append(coords[1, 0])
# FK5 to FK4
frameset = frame_fk5.convert(frame_fk4)
coords = np.degrees(frameset.tran([[np.radians(ra[i])], [np.radians(dec[i])]]))
ra_fk4.append(coords[0, 0])
dec_fk4.append(coords[1, 0])
# Write out table to a CSV file
t = Table()
t.add_column(Column(name='equinox_fk4', data=equinox_fk4))
t.add_column(Column(name='equinox_fk5', data=equinox_fk5))
t.add_column(Column(name='obstime', data=obstime))
t.add_column(Column(name='ra_in', data=ra))
t.add_column(Column(name='dec_in', data=dec))
t.add_column(Column(name='ra_fk5', data=ra_fk5))
t.add_column(Column(name='dec_fk5', data=dec_fk5))
t.add_column(Column(name='ra_fk4', data=ra_fk4))
t.add_column(Column(name='dec_fk4', data=dec_fk4))
f = open(os.path.join('data', fnout), 'wb')
f.write("# This file was generated with the {0} script, and the reference "
"values were computed using AST\n".format(os.path.basename(__file__)))
t.write(f, format='ascii', delimiter=',')
def ref_galactic_fk4(fnout='galactic_fk4.csv'):
"""
Accuracy tests for the ICRS (with no E-terms of aberration) to/from FK5
conversion, with arbitrary equinoxes and epoch of observation.
"""
import starlink.Ast as Ast
np.random.seed(12345)
N = 200
# Sample uniformly on the unit sphere. These will be either the ICRS
# coordinates for the transformation to FK5, or the FK5 coordinates for the
# transformation to ICRS.
lon = np.random.uniform(0., 360., N)
lat = np.degrees(np.arcsin(np.random.uniform(-1., 1., N)))
# Generate random observation epoch and equinoxes
obstime = ["B{0:7.2f}".format(x) for x in np.random.uniform(1950., 2000., N)]
equinox_fk4 = ["J{0:7.2f}".format(x) for x in np.random.uniform(1975., 2025., N)]
lon_gal, lat_gal = [], []
ra_fk4, dec_fk4 = [], []
for i in range(N):
# Set up frames for AST
frame_gal = Ast.SkyFrame('System=Galactic,Epoch={epoch}'.format(epoch=obstime[i]))
frame_fk4 = Ast.SkyFrame('System=FK4,Epoch={epoch},Equinox={equinox_fk4}'.format(epoch=obstime[i], equinox_fk4=equinox_fk4[i]))
# ICRS to FK5
frameset = frame_gal.convert(frame_fk4)
coords = np.degrees(frameset.tran([[np.radians(lon[i])], [np.radians(lat[i])]]))
ra_fk4.append(coords[0, 0])
dec_fk4.append(coords[1, 0])
# FK5 to ICRS
frameset = frame_fk4.convert(frame_gal)
coords = np.degrees(frameset.tran([[np.radians(lon[i])], [np.radians(lat[i])]]))
lon_gal.append(coords[0, 0])
lat_gal.append(coords[1, 0])
# Write out table to a CSV file
t = Table()
t.add_column(Column(name='equinox_fk4', data=equinox_fk4))
t.add_column(Column(name='obstime', data=obstime))
t.add_column(Column(name='lon_in', data=lon))
t.add_column(Column(name='lat_in', data=lat))
t.add_column(Column(name='ra_fk4', data=ra_fk4))
t.add_column(Column(name='dec_fk4', data=dec_fk4))
t.add_column(Column(name='lon_gal', data=lon_gal))
t.add_column(Column(name='lat_gal', data=lat_gal))
f = open(os.path.join('data', fnout), 'wb')
f.write("# This file was generated with the {0} script, and the reference "
"values were computed using AST\n".format(os.path.basename(__file__)))
t.write(f, format='ascii', delimiter=',')
def ref_icrs_fk5(fnout='icrs_fk5.csv'):
"""
Accuracy tests for the ICRS (with no E-terms of aberration) to/from FK5
conversion, with arbitrary equinoxes and epoch of observation.
"""
import starlink.Ast as Ast
np.random.seed(12345)
N = 200
# Sample uniformly on the unit sphere. These will be either the ICRS
# coordinates for the transformation to FK5, or the FK5 coordinates for the
# transformation to ICRS.
ra = np.random.uniform(0., 360., N)
dec = np.degrees(np.arcsin(np.random.uniform(-1., 1., N)))
# Generate random observation epoch and equinoxes
obstime = ["B{0:7.2f}".format(x) for x in np.random.uniform(1950., 2000., N)]
equinox_fk5 = ["J{0:7.2f}".format(x) for x in np.random.uniform(1975., 2025., N)]
ra_icrs, dec_icrs = [], []
ra_fk5, dec_fk5 = [], []
for i in range(N):
# Set up frames for AST
frame_icrs = Ast.SkyFrame('System=ICRS,Epoch={epoch}'.format(epoch=obstime[i]))
frame_fk5 = Ast.SkyFrame('System=FK5,Epoch={epoch},Equinox={equinox_fk5}'.format(epoch=obstime[i], equinox_fk5=equinox_fk5[i]))
# ICRS to FK5
frameset = frame_icrs.convert(frame_fk5)
coords = np.degrees(frameset.tran([[np.radians(ra[i])], [np.radians(dec[i])]]))
ra_fk5.append(coords[0, 0])
dec_fk5.append(coords[1, 0])
# FK5 to ICRS
frameset = frame_fk5.convert(frame_icrs)
coords = np.degrees(frameset.tran([[np.radians(ra[i])], [np.radians(dec[i])]]))
ra_icrs.append(coords[0, 0])
dec_icrs.append(coords[1, 0])
# Write out table to a CSV file
t = Table()
t.add_column(Column(name='equinox_fk5', data=equinox_fk5))
t.add_column(Column(name='obstime', data=obstime))
t.add_column(Column(name='ra_in', data=ra))
t.add_column(Column(name='dec_in', data=dec))
t.add_column(Column(name='ra_fk5', data=ra_fk5))
t.add_column(Column(name='dec_fk5', data=dec_fk5))
t.add_column(Column(name='ra_icrs', data=ra_icrs))
t.add_column(Column(name='dec_icrs', data=dec_icrs))
f = open(os.path.join('data', fnout), 'wb')
f.write("# This file was generated with the {0} script, and the reference "
"values were computed using AST\n".format(os.path.basename(__file__)))
t.write(f, format='ascii', delimiter=',')
if __name__ == '__main__':
ref_fk4_no_e_fk4()
ref_fk4_no_e_fk5()
ref_galactic_fk4()
ref_icrs_fk5()
|
1a76763f96794e4bb4b1e85a7003027ed4c900d110d5eed21d0b23c0ed7061e7 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import numpy as np
from astropy import units as u
from astropy.coordinates.builtin_frames import Galactic, FK4
from astropy.time import Time
from astropy.table import Table
from astropy.coordinates.angle_utilities import angular_separation
from astropy.utils.data import get_pkg_data_contents
# the number of tests to run
from . import N_ACCURACY_TESTS
TOLERANCE = 0.3 # arcseconds
def test_galactic_fk4():
lines = get_pkg_data_contents('data/galactic_fk4.csv').split('\n')
t = Table.read(lines, format='ascii', delimiter=',', guess=False)
if N_ACCURACY_TESTS >= len(t):
idxs = range(len(t))
else:
idxs = np.random.randint(len(t), size=N_ACCURACY_TESTS)
diffarcsec1 = []
diffarcsec2 = []
for i in idxs:
# Extract row
r = t[int(i)] # int here is to get around a py 3.x astropy.table bug
# Galactic to FK4
c1 = Galactic(l=r['lon_in']*u.deg, b=r['lat_in']*u.deg)
c2 = c1.transform_to(FK4(equinox=Time(r['equinox_fk4'])))
# Find difference
diff = angular_separation(c2.ra.radian, c2.dec.radian,
np.radians(r['ra_fk4']),
np.radians(r['dec_fk4']))
diffarcsec1.append(np.degrees(diff) * 3600.)
# FK4 to Galactic
c1 = FK4(ra=r['lon_in']*u.deg, dec=r['lat_in']*u.deg,
obstime=Time(r['obstime']),
equinox=Time(r['equinox_fk4']))
c2 = c1.transform_to(Galactic)
# Find difference
diff = angular_separation(c2.l.radian, c2.b.radian,
np.radians(r['lon_gal']),
np.radians(r['lat_gal']))
diffarcsec2.append(np.degrees(diff) * 3600.)
np.testing.assert_array_less(diffarcsec1, TOLERANCE)
np.testing.assert_array_less(diffarcsec2, TOLERANCE)
|
4c3696122f6355256fa84819b88cb593cf8bf22f4277a8bed8ba274c9b1e1f3e | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import numpy as np
from astropy import units as u
from astropy.coordinates.builtin_frames import ICRS, FK5
from astropy.time import Time
from astropy.table import Table
from astropy.coordinates.angle_utilities import angular_separation
from astropy.utils.data import get_pkg_data_contents
# the number of tests to run
from . import N_ACCURACY_TESTS
TOLERANCE = 0.03 # arcseconds
def test_icrs_fk5():
lines = get_pkg_data_contents('data/icrs_fk5.csv').split('\n')
t = Table.read(lines, format='ascii', delimiter=',', guess=False)
if N_ACCURACY_TESTS >= len(t):
idxs = range(len(t))
else:
idxs = np.random.randint(len(t), size=N_ACCURACY_TESTS)
diffarcsec1 = []
diffarcsec2 = []
for i in idxs:
# Extract row
r = t[int(i)] # int here is to get around a py 3.x astropy.table bug
# ICRS to FK5
c1 = ICRS(ra=r['ra_in']*u.deg, dec=r['dec_in']*u.deg)
c2 = c1.transform_to(FK5(equinox=Time(r['equinox_fk5'])))
# Find difference
diff = angular_separation(c2.ra.radian, c2.dec.radian,
np.radians(r['ra_fk5']),
np.radians(r['dec_fk5']))
diffarcsec1.append(np.degrees(diff) * 3600.)
# FK5 to ICRS
c1 = FK5(ra=r['ra_in']*u.deg, dec=r['dec_in']*u.deg,
equinox=Time(r['equinox_fk5']))
c2 = c1.transform_to(ICRS)
# Find difference
diff = angular_separation(c2.ra.radian, c2.dec.radian,
np.radians(r['ra_icrs']),
np.radians(r['dec_icrs']))
diffarcsec2.append(np.degrees(diff) * 3600.)
np.testing.assert_array_less(diffarcsec1, TOLERANCE)
np.testing.assert_array_less(diffarcsec2, TOLERANCE)
|
ca26ee54a09f84370c65d1ba3064130b9e27715096ad7a3ff3526ed1fc31617a | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import numpy as np
from astropy import units as u
from astropy.coordinates.builtin_frames import FK4NoETerms, FK4
from astropy.time import Time
from astropy.table import Table
from astropy.coordinates.angle_utilities import angular_separation
from astropy.utils.data import get_pkg_data_contents
# the number of tests to run
from . import N_ACCURACY_TESTS
# It looks as though SLALIB, which AST relies on, assumes a simplified version
# of the e-terms corretion, so we have to up the tolerance a bit to get things
# to agree.
TOLERANCE = 1.e-5 # arcseconds
def test_fk4_no_e_fk4():
lines = get_pkg_data_contents('data/fk4_no_e_fk4.csv').split('\n')
t = Table.read(lines, format='ascii', delimiter=',', guess=False)
if N_ACCURACY_TESTS >= len(t):
idxs = range(len(t))
else:
idxs = np.random.randint(len(t), size=N_ACCURACY_TESTS)
diffarcsec1 = []
diffarcsec2 = []
for i in idxs:
# Extract row
r = t[int(i)] # int here is to get around a py 3.x astropy.table bug
# FK4 to FK4NoETerms
c1 = FK4(ra=r['ra_in']*u.deg, dec=r['dec_in']*u.deg,
obstime=Time(r['obstime']))
c2 = c1.transform_to(FK4NoETerms)
# Find difference
diff = angular_separation(c2.ra.radian, c2.dec.radian,
np.radians(r['ra_fk4ne']), np.radians(r['dec_fk4ne']))
diffarcsec1.append(np.degrees(diff) * 3600.)
# FK4NoETerms to FK4
c1 = FK4NoETerms(ra=r['ra_in']*u.deg, dec=r['dec_in']*u.deg,
obstime=Time(r['obstime']))
c2 = c1.transform_to(FK4)
# Find difference
diff = angular_separation(c2.ra.radian, c2.dec.radian,
np.radians(r['ra_fk4']),
np.radians(r['dec_fk4']))
diffarcsec2.append(np.degrees(diff) * 3600.)
np.testing.assert_array_less(diffarcsec1, TOLERANCE)
np.testing.assert_array_less(diffarcsec2, TOLERANCE)
|
34ba96f647f92a86e50874998b39a92c1231e9c4162468e1bca82c3bf0607888 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Accuracy tests for Ecliptic coordinate systems.
"""
import numpy as np
import pytest
from astropy.units import allclose as quantity_allclose
from astropy import units as u
from astropy.coordinates import SkyCoord
from astropy.coordinates.builtin_frames import FK5, ICRS, GCRS, GeocentricMeanEcliptic, BarycentricMeanEcliptic, HeliocentricMeanEcliptic, GeocentricTrueEcliptic, BarycentricTrueEcliptic, HeliocentricTrueEcliptic, HeliocentricEclipticIAU76
from astropy.constants import R_sun, R_earth
def test_against_pytpm_doc_example():
"""
Check that Astropy's Ecliptic systems give answers consistent with pyTPM
Currently this is only testing against the example given in the pytpm docs
"""
fk5_in = SkyCoord('12h22m54.899s', '15d49m20.57s', frame=FK5(equinox='J2000'))
pytpm_out = BarycentricMeanEcliptic(lon=178.78256462*u.deg,
lat=16.7597002513*u.deg,
equinox='J2000')
astropy_out = fk5_in.transform_to(pytpm_out)
assert pytpm_out.separation(astropy_out) < (1*u.arcsec)
def test_ecliptic_heliobary():
"""
Check that the ecliptic transformations for heliocentric and barycentric
at least more or less make sense
"""
icrs = ICRS(1*u.deg, 2*u.deg, distance=1.5*R_sun)
bary = icrs.transform_to(BarycentricMeanEcliptic)
helio = icrs.transform_to(HeliocentricMeanEcliptic)
# make sure there's a sizable distance shift - in 3d hundreds of km, but
# this is 1D so we allow it to be somewhat smaller
assert np.abs(bary.distance - helio.distance) > 1*u.km
# now make something that's got the location of helio but in bary's frame.
# this is a convenience to allow `separation` to work as expected
helio_in_bary_frame = bary.realize_frame(helio.cartesian)
assert bary.separation(helio_in_bary_frame) > 1*u.arcmin
@pytest.mark.parametrize(('trueframe', 'meanframe'),
[(BarycentricTrueEcliptic, BarycentricMeanEcliptic),
(HeliocentricTrueEcliptic, HeliocentricMeanEcliptic),
(GeocentricTrueEcliptic, GeocentricMeanEcliptic),
(HeliocentricEclipticIAU76, HeliocentricMeanEcliptic)])
def test_ecliptic_true_mean(trueframe, meanframe):
"""
Check that the ecliptic true/mean transformations at least roundtrip
"""
icrs = ICRS(1*u.deg, 2*u.deg, distance=1.5*R_sun)
truecoo = icrs.transform_to(trueframe)
meancoo = icrs.transform_to(meanframe)
truecoo2 = icrs.transform_to(trueframe)
assert not quantity_allclose(truecoo.cartesian.xyz, meancoo.cartesian.xyz)
assert quantity_allclose(truecoo.cartesian.xyz, truecoo2.cartesian.xyz)
def test_ecl_geo():
"""
Check that the geocentric version at least gets well away from GCRS. For a
true "accuracy" test we need a comparison dataset that is similar to the
geocentric/GCRS comparison we want to do here. Contributions welcome!
"""
gcrs = GCRS(10*u.deg, 20*u.deg, distance=1.5*R_earth)
gecl = gcrs.transform_to(GeocentricMeanEcliptic)
assert quantity_allclose(gecl.distance, gcrs.distance)
def test_arraytransforms():
"""
Test that transforms to/from ecliptic coordinates work on array coordinates
(not testing for accuracy.)
"""
ra = np.ones((4, ), dtype=float) * u.deg
dec = 2*np.ones((4, ), dtype=float) * u.deg
distance = np.ones((4, ), dtype=float) * u.au
test_icrs = ICRS(ra=ra, dec=dec, distance=distance)
test_gcrs = GCRS(test_icrs.data)
bary_arr = test_icrs.transform_to(BarycentricMeanEcliptic)
assert bary_arr.shape == ra.shape
helio_arr = test_icrs.transform_to(HeliocentricMeanEcliptic)
assert helio_arr.shape == ra.shape
geo_arr = test_gcrs.transform_to(GeocentricMeanEcliptic)
assert geo_arr.shape == ra.shape
# now check that we also can go back the other way without shape problems
bary_icrs = bary_arr.transform_to(ICRS)
assert bary_icrs.shape == test_icrs.shape
helio_icrs = helio_arr.transform_to(ICRS)
assert helio_icrs.shape == test_icrs.shape
geo_gcrs = geo_arr.transform_to(GCRS)
assert geo_gcrs.shape == test_gcrs.shape
def test_roundtrip_scalar():
icrs = ICRS(ra=1*u.deg, dec=2*u.deg, distance=3*u.au)
gcrs = GCRS(icrs.cartesian)
bary = icrs.transform_to(BarycentricMeanEcliptic)
helio = icrs.transform_to(HeliocentricMeanEcliptic)
geo = gcrs.transform_to(GeocentricMeanEcliptic)
bary_icrs = bary.transform_to(ICRS)
helio_icrs = helio.transform_to(ICRS)
geo_gcrs = geo.transform_to(GCRS)
assert quantity_allclose(bary_icrs.cartesian.xyz, icrs.cartesian.xyz)
assert quantity_allclose(helio_icrs.cartesian.xyz, icrs.cartesian.xyz)
assert quantity_allclose(geo_gcrs.cartesian.xyz, gcrs.cartesian.xyz)
|
ab81547069743ec22fc08474dd67fd9ae9012fe9b44757b5826dc5569dbfc926 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Accuracy tests for AltAz to ICRS coordinate transformations.
We use "known good" examples computed with other coordinate libraries.
Note that we use very low precision asserts because some people run tests on 32-bit
machines and we want the tests to pass there.
TODO: check if these tests pass on 32-bit machines and implement
higher-precision checks on 64-bit machines.
"""
import pytest
from astropy import units as u
from astropy.time import Time
from astropy.coordinates.builtin_frames import AltAz
from astropy.coordinates import EarthLocation
from astropy.coordinates import Angle, SkyCoord
@pytest.mark.remote_data
def test_against_hor2eq():
"""Check that Astropy gives consistent results with an IDL hor2eq example.
See : http://idlastro.gsfc.nasa.gov/ftp/pro/astro/hor2eq.pro
Test is against these run outputs, run at 2000-01-01T12:00:00:
# NORMAL ATMOSPHERE CASE
IDL> hor2eq, ten(37,54,41), ten(264,55,06), 2451545.0d, ra, dec, /verb, obs='kpno', pres=781.0, temp=273.0
Latitude = +31 57 48.0 Longitude = *** 36 00.0
Julian Date = 2451545.000000
Az, El = 17 39 40.4 +37 54 41 (Observer Coords)
Az, El = 17 39 40.4 +37 53 40 (Apparent Coords)
LMST = +11 15 26.5
LAST = +11 15 25.7
Hour Angle = +03 38 30.1 (hh:mm:ss)
Ra, Dec: 07 36 55.6 +15 25 02 (Apparent Coords)
Ra, Dec: 07 36 55.2 +15 25 08 (J2000.0000)
Ra, Dec: 07 36 55.2 +15 25 08 (J2000)
IDL> print, ra, dec
114.23004 15.418818
# NO PRESSURE CASE
IDL> hor2eq, ten(37,54,41), ten(264,55,06), 2451545.0d, ra, dec, /verb, obs='kpno', pres=0.0, temp=273.0
Latitude = +31 57 48.0 Longitude = *** 36 00.0
Julian Date = 2451545.000000
Az, El = 17 39 40.4 +37 54 41 (Observer Coords)
Az, El = 17 39 40.4 +37 54 41 (Apparent Coords)
LMST = +11 15 26.5
LAST = +11 15 25.7
Hour Angle = +03 38 26.4 (hh:mm:ss)
Ra, Dec: 07 36 59.3 +15 25 31 (Apparent Coords)
Ra, Dec: 07 36 58.9 +15 25 37 (J2000.0000)
Ra, Dec: 07 36 58.9 +15 25 37 (J2000)
IDL> print, ra, dec
114.24554 15.427022
"""
# Observatory position for `kpno` from here:
# http://idlastro.gsfc.nasa.gov/ftp/pro/astro/observatory.pro
location = EarthLocation(lon=Angle('-111d36.0m'),
lat=Angle('31d57.8m'),
height=2120. * u.m)
obstime = Time(2451545.0, format='jd', scale='ut1')
altaz_frame = AltAz(obstime=obstime, location=location,
temperature=0 * u.deg_C, pressure=0.781 * u.bar)
altaz_frame_noatm = AltAz(obstime=obstime, location=location,
temperature=0 * u.deg_C, pressure=0.0 * u.bar)
altaz = SkyCoord('264d55m06s 37d54m41s', frame=altaz_frame)
altaz_noatm = SkyCoord('264d55m06s 37d54m41s', frame=altaz_frame_noatm)
radec_frame = 'icrs'
radec_actual = altaz.transform_to(radec_frame)
radec_actual_noatm = altaz_noatm.transform_to(radec_frame)
radec_expected = SkyCoord('07h36m55.2s +15d25m08s', frame=radec_frame)
distance = radec_actual.separation(radec_expected).to('arcsec')
# this comes from running the example hor2eq but with the pressure set to 0
radec_expected_noatm = SkyCoord('07h36m58.9s +15d25m37s', frame=radec_frame)
distance_noatm = radec_actual_noatm.separation(radec_expected_noatm).to('arcsec')
# The baseline difference is ~2.3 arcsec with one atm of pressure. The
# difference is mainly due to the somewhat different atmospheric model that
# hor2eq assumes. This is confirmed by the second test which has the
# atmosphere "off" - the residual difference is small enough to be embedded
# in the assumptions about "J2000" or rounding errors.
assert distance < 5 * u.arcsec
assert distance_noatm < 0.4 * u.arcsec
@pytest.mark.remote_data
def test_against_pyephem():
"""Check that Astropy gives consistent results with one PyEphem example.
PyEphem: http://rhodesmill.org/pyephem/
See example input and output here:
https://gist.github.com/zonca/1672906
https://github.com/phn/pytpm/issues/2#issuecomment-3698679
"""
obstime = Time('2011-09-18 08:50:00')
location = EarthLocation(lon=Angle('-109d24m53.1s'),
lat=Angle('33d41m46.0s'),
height=30000. * u.m)
# We are using the default pressure and temperature in PyEphem
# relative_humidity = ?
# obswl = ?
altaz_frame = AltAz(obstime=obstime, location=location,
temperature=15 * u.deg_C, pressure=1.010 * u.bar)
altaz = SkyCoord('6.8927d -60.7665d', frame=altaz_frame)
radec_actual = altaz.transform_to('icrs')
radec_expected = SkyCoord('196.497518d -4.569323d', frame='icrs') # EPHEM
# radec_expected = SkyCoord('196.496220d -4.569390d', frame='icrs') # HORIZON
distance = radec_actual.separation(radec_expected).to('arcsec')
# TODO: why is this difference so large?
# It currently is: 31.45187984720655 arcsec
assert distance < 1e3 * u.arcsec
# Add assert on current Astropy result so that we notice if something changes
radec_expected = SkyCoord('196.495372d -4.560694d', frame='icrs')
distance = radec_actual.separation(radec_expected).to('arcsec')
# Current value: 0.0031402822944751997 arcsec
assert distance < 1 * u.arcsec
@pytest.mark.remote_data
def test_against_jpl_horizons():
"""Check that Astropy gives consistent results with the JPL Horizons example.
The input parameters and reference results are taken from this page:
(from the first row of the Results table at the bottom of that page)
http://ssd.jpl.nasa.gov/?horizons_tutorial
"""
obstime = Time('1998-07-28 03:00')
location = EarthLocation(lon=Angle('248.405300d'),
lat=Angle('31.9585d'),
height=2.06 * u.km)
# No atmosphere
altaz_frame = AltAz(obstime=obstime, location=location)
altaz = SkyCoord('143.2970d 2.6223d', frame=altaz_frame)
radec_actual = altaz.transform_to('icrs')
radec_expected = SkyCoord('19h24m55.01s -40d56m28.9s', frame='icrs')
distance = radec_actual.separation(radec_expected).to('arcsec')
# Current value: 0.238111 arcsec
assert distance < 1 * u.arcsec
@pytest.mark.remote_data
@pytest.mark.xfail(reason="Current output is completely incorrect")
def test_fk5_equinox_and_epoch_j2000_0_to_topocentric_observed():
"""
http://phn.github.io/pytpm/conversions.html#fk5-equinox-and-epoch-j2000-0-to-topocentric-observed
"""
# Observatory position for `kpno` from here:
# http://idlastro.gsfc.nasa.gov/ftp/pro/astro/observatory.pro
location = EarthLocation(lon=Angle('-111.598333d'),
lat=Angle('31.956389d'),
height=2093.093 * u.m) # TODO: height correct?
obstime = Time('2010-01-01 12:00:00')
# relative_humidity = ?
# obswl = ?
altaz_frame = AltAz(obstime=obstime, location=location,
temperature=0 * u.deg_C, pressure=0.781 * u.bar)
radec = SkyCoord('12h22m54.899s 15d49m20.57s', frame='fk5')
altaz_actual = radec.transform_to(altaz_frame)
altaz_expected = SkyCoord('264d55m06s 37d54m41s', frame='altaz')
# altaz_expected = SkyCoord('343.586827647d 15.7683070508d', frame='altaz')
# altaz_expected = SkyCoord('133.498195532d 22.0162383595d', frame='altaz')
distance = altaz_actual.separation(altaz_expected)
# print(altaz_actual)
# print(altaz_expected)
# print(distance)
"""TODO: Current output is completely incorrect ... xfailing this test for now.
<SkyCoord (AltAz: obstime=2010-01-01 12:00:00.000, location=(-1994497.7199061865, -5037954.447348028, 3357437.2294832403) m, pressure=781.0 hPa, temperature=0.0 deg_C, relative_humidity=0, obswl=1.0 micron):00:00.000, location=(-1994497.7199061865, -5037954.447348028, 3357437.2294832403) m, pressure=781.0 hPa, temperature=0.0 deg_C, relative_humidity=0, obswl=1.0 micron): az=133.4869896371561 deg, alt=67.97857990957701 deg>
<SkyCoord (AltAz: obstime=None, location=None, pressure=0.0 hPa, temperature=0.0 deg_C, relative_humidity=0, obswl=1.0 micron): az=264.91833333333335 deg, alt=37.91138888888889 deg>
68d02m45.732s
"""
assert distance < 1 * u.arcsec
|
0a93b6c07c04465f570c5d22a26c1c923b6b4c4cc5414b34611901be5ff1e72f | # Licensed under a 3-clause BSD style license - see PYFITS.rst
import bz2
import gzip
import errno
import http.client
import mmap
import operator
import pathlib
import io
import os
import sys
import tempfile
import warnings
import zipfile
import re
from functools import reduce
import numpy as np
from .util import (isreadable, iswritable, isfile, fileobj_open, fileobj_name,
fileobj_closed, fileobj_mode, _array_from_file,
_array_to_file, _write_string)
from astropy.utils.data import download_file, _is_url
from astropy.utils.decorators import classproperty, deprecated_renamed_argument
from astropy.utils.exceptions import AstropyUserWarning
# Maps astropy.io.fits-specific file mode names to the appropriate file
# modes to use for the underlying raw files
IO_FITS_MODES = {
'readonly': 'rb',
'copyonwrite': 'rb',
'update': 'rb+',
'append': 'ab+',
'ostream': 'wb',
'denywrite': 'rb'}
# Maps OS-level file modes to the appropriate astropy.io.fits specific mode
# to use when given file objects but no mode specified; obviously in
# IO_FITS_MODES there are overlaps; for example 'readonly' and 'denywrite'
# both require the file to be opened in 'rb' mode. But 'readonly' is the
# default behavior for such files if not otherwise specified.
# Note: 'ab' is only supported for 'ostream' which is output-only.
FILE_MODES = {
'rb': 'readonly', 'rb+': 'update',
'wb': 'ostream', 'wb+': 'update',
'ab': 'ostream', 'ab+': 'append'}
# A match indicates the file was opened in text mode, which is not allowed
TEXT_RE = re.compile(r'^[rwa]((t?\+?)|(\+?t?))$')
# readonly actually uses copyonwrite for mmap so that readonly without mmap and
# with mmap still have to same behavior with regard to updating the array. To
# get a truly readonly mmap use denywrite
# the name 'denywrite' comes from a deprecated flag to mmap() on Linux--it
# should be clarified that 'denywrite' mode is not directly analogous to the
# use of that flag; it was just taken, for lack of anything better, as a name
# that means something like "read only" but isn't readonly.
MEMMAP_MODES = {'readonly': mmap.ACCESS_COPY,
'copyonwrite': mmap.ACCESS_COPY,
'update': mmap.ACCESS_WRITE,
'append': mmap.ACCESS_COPY,
'denywrite': mmap.ACCESS_READ}
# TODO: Eventually raise a warning, and maybe even later disable the use of
# 'copyonwrite' and 'denywrite' modes unless memmap=True. For now, however,
# that would generate too many warnings for too many users. If nothing else,
# wait until the new logging system is in place.
GZIP_MAGIC = b'\x1f\x8b\x08'
PKZIP_MAGIC = b'\x50\x4b\x03\x04'
BZIP2_MAGIC = b'\x42\x5a'
def _normalize_fits_mode(mode):
if mode is not None and mode not in IO_FITS_MODES:
if TEXT_RE.match(mode):
raise ValueError(
"Text mode '{}' not supported: "
"files must be opened in binary mode".format(mode))
new_mode = FILE_MODES.get(mode)
if new_mode not in IO_FITS_MODES:
raise ValueError("Mode '{}' not recognized".format(mode))
mode = new_mode
return mode
class _File:
"""
Represents a FITS file on disk (or in some other file-like object).
"""
@deprecated_renamed_argument('clobber', 'overwrite', '2.0')
def __init__(self, fileobj=None, mode=None, memmap=None, overwrite=False,
cache=True):
self.strict_memmap = bool(memmap)
memmap = True if memmap is None else memmap
if fileobj is None:
self._file = None
self.closed = False
self.binary = True
self.mode = mode
self.memmap = memmap
self.compression = None
self.readonly = False
self.writeonly = False
self.simulateonly = True
self.close_on_error = False
return
else:
self.simulateonly = False
# If fileobj is of type pathlib.Path
if isinstance(fileobj, pathlib.Path):
fileobj = str(fileobj)
elif isinstance(fileobj, bytes):
# Using bytes as filename is tricky, it's deprecated for Windows
# in Python 3.5 (because it could lead to false-positives) but
# was fixed and un-deprecated in Python 3.6.
# However it requires that the bytes object is encoded with the
# file system encoding.
# Probably better to error out and ask for a str object instead.
# TODO: This could be revised when Python 3.5 support is dropped
# See also: https://github.com/astropy/astropy/issues/6789
raise TypeError("names should be `str` not `bytes`.")
# Holds mmap instance for files that use mmap
self._mmap = None
if mode is not None and mode not in IO_FITS_MODES:
raise ValueError("Mode '{}' not recognized".format(mode))
if isfile(fileobj):
objmode = _normalize_fits_mode(fileobj_mode(fileobj))
if mode is not None and mode != objmode:
raise ValueError(
"Requested FITS mode '{}' not compatible with open file "
"handle mode '{}'".format(mode, objmode))
mode = objmode
if mode is None:
mode = 'readonly'
# Handle raw URLs
if (isinstance(fileobj, str) and
mode not in ('ostream', 'append', 'update') and _is_url(fileobj)):
self.name = download_file(fileobj, cache=cache)
# Handle responses from URL requests that have already been opened
elif isinstance(fileobj, http.client.HTTPResponse):
if mode in ('ostream', 'append', 'update'):
raise ValueError(
"Mode {} not supported for HTTPResponse".format(mode))
fileobj = io.BytesIO(fileobj.read())
else:
self.name = fileobj_name(fileobj)
self.closed = False
self.binary = True
self.mode = mode
self.memmap = memmap
# Underlying fileobj is a file-like object, but an actual file object
self.file_like = False
# Should the object be closed on error: see
# https://github.com/astropy/astropy/issues/6168
self.close_on_error = False
# More defaults to be adjusted below as necessary
self.compression = None
self.readonly = False
self.writeonly = False
# Initialize the internal self._file object
if isfile(fileobj):
self._open_fileobj(fileobj, mode, overwrite)
elif isinstance(fileobj, str):
self._open_filename(fileobj, mode, overwrite)
else:
self._open_filelike(fileobj, mode, overwrite)
self.fileobj_mode = fileobj_mode(self._file)
if isinstance(fileobj, gzip.GzipFile):
self.compression = 'gzip'
elif isinstance(fileobj, zipfile.ZipFile):
# Reading from zip files is supported but not writing (yet)
self.compression = 'zip'
elif isinstance(fileobj, bz2.BZ2File):
self.compression = 'bzip2'
if (mode in ('readonly', 'copyonwrite', 'denywrite') or
(self.compression and mode == 'update')):
self.readonly = True
elif (mode == 'ostream' or
(self.compression and mode == 'append')):
self.writeonly = True
# For 'ab+' mode, the pointer is at the end after the open in
# Linux, but is at the beginning in Solaris.
if (mode == 'ostream' or self.compression or
not hasattr(self._file, 'seek')):
# For output stream start with a truncated file.
# For compressed files we can't really guess at the size
self.size = 0
else:
pos = self._file.tell()
self._file.seek(0, 2)
self.size = self._file.tell()
self._file.seek(pos)
if self.memmap:
if not isfile(self._file):
self.memmap = False
elif not self.readonly and not self._mmap_available:
# Test mmap.flush--see
# https://github.com/astropy/astropy/issues/968
self.memmap = False
def __repr__(self):
return '<{}.{} {}>'.format(self.__module__, self.__class__.__name__,
self._file)
# Support the 'with' statement
def __enter__(self):
return self
def __exit__(self, type, value, traceback):
self.close()
def readable(self):
if self.writeonly:
return False
return isreadable(self._file)
def read(self, size=None):
if not hasattr(self._file, 'read'):
raise EOFError
try:
return self._file.read(size)
except OSError:
# On some versions of Python, it appears, GzipFile will raise an
# OSError if you try to read past its end (as opposed to just
# returning '')
if self.compression == 'gzip':
return ''
raise
def readarray(self, size=None, offset=0, dtype=np.uint8, shape=None):
"""
Similar to file.read(), but returns the contents of the underlying
file as a numpy array (or mmap'd array if memmap=True) rather than a
string.
Usually it's best not to use the `size` argument with this method, but
it's provided for compatibility.
"""
if not hasattr(self._file, 'read'):
raise EOFError
if not isinstance(dtype, np.dtype):
dtype = np.dtype(dtype)
if size and size % dtype.itemsize != 0:
raise ValueError('size {} not a multiple of {}'.format(size, dtype))
if isinstance(shape, int):
shape = (shape,)
if not (size or shape):
warnings.warn('No size or shape given to readarray(); assuming a '
'shape of (1,)', AstropyUserWarning)
shape = (1,)
if size and not shape:
shape = (size // dtype.itemsize,)
if size and shape:
actualsize = np.prod(shape) * dtype.itemsize
if actualsize > size:
raise ValueError('size {} is too few bytes for a {} array of '
'{}'.format(size, shape, dtype))
elif actualsize < size:
raise ValueError('size {} is too many bytes for a {} array of '
'{}'.format(size, shape, dtype))
filepos = self._file.tell()
try:
if self.memmap:
if self._mmap is None:
# Instantiate Memmap array of the file offset at 0 (so we
# can return slices of it to offset anywhere else into the
# file)
access_mode = MEMMAP_MODES[self.mode]
# For reasons unknown the file needs to point to (near)
# the beginning or end of the file. No idea how close to
# the beginning or end.
# If I had to guess there is some bug in the mmap module
# of CPython or perhaps in microsoft's underlying code
# for generating the mmap.
self._file.seek(0, 0)
# This would also work:
# self._file.seek(0, 2) # moves to the end
try:
self._mmap = mmap.mmap(self._file.fileno(), 0,
access=access_mode,
offset=0)
except OSError as exc:
# NOTE: mode='readonly' results in the memory-mapping
# using the ACCESS_COPY mode in mmap so that users can
# modify arrays. However, on some systems, the OS raises
# a '[Errno 12] Cannot allocate memory' OSError if the
# address space is smaller than the file. The solution
# is to open the file in mode='denywrite', which at
# least allows the file to be opened even if the
# resulting arrays will be truly read-only.
if exc.errno == errno.ENOMEM and self.mode == 'readonly':
warnings.warn("Could not memory map array with "
"mode='readonly', falling back to "
"mode='denywrite', which means that "
"the array will be read-only",
AstropyUserWarning)
self._mmap = mmap.mmap(self._file.fileno(), 0,
access=MEMMAP_MODES['denywrite'],
offset=0)
else:
raise
return np.ndarray(shape=shape, dtype=dtype, offset=offset,
buffer=self._mmap)
else:
count = reduce(operator.mul, shape)
self._file.seek(offset)
data = _array_from_file(self._file, dtype, count)
data.shape = shape
return data
finally:
# Make sure we leave the file in the position we found it; on
# some platforms (e.g. Windows) mmaping a file handle can also
# reset its file pointer
self._file.seek(filepos)
def writable(self):
if self.readonly:
return False
return iswritable(self._file)
def write(self, string):
if hasattr(self._file, 'write'):
_write_string(self._file, string)
def writearray(self, array):
"""
Similar to file.write(), but writes a numpy array instead of a string.
Also like file.write(), a flush() or close() may be needed before
the file on disk reflects the data written.
"""
if hasattr(self._file, 'write'):
_array_to_file(array, self._file)
def flush(self):
if hasattr(self._file, 'flush'):
self._file.flush()
def seek(self, offset, whence=0):
if not hasattr(self._file, 'seek'):
return
self._file.seek(offset, whence)
pos = self._file.tell()
if self.size and pos > self.size:
warnings.warn('File may have been truncated: actual file length '
'({}) is smaller than the expected size ({})'
.format(self.size, pos), AstropyUserWarning)
def tell(self):
if not hasattr(self._file, 'tell'):
raise EOFError
return self._file.tell()
def truncate(self, size=None):
if hasattr(self._file, 'truncate'):
self._file.truncate(size)
def close(self):
"""
Close the 'physical' FITS file.
"""
if hasattr(self._file, 'close'):
self._file.close()
self._maybe_close_mmap()
# Set self._memmap to None anyways since no new .data attributes can be
# loaded after the file is closed
self._mmap = None
self.closed = True
self.close_on_error = False
def _maybe_close_mmap(self, refcount_delta=0):
"""
When mmap is in use these objects hold a reference to the mmap of the
file (so there is only one, shared by all HDUs that reference this
file).
This will close the mmap if there are no arrays referencing it.
"""
if (self._mmap is not None and
sys.getrefcount(self._mmap) == 2 + refcount_delta):
self._mmap.close()
self._mmap = None
def _overwrite_existing(self, overwrite, fileobj, closed):
"""Overwrite an existing file if ``overwrite`` is ``True``, otherwise
raise an OSError. The exact behavior of this method depends on the
_File object state and is only meant for use within the ``_open_*``
internal methods.
"""
# The file will be overwritten...
if ((self.file_like and hasattr(fileobj, 'len') and fileobj.len > 0) or
(os.path.exists(self.name) and os.path.getsize(self.name) != 0)):
if overwrite:
if self.file_like and hasattr(fileobj, 'truncate'):
fileobj.truncate(0)
else:
if not closed:
fileobj.close()
os.remove(self.name)
else:
raise OSError("File {!r} already exists.".format(self.name))
def _try_read_compressed(self, obj_or_name, magic, mode, ext=''):
"""Attempt to determine if the given file is compressed"""
if ext == '.gz' or magic.startswith(GZIP_MAGIC):
if mode == 'append':
raise OSError("'append' mode is not supported with gzip files."
"Use 'update' mode instead")
# Handle gzip files
kwargs = dict(mode=IO_FITS_MODES[mode])
if isinstance(obj_or_name, str):
kwargs['filename'] = obj_or_name
else:
kwargs['fileobj'] = obj_or_name
self._file = gzip.GzipFile(**kwargs)
self.compression = 'gzip'
elif ext == '.zip' or magic.startswith(PKZIP_MAGIC):
# Handle zip files
self._open_zipfile(self.name, mode)
self.compression = 'zip'
elif ext == '.bz2' or magic.startswith(BZIP2_MAGIC):
# Handle bzip2 files
if mode in ['update', 'append']:
raise OSError("update and append modes are not supported "
"with bzip2 files")
# bzip2 only supports 'w' and 'r' modes
bzip2_mode = 'w' if mode == 'ostream' else 'r'
self._file = bz2.BZ2File(obj_or_name, mode=bzip2_mode)
self.compression = 'bzip2'
return self.compression is not None
def _open_fileobj(self, fileobj, mode, overwrite):
"""Open a FITS file from a file object (including compressed files)."""
closed = fileobj_closed(fileobj)
fmode = fileobj_mode(fileobj) or IO_FITS_MODES[mode]
if mode == 'ostream':
self._overwrite_existing(overwrite, fileobj, closed)
if not closed:
self._file = fileobj
elif isfile(fileobj):
self._file = fileobj_open(self.name, IO_FITS_MODES[mode])
# Attempt to determine if the file represented by the open file object
# is compressed
try:
# We need to account for the possibility that the underlying file
# handle may have been opened with either 'ab' or 'ab+', which
# means that the current file position is at the end of the file.
if mode in ['ostream', 'append']:
self._file.seek(0)
magic = self._file.read(4)
# No matter whether the underlying file was opened with 'ab' or
# 'ab+', we need to return to the beginning of the file in order
# to properly process the FITS header (and handle the possibility
# of a compressed file).
self._file.seek(0)
except (OSError,OSError):
return
self._try_read_compressed(fileobj, magic, mode)
def _open_filelike(self, fileobj, mode, overwrite):
"""Open a FITS file from a file-like object, i.e. one that has
read and/or write methods.
"""
self.file_like = True
self._file = fileobj
if fileobj_closed(fileobj):
raise OSError("Cannot read from/write to a closed file-like "
"object ({!r}).".format(fileobj))
if isinstance(fileobj, zipfile.ZipFile):
self._open_zipfile(fileobj, mode)
# We can bypass any additional checks at this point since now
# self._file points to the temp file extracted from the zip
return
# If there is not seek or tell methods then set the mode to
# output streaming.
if (not hasattr(self._file, 'seek') or
not hasattr(self._file, 'tell')):
self.mode = mode = 'ostream'
if mode == 'ostream':
self._overwrite_existing(overwrite, fileobj, False)
# Any "writeable" mode requires a write() method on the file object
if (self.mode in ('update', 'append', 'ostream') and
not hasattr(self._file, 'write')):
raise OSError("File-like object does not have a 'write' "
"method, required for mode '{}'.".format(self.mode))
# Any mode except for 'ostream' requires readability
if self.mode != 'ostream' and not hasattr(self._file, 'read'):
raise OSError("File-like object does not have a 'read' "
"method, required for mode {!r}.".format(self.mode))
def _open_filename(self, filename, mode, overwrite):
"""Open a FITS file from a filename string."""
if mode == 'ostream':
self._overwrite_existing(overwrite, None, True)
if os.path.exists(self.name):
with fileobj_open(self.name, 'rb') as f:
magic = f.read(4)
else:
magic = b''
ext = os.path.splitext(self.name)[1]
if not self._try_read_compressed(self.name, magic, mode, ext=ext):
self._file = fileobj_open(self.name, IO_FITS_MODES[mode])
self.close_on_error = True
# Make certain we're back at the beginning of the file
# BZ2File does not support seek when the file is open for writing, but
# when opening a file for write, bz2.BZ2File always truncates anyway.
if not (isinstance(self._file, bz2.BZ2File) and mode == 'ostream'):
self._file.seek(0)
@classproperty(lazy=True)
def _mmap_available(cls):
"""Tests that mmap, and specifically mmap.flush works. This may
be the case on some uncommon platforms (see
https://github.com/astropy/astropy/issues/968).
If mmap.flush is found not to work, ``self.memmap = False`` is
set and a warning is issued.
"""
tmpfd, tmpname = tempfile.mkstemp()
try:
# Windows does not allow mappings on empty files
os.write(tmpfd, b' ')
os.fsync(tmpfd)
try:
mm = mmap.mmap(tmpfd, 1, access=mmap.ACCESS_WRITE)
except OSError as exc:
warnings.warn('Failed to create mmap: {}; mmap use will be '
'disabled'.format(str(exc)), AstropyUserWarning)
del exc
return False
try:
mm.flush()
except OSError:
warnings.warn('mmap.flush is unavailable on this platform; '
'using mmap in writeable mode will be disabled',
AstropyUserWarning)
return False
finally:
mm.close()
finally:
os.close(tmpfd)
os.remove(tmpname)
return True
def _open_zipfile(self, fileobj, mode):
"""Limited support for zipfile.ZipFile objects containing a single
a file. Allows reading only for now by extracting the file to a
tempfile.
"""
if mode in ('update', 'append'):
raise OSError(
"Writing to zipped fits files is not currently "
"supported")
if not isinstance(fileobj, zipfile.ZipFile):
zfile = zipfile.ZipFile(fileobj)
close = True
else:
zfile = fileobj
close = False
namelist = zfile.namelist()
if len(namelist) != 1:
raise OSError(
"Zip files with multiple members are not supported.")
self._file = tempfile.NamedTemporaryFile(suffix='.fits')
self._file.write(zfile.read(namelist[0]))
if close:
zfile.close()
# We just wrote the contents of the first file in the archive to a new
# temp file, which now serves as our underlying file object. So it's
# necessary to reset the position back to the beginning
self._file.seek(0)
|
a7ad88efcb9e47cf2b00ddb091984aee775acb2a6de7a123c5f1a0de801f203d | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import os
import re
import warnings
from collections import OrderedDict
from astropy.io import registry as io_registry
from astropy import units as u
from astropy.table import Table, serialize, meta, Column, MaskedColumn
from astropy.table.table import has_info_class
from astropy.time import Time
from astropy.utils.exceptions import AstropyUserWarning
from astropy.utils.data_info import MixinInfo, serialize_context_as
from . import HDUList, TableHDU, BinTableHDU, GroupsHDU
from .column import KEYWORD_NAMES, _fortran_to_python_format
from .convenience import table_to_hdu
from .hdu.hdulist import fitsopen as fits_open
from .util import first
# FITS file signature as per RFC 4047
FITS_SIGNATURE = (b"\x53\x49\x4d\x50\x4c\x45\x20\x20\x3d\x20\x20\x20\x20\x20"
b"\x20\x20\x20\x20\x20\x20\x20\x20\x20\x20\x20\x20\x20\x20"
b"\x20\x54")
# Keywords to remove for all tables that are read in
REMOVE_KEYWORDS = ['XTENSION', 'BITPIX', 'NAXIS', 'NAXIS1', 'NAXIS2',
'PCOUNT', 'GCOUNT', 'TFIELDS', 'THEAP']
# Column-specific keywords regex
COLUMN_KEYWORD_REGEXP = '(' + '|'.join(KEYWORD_NAMES) + ')[0-9]+'
def is_column_keyword(keyword):
return re.match(COLUMN_KEYWORD_REGEXP, keyword) is not None
def is_fits(origin, filepath, fileobj, *args, **kwargs):
"""
Determine whether `origin` is a FITS file.
Parameters
----------
origin : str or readable file-like object
Path or file object containing a potential FITS file.
Returns
-------
is_fits : bool
Returns `True` if the given file is a FITS file.
"""
if fileobj is not None:
pos = fileobj.tell()
sig = fileobj.read(30)
fileobj.seek(pos)
return sig == FITS_SIGNATURE
elif filepath is not None:
if filepath.lower().endswith(('.fits', '.fits.gz', '.fit', '.fit.gz',
'.fts', '.fts.gz')):
return True
elif isinstance(args[0], (HDUList, TableHDU, BinTableHDU, GroupsHDU)):
return True
else:
return False
def _decode_mixins(tbl):
"""Decode a Table ``tbl`` that has astropy Columns + appropriate meta-data into
the corresponding table with mixin columns (as appropriate).
"""
# If available read in __serialized_columns__ meta info which is stored
# in FITS COMMENTS between two sentinels.
try:
i0 = tbl.meta['comments'].index('--BEGIN-ASTROPY-SERIALIZED-COLUMNS--')
i1 = tbl.meta['comments'].index('--END-ASTROPY-SERIALIZED-COLUMNS--')
except (ValueError, KeyError):
return tbl
# The YAML data are split into COMMENT cards, with lines longer than 70
# characters being split with a continuation character \ (backslash).
# Strip the backslashes and join together.
continuation_line = False
lines = []
for line in tbl.meta['comments'][i0 + 1:i1]:
if continuation_line:
lines[-1] = lines[-1] + line[:70]
else:
lines.append(line[:70])
continuation_line = len(line) == 71
del tbl.meta['comments'][i0:i1 + 1]
if not tbl.meta['comments']:
del tbl.meta['comments']
info = meta.get_header_from_yaml(lines)
# Add serialized column information to table meta for use in constructing mixins
tbl.meta['__serialized_columns__'] = info['meta']['__serialized_columns__']
# Use the `datatype` attribute info to update column attributes that are
# NOT already handled via standard FITS column keys (name, dtype, unit).
for col in info['datatype']:
for attr in ['description', 'meta']:
if attr in col:
setattr(tbl[col['name']].info, attr, col[attr])
# Construct new table with mixins, using tbl.meta['__serialized_columns__']
# as guidance.
tbl = serialize._construct_mixins_from_columns(tbl)
return tbl
def read_table_fits(input, hdu=None, astropy_native=False, memmap=False,
character_as_bytes=True):
"""
Read a Table object from an FITS file
If the ``astropy_native`` argument is ``True``, then input FITS columns
which are representations of an astropy core object will be converted to
that class and stored in the ``Table`` as "mixin columns". Currently this
is limited to FITS columns which adhere to the FITS Time standard, in which
case they will be converted to a `~astropy.time.Time` column in the output
table.
Parameters
----------
input : str or file-like object or compatible `astropy.io.fits` HDU object
If a string, the filename to read the table from. If a file object, or
a compatible HDU object, the object to extract the table from. The
following `astropy.io.fits` HDU objects can be used as input:
- :class:`~astropy.io.fits.hdu.table.TableHDU`
- :class:`~astropy.io.fits.hdu.table.BinTableHDU`
- :class:`~astropy.io.fits.hdu.table.GroupsHDU`
- :class:`~astropy.io.fits.hdu.hdulist.HDUList`
hdu : int or str, optional
The HDU to read the table from.
astropy_native : bool, optional
Read in FITS columns as native astropy objects where possible instead
of standard Table Column objects. Default is False.
memmap : bool, optional
Whether to use memory mapping, which accesses data on disk as needed. If
you are only accessing part of the data, this is often more efficient.
If you want to access all the values in the table, and you are able to
fit the table in memory, you may be better off leaving memory mapping
off. However, if your table would not fit in memory, you should set this
to `True`.
character_as_bytes : bool, optional
If `True`, string columns are stored as Numpy byte arrays (dtype ``S``)
and are converted on-the-fly to unicode strings when accessing
individual elements. If you need to use Numpy unicode arrays (dtype
``U``) internally, you should set this to `False`, but note that this
will use more memory. If set to `False`, string columns will not be
memory-mapped even if ``memmap`` is `True`.
"""
if isinstance(input, HDUList):
# Parse all table objects
tables = OrderedDict()
for ihdu, hdu_item in enumerate(input):
if isinstance(hdu_item, (TableHDU, BinTableHDU, GroupsHDU)):
tables[ihdu] = hdu_item
if len(tables) > 1:
if hdu is None:
warnings.warn("hdu= was not specified but multiple tables"
" are present, reading in first available"
" table (hdu={0})".format(first(tables)),
AstropyUserWarning)
hdu = first(tables)
# hdu might not be an integer, so we first need to convert it
# to the correct HDU index
hdu = input.index_of(hdu)
if hdu in tables:
table = tables[hdu]
else:
raise ValueError("No table found in hdu={0}".format(hdu))
elif len(tables) == 1:
table = tables[first(tables)]
else:
raise ValueError("No table found")
elif isinstance(input, (TableHDU, BinTableHDU, GroupsHDU)):
table = input
else:
hdulist = fits_open(input, character_as_bytes=character_as_bytes,
memmap=memmap)
try:
return read_table_fits(hdulist, hdu=hdu,
astropy_native=astropy_native)
finally:
hdulist.close()
# Check if table is masked
masked = any(col.null is not None for col in table.columns)
# TODO: in future, it may make more sense to do this column-by-column,
# rather than via the structured array.
# In the loop below we access the data using data[col.name] rather than
# col.array to make sure that the data is scaled correctly if needed.
data = table.data
columns = []
for col in data.columns:
# Set column data
if masked:
column = MaskedColumn(data=data[col.name], name=col.name, copy=False)
if col.null is not None:
column.set_fill_value(col.null)
column.mask[column.data == col.null] = True
else:
column = Column(data=data[col.name], name=col.name, copy=False)
# Copy over units
if col.unit is not None:
column.unit = u.Unit(col.unit, format='fits', parse_strict='silent')
# Copy over display format
if col.disp is not None:
column.format = _fortran_to_python_format(col.disp)
columns.append(column)
# Create Table object
t = Table(columns, masked=masked, copy=False)
# TODO: deal properly with unsigned integers
hdr = table.header
if astropy_native:
# Avoid circular imports, and also only import if necessary.
from .fitstime import fits_to_time
hdr = fits_to_time(hdr, t)
for key, value, comment in hdr.cards:
if key in ['COMMENT', 'HISTORY']:
# Convert to io.ascii format
if key == 'COMMENT':
key = 'comments'
if key in t.meta:
t.meta[key].append(value)
else:
t.meta[key] = [value]
elif key in t.meta: # key is duplicate
if isinstance(t.meta[key], list):
t.meta[key].append(value)
else:
t.meta[key] = [t.meta[key], value]
elif is_column_keyword(key) or key in REMOVE_KEYWORDS:
pass
else:
t.meta[key] = value
# TODO: implement masking
# Decode any mixin columns that have been stored as standard Columns.
t = _decode_mixins(t)
return t
def _encode_mixins(tbl):
"""Encode a Table ``tbl`` that may have mixin columns to a Table with only
astropy Columns + appropriate meta-data to allow subsequent decoding.
"""
# Determine if information will be lost without serializing meta. This is hardcoded
# to the set difference between column info attributes and what FITS can store
# natively (name, dtype, unit). See _get_col_attributes() in table/meta.py for where
# this comes from.
info_lost = any(any(getattr(col.info, attr, None) not in (None, {})
for attr in ('description', 'meta'))
for col in tbl.itercols())
# If PyYAML is not available then check to see if there are any mixin cols
# that *require* YAML serialization. FITS already has support for Time,
# Quantity, so if those are the only mixins the proceed without doing the
# YAML bit, for backward compatibility (i.e. not requiring YAML to write
# Time or Quantity). In this case other mixin column meta (e.g.
# description or meta) will be silently dropped, consistent with astropy <=
# 2.0 behavior.
try:
import yaml # noqa
except ImportError:
for col in tbl.itercols():
if (has_info_class(col, MixinInfo) and
col.__class__ not in (u.Quantity, Time)):
raise TypeError("cannot write type {} column '{}' "
"to FITS without PyYAML installed."
.format(col.__class__.__name__, col.info.name))
else:
if info_lost:
warnings.warn("table contains column(s) with defined 'format',"
" 'description', or 'meta' info attributes. These"
" will be dropped unless you install PyYAML.",
AstropyUserWarning)
return tbl
# Convert the table to one with no mixins, only Column objects. This adds
# meta data which is extracted with meta.get_yaml_from_table. This ignores
# Time-subclass columns and leave them in the table so that the downstream
# FITS Time handling does the right thing.
with serialize_context_as('fits'):
encode_tbl = serialize.represent_mixins_as_columns(
tbl, exclude_classes=(Time,))
# If the encoded table is unchanged then there were no mixins. But if there
# is column metadata (format, description, meta) that would be lost, then
# still go through the serialized columns machinery.
if encode_tbl is tbl and not info_lost:
return tbl
# Get the YAML serialization of information describing the table columns.
# This is re-using ECSV code that combined existing table.meta with with
# the extra __serialized_columns__ key. For FITS the table.meta is handled
# by the native FITS connect code, so don't include that in the YAML
# output.
ser_col = '__serialized_columns__'
# encode_tbl might not have a __serialized_columns__ key if there were no mixins,
# but machinery below expects it to be available, so just make an empty dict.
encode_tbl.meta.setdefault(ser_col, {})
tbl_meta_copy = encode_tbl.meta.copy()
try:
encode_tbl.meta = {ser_col: encode_tbl.meta[ser_col]}
meta_yaml_lines = meta.get_yaml_from_table(encode_tbl)
finally:
encode_tbl.meta = tbl_meta_copy
del encode_tbl.meta[ser_col]
if 'comments' not in encode_tbl.meta:
encode_tbl.meta['comments'] = []
encode_tbl.meta['comments'].append('--BEGIN-ASTROPY-SERIALIZED-COLUMNS--')
for line in meta_yaml_lines:
if len(line) == 0:
lines = ['']
else:
# Split line into 70 character chunks for COMMENT cards
idxs = list(range(0, len(line) + 70, 70))
lines = [line[i0:i1] + '\\' for i0, i1 in zip(idxs[:-1], idxs[1:])]
lines[-1] = lines[-1][:-1]
encode_tbl.meta['comments'].extend(lines)
encode_tbl.meta['comments'].append('--END-ASTROPY-SERIALIZED-COLUMNS--')
return encode_tbl
def write_table_fits(input, output, overwrite=False):
"""
Write a Table object to a FITS file
Parameters
----------
input : Table
The table to write out.
output : str
The filename to write the table to.
overwrite : bool
Whether to overwrite any existing file without warning.
"""
# Encode any mixin columns into standard Columns.
input = _encode_mixins(input)
table_hdu = table_to_hdu(input, character_as_bytes=True)
# Check if output file already exists
if isinstance(output, str) and os.path.exists(output):
if overwrite:
os.remove(output)
else:
raise OSError("File exists: {0}".format(output))
table_hdu.writeto(output)
io_registry.register_reader('fits', Table, read_table_fits)
io_registry.register_writer('fits', Table, write_table_fits)
io_registry.register_identifier('fits', Table, is_fits)
|
47ead76c5e59091a327187103fe53224094304d3dd10e004bdfcb24b2fda5022 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Facilities for diffing two FITS files. Includes objects for diffing entire
FITS files, individual HDUs, FITS headers, or just FITS data.
Used to implement the fitsdiff program.
"""
import fnmatch
import glob
import io
import operator
import os.path
import textwrap
import warnings
from collections import defaultdict
from inspect import signature
from itertools import islice
import numpy as np
from astropy import __version__
from .card import Card, BLANK_CARD
from .header import Header
from astropy.utils.decorators import deprecated_renamed_argument
# HDUList is used in one of the doctests
from .hdu.hdulist import fitsopen, HDUList # pylint: disable=W0611
from .hdu.table import _TableLikeHDU
from astropy.utils.exceptions import AstropyDeprecationWarning
from astropy.utils.diff import (report_diff_values, fixed_width_indent,
where_not_allclose, diff_values)
__all__ = ['FITSDiff', 'HDUDiff', 'HeaderDiff', 'ImageDataDiff', 'RawDataDiff',
'TableDataDiff']
# Column attributes of interest for comparison
_COL_ATTRS = [('unit', 'units'), ('null', 'null values'),
('bscale', 'bscales'), ('bzero', 'bzeros'),
('disp', 'display formats'), ('dim', 'dimensions')]
class _BaseDiff:
"""
Base class for all FITS diff objects.
When instantiating a FITS diff object, the first two arguments are always
the two objects to diff (two FITS files, two FITS headers, etc.).
Instantiating a ``_BaseDiff`` also causes the diff itself to be executed.
The returned ``_BaseDiff`` instance has a number of attribute that describe
the results of the diff operation.
The most basic attribute, present on all ``_BaseDiff`` instances, is
``.identical`` which is `True` if the two objects being compared are
identical according to the diff method for objects of that type.
"""
def __init__(self, a, b):
"""
The ``_BaseDiff`` class does not implement a ``_diff`` method and
should not be instantiated directly. Instead instantiate the
appropriate subclass of ``_BaseDiff`` for the objects being compared
(for example, use `HeaderDiff` to compare two `Header` objects.
"""
self.a = a
self.b = b
# For internal use in report output
self._fileobj = None
self._indent = 0
self._diff()
def __bool__(self):
"""
A ``_BaseDiff`` object acts as `True` in a boolean context if the two
objects compared are identical. Otherwise it acts as `False`.
"""
return not self.identical
@classmethod
def fromdiff(cls, other, a, b):
"""
Returns a new Diff object of a specific subclass from an existing diff
object, passing on the values for any arguments they share in common
(such as ignore_keywords).
For example::
>>> from astropy.io import fits
>>> hdul1, hdul2 = fits.HDUList(), fits.HDUList()
>>> headera, headerb = fits.Header(), fits.Header()
>>> fd = fits.FITSDiff(hdul1, hdul2, ignore_keywords=['*'])
>>> hd = fits.HeaderDiff.fromdiff(fd, headera, headerb)
>>> list(hd.ignore_keywords)
['*']
"""
sig = signature(cls.__init__)
# The first 3 arguments of any Diff initializer are self, a, and b.
kwargs = {}
for arg in list(sig.parameters.keys())[3:]:
if hasattr(other, arg):
kwargs[arg] = getattr(other, arg)
return cls(a, b, **kwargs)
@property
def identical(self):
"""
`True` if all the ``.diff_*`` attributes on this diff instance are
empty, implying that no differences were found.
Any subclass of ``_BaseDiff`` must have at least one ``.diff_*``
attribute, which contains a non-empty value if and only if some
difference was found between the two objects being compared.
"""
return not any(getattr(self, attr) for attr in self.__dict__
if attr.startswith('diff_'))
@deprecated_renamed_argument('clobber', 'overwrite', '2.0')
def report(self, fileobj=None, indent=0, overwrite=False):
"""
Generates a text report on the differences (if any) between two
objects, and either returns it as a string or writes it to a file-like
object.
Parameters
----------
fileobj : file-like object, string, or None (optional)
If `None`, this method returns the report as a string. Otherwise it
returns `None` and writes the report to the given file-like object
(which must have a ``.write()`` method at a minimum), or to a new
file at the path specified.
indent : int
The number of 4 space tabs to indent the report.
overwrite : bool, optional
If ``True``, overwrite the output file if it exists. Raises an
``OSError`` if ``False`` and the output file exists. Default is
``False``.
.. versionchanged:: 1.3
``overwrite`` replaces the deprecated ``clobber`` argument.
Returns
-------
report : str or None
"""
return_string = False
filepath = None
if isinstance(fileobj, str):
if os.path.exists(fileobj) and not overwrite:
raise OSError("File {0} exists, aborting (pass in "
"overwrite=True to overwrite)".format(fileobj))
else:
filepath = fileobj
fileobj = open(filepath, 'w')
elif fileobj is None:
fileobj = io.StringIO()
return_string = True
self._fileobj = fileobj
self._indent = indent # This is used internally by _writeln
try:
self._report()
finally:
if filepath:
fileobj.close()
if return_string:
return fileobj.getvalue()
def _writeln(self, text):
self._fileobj.write(fixed_width_indent(text, self._indent) + '\n')
def _diff(self):
raise NotImplementedError
def _report(self):
raise NotImplementedError
class FITSDiff(_BaseDiff):
"""Diff two FITS files by filename, or two `HDUList` objects.
`FITSDiff` objects have the following diff attributes:
- ``diff_hdu_count``: If the FITS files being compared have different
numbers of HDUs, this contains a 2-tuple of the number of HDUs in each
file.
- ``diff_hdus``: If any HDUs with the same index are different, this
contains a list of 2-tuples of the HDU index and the `HDUDiff` object
representing the differences between the two HDUs.
"""
def __init__(self, a, b, ignore_hdus=[], ignore_keywords=[],
ignore_comments=[], ignore_fields=[],
numdiffs=10, rtol=0.0, atol=0.0,
ignore_blanks=True, ignore_blank_cards=True, tolerance=None):
"""
Parameters
----------
a : str or `HDUList`
The filename of a FITS file on disk, or an `HDUList` object.
b : str or `HDUList`
The filename of a FITS file on disk, or an `HDUList` object to
compare to the first file.
ignore_hdus : sequence, optional
HDU names to ignore when comparing two FITS files or HDU lists; the
presence of these HDUs and their contents are ignored. Wildcard
strings may also be included in the list.
ignore_keywords : sequence, optional
Header keywords to ignore when comparing two headers; the presence
of these keywords and their values are ignored. Wildcard strings
may also be included in the list.
ignore_comments : sequence, optional
A list of header keywords whose comments should be ignored in the
comparison. May contain wildcard strings as with ignore_keywords.
ignore_fields : sequence, optional
The (case-insensitive) names of any table columns to ignore if any
table data is to be compared.
numdiffs : int, optional
The number of pixel/table values to output when reporting HDU data
differences. Though the count of differences is the same either
way, this allows controlling the number of different values that
are kept in memory or output. If a negative value is given, then
numdiffs is treated as unlimited (default: 10).
rtol : float, optional
The relative difference to allow when comparing two float values
either in header values, image arrays, or table columns
(default: 0.0). Values which satisfy the expression
.. math::
\\left| a - b \\right| > \\text{atol} + \\text{rtol} \\cdot \\left| b \\right|
are considered to be different.
The underlying function used for comparison is `numpy.allclose`.
.. versionchanged:: 2.0
``rtol`` replaces the deprecated ``tolerance`` argument.
atol : float, optional
The allowed absolute difference. See also ``rtol`` parameter.
.. versionadded:: 2.0
ignore_blanks : bool, optional
Ignore extra whitespace at the end of string values either in
headers or data. Extra leading whitespace is not ignored
(default: True).
ignore_blank_cards : bool, optional
Ignore all cards that are blank, i.e. they only contain
whitespace (default: True).
"""
if isinstance(a, str):
try:
a = fitsopen(a)
except Exception as exc:
raise OSError("error opening file a ({}): {}: {}".format(
a, exc.__class__.__name__, exc.args[0]))
close_a = True
else:
close_a = False
if isinstance(b, str):
try:
b = fitsopen(b)
except Exception as exc:
raise OSError("error opening file b ({}): {}: {}".format(
b, exc.__class__.__name__, exc.args[0]))
close_b = True
else:
close_b = False
# Normalize keywords/fields to ignore to upper case
self.ignore_hdus = set(k.upper() for k in ignore_hdus)
self.ignore_keywords = set(k.upper() for k in ignore_keywords)
self.ignore_comments = set(k.upper() for k in ignore_comments)
self.ignore_fields = set(k.upper() for k in ignore_fields)
self.numdiffs = numdiffs
self.rtol = rtol
self.atol = atol
if tolerance is not None: # This should be removed in the next astropy version
warnings.warn(
'"tolerance" was deprecated in version 2.0 and will be removed in '
'a future version. Use argument "rtol" instead.',
AstropyDeprecationWarning)
self.rtol = tolerance # when tolerance is provided *always* ignore `rtol`
# during the transition/deprecation period
self.ignore_blanks = ignore_blanks
self.ignore_blank_cards = ignore_blank_cards
# Some hdu names may be pattern wildcards. Find them.
self.ignore_hdu_patterns = set()
for name in list(self.ignore_hdus):
if name != '*' and glob.has_magic(name):
self.ignore_hdus.remove(name)
self.ignore_hdu_patterns.add(name)
self.diff_hdu_count = ()
self.diff_hdus = []
try:
super().__init__(a, b)
finally:
if close_a:
a.close()
if close_b:
b.close()
def _diff(self):
if len(self.a) != len(self.b):
self.diff_hdu_count = (len(self.a), len(self.b))
# Record filenames for use later in _report
self.filenamea = self.a.filename()
if not self.filenamea:
self.filenamea = '<{} object at {:#x}>'.format(
self.a.__class__.__name__, id(self.a))
self.filenameb = self.b.filename()
if not self.filenameb:
self.filenameb = '<{} object at {:#x}>'.format(
self.b.__class__.__name__, id(self.b))
if self.ignore_hdus:
self.a = HDUList([h for h in self.a if h.name not in self.ignore_hdus])
self.b = HDUList([h for h in self.b if h.name not in self.ignore_hdus])
if self.ignore_hdu_patterns:
a_names = [hdu.name for hdu in self.a]
b_names = [hdu.name for hdu in self.b]
for pattern in self.ignore_hdu_patterns:
self.a = HDUList([h for h in self.a if h.name not in fnmatch.filter(
a_names, pattern)])
self.b = HDUList([h for h in self.b if h.name not in fnmatch.filter(
b_names, pattern)])
# For now, just compare the extensions one by one in order.
# Might allow some more sophisticated types of diffing later.
# TODO: Somehow or another simplify the passing around of diff
# options--this will become important as the number of options grows
for idx in range(min(len(self.a), len(self.b))):
hdu_diff = HDUDiff.fromdiff(self, self.a[idx], self.b[idx])
if not hdu_diff.identical:
self.diff_hdus.append((idx, hdu_diff))
def _report(self):
wrapper = textwrap.TextWrapper(initial_indent=' ',
subsequent_indent=' ')
self._fileobj.write('\n')
self._writeln(' fitsdiff: {}'.format(__version__))
self._writeln(' a: {}\n b: {}'.format(self.filenamea, self.filenameb))
if self.ignore_hdus:
ignore_hdus = ' '.join(sorted(self.ignore_hdus))
self._writeln(' HDU(s) not to be compared:\n{}'
.format(wrapper.fill(ignore_hdus)))
if self.ignore_hdu_patterns:
ignore_hdu_patterns = ' '.join(sorted(self.ignore_hdu_patterns))
self._writeln(' HDU(s) not to be compared:\n{}'
.format(wrapper.fill(ignore_hdu_patterns)))
if self.ignore_keywords:
ignore_keywords = ' '.join(sorted(self.ignore_keywords))
self._writeln(' Keyword(s) not to be compared:\n{}'
.format(wrapper.fill(ignore_keywords)))
if self.ignore_comments:
ignore_comments = ' '.join(sorted(self.ignore_comments))
self._writeln(' Keyword(s) whose comments are not to be compared'
':\n{}'.format(wrapper.fill(ignore_comments)))
if self.ignore_fields:
ignore_fields = ' '.join(sorted(self.ignore_fields))
self._writeln(' Table column(s) not to be compared:\n{}'
.format(wrapper.fill(ignore_fields)))
self._writeln(' Maximum number of different data values to be '
'reported: {}'.format(self.numdiffs))
self._writeln(' Relative tolerance: {}, Absolute tolerance: {}'
.format(self.rtol, self.atol))
if self.diff_hdu_count:
self._fileobj.write('\n')
self._writeln('Files contain different numbers of HDUs:')
self._writeln(' a: {}'.format(self.diff_hdu_count[0]))
self._writeln(' b: {}'.format(self.diff_hdu_count[1]))
if not self.diff_hdus:
self._writeln('No differences found between common HDUs.')
return
elif not self.diff_hdus:
self._fileobj.write('\n')
self._writeln('No differences found.')
return
for idx, hdu_diff in self.diff_hdus:
# print out the extension heading
if idx == 0:
self._fileobj.write('\n')
self._writeln('Primary HDU:')
else:
self._fileobj.write('\n')
self._writeln('Extension HDU {}:'.format(idx))
hdu_diff.report(self._fileobj, indent=self._indent + 1)
class HDUDiff(_BaseDiff):
"""
Diff two HDU objects, including their headers and their data (but only if
both HDUs contain the same type of data (image, table, or unknown).
`HDUDiff` objects have the following diff attributes:
- ``diff_extnames``: If the two HDUs have different EXTNAME values, this
contains a 2-tuple of the different extension names.
- ``diff_extvers``: If the two HDUS have different EXTVER values, this
contains a 2-tuple of the different extension versions.
- ``diff_extlevels``: If the two HDUs have different EXTLEVEL values, this
contains a 2-tuple of the different extension levels.
- ``diff_extension_types``: If the two HDUs have different XTENSION values,
this contains a 2-tuple of the different extension types.
- ``diff_headers``: Contains a `HeaderDiff` object for the headers of the
two HDUs. This will always contain an object--it may be determined
whether the headers are different through ``diff_headers.identical``.
- ``diff_data``: Contains either a `ImageDataDiff`, `TableDataDiff`, or
`RawDataDiff` as appropriate for the data in the HDUs, and only if the
two HDUs have non-empty data of the same type (`RawDataDiff` is used for
HDUs containing non-empty data of an indeterminate type).
"""
def __init__(self, a, b, ignore_keywords=[], ignore_comments=[],
ignore_fields=[], numdiffs=10, rtol=0.0, atol=0.0,
ignore_blanks=True, ignore_blank_cards=True, tolerance=None):
"""
Parameters
----------
a : `HDUList`
An `HDUList` object.
b : str or `HDUList`
An `HDUList` object to compare to the first `HDUList` object.
ignore_keywords : sequence, optional
Header keywords to ignore when comparing two headers; the presence
of these keywords and their values are ignored. Wildcard strings
may also be included in the list.
ignore_comments : sequence, optional
A list of header keywords whose comments should be ignored in the
comparison. May contain wildcard strings as with ignore_keywords.
ignore_fields : sequence, optional
The (case-insensitive) names of any table columns to ignore if any
table data is to be compared.
numdiffs : int, optional
The number of pixel/table values to output when reporting HDU data
differences. Though the count of differences is the same either
way, this allows controlling the number of different values that
are kept in memory or output. If a negative value is given, then
numdiffs is treated as unlimited (default: 10).
rtol : float, optional
The relative difference to allow when comparing two float values
either in header values, image arrays, or table columns
(default: 0.0). Values which satisfy the expression
.. math::
\\left| a - b \\right| > \\text{atol} + \\text{rtol} \\cdot \\left| b \\right|
are considered to be different.
The underlying function used for comparison is `numpy.allclose`.
.. versionchanged:: 2.0
``rtol`` replaces the deprecated ``tolerance`` argument.
atol : float, optional
The allowed absolute difference. See also ``rtol`` parameter.
.. versionadded:: 2.0
ignore_blanks : bool, optional
Ignore extra whitespace at the end of string values either in
headers or data. Extra leading whitespace is not ignored
(default: True).
ignore_blank_cards : bool, optional
Ignore all cards that are blank, i.e. they only contain
whitespace (default: True).
"""
self.ignore_keywords = {k.upper() for k in ignore_keywords}
self.ignore_comments = {k.upper() for k in ignore_comments}
self.ignore_fields = {k.upper() for k in ignore_fields}
self.rtol = rtol
self.atol = atol
if tolerance is not None: # This should be removed in the next astropy version
warnings.warn(
'"tolerance" was deprecated in version 2.0 and will be removed in '
'a future version. Use argument "rtol" instead.',
AstropyDeprecationWarning)
self.rtol = tolerance # when tolerance is provided *always* ignore `rtol`
# during the transition/deprecation period
self.numdiffs = numdiffs
self.ignore_blanks = ignore_blanks
self.diff_extnames = ()
self.diff_extvers = ()
self.diff_extlevels = ()
self.diff_extension_types = ()
self.diff_headers = None
self.diff_data = None
super().__init__(a, b)
def _diff(self):
if self.a.name != self.b.name:
self.diff_extnames = (self.a.name, self.b.name)
if self.a.ver != self.b.ver:
self.diff_extvers = (self.a.ver, self.b.ver)
if self.a.level != self.b.level:
self.diff_extlevels = (self.a.level, self.b.level)
if self.a.header.get('XTENSION') != self.b.header.get('XTENSION'):
self.diff_extension_types = (self.a.header.get('XTENSION'),
self.b.header.get('XTENSION'))
self.diff_headers = HeaderDiff.fromdiff(self, self.a.header.copy(),
self.b.header.copy())
if self.a.data is None or self.b.data is None:
# TODO: Perhaps have some means of marking this case
pass
elif self.a.is_image and self.b.is_image:
self.diff_data = ImageDataDiff.fromdiff(self, self.a.data,
self.b.data)
elif (isinstance(self.a, _TableLikeHDU) and
isinstance(self.b, _TableLikeHDU)):
# TODO: Replace this if/when _BaseHDU grows a .is_table property
self.diff_data = TableDataDiff.fromdiff(self, self.a.data,
self.b.data)
elif not self.diff_extension_types:
# Don't diff the data for unequal extension types that are not
# recognized image or table types
self.diff_data = RawDataDiff.fromdiff(self, self.a.data,
self.b.data)
def _report(self):
if self.identical:
self._writeln(" No differences found.")
if self.diff_extension_types:
self._writeln(" Extension types differ:\n a: {}\n "
"b: {}".format(*self.diff_extension_types))
if self.diff_extnames:
self._writeln(" Extension names differ:\n a: {}\n "
"b: {}".format(*self.diff_extnames))
if self.diff_extvers:
self._writeln(" Extension versions differ:\n a: {}\n "
"b: {}".format(*self.diff_extvers))
if self.diff_extlevels:
self._writeln(" Extension levels differ:\n a: {}\n "
"b: {}".format(*self.diff_extlevels))
if not self.diff_headers.identical:
self._fileobj.write('\n')
self._writeln(" Headers contain differences:")
self.diff_headers.report(self._fileobj, indent=self._indent + 1)
if self.diff_data is not None and not self.diff_data.identical:
self._fileobj.write('\n')
self._writeln(" Data contains differences:")
self.diff_data.report(self._fileobj, indent=self._indent + 1)
class HeaderDiff(_BaseDiff):
"""
Diff two `Header` objects.
`HeaderDiff` objects have the following diff attributes:
- ``diff_keyword_count``: If the two headers contain a different number of
keywords, this contains a 2-tuple of the keyword count for each header.
- ``diff_keywords``: If either header contains one or more keywords that
don't appear at all in the other header, this contains a 2-tuple
consisting of a list of the keywords only appearing in header a, and a
list of the keywords only appearing in header b.
- ``diff_duplicate_keywords``: If a keyword appears in both headers at
least once, but contains a different number of duplicates (for example, a
different number of HISTORY cards in each header), an item is added to
this dict with the keyword as the key, and a 2-tuple of the different
counts of that keyword as the value. For example::
{'HISTORY': (20, 19)}
means that header a contains 20 HISTORY cards, while header b contains
only 19 HISTORY cards.
- ``diff_keyword_values``: If any of the common keyword between the two
headers have different values, they appear in this dict. It has a
structure similar to ``diff_duplicate_keywords``, with the keyword as the
key, and a 2-tuple of the different values as the value. For example::
{'NAXIS': (2, 3)}
means that the NAXIS keyword has a value of 2 in header a, and a value of
3 in header b. This excludes any keywords matched by the
``ignore_keywords`` list.
- ``diff_keyword_comments``: Like ``diff_keyword_values``, but contains
differences between keyword comments.
`HeaderDiff` objects also have a ``common_keywords`` attribute that lists
all keywords that appear in both headers.
"""
def __init__(self, a, b, ignore_keywords=[], ignore_comments=[],
rtol=0.0, atol=0.0, ignore_blanks=True, ignore_blank_cards=True,
tolerance=None):
"""
Parameters
----------
a : `HDUList`
An `HDUList` object.
b : `HDUList`
An `HDUList` object to compare to the first `HDUList` object.
ignore_keywords : sequence, optional
Header keywords to ignore when comparing two headers; the presence
of these keywords and their values are ignored. Wildcard strings
may also be included in the list.
ignore_comments : sequence, optional
A list of header keywords whose comments should be ignored in the
comparison. May contain wildcard strings as with ignore_keywords.
numdiffs : int, optional
The number of pixel/table values to output when reporting HDU data
differences. Though the count of differences is the same either
way, this allows controlling the number of different values that
are kept in memory or output. If a negative value is given, then
numdiffs is treated as unlimited (default: 10).
rtol : float, optional
The relative difference to allow when comparing two float values
either in header values, image arrays, or table columns
(default: 0.0). Values which satisfy the expression
.. math::
\\left| a - b \\right| > \\text{atol} + \\text{rtol} \\cdot \\left| b \\right|
are considered to be different.
The underlying function used for comparison is `numpy.allclose`.
.. versionchanged:: 2.0
``rtol`` replaces the deprecated ``tolerance`` argument.
atol : float, optional
The allowed absolute difference. See also ``rtol`` parameter.
.. versionadded:: 2.0
ignore_blanks : bool, optional
Ignore extra whitespace at the end of string values either in
headers or data. Extra leading whitespace is not ignored
(default: True).
ignore_blank_cards : bool, optional
Ignore all cards that are blank, i.e. they only contain
whitespace (default: True).
"""
self.ignore_keywords = {k.upper() for k in ignore_keywords}
self.ignore_comments = {k.upper() for k in ignore_comments}
self.rtol = rtol
self.atol = atol
if tolerance is not None: # This should be removed in the next astropy version
warnings.warn(
'"tolerance" was deprecated in version 2.0 and will be removed in '
'a future version. Use argument "rtol" instead.',
AstropyDeprecationWarning)
self.rtol = tolerance # when tolerance is provided *always* ignore `rtol`
# during the transition/deprecation period
self.ignore_blanks = ignore_blanks
self.ignore_blank_cards = ignore_blank_cards
self.ignore_keyword_patterns = set()
self.ignore_comment_patterns = set()
for keyword in list(self.ignore_keywords):
keyword = keyword.upper()
if keyword != '*' and glob.has_magic(keyword):
self.ignore_keywords.remove(keyword)
self.ignore_keyword_patterns.add(keyword)
for keyword in list(self.ignore_comments):
keyword = keyword.upper()
if keyword != '*' and glob.has_magic(keyword):
self.ignore_comments.remove(keyword)
self.ignore_comment_patterns.add(keyword)
# Keywords appearing in each header
self.common_keywords = []
# Set to the number of keywords in each header if the counts differ
self.diff_keyword_count = ()
# Set if the keywords common to each header (excluding ignore_keywords)
# appear in different positions within the header
# TODO: Implement this
self.diff_keyword_positions = ()
# Keywords unique to each header (excluding keywords in
# ignore_keywords)
self.diff_keywords = ()
# Keywords that have different numbers of duplicates in each header
# (excluding keywords in ignore_keywords)
self.diff_duplicate_keywords = {}
# Keywords common to each header but having different values (excluding
# keywords in ignore_keywords)
self.diff_keyword_values = defaultdict(list)
# Keywords common to each header but having different comments
# (excluding keywords in ignore_keywords or in ignore_comments)
self.diff_keyword_comments = defaultdict(list)
if isinstance(a, str):
a = Header.fromstring(a)
if isinstance(b, str):
b = Header.fromstring(b)
if not (isinstance(a, Header) and isinstance(b, Header)):
raise TypeError('HeaderDiff can only diff astropy.io.fits.Header '
'objects or strings containing FITS headers.')
super().__init__(a, b)
# TODO: This doesn't pay much attention to the *order* of the keywords,
# except in the case of duplicate keywords. The order should be checked
# too, or at least it should be an option.
def _diff(self):
if self.ignore_blank_cards:
cardsa = [c for c in self.a.cards if str(c) != BLANK_CARD]
cardsb = [c for c in self.b.cards if str(c) != BLANK_CARD]
else:
cardsa = list(self.a.cards)
cardsb = list(self.b.cards)
# build dictionaries of keyword values and comments
def get_header_values_comments(cards):
values = {}
comments = {}
for card in cards:
value = card.value
if self.ignore_blanks and isinstance(value, str):
value = value.rstrip()
values.setdefault(card.keyword, []).append(value)
comments.setdefault(card.keyword, []).append(card.comment)
return values, comments
valuesa, commentsa = get_header_values_comments(cardsa)
valuesb, commentsb = get_header_values_comments(cardsb)
# Normalize all keyword to upper-case for comparison's sake;
# TODO: HIERARCH keywords should be handled case-sensitively I think
keywordsa = {k.upper() for k in valuesa}
keywordsb = {k.upper() for k in valuesb}
self.common_keywords = sorted(keywordsa.intersection(keywordsb))
if len(cardsa) != len(cardsb):
self.diff_keyword_count = (len(cardsa), len(cardsb))
# Any other diff attributes should exclude ignored keywords
keywordsa = keywordsa.difference(self.ignore_keywords)
keywordsb = keywordsb.difference(self.ignore_keywords)
if self.ignore_keyword_patterns:
for pattern in self.ignore_keyword_patterns:
keywordsa = keywordsa.difference(fnmatch.filter(keywordsa,
pattern))
keywordsb = keywordsb.difference(fnmatch.filter(keywordsb,
pattern))
if '*' in self.ignore_keywords:
# Any other differences between keywords are to be ignored
return
left_only_keywords = sorted(keywordsa.difference(keywordsb))
right_only_keywords = sorted(keywordsb.difference(keywordsa))
if left_only_keywords or right_only_keywords:
self.diff_keywords = (left_only_keywords, right_only_keywords)
# Compare count of each common keyword
for keyword in self.common_keywords:
if keyword in self.ignore_keywords:
continue
if self.ignore_keyword_patterns:
skip = False
for pattern in self.ignore_keyword_patterns:
if fnmatch.fnmatch(keyword, pattern):
skip = True
break
if skip:
continue
counta = len(valuesa[keyword])
countb = len(valuesb[keyword])
if counta != countb:
self.diff_duplicate_keywords[keyword] = (counta, countb)
# Compare keywords' values and comments
for a, b in zip(valuesa[keyword], valuesb[keyword]):
if diff_values(a, b, rtol=self.rtol, atol=self.atol):
self.diff_keyword_values[keyword].append((a, b))
else:
# If there are duplicate keywords we need to be able to
# index each duplicate; if the values of a duplicate
# are identical use None here
self.diff_keyword_values[keyword].append(None)
if not any(self.diff_keyword_values[keyword]):
# No differences found; delete the array of Nones
del self.diff_keyword_values[keyword]
if '*' in self.ignore_comments or keyword in self.ignore_comments:
continue
if self.ignore_comment_patterns:
skip = False
for pattern in self.ignore_comment_patterns:
if fnmatch.fnmatch(keyword, pattern):
skip = True
break
if skip:
continue
for a, b in zip(commentsa[keyword], commentsb[keyword]):
if diff_values(a, b):
self.diff_keyword_comments[keyword].append((a, b))
else:
self.diff_keyword_comments[keyword].append(None)
if not any(self.diff_keyword_comments[keyword]):
del self.diff_keyword_comments[keyword]
def _report(self):
if self.diff_keyword_count:
self._writeln(' Headers have different number of cards:')
self._writeln(' a: {}'.format(self.diff_keyword_count[0]))
self._writeln(' b: {}'.format(self.diff_keyword_count[1]))
if self.diff_keywords:
for keyword in self.diff_keywords[0]:
if keyword in Card._commentary_keywords:
val = self.a[keyword][0]
else:
val = self.a[keyword]
self._writeln(' Extra keyword {!r:8} in a: {!r}'.format(
keyword, val))
for keyword in self.diff_keywords[1]:
if keyword in Card._commentary_keywords:
val = self.b[keyword][0]
else:
val = self.b[keyword]
self._writeln(' Extra keyword {!r:8} in b: {!r}'.format(
keyword, val))
if self.diff_duplicate_keywords:
for keyword, count in sorted(self.diff_duplicate_keywords.items()):
self._writeln(' Inconsistent duplicates of keyword {!r:8}:'
.format(keyword))
self._writeln(' Occurs {} time(s) in a, {} times in (b)'
.format(*count))
if self.diff_keyword_values or self.diff_keyword_comments:
for keyword in self.common_keywords:
report_diff_keyword_attr(self._fileobj, 'values',
self.diff_keyword_values, keyword,
ind=self._indent)
report_diff_keyword_attr(self._fileobj, 'comments',
self.diff_keyword_comments, keyword,
ind=self._indent)
# TODO: It might be good if there was also a threshold option for percentage of
# different pixels: For example ignore if only 1% of the pixels are different
# within some threshold. There are lots of possibilities here, but hold off
# for now until specific cases come up.
class ImageDataDiff(_BaseDiff):
"""
Diff two image data arrays (really any array from a PRIMARY HDU or an IMAGE
extension HDU, though the data unit is assumed to be "pixels").
`ImageDataDiff` objects have the following diff attributes:
- ``diff_dimensions``: If the two arrays contain either a different number
of dimensions or different sizes in any dimension, this contains a
2-tuple of the shapes of each array. Currently no further comparison is
performed on images that don't have the exact same dimensions.
- ``diff_pixels``: If the two images contain any different pixels, this
contains a list of 2-tuples of the array index where the difference was
found, and another 2-tuple containing the different values. For example,
if the pixel at (0, 0) contains different values this would look like::
[(0, 0), (1.1, 2.2)]
where 1.1 and 2.2 are the values of that pixel in each array. This
array only contains up to ``self.numdiffs`` differences, for storage
efficiency.
- ``diff_total``: The total number of different pixels found between the
arrays. Although ``diff_pixels`` does not necessarily contain all the
different pixel values, this can be used to get a count of the total
number of differences found.
- ``diff_ratio``: Contains the ratio of ``diff_total`` to the total number
of pixels in the arrays.
"""
def __init__(self, a, b, numdiffs=10, rtol=0.0, atol=0.0, tolerance=None):
"""
Parameters
----------
a : `HDUList`
An `HDUList` object.
b : `HDUList`
An `HDUList` object to compare to the first `HDUList` object.
numdiffs : int, optional
The number of pixel/table values to output when reporting HDU data
differences. Though the count of differences is the same either
way, this allows controlling the number of different values that
are kept in memory or output. If a negative value is given, then
numdiffs is treated as unlimited (default: 10).
rtol : float, optional
The relative difference to allow when comparing two float values
either in header values, image arrays, or table columns
(default: 0.0). Values which satisfy the expression
.. math::
\\left| a - b \\right| > \\text{atol} + \\text{rtol} \\cdot \\left| b \\right|
are considered to be different.
The underlying function used for comparison is `numpy.allclose`.
.. versionchanged:: 2.0
``rtol`` replaces the deprecated ``tolerance`` argument.
atol : float, optional
The allowed absolute difference. See also ``rtol`` parameter.
.. versionadded:: 2.0
"""
self.numdiffs = numdiffs
self.rtol = rtol
self.atol = atol
if tolerance is not None: # This should be removed in the next astropy version
warnings.warn(
'"tolerance" was deprecated in version 2.0 and will be removed in '
'a future version. Use argument "rtol" instead.',
AstropyDeprecationWarning)
self.rtol = tolerance # when tolerance is provided *always* ignore `rtol`
# during the transition/deprecation period
self.diff_dimensions = ()
self.diff_pixels = []
self.diff_ratio = 0
# self.diff_pixels only holds up to numdiffs differing pixels, but this
# self.diff_total stores the total count of differences between
# the images, but not the different values
self.diff_total = 0
super().__init__(a, b)
def _diff(self):
if self.a.shape != self.b.shape:
self.diff_dimensions = (self.a.shape, self.b.shape)
# Don't do any further comparison if the dimensions differ
# TODO: Perhaps we could, however, diff just the intersection
# between the two images
return
# Find the indices where the values are not equal
# If neither a nor b are floating point (or complex), ignore rtol and
# atol
if not (np.issubdtype(self.a.dtype, np.inexact) or
np.issubdtype(self.b.dtype, np.inexact)):
rtol = 0
atol = 0
else:
rtol = self.rtol
atol = self.atol
diffs = where_not_allclose(self.a, self.b, atol=atol, rtol=rtol)
self.diff_total = len(diffs[0])
if self.diff_total == 0:
# Then we're done
return
if self.numdiffs < 0:
numdiffs = self.diff_total
else:
numdiffs = self.numdiffs
self.diff_pixels = [(idx, (self.a[idx], self.b[idx]))
for idx in islice(zip(*diffs), 0, numdiffs)]
self.diff_ratio = float(self.diff_total) / float(len(self.a.flat))
def _report(self):
if self.diff_dimensions:
dimsa = ' x '.join(str(d) for d in
reversed(self.diff_dimensions[0]))
dimsb = ' x '.join(str(d) for d in
reversed(self.diff_dimensions[1]))
self._writeln(' Data dimensions differ:')
self._writeln(' a: {}'.format(dimsa))
self._writeln(' b: {}'.format(dimsb))
# For now we don't do any further comparison if the dimensions
# differ; though in the future it might be nice to be able to
# compare at least where the images intersect
self._writeln(' No further data comparison performed.')
return
if not self.diff_pixels:
return
for index, values in self.diff_pixels:
index = [x + 1 for x in reversed(index)]
self._writeln(' Data differs at {}:'.format(index))
report_diff_values(values[0], values[1], fileobj=self._fileobj,
indent_width=self._indent + 1)
if self.diff_total > self.numdiffs:
self._writeln(' ...')
self._writeln(' {} different pixels found ({:.2%} different).'
.format(self.diff_total, self.diff_ratio))
class RawDataDiff(ImageDataDiff):
"""
`RawDataDiff` is just a special case of `ImageDataDiff` where the images
are one-dimensional, and the data is treated as a 1-dimensional array of
bytes instead of pixel values. This is used to compare the data of two
non-standard extension HDUs that were not recognized as containing image or
table data.
`ImageDataDiff` objects have the following diff attributes:
- ``diff_dimensions``: Same as the ``diff_dimensions`` attribute of
`ImageDataDiff` objects. Though the "dimension" of each array is just an
integer representing the number of bytes in the data.
- ``diff_bytes``: Like the ``diff_pixels`` attribute of `ImageDataDiff`
objects, but renamed to reflect the minor semantic difference that these
are raw bytes and not pixel values. Also the indices are integers
instead of tuples.
- ``diff_total`` and ``diff_ratio``: Same as `ImageDataDiff`.
"""
def __init__(self, a, b, numdiffs=10):
"""
Parameters
----------
a : `HDUList`
An `HDUList` object.
b : `HDUList`
An `HDUList` object to compare to the first `HDUList` object.
numdiffs : int, optional
The number of pixel/table values to output when reporting HDU data
differences. Though the count of differences is the same either
way, this allows controlling the number of different values that
are kept in memory or output. If a negative value is given, then
numdiffs is treated as unlimited (default: 10).
"""
self.diff_dimensions = ()
self.diff_bytes = []
super().__init__(a, b, numdiffs=numdiffs)
def _diff(self):
super()._diff()
if self.diff_dimensions:
self.diff_dimensions = (self.diff_dimensions[0][0],
self.diff_dimensions[1][0])
self.diff_bytes = [(x[0], y) for x, y in self.diff_pixels]
del self.diff_pixels
def _report(self):
if self.diff_dimensions:
self._writeln(' Data sizes differ:')
self._writeln(' a: {} bytes'.format(self.diff_dimensions[0]))
self._writeln(' b: {} bytes'.format(self.diff_dimensions[1]))
# For now we don't do any further comparison if the dimensions
# differ; though in the future it might be nice to be able to
# compare at least where the images intersect
self._writeln(' No further data comparison performed.')
return
if not self.diff_bytes:
return
for index, values in self.diff_bytes:
self._writeln(' Data differs at byte {}:'.format(index))
report_diff_values(values[0], values[1], fileobj=self._fileobj,
indent_width=self._indent + 1)
self._writeln(' ...')
self._writeln(' {} different bytes found ({:.2%} different).'
.format(self.diff_total, self.diff_ratio))
class TableDataDiff(_BaseDiff):
"""
Diff two table data arrays. It doesn't matter whether the data originally
came from a binary or ASCII table--the data should be passed in as a
recarray.
`TableDataDiff` objects have the following diff attributes:
- ``diff_column_count``: If the tables being compared have different
numbers of columns, this contains a 2-tuple of the column count in each
table. Even if the tables have different column counts, an attempt is
still made to compare any columns they have in common.
- ``diff_columns``: If either table contains columns unique to that table,
either in name or format, this contains a 2-tuple of lists. The first
element is a list of columns (these are full `Column` objects) that
appear only in table a. The second element is a list of tables that
appear only in table b. This only lists columns with different column
definitions, and has nothing to do with the data in those columns.
- ``diff_column_names``: This is like ``diff_columns``, but lists only the
names of columns unique to either table, rather than the full `Column`
objects.
- ``diff_column_attributes``: Lists columns that are in both tables but
have different secondary attributes, such as TUNIT or TDISP. The format
is a list of 2-tuples: The first a tuple of the column name and the
attribute, the second a tuple of the different values.
- ``diff_values``: `TableDataDiff` compares the data in each table on a
column-by-column basis. If any different data is found, it is added to
this list. The format of this list is similar to the ``diff_pixels``
attribute on `ImageDataDiff` objects, though the "index" consists of a
(column_name, row) tuple. For example::
[('TARGET', 0), ('NGC1001', 'NGC1002')]
shows that the tables contain different values in the 0-th row of the
'TARGET' column.
- ``diff_total`` and ``diff_ratio``: Same as `ImageDataDiff`.
`TableDataDiff` objects also have a ``common_columns`` attribute that lists
the `Column` objects for columns that are identical in both tables, and a
``common_column_names`` attribute which contains a set of the names of
those columns.
"""
def __init__(self, a, b, ignore_fields=[], numdiffs=10, rtol=0.0, atol=0.0,
tolerance=None):
"""
Parameters
----------
a : `HDUList`
An `HDUList` object.
b : `HDUList`
An `HDUList` object to compare to the first `HDUList` object.
ignore_fields : sequence, optional
The (case-insensitive) names of any table columns to ignore if any
table data is to be compared.
numdiffs : int, optional
The number of pixel/table values to output when reporting HDU data
differences. Though the count of differences is the same either
way, this allows controlling the number of different values that
are kept in memory or output. If a negative value is given, then
numdiffs is treated as unlimited (default: 10).
rtol : float, optional
The relative difference to allow when comparing two float values
either in header values, image arrays, or table columns
(default: 0.0). Values which satisfy the expression
.. math::
\\left| a - b \\right| > \\text{atol} + \\text{rtol} \\cdot \\left| b \\right|
are considered to be different.
The underlying function used for comparison is `numpy.allclose`.
.. versionchanged:: 2.0
``rtol`` replaces the deprecated ``tolerance`` argument.
atol : float, optional
The allowed absolute difference. See also ``rtol`` parameter.
.. versionadded:: 2.0
"""
self.ignore_fields = set(ignore_fields)
self.numdiffs = numdiffs
self.rtol = rtol
self.atol = atol
if tolerance is not None: # This should be removed in the next astropy version
warnings.warn(
'"tolerance" was deprecated in version 2.0 and will be removed in '
'a future version. Use argument "rtol" instead.',
AstropyDeprecationWarning)
self.rtol = tolerance # when tolerance is provided *always* ignore `rtol`
# during the transition/deprecation period
self.common_columns = []
self.common_column_names = set()
# self.diff_columns contains columns with different column definitions,
# but not different column data. Column data is only compared in
# columns that have the same definitions
self.diff_rows = ()
self.diff_column_count = ()
self.diff_columns = ()
# If two columns have the same name+format, but other attributes are
# different (such as TUNIT or such) they are listed here
self.diff_column_attributes = []
# Like self.diff_columns, but just contains a list of the column names
# unique to each table, and in the order they appear in the tables
self.diff_column_names = ()
self.diff_values = []
self.diff_ratio = 0
self.diff_total = 0
super().__init__(a, b)
def _diff(self):
# Much of the code for comparing columns is similar to the code for
# comparing headers--consider refactoring
colsa = self.a.columns
colsb = self.b.columns
if len(colsa) != len(colsb):
self.diff_column_count = (len(colsa), len(colsb))
# Even if the number of columns are unequal, we still do comparison of
# any common columns
colsa = {c.name.lower(): c for c in colsa}
colsb = {c.name.lower(): c for c in colsb}
if '*' in self.ignore_fields:
# If all columns are to be ignored, ignore any further differences
# between the columns
return
# Keep the user's original ignore_fields list for reporting purposes,
# but internally use a case-insensitive version
ignore_fields = {f.lower() for f in self.ignore_fields}
# It might be nice if there were a cleaner way to do this, but for now
# it'll do
for fieldname in ignore_fields:
fieldname = fieldname.lower()
if fieldname in colsa:
del colsa[fieldname]
if fieldname in colsb:
del colsb[fieldname]
colsa_set = set(colsa.values())
colsb_set = set(colsb.values())
self.common_columns = sorted(colsa_set.intersection(colsb_set),
key=operator.attrgetter('name'))
self.common_column_names = {col.name.lower()
for col in self.common_columns}
left_only_columns = {col.name.lower(): col
for col in colsa_set.difference(colsb_set)}
right_only_columns = {col.name.lower(): col
for col in colsb_set.difference(colsa_set)}
if left_only_columns or right_only_columns:
self.diff_columns = (left_only_columns, right_only_columns)
self.diff_column_names = ([], [])
if left_only_columns:
for col in self.a.columns:
if col.name.lower() in left_only_columns:
self.diff_column_names[0].append(col.name)
if right_only_columns:
for col in self.b.columns:
if col.name.lower() in right_only_columns:
self.diff_column_names[1].append(col.name)
# If the tables have a different number of rows, we don't compare the
# columns right now.
# TODO: It might be nice to optionally compare the first n rows where n
# is the minimum of the row counts between the two tables.
if len(self.a) != len(self.b):
self.diff_rows = (len(self.a), len(self.b))
return
# If the tables contain no rows there's no data to compare, so we're
# done at this point. (See ticket #178)
if len(self.a) == len(self.b) == 0:
return
# Like in the old fitsdiff, compare tables on a column by column basis
# The difficulty here is that, while FITS column names are meant to be
# case-insensitive, Astropy still allows, for the sake of flexibility,
# two columns with the same name but different case. When columns are
# accessed in FITS tables, a case-sensitive is tried first, and failing
# that a case-insensitive match is made.
# It's conceivable that the same column could appear in both tables
# being compared, but with different case.
# Though it *may* lead to inconsistencies in these rare cases, this
# just assumes that there are no duplicated column names in either
# table, and that the column names can be treated case-insensitively.
for col in self.common_columns:
name_lower = col.name.lower()
if name_lower in ignore_fields:
continue
cola = colsa[name_lower]
colb = colsb[name_lower]
for attr, _ in _COL_ATTRS:
vala = getattr(cola, attr, None)
valb = getattr(colb, attr, None)
if diff_values(vala, valb):
self.diff_column_attributes.append(
((col.name.upper(), attr), (vala, valb)))
arra = self.a[col.name]
arrb = self.b[col.name]
if (np.issubdtype(arra.dtype, np.floating) and
np.issubdtype(arrb.dtype, np.floating)):
diffs = where_not_allclose(arra, arrb,
rtol=self.rtol,
atol=self.atol)
elif 'P' in col.format:
diffs = ([idx for idx in range(len(arra))
if not np.allclose(arra[idx], arrb[idx],
rtol=self.rtol,
atol=self.atol)],)
else:
diffs = np.where(arra != arrb)
self.diff_total += len(set(diffs[0]))
if self.numdiffs >= 0:
if len(self.diff_values) >= self.numdiffs:
# Don't save any more diff values
continue
# Add no more diff'd values than this
max_diffs = self.numdiffs - len(self.diff_values)
else:
max_diffs = len(diffs[0])
last_seen_idx = None
for idx in islice(diffs[0], 0, max_diffs):
if idx == last_seen_idx:
# Skip duplicate indices, which my occur when the column
# data contains multi-dimensional values; we're only
# interested in storing row-by-row differences
continue
last_seen_idx = idx
self.diff_values.append(((col.name, idx),
(arra[idx], arrb[idx])))
total_values = len(self.a) * len(self.a.dtype.fields)
self.diff_ratio = float(self.diff_total) / float(total_values)
def _report(self):
if self.diff_column_count:
self._writeln(' Tables have different number of columns:')
self._writeln(' a: {}'.format(self.diff_column_count[0]))
self._writeln(' b: {}'.format(self.diff_column_count[1]))
if self.diff_column_names:
# Show columns with names unique to either table
for name in self.diff_column_names[0]:
format = self.diff_columns[0][name.lower()].format
self._writeln(' Extra column {} of format {} in a'.format(
name, format))
for name in self.diff_column_names[1]:
format = self.diff_columns[1][name.lower()].format
self._writeln(' Extra column {} of format {} in b'.format(
name, format))
col_attrs = dict(_COL_ATTRS)
# Now go through each table again and show columns with common
# names but other property differences...
for col_attr, vals in self.diff_column_attributes:
name, attr = col_attr
self._writeln(' Column {} has different {}:'.format(
name, col_attrs[attr]))
report_diff_values(vals[0], vals[1], fileobj=self._fileobj,
indent_width=self._indent + 1)
if self.diff_rows:
self._writeln(' Table rows differ:')
self._writeln(' a: {}'.format(self.diff_rows[0]))
self._writeln(' b: {}'.format(self.diff_rows[1]))
self._writeln(' No further data comparison performed.')
return
if not self.diff_values:
return
# Finally, let's go through and report column data differences:
for indx, values in self.diff_values:
self._writeln(' Column {} data differs in row {}:'.format(*indx))
report_diff_values(values[0], values[1], fileobj=self._fileobj,
indent_width=self._indent + 1)
if self.diff_values and self.numdiffs < self.diff_total:
self._writeln(' ...{} additional difference(s) found.'.format(
(self.diff_total - self.numdiffs)))
if self.diff_total > self.numdiffs:
self._writeln(' ...')
self._writeln(' {} different table data element(s) found '
'({:.2%} different).'
.format(self.diff_total, self.diff_ratio))
def report_diff_keyword_attr(fileobj, attr, diffs, keyword, ind=0):
"""
Write a diff between two header keyword values or comments to the specified
file-like object.
"""
if keyword in diffs:
vals = diffs[keyword]
for idx, val in enumerate(vals):
if val is None:
continue
if idx == 0:
dup = ''
else:
dup = '[{}]'.format(idx + 1)
fileobj.write(
fixed_width_indent(' Keyword {:8}{} has different {}:\n'
.format(keyword, dup, attr), ind))
report_diff_values(val[0], val[1], fileobj=fileobj,
indent_width=ind + 1)
|
a61a544ee28c51ba84ac16eb8662d19e2ce119f815d027bc30863e812bb811b0 | # Licensed under a 3-clause BSD style license - see PYFITS.rst
"""
A package for reading and writing FITS files and manipulating their
contents.
A module for reading and writing Flexible Image Transport System
(FITS) files. This file format was endorsed by the International
Astronomical Union in 1999 and mandated by NASA as the standard format
for storing high energy astrophysics data. For details of the FITS
standard, see the NASA/Science Office of Standards and Technology
publication, NOST 100-2.0.
"""
from astropy import config as _config
# Set module-global boolean variables
# TODO: Make it possible to set these variables via environment variables
# again, once support for that is added to Astropy
class Conf(_config.ConfigNamespace):
"""
Configuration parameters for `astropy.io.fits`.
"""
enable_record_valued_keyword_cards = _config.ConfigItem(
True,
'If True, enable support for record-valued keywords as described by '
'FITS WCS distortion paper. Otherwise they are treated as normal '
'keywords.',
aliases=['astropy.io.fits.enabled_record_valued_keyword_cards'])
extension_name_case_sensitive = _config.ConfigItem(
False,
'If True, extension names (i.e. the ``EXTNAME`` keyword) should be '
'treated as case-sensitive.')
strip_header_whitespace = _config.ConfigItem(
True,
'If True, automatically remove trailing whitespace for string values in '
'headers. Otherwise the values are returned verbatim, with all '
'whitespace intact.')
use_memmap = _config.ConfigItem(
True,
'If True, use memory-mapped file access to read/write the data in '
'FITS files. This generally provides better performance, especially '
'for large files, but may affect performance in I/O-heavy '
'applications.')
lazy_load_hdus = _config.ConfigItem(
True,
'If True, use lazy loading of HDUs when opening FITS files by '
'default; that is fits.open() will only seek for and read HDUs on '
'demand rather than reading all HDUs at once. See the documentation '
'for fits.open() for more datails.')
enable_uint = _config.ConfigItem(
True,
'If True, default to recognizing the convention for representing '
'unsigned integers in FITS--if an array has BITPIX > 0, BSCALE = 1, '
'and BZERO = 2**BITPIX, represent the data as unsigned integers '
'per this convention.')
conf = Conf()
# Public API compatibility imports
# These need to come after the global config variables, as some of the
# submodules use them
from . import card
from . import column
from . import convenience
from . import hdu
from .card import *
from .column import *
from .convenience import *
from .diff import *
from .fitsrec import FITS_record, FITS_rec
from .hdu import *
from .hdu.groups import GroupData
from .hdu.hdulist import fitsopen as open
from .hdu.image import Section
from .header import Header
from .verify import VerifyError
__all__ = (['Conf', 'conf'] + card.__all__ + column.__all__ +
convenience.__all__ + hdu.__all__ +
['FITS_record', 'FITS_rec', 'GroupData', 'open', 'Section',
'Header', 'VerifyError', 'conf'])
|
7f3fa5efcdd3dbccfdc8d7454cd8061d25c1d48ade46eada3ad5f8a1a927f06b | # Licensed under a 3-clause BSD style license - see PYFITS.rst
import copy
import operator
import re
import sys
import warnings
import weakref
import numbers
from functools import reduce
from collections import OrderedDict
from contextlib import suppress
import numpy as np
from numpy import char as chararray
from .card import Card, CARD_LENGTH
from .util import (pairwise, _is_int, _convert_array, encode_ascii, cmp,
NotifierMixin)
from .verify import VerifyError, VerifyWarning
from astropy.utils import lazyproperty, isiterable, indent
from astropy.utils.exceptions import AstropyUserWarning
__all__ = ['Column', 'ColDefs', 'Delayed']
# mapping from TFORM data type to numpy data type (code)
# L: Logical (Boolean)
# B: Unsigned Byte
# I: 16-bit Integer
# J: 32-bit Integer
# K: 64-bit Integer
# E: Single-precision Floating Point
# D: Double-precision Floating Point
# C: Single-precision Complex
# M: Double-precision Complex
# A: Character
FITS2NUMPY = {'L': 'i1', 'B': 'u1', 'I': 'i2', 'J': 'i4', 'K': 'i8', 'E': 'f4',
'D': 'f8', 'C': 'c8', 'M': 'c16', 'A': 'a'}
# the inverse dictionary of the above
NUMPY2FITS = {val: key for key, val in FITS2NUMPY.items()}
# Normally booleans are represented as ints in Astropy, but if passed in a numpy
# boolean array, that should be supported
NUMPY2FITS['b1'] = 'L'
# Add unsigned types, which will be stored as signed ints with a TZERO card.
NUMPY2FITS['u2'] = 'I'
NUMPY2FITS['u4'] = 'J'
NUMPY2FITS['u8'] = 'K'
# Add half precision floating point numbers which will be up-converted to
# single precision.
NUMPY2FITS['f2'] = 'E'
# This is the order in which values are converted to FITS types
# Note that only double precision floating point/complex are supported
FORMATORDER = ['L', 'B', 'I', 'J', 'K', 'D', 'M', 'A']
# Convert single precision floating point/complex to double precision.
FITSUPCONVERTERS = {'E': 'D', 'C': 'M'}
# mapping from ASCII table TFORM data type to numpy data type
# A: Character
# I: Integer (32-bit)
# J: Integer (64-bit; non-standard)
# F: Float (64-bit; fixed decimal notation)
# E: Float (64-bit; exponential notation)
# D: Float (64-bit; exponential notation, always 64-bit by convention)
ASCII2NUMPY = {'A': 'a', 'I': 'i4', 'J': 'i8', 'F': 'f8', 'E': 'f8', 'D': 'f8'}
# Maps FITS ASCII column format codes to the appropriate Python string
# formatting codes for that type.
ASCII2STR = {'A': '', 'I': 'd', 'J': 'd', 'F': 'f', 'E': 'E', 'D': 'E'}
# For each ASCII table format code, provides a default width (and decimal
# precision) for when one isn't given explicitly in the column format
ASCII_DEFAULT_WIDTHS = {'A': (1, 0), 'I': (10, 0), 'J': (15, 0),
'E': (15, 7), 'F': (16, 7), 'D': (25, 17)}
# TDISPn for both ASCII and Binary tables
TDISP_RE_DICT = {}
TDISP_RE_DICT['F'] = re.compile(r'(?:(?P<formatc>[F])(?:(?P<width>[0-9]+)\.{1}'
r'(?P<precision>[0-9])+)+)|')
TDISP_RE_DICT['A'] = TDISP_RE_DICT['L'] = \
re.compile(r'(?:(?P<formatc>[AL])(?P<width>[0-9]+)+)|')
TDISP_RE_DICT['I'] = TDISP_RE_DICT['B'] = \
TDISP_RE_DICT['O'] = TDISP_RE_DICT['Z'] = \
re.compile(r'(?:(?P<formatc>[IBOZ])(?:(?P<width>[0-9]+)'
r'(?:\.{0,1}(?P<precision>[0-9]+))?))|')
TDISP_RE_DICT['E'] = TDISP_RE_DICT['G'] = \
TDISP_RE_DICT['D'] = \
re.compile(r'(?:(?P<formatc>[EGD])(?:(?P<width>[0-9]+)\.'
r'(?P<precision>[0-9]+))+)'
r'(?:E{0,1}(?P<exponential>[0-9]+)?)|')
TDISP_RE_DICT['EN'] = TDISP_RE_DICT['ES'] = \
re.compile(r'(?:(?P<formatc>E[NS])(?:(?P<width>[0-9]+)\.{1}'
r'(?P<precision>[0-9])+)+)')
# mapping from TDISP format to python format
# A: Character
# L: Logical (Boolean)
# I: 16-bit Integer
# Can't predefine zero padding and space padding before hand without
# knowing the value being formatted, so grabbing precision and using that
# to zero pad, ignoring width. Same with B, O, and Z
# B: Binary Integer
# O: Octal Integer
# Z: Hexadecimal Integer
# F: Float (64-bit; fixed decimal notation)
# EN: Float (engineering fortran format, exponential multiple of thee
# ES: Float (scientific, same as EN but non-zero leading digit
# E: Float, exponential notation
# Can't get exponential restriction to work without knowing value
# before hand, so just using width and precision, same with D, G, EN, and
# ES formats
# D: Double-precision Floating Point with exponential
# (E but for double precision)
# G: Double-precision Floating Point, may or may not show exponent
TDISP_FMT_DICT = {'I' : '{{:{width}d}}',
'B' : '{{:{width}b}}',
'O' : '{{:{width}o}}',
'Z' : '{{:{width}x}}',
'F' : '{{:{width}.{precision}f}}',
'G' : '{{:{width}.{precision}g}}'}
TDISP_FMT_DICT['A'] = TDISP_FMT_DICT['L'] = '{{:>{width}}}'
TDISP_FMT_DICT['E'] = TDISP_FMT_DICT['D'] = \
TDISP_FMT_DICT['EN'] = TDISP_FMT_DICT['ES'] ='{{:{width}.{precision}e}}'
# tuple of column/field definition common names and keyword names, make
# sure to preserve the one-to-one correspondence when updating the list(s).
# Use lists, instead of dictionaries so the names can be displayed in a
# preferred order.
KEYWORD_NAMES = ('TTYPE', 'TFORM', 'TUNIT', 'TNULL', 'TSCAL', 'TZERO',
'TDISP', 'TBCOL', 'TDIM', 'TCTYP', 'TCUNI', 'TCRPX',
'TCRVL', 'TCDLT', 'TRPOS')
KEYWORD_ATTRIBUTES = ('name', 'format', 'unit', 'null', 'bscale', 'bzero',
'disp', 'start', 'dim', 'coord_type', 'coord_unit',
'coord_ref_point', 'coord_ref_value', 'coord_inc',
'time_ref_pos')
"""This is a list of the attributes that can be set on `Column` objects."""
KEYWORD_TO_ATTRIBUTE = OrderedDict(zip(KEYWORD_NAMES, KEYWORD_ATTRIBUTES))
ATTRIBUTE_TO_KEYWORD = OrderedDict(zip(KEYWORD_ATTRIBUTES, KEYWORD_NAMES))
# TODO: Define a list of default comments to associate with each table keyword
# TFORMn regular expression
TFORMAT_RE = re.compile(r'(?P<repeat>^[0-9]*)(?P<format>[LXBIJKAEDCMPQ])'
r'(?P<option>[!-~]*)', re.I)
# TFORMn for ASCII tables; two different versions depending on whether
# the format is floating-point or not; allows empty values for width
# in which case defaults are used
TFORMAT_ASCII_RE = re.compile(r'(?:(?P<format>[AIJ])(?P<width>[0-9]+)?)|'
r'(?:(?P<formatf>[FED])'
r'(?:(?P<widthf>[0-9]+)\.'
r'(?P<precision>[0-9]+))?)')
TTYPE_RE = re.compile(r'[0-9a-zA-Z_]+')
"""
Regular expression for valid table column names. See FITS Standard v3.0 section
7.2.2.
"""
# table definition keyword regular expression
TDEF_RE = re.compile(r'(?P<label>^T[A-Z]*)(?P<num>[1-9][0-9 ]*$)')
# table dimension keyword regular expression (fairly flexible with whitespace)
TDIM_RE = re.compile(r'\(\s*(?P<dims>(?:\d+,\s*)+\s*\d+)\s*\)\s*')
# value for ASCII table cell with value = TNULL
# this can be reset by user.
ASCIITNULL = 0
# The default placeholder to use for NULL values in ASCII tables when
# converting from binary to ASCII tables
DEFAULT_ASCII_TNULL = '---'
class Delayed:
"""Delayed file-reading data."""
def __init__(self, hdu=None, field=None):
self.hdu = weakref.proxy(hdu)
self.field = field
def __getitem__(self, key):
# This forces the data for the HDU to be read, which will replace
# the corresponding Delayed objects in the Tables Columns to be
# transformed into ndarrays. It will also return the value of the
# requested data element.
return self.hdu.data[key][self.field]
class _BaseColumnFormat(str):
"""
Base class for binary table column formats (just called _ColumnFormat)
and ASCII table column formats (_AsciiColumnFormat).
"""
def __eq__(self, other):
if not other:
return False
if isinstance(other, str):
if not isinstance(other, self.__class__):
try:
other = self.__class__(other)
except ValueError:
return False
else:
return False
return self.canonical == other.canonical
def __hash__(self):
return hash(self.canonical)
@lazyproperty
def dtype(self):
"""
The Numpy dtype object created from the format's associated recformat.
"""
return np.dtype(self.recformat)
@classmethod
def from_column_format(cls, format):
"""Creates a column format object from another column format object
regardless of their type.
That is, this can convert a _ColumnFormat to an _AsciiColumnFormat
or vice versa at least in cases where a direct translation is possible.
"""
return cls.from_recformat(format.recformat)
class _ColumnFormat(_BaseColumnFormat):
"""
Represents a FITS binary table column format.
This is an enhancement over using a normal string for the format, since the
repeat count, format code, and option are available as separate attributes,
and smart comparison is used. For example 1J == J.
"""
def __new__(cls, format):
self = super().__new__(cls, format)
self.repeat, self.format, self.option = _parse_tformat(format)
self.format = self.format.upper()
if self.format in ('P', 'Q'):
# TODO: There should be a generic factory that returns either
# _FormatP or _FormatQ as appropriate for a given TFORMn
if self.format == 'P':
recformat = _FormatP.from_tform(format)
else:
recformat = _FormatQ.from_tform(format)
# Format of variable length arrays
self.p_format = recformat.format
else:
self.p_format = None
return self
@classmethod
def from_recformat(cls, recformat):
"""Creates a column format from a Numpy record dtype format."""
return cls(_convert_format(recformat, reverse=True))
@lazyproperty
def recformat(self):
"""Returns the equivalent Numpy record format string."""
return _convert_format(self)
@lazyproperty
def canonical(self):
"""
Returns a 'canonical' string representation of this format.
This is in the proper form of rTa where T is the single character data
type code, a is the optional part, and r is the repeat. If repeat == 1
(the default) it is left out of this representation.
"""
if self.repeat == 1:
repeat = ''
else:
repeat = str(self.repeat)
return '{}{}{}'.format(repeat, self.format, self.option)
class _AsciiColumnFormat(_BaseColumnFormat):
"""Similar to _ColumnFormat but specifically for columns in ASCII tables.
The formats of ASCII table columns and binary table columns are inherently
incompatible in FITS. They don't support the same ranges and types of
values, and even reuse format codes in subtly different ways. For example
the format code 'Iw' in ASCII columns refers to any integer whose string
representation is at most w characters wide, so 'I' can represent
effectively any integer that will fit in a FITS columns. Whereas for
binary tables 'I' very explicitly refers to a 16-bit signed integer.
Conversions between the two column formats can be performed using the
``to/from_binary`` methods on this class, or the ``to/from_ascii``
methods on the `_ColumnFormat` class. But again, not all conversions are
possible and may result in a `ValueError`.
"""
def __new__(cls, format, strict=False):
self = super().__new__(cls, format)
self.format, self.width, self.precision = \
_parse_ascii_tformat(format, strict)
# This is to support handling logical (boolean) data from binary tables
# in an ASCII table
self._pseudo_logical = False
return self
@classmethod
def from_column_format(cls, format):
inst = cls.from_recformat(format.recformat)
# Hack
if format.format == 'L':
inst._pseudo_logical = True
return inst
@classmethod
def from_recformat(cls, recformat):
"""Creates a column format from a Numpy record dtype format."""
return cls(_convert_ascii_format(recformat, reverse=True))
@lazyproperty
def recformat(self):
"""Returns the equivalent Numpy record format string."""
return _convert_ascii_format(self)
@lazyproperty
def canonical(self):
"""
Returns a 'canonical' string representation of this format.
This is in the proper form of Tw.d where T is the single character data
type code, w is the width in characters for this field, and d is the
number of digits after the decimal place (for format codes 'E', 'F',
and 'D' only).
"""
if self.format in ('E', 'F', 'D'):
return '{}{}.{}'.format(self.format, self.width, self.precision)
return '{}{}'.format(self.format, self.width)
class _FormatX(str):
"""For X format in binary tables."""
def __new__(cls, repeat=1):
nbytes = ((repeat - 1) // 8) + 1
# use an array, even if it is only ONE u1 (i.e. use tuple always)
obj = super().__new__(cls, repr((nbytes,)) + 'u1')
obj.repeat = repeat
return obj
def __getnewargs__(self):
return (self.repeat,)
@property
def tform(self):
return '{}X'.format(self.repeat)
# TODO: Table column formats need to be verified upon first reading the file;
# as it is, an invalid P format will raise a VerifyError from some deep,
# unexpected place
class _FormatP(str):
"""For P format in variable length table."""
# As far as I can tell from my reading of the FITS standard, a type code is
# *required* for P and Q formats; there is no default
_format_re_template = (r'(?P<repeat>\d+)?{}(?P<dtype>[LXBIJKAEDCM])'
r'(?:\((?P<max>\d*)\))?')
_format_code = 'P'
_format_re = re.compile(_format_re_template.format(_format_code))
_descriptor_format = '2i4'
def __new__(cls, dtype, repeat=None, max=None):
obj = super().__new__(cls, cls._descriptor_format)
obj.format = NUMPY2FITS[dtype]
obj.dtype = dtype
obj.repeat = repeat
obj.max = max
return obj
def __getnewargs__(self):
return (self.dtype, self.repeat, self.max)
@classmethod
def from_tform(cls, format):
m = cls._format_re.match(format)
if not m or m.group('dtype') not in FITS2NUMPY:
raise VerifyError('Invalid column format: {}'.format(format))
repeat = m.group('repeat')
array_dtype = m.group('dtype')
max = m.group('max')
if not max:
max = None
return cls(FITS2NUMPY[array_dtype], repeat=repeat, max=max)
@property
def tform(self):
repeat = '' if self.repeat is None else self.repeat
max = '' if self.max is None else self.max
return '{}{}{}({})'.format(repeat, self._format_code, self.format, max)
class _FormatQ(_FormatP):
"""Carries type description of the Q format for variable length arrays.
The Q format is like the P format but uses 64-bit integers in the array
descriptors, allowing for heaps stored beyond 2GB into a file.
"""
_format_code = 'Q'
_format_re = re.compile(_FormatP._format_re_template.format(_format_code))
_descriptor_format = '2i8'
class ColumnAttribute:
"""
Descriptor for attributes of `Column` that are associated with keywords
in the FITS header and describe properties of the column as specified in
the FITS standard.
Each `ColumnAttribute` may have a ``validator`` method defined on it.
This validates values set on this attribute to ensure that they meet the
FITS standard. Invalid values will raise a warning and will not be used in
formatting the column. The validator should take two arguments--the
`Column` it is being assigned to, and the new value for the attribute, and
it must raise an `AssertionError` if the value is invalid.
The `ColumnAttribute` itself is a decorator that can be used to define the
``validator`` for each column attribute. For example::
@ColumnAttribute('TTYPE')
def name(col, name):
if not isinstance(name, str):
raise AssertionError
The actual object returned by this decorator is the `ColumnAttribute`
instance though, not the ``name`` function. As such ``name`` is not a
method of the class it is defined in.
The setter for `ColumnAttribute` also updates the header of any table
HDU this column is attached to in order to reflect the change. The
``validator`` should ensure that the value is valid for inclusion in a FITS
header.
"""
def __init__(self, keyword):
self._keyword = keyword
self._validator = None
# The name of the attribute associated with this keyword is currently
# determined from the KEYWORD_NAMES/ATTRIBUTES lists. This could be
# make more flexible in the future, for example, to support custom
# column attributes.
self._attr = '_' + KEYWORD_TO_ATTRIBUTE[self._keyword]
def __get__(self, obj, objtype=None):
if obj is None:
return self
else:
return getattr(obj, self._attr)
def __set__(self, obj, value):
if self._validator is not None:
self._validator(obj, value)
old_value = getattr(obj, self._attr, None)
setattr(obj, self._attr, value)
obj._notify('column_attribute_changed', obj, self._attr[1:], old_value,
value)
def __call__(self, func):
"""
Set the validator for this column attribute.
Returns ``self`` so that this can be used as a decorator, as described
in the docs for this class.
"""
self._validator = func
return self
def __repr__(self):
return "{0}('{1}')".format(self.__class__.__name__, self._keyword)
class Column(NotifierMixin):
"""
Class which contains the definition of one column, e.g. ``ttype``,
``tform``, etc. and the array containing values for the column.
"""
def __init__(self, name=None, format=None, unit=None, null=None,
bscale=None, bzero=None, disp=None, start=None, dim=None,
array=None, ascii=None, coord_type=None, coord_unit=None,
coord_ref_point=None, coord_ref_value=None, coord_inc=None,
time_ref_pos=None):
"""
Construct a `Column` by specifying attributes. All attributes
except ``format`` can be optional; see :ref:`column_creation` and
:ref:`creating_ascii_table` for more information regarding
``TFORM`` keyword.
Parameters
----------
name : str, optional
column name, corresponding to ``TTYPE`` keyword
format : str
column format, corresponding to ``TFORM`` keyword
unit : str, optional
column unit, corresponding to ``TUNIT`` keyword
null : str, optional
null value, corresponding to ``TNULL`` keyword
bscale : int-like, optional
bscale value, corresponding to ``TSCAL`` keyword
bzero : int-like, optional
bzero value, corresponding to ``TZERO`` keyword
disp : str, optional
display format, corresponding to ``TDISP`` keyword
start : int, optional
column starting position (ASCII table only), corresponding
to ``TBCOL`` keyword
dim : str, optional
column dimension corresponding to ``TDIM`` keyword
array : iterable, optional
a `list`, `numpy.ndarray` (or other iterable that can be used to
initialize an ndarray) providing initial data for this column.
The array will be automatically converted, if possible, to the data
format of the column. In the case were non-trivial ``bscale``
and/or ``bzero`` arguments are given, the values in the array must
be the *physical* values--that is, the values of column as if the
scaling has already been applied (the array stored on the column
object will then be converted back to its storage values).
ascii : bool, optional
set `True` if this describes a column for an ASCII table; this
may be required to disambiguate the column format
coord_type : str, optional
coordinate/axis type corresponding to ``TCTYP`` keyword
coord_unit : str, optional
coordinate/axis unit corresponding to ``TCUNI`` keyword
coord_ref_point : int-like, optional
pixel coordinate of the reference point corresponding to ``TCRPX``
keyword
coord_ref_value : int-like, optional
coordinate value at reference point corresponding to ``TCRVL``
keyword
coord_inc : int-like, optional
coordinate increment at reference point corresponding to ``TCDLT``
keyword
time_ref_pos : str, optional
reference position for a time coordinate column corresponding to
``TRPOS`` keyword
"""
if format is None:
raise ValueError('Must specify format to construct Column.')
# any of the input argument (except array) can be a Card or just
# a number/string
kwargs = {'ascii': ascii}
for attr in KEYWORD_ATTRIBUTES:
value = locals()[attr] # get the argument's value
if isinstance(value, Card):
value = value.value
kwargs[attr] = value
valid_kwargs, invalid_kwargs = self._verify_keywords(**kwargs)
if invalid_kwargs:
msg = ['The following keyword arguments to Column were invalid:']
for val in invalid_kwargs.values():
msg.append(indent(val[1]))
raise VerifyError('\n'.join(msg))
for attr in KEYWORD_ATTRIBUTES:
setattr(self, attr, valid_kwargs.get(attr))
# TODO: Try to eliminate the following two special cases
# for recformat and dim:
# This is not actually stored as an attribute on columns for some
# reason
recformat = valid_kwargs['recformat']
# The 'dim' keyword's original value is stored in self.dim, while
# *only* the tuple form is stored in self._dims.
self._dims = self.dim
self.dim = dim
# Awful hack to use for now to keep track of whether the column holds
# pseudo-unsigned int data
self._pseudo_unsigned_ints = False
# if the column data is not ndarray, make it to be one, i.e.
# input arrays can be just list or tuple, not required to be ndarray
# does not include Object array because there is no guarantee
# the elements in the object array are consistent.
if not isinstance(array,
(np.ndarray, chararray.chararray, Delayed)):
try: # try to convert to a ndarray first
if array is not None:
array = np.array(array)
except Exception:
try: # then try to convert it to a strings array
itemsize = int(recformat[1:])
array = chararray.array(array, itemsize=itemsize)
except ValueError:
# then try variable length array
# Note: This includes _FormatQ by inheritance
if isinstance(recformat, _FormatP):
array = _VLF(array, dtype=recformat.dtype)
else:
raise ValueError('Data is inconsistent with the '
'format `{}`.'.format(format))
array = self._convert_to_valid_data_type(array)
# We have required (through documentation) that arrays passed in to
# this constructor are already in their physical values, so we make
# note of that here
if isinstance(array, np.ndarray):
self._physical_values = True
else:
self._physical_values = False
self._parent_fits_rec = None
self.array = array
def __repr__(self):
text = ''
for attr in KEYWORD_ATTRIBUTES:
value = getattr(self, attr)
if value is not None:
text += attr + ' = ' + repr(value) + '; '
return text[:-2]
def __eq__(self, other):
"""
Two columns are equal if their name and format are the same. Other
attributes aren't taken into account at this time.
"""
# According to the FITS standard column names must be case-insensitive
a = (self.name.lower(), self.format)
b = (other.name.lower(), other.format)
return a == b
def __hash__(self):
"""
Like __eq__, the hash of a column should be based on the unique column
name and format, and be case-insensitive with respect to the column
name.
"""
return hash((self.name.lower(), self.format))
@property
def array(self):
"""
The Numpy `~numpy.ndarray` associated with this `Column`.
If the column was instantiated with an array passed to the ``array``
argument, this will return that array. However, if the column is
later added to a table, such as via `BinTableHDU.from_columns` as
is typically the case, this attribute will be updated to reference
the associated field in the table, which may no longer be the same
array.
"""
# Ideally the .array attribute never would have existed in the first
# place, or would have been internal-only. This is a legacy of the
# older design from Astropy that needs to have continued support, for
# now.
# One of the main problems with this design was that it created a
# reference cycle. When the .array attribute was updated after
# creating a FITS_rec from the column (as explained in the docstring) a
# reference cycle was created. This is because the code in BinTableHDU
# (and a few other places) does essentially the following:
#
# data._coldefs = columns # The ColDefs object holding this Column
# for col in columns:
# col.array = data.field(col.name)
#
# This way each columns .array attribute now points to the field in the
# table data. It's actually a pretty confusing interface (since it
# replaces the array originally pointed to by .array), but it's the way
# things have been for a long, long time.
#
# However, this results, in *many* cases, in a reference cycle.
# Because the array returned by data.field(col.name), while sometimes
# an array that owns its own data, is usually like a slice of the
# original data. It has the original FITS_rec as the array .base.
# This results in the following reference cycle (for the n-th column):
#
# data -> data._coldefs -> data._coldefs[n] ->
# data._coldefs[n].array -> data._coldefs[n].array.base -> data
#
# Because ndarray objects do not handled by Python's garbage collector
# the reference cycle cannot be broken. Therefore the FITS_rec's
# refcount never goes to zero, its __del__ is never called, and its
# memory is never freed. This didn't occur in *all* cases, but it did
# occur in many cases.
#
# To get around this, Column.array is no longer a simple attribute
# like it was previously. Now each Column has a ._parent_fits_rec
# attribute which is a weakref to a FITS_rec object. Code that
# previously assigned each col.array to field in a FITS_rec (as in
# the example a few paragraphs above) is still used, however now
# array.setter checks if a reference cycle will be created. And if
# so, instead of saving directly to the Column's __dict__, it creates
# the ._prent_fits_rec weakref, and all lookups of the column's .array
# go through that instead.
#
# This alone does not fully solve the problem. Because
# _parent_fits_rec is a weakref, if the user ever holds a reference to
# the Column, but deletes all references to the underlying FITS_rec,
# the .array attribute would suddenly start returning None instead of
# the array data. This problem is resolved on FITS_rec's end. See the
# note in the FITS_rec._coldefs property for the rest of the story.
# If the Columns's array is not a reference to an existing FITS_rec,
# then it is just stored in self.__dict__; otherwise check the
# _parent_fits_rec reference if it 's still available.
if 'array' in self.__dict__:
return self.__dict__['array']
elif self._parent_fits_rec is not None:
parent = self._parent_fits_rec()
if parent is not None:
return parent[self.name]
else:
return None
@array.setter
def array(self, array):
# The following looks over the bases of the given array to check if it
# has a ._coldefs attribute (i.e. is a FITS_rec) and that that _coldefs
# contains this Column itself, and would create a reference cycle if we
# stored the array directly in self.__dict__.
# In this case it instead sets up the _parent_fits_rec weakref to the
# underlying FITS_rec, so that array.getter can return arrays through
# self._parent_fits_rec().field(self.name), rather than storing a
# hard reference to the field like it used to.
base = array
while True:
if (hasattr(base, '_coldefs') and
isinstance(base._coldefs, ColDefs)):
for col in base._coldefs:
if col is self and self._parent_fits_rec is None:
self._parent_fits_rec = weakref.ref(base)
# Just in case the user already set .array to their own
# array.
if 'array' in self.__dict__:
del self.__dict__['array']
return
if getattr(base, 'base', None) is not None:
base = base.base
else:
break
self.__dict__['array'] = array
@array.deleter
def array(self):
try:
del self.__dict__['array']
except KeyError:
pass
self._parent_fits_rec = None
@ColumnAttribute('TTYPE')
def name(col, name):
if name is None:
# Allow None to indicate deleting the name, or to just indicate an
# unspecified name (when creating a new Column).
return
# Check that the name meets the recommended standard--other column
# names are *allowed*, but will be discouraged
if isinstance(name, str) and not TTYPE_RE.match(name):
warnings.warn(
'It is strongly recommended that column names contain only '
'upper and lower-case ASCII letters, digits, or underscores '
'for maximum compatibility with other software '
'(got {0!r}).'.format(name), VerifyWarning)
# This ensures that the new name can fit into a single FITS card
# without any special extension like CONTINUE cards or the like.
if (not isinstance(name, str)
or len(str(Card('TTYPE', name))) != CARD_LENGTH):
raise AssertionError(
'Column name must be a string able to fit in a single '
'FITS card--typically this means a maximum of 68 '
'characters, though it may be fewer if the string '
'contains special characters like quotes.')
@ColumnAttribute('TCTYP')
def coord_type(col, coord_type):
if coord_type is None:
return
if (not isinstance(coord_type, str)
or len(coord_type) > 8):
raise AssertionError(
'Coordinate/axis type must be a string of atmost 8 '
'characters.')
@ColumnAttribute('TCUNI')
def coord_unit(col, coord_unit):
if (coord_unit is not None
and not isinstance(coord_unit, str)):
raise AssertionError(
'Coordinate/axis unit must be a string.')
@ColumnAttribute('TCRPX')
def coord_ref_point(col, coord_ref_point):
if (coord_ref_point is not None
and not isinstance(coord_ref_point, numbers.Real)):
raise AssertionError(
'Pixel coordinate of the reference point must be '
'real floating type.')
@ColumnAttribute('TCRVL')
def coord_ref_value(col, coord_ref_value):
if (coord_ref_value is not None
and not isinstance(coord_ref_value, numbers.Real)):
raise AssertionError(
'Coordinate value at reference point must be real '
'floating type.')
@ColumnAttribute('TCDLT')
def coord_inc(col, coord_inc):
if (coord_inc is not None
and not isinstance(coord_inc, numbers.Real)):
raise AssertionError(
'Coordinate increment must be real floating type.')
@ColumnAttribute('TRPOS')
def time_ref_pos(col, time_ref_pos):
if (time_ref_pos is not None
and not isinstance(time_ref_pos, str)):
raise AssertionError(
'Time reference position must be a string.')
format = ColumnAttribute('TFORM')
unit = ColumnAttribute('TUNIT')
null = ColumnAttribute('TNULL')
bscale = ColumnAttribute('TSCAL')
bzero = ColumnAttribute('TZERO')
disp = ColumnAttribute('TDISP')
start = ColumnAttribute('TBCOL')
dim = ColumnAttribute('TDIM')
@lazyproperty
def ascii(self):
"""Whether this `Column` represents a column in an ASCII table."""
return isinstance(self.format, _AsciiColumnFormat)
@lazyproperty
def dtype(self):
return self.format.dtype
def copy(self):
"""
Return a copy of this `Column`.
"""
tmp = Column(format='I') # just use a throw-away format
tmp.__dict__ = self.__dict__.copy()
return tmp
@staticmethod
def _convert_format(format, cls):
"""The format argument to this class's initializer may come in many
forms. This uses the given column format class ``cls`` to convert
to a format of that type.
TODO: There should be an abc base class for column format classes
"""
# Short circuit in case we're already a _BaseColumnFormat--there is at
# least one case in which this can happen
if isinstance(format, _BaseColumnFormat):
return format, format.recformat
if format in NUMPY2FITS:
with suppress(VerifyError):
# legit recarray format?
recformat = format
format = cls.from_recformat(format)
try:
# legit FITS format?
format = cls(format)
recformat = format.recformat
except VerifyError:
raise VerifyError('Illegal format `{}`.'.format(format))
return format, recformat
@classmethod
def _verify_keywords(cls, name=None, format=None, unit=None, null=None,
bscale=None, bzero=None, disp=None, start=None,
dim=None, ascii=None, coord_type=None, coord_unit=None,
coord_ref_point=None, coord_ref_value=None,
coord_inc=None, time_ref_pos=None):
"""
Given the keyword arguments used to initialize a Column, specifically
those that typically read from a FITS header (so excluding array),
verify that each keyword has a valid value.
Returns a 2-tuple of dicts. The first maps valid keywords to their
values. The second maps invalid keywords to a 2-tuple of their value,
and a message explaining why they were found invalid.
"""
valid = {}
invalid = {}
format, recformat = cls._determine_formats(format, start, dim, ascii)
valid.update(format=format, recformat=recformat)
# Currently we don't have any validation for name, unit, bscale, or
# bzero so include those by default
# TODO: Add validation for these keywords, obviously
for k, v in [('name', name), ('unit', unit), ('bscale', bscale),
('bzero', bzero)]:
if v is not None and v != '':
valid[k] = v
# Validate null option
# Note: Enough code exists that thinks empty strings are sensible
# inputs for these options that we need to treat '' as None
if null is not None and null != '':
msg = None
if isinstance(format, _AsciiColumnFormat):
null = str(null)
if len(null) > format.width:
msg = (
"ASCII table null option (TNULLn) is longer than "
"the column's character width and will be truncated "
"(got {!r}).".format(null))
else:
tnull_formats = ('B', 'I', 'J', 'K')
if not _is_int(null):
# Make this an exception instead of a warning, since any
# non-int value is meaningless
msg = (
'Column null option (TNULLn) must be an integer for '
'binary table columns (got {!r}). The invalid value '
'will be ignored for the purpose of formatting '
'the data in this column.'.format(null))
elif not (format.format in tnull_formats or
(format.format in ('P', 'Q') and
format.p_format in tnull_formats)):
# TODO: We should also check that TNULLn's integer value
# is in the range allowed by the column's format
msg = (
'Column null option (TNULLn) is invalid for binary '
'table columns of type {!r} (got {!r}). The invalid '
'value will be ignored for the purpose of formatting '
'the data in this column.'.format(format, null))
if msg is None:
valid['null'] = null
else:
invalid['null'] = (null, msg)
# Validate the disp option
# TODO: Add full parsing and validation of TDISPn keywords
if disp is not None and disp != '':
msg = None
if not isinstance(disp, str):
msg = (
'Column disp option (TDISPn) must be a string (got {!r}).'
'The invalid value will be ignored for the purpose of '
'formatting the data in this column.'.format(disp))
elif (isinstance(format, _AsciiColumnFormat) and
disp[0].upper() == 'L'):
# disp is at least one character long and has the 'L' format
# which is not recognized for ASCII tables
msg = (
"Column disp option (TDISPn) may not use the 'L' format "
"with ASCII table columns. The invalid value will be "
"ignored for the purpose of formatting the data in this "
"column.")
if msg is None:
valid['disp'] = disp
else:
invalid['disp'] = (disp, msg)
# Validate the start option
if start is not None and start != '':
msg = None
if not isinstance(format, _AsciiColumnFormat):
# The 'start' option only applies to ASCII columns
msg = (
'Column start option (TBCOLn) is not allowed for binary '
'table columns (got {!r}). The invalid keyword will be '
'ignored for the purpose of formatting the data in this '
'column.'.format(start))
else:
try:
start = int(start)
except (TypeError, ValueError):
pass
if not _is_int(start) or start < 1:
msg = (
'Column start option (TBCOLn) must be a positive integer '
'(got {!r}). The invalid value will be ignored for the '
'purpose of formatting the data in this column.'.format(start))
if msg is None:
valid['start'] = start
else:
invalid['start'] = (start, msg)
# Process TDIMn options
# ASCII table columns can't have a TDIMn keyword associated with it;
# for now we just issue a warning and ignore it.
# TODO: This should be checked by the FITS verification code
if dim is not None and dim != '':
msg = None
dims_tuple = tuple()
# NOTE: If valid, the dim keyword's value in the the valid dict is
# a tuple, not the original string; if invalid just the original
# string is returned
if isinstance(format, _AsciiColumnFormat):
msg = (
'Column dim option (TDIMn) is not allowed for ASCII table '
'columns (got {!r}). The invalid keyword will be ignored '
'for the purpose of formatting this column.'.format(dim))
elif isinstance(dim, str):
dims_tuple = _parse_tdim(dim)
elif isinstance(dim, tuple):
dims_tuple = dim
else:
msg = (
"`dim` argument must be a string containing a valid value "
"for the TDIMn header keyword associated with this column, "
"or a tuple containing the C-order dimensions for the "
"column. The invalid value will be ignored for the purpose "
"of formatting this column.")
if dims_tuple:
if reduce(operator.mul, dims_tuple) > format.repeat:
msg = (
"The repeat count of the column format {!r} for column {!r} "
"is fewer than the number of elements per the TDIM "
"argument {!r}. The invalid TDIMn value will be ignored "
"for the purpose of formatting this column.".format(
name, format, dim))
if msg is None:
valid['dim'] = dims_tuple
else:
invalid['dim'] = (dim, msg)
if coord_type is not None and coord_type != '':
msg = None
if not isinstance(coord_type, str):
msg = (
"Coordinate/axis type option (TCTYPn) must be a string "
"(got {!r}). The invalid keyword will be ignored for the "
"purpose of formatting this column.".format(coord_type))
elif len(coord_type) > 8:
msg = (
"Coordinate/axis type option (TCTYPn) must be a string "
"of atmost 8 characters (got {!r}). The invalid keyword "
"will be ignored for the purpose of formatting this "
"column.".format(coord_type))
if msg is None:
valid['coord_type'] = coord_type
else:
invalid['coord_type'] = (coord_type, msg)
if coord_unit is not None and coord_unit != '':
msg = None
if not isinstance(coord_unit, str):
msg = (
"Coordinate/axis unit option (TCUNIn) must be a string "
"(got {!r}). The invalid keyword will be ignored for the "
"purpose of formatting this column.".format(coord_unit))
if msg is None:
valid['coord_unit'] = coord_unit
else:
invalid['coord_unit'] = (coord_unit, msg)
for k, v in [('coord_ref_point', coord_ref_point),
('coord_ref_value', coord_ref_value),
('coord_inc', coord_inc)]:
if v is not None and v != '':
msg = None
if not isinstance(v, numbers.Real):
msg = (
"Column {} option ({}n) must be a real floating type (got {!r}). "
"The invalid value will be ignored for the purpose of formatting "
"the data in this column.".format(k, ATTRIBUTE_TO_KEYWORD[k], v))
if msg is None:
valid[k] = v
else:
invalid[k] = (v, msg)
if time_ref_pos is not None and time_ref_pos != '':
msg=None
if not isinstance(time_ref_pos, str):
msg = (
"Time coordinate reference position option (TRPOSn) must be "
"a string (got {!r}). The invalid keyword will be ignored for "
"the purpose of formatting this column.".format(time_ref_pos))
if msg is None:
valid['time_ref_pos'] = time_ref_pos
else:
invalid['time_ref_pos'] = (time_ref_pos, msg)
return valid, invalid
@classmethod
def _determine_formats(cls, format, start, dim, ascii):
"""
Given a format string and whether or not the Column is for an
ASCII table (ascii=None means unspecified, but lean toward binary table
where ambiguous) create an appropriate _BaseColumnFormat instance for
the column's format, and determine the appropriate recarray format.
The values of the start and dim keyword arguments are also useful, as
the former is only valid for ASCII tables and the latter only for
BINARY tables.
"""
# If the given format string is unambiguously a Numpy dtype or one of
# the Numpy record format type specifiers supported by Astropy then that
# should take priority--otherwise assume it is a FITS format
if isinstance(format, np.dtype):
format, _, _ = _dtype_to_recformat(format)
# check format
if ascii is None and not isinstance(format, _BaseColumnFormat):
# We're just give a string which could be either a Numpy format
# code, or a format for a binary column array *or* a format for an
# ASCII column array--there may be many ambiguities here. Try our
# best to guess what the user intended.
format, recformat = cls._guess_format(format, start, dim)
elif not ascii and not isinstance(format, _BaseColumnFormat):
format, recformat = cls._convert_format(format, _ColumnFormat)
elif ascii and not isinstance(format, _AsciiColumnFormat):
format, recformat = cls._convert_format(format,
_AsciiColumnFormat)
else:
# The format is already acceptable and unambiguous
recformat = format.recformat
return format, recformat
@classmethod
def _guess_format(cls, format, start, dim):
if start and dim:
# This is impossible; this can't be a valid FITS column
raise ValueError(
'Columns cannot have both a start (TCOLn) and dim '
'(TDIMn) option, since the former is only applies to '
'ASCII tables, and the latter is only valid for binary '
'tables.')
elif start:
# Only ASCII table columns can have a 'start' option
guess_format = _AsciiColumnFormat
elif dim:
# Only binary tables can have a dim option
guess_format = _ColumnFormat
else:
# If the format is *technically* a valid binary column format
# (i.e. it has a valid format code followed by arbitrary
# "optional" codes), but it is also strictly a valid ASCII
# table format, then assume an ASCII table column was being
# requested (the more likely case, after all).
with suppress(VerifyError):
format = _AsciiColumnFormat(format, strict=True)
# A safe guess which reflects the existing behavior of previous
# Astropy versions
guess_format = _ColumnFormat
try:
format, recformat = cls._convert_format(format, guess_format)
except VerifyError:
# For whatever reason our guess was wrong (for example if we got
# just 'F' that's not a valid binary format, but it an ASCII format
# code albeit with the width/precision omitted
guess_format = (_AsciiColumnFormat
if guess_format is _ColumnFormat
else _ColumnFormat)
# If this fails too we're out of options--it is truly an invalid
# format, or at least not supported
format, recformat = cls._convert_format(format, guess_format)
return format, recformat
def _convert_to_valid_data_type(self, array):
# Convert the format to a type we understand
if isinstance(array, Delayed):
return array
elif array is None:
return array
else:
format = self.format
dims = self._dims
if dims:
shape = dims[:-1] if 'A' in format else dims
shape = (len(array),) + shape
array = array.reshape(shape)
if 'P' in format or 'Q' in format:
return array
elif 'A' in format:
if array.dtype.char in 'SU':
if dims:
# The 'last' dimension (first in the order given
# in the TDIMn keyword itself) is the number of
# characters in each string
fsize = dims[-1]
else:
fsize = np.dtype(format.recformat).itemsize
return chararray.array(array, itemsize=fsize, copy=False)
else:
return _convert_array(array, np.dtype(format.recformat))
elif 'L' in format:
# boolean needs to be scaled back to storage values ('T', 'F')
if array.dtype == np.dtype('bool'):
return np.where(array == np.False_, ord('F'), ord('T'))
else:
return np.where(array == 0, ord('F'), ord('T'))
elif 'X' in format:
return _convert_array(array, np.dtype('uint8'))
else:
# Preserve byte order of the original array for now; see #77
numpy_format = array.dtype.byteorder + format.recformat
# Handle arrays passed in as unsigned ints as pseudo-unsigned
# int arrays; blatantly tacked in here for now--we need columns
# to have explicit knowledge of whether they treated as
# pseudo-unsigned
bzeros = {2: np.uint16(2**15), 4: np.uint32(2**31),
8: np.uint64(2**63)}
if (array.dtype.kind == 'u' and
array.dtype.itemsize in bzeros and
self.bscale in (1, None, '') and
self.bzero == bzeros[array.dtype.itemsize]):
# Basically the array is uint, has scale == 1.0, and the
# bzero is the appropriate value for a pseudo-unsigned
# integer of the input dtype, then go ahead and assume that
# uint is assumed
numpy_format = numpy_format.replace('i', 'u')
self._pseudo_unsigned_ints = True
# The .base here means we're dropping the shape information,
# which is only used to format recarray fields, and is not
# useful for converting input arrays to the correct data type
dtype = np.dtype(numpy_format).base
return _convert_array(array, dtype)
class ColDefs(NotifierMixin):
"""
Column definitions class.
It has attributes corresponding to the `Column` attributes
(e.g. `ColDefs` has the attribute ``names`` while `Column`
has ``name``). Each attribute in `ColDefs` is a list of
corresponding attribute values from all `Column` objects.
"""
_padding_byte = '\x00'
_col_format_cls = _ColumnFormat
def __new__(cls, input, ascii=False):
klass = cls
if (hasattr(input, '_columns_type') and
issubclass(input._columns_type, ColDefs)):
klass = input._columns_type
elif (hasattr(input, '_col_format_cls') and
issubclass(input._col_format_cls, _AsciiColumnFormat)):
klass = _AsciiColDefs
if ascii: # force ASCII if this has been explicitly requested
klass = _AsciiColDefs
return object.__new__(klass)
def __getnewargs__(self):
return (self._arrays,)
def __init__(self, input, ascii=False):
"""
Parameters
----------
input : sequence of `Column`, `ColDefs`, other
An existing table HDU, an existing `ColDefs`, or any multi-field
Numpy array or `numpy.recarray`.
ascii : bool
Use True to ensure that ASCII table columns are used.
"""
from .hdu.table import _TableBaseHDU
from .fitsrec import FITS_rec
if isinstance(input, ColDefs):
self._init_from_coldefs(input)
elif (isinstance(input, FITS_rec) and hasattr(input, '_coldefs') and
input._coldefs):
# If given a FITS_rec object we can directly copy its columns, but
# only if its columns have already been defined, otherwise this
# will loop back in on itself and blow up
self._init_from_coldefs(input._coldefs)
elif isinstance(input, np.ndarray) and input.dtype.fields is not None:
# Construct columns from the fields of a record array
self._init_from_array(input)
elif isiterable(input):
# if the input is a list of Columns
self._init_from_sequence(input)
elif isinstance(input, _TableBaseHDU):
# Construct columns from fields in an HDU header
self._init_from_table(input)
else:
raise TypeError('Input to ColDefs must be a table HDU, a list '
'of Columns, or a record/field array.')
# Listen for changes on all columns
for col in self.columns:
col._add_listener(self)
def _init_from_coldefs(self, coldefs):
"""Initialize from an existing ColDefs object (just copy the
columns and convert their formats if necessary).
"""
self.columns = [self._copy_column(col) for col in coldefs]
def _init_from_sequence(self, columns):
for idx, col in enumerate(columns):
if not isinstance(col, Column):
raise TypeError('Element {} in the ColDefs input is not a '
'Column.'.format(idx))
self._init_from_coldefs(columns)
def _init_from_array(self, array):
self.columns = []
for idx in range(len(array.dtype)):
cname = array.dtype.names[idx]
ftype = array.dtype.fields[cname][0]
format = self._col_format_cls.from_recformat(ftype)
# Determine the appropriate dimensions for items in the column
# (typically just 1D)
dim = array.dtype[idx].shape[::-1]
if dim and (len(dim) > 1 or 'A' in format):
if 'A' in format:
# n x m string arrays must include the max string
# length in their dimensions (e.g. l x n x m)
dim = (array.dtype[idx].base.itemsize,) + dim
dim = repr(dim).replace(' ', '')
else:
dim = None
# Check for unsigned ints.
bzero = None
if ftype.base.kind == 'u':
if 'I' in format:
bzero = np.uint16(2**15)
elif 'J' in format:
bzero = np.uint32(2**31)
elif 'K' in format:
bzero = np.uint64(2**63)
c = Column(name=cname, format=format,
array=array.view(np.ndarray)[cname], bzero=bzero,
dim=dim)
self.columns.append(c)
def _init_from_table(self, table):
hdr = table._header
nfields = hdr['TFIELDS']
# go through header keywords to pick out column definition keywords
# definition dictionaries for each field
col_keywords = [{} for i in range(nfields)]
for keyword, value in hdr.items():
key = TDEF_RE.match(keyword)
try:
keyword = key.group('label')
except Exception:
continue # skip if there is no match
if keyword in KEYWORD_NAMES:
col = int(key.group('num'))
if 0 < col <= nfields:
attr = KEYWORD_TO_ATTRIBUTE[keyword]
if attr == 'format':
# Go ahead and convert the format value to the
# appropriate ColumnFormat container now
value = self._col_format_cls(value)
col_keywords[col - 1][attr] = value
# Verify the column keywords and display any warnings if necessary;
# we only want to pass on the valid keywords
for idx, kwargs in enumerate(col_keywords):
valid_kwargs, invalid_kwargs = Column._verify_keywords(**kwargs)
for val in invalid_kwargs.values():
warnings.warn(
'Invalid keyword for column {}: {}'.format(idx + 1, val[1]),
VerifyWarning)
# Special cases for recformat and dim
# TODO: Try to eliminate the need for these special cases
del valid_kwargs['recformat']
if 'dim' in valid_kwargs:
valid_kwargs['dim'] = kwargs['dim']
col_keywords[idx] = valid_kwargs
# data reading will be delayed
for col in range(nfields):
col_keywords[col]['array'] = Delayed(table, col)
# now build the columns
self.columns = [Column(**attrs) for attrs in col_keywords]
# Add the table HDU is a listener to changes to the columns
# (either changes to individual columns, or changes to the set of
# columns (add/remove/etc.))
self._add_listener(table)
def __copy__(self):
return self.__class__(self)
def __deepcopy__(self, memo):
return self.__class__([copy.deepcopy(c, memo) for c in self.columns])
def _copy_column(self, column):
"""Utility function used currently only by _init_from_coldefs
to help convert columns from binary format to ASCII format or vice
versa if necessary (otherwise performs a straight copy).
"""
if isinstance(column.format, self._col_format_cls):
# This column has a FITS format compatible with this column
# definitions class (that is ascii or binary)
return column.copy()
new_column = column.copy()
# Try to use the Numpy recformat as the equivalency between the
# two formats; if that conversion can't be made then these
# columns can't be transferred
# TODO: Catch exceptions here and raise an explicit error about
# column format conversion
new_column.format = self._col_format_cls.from_column_format(
column.format)
# Handle a few special cases of column format options that are not
# compatible between ASCII an binary tables
# TODO: This is sort of hacked in right now; we really need
# separate classes for ASCII and Binary table Columns, and they
# should handle formatting issues like these
if not isinstance(new_column.format, _AsciiColumnFormat):
# the column is a binary table column...
new_column.start = None
if new_column.null is not None:
# We can't just "guess" a value to represent null
# values in the new column, so just disable this for
# now; users may modify it later
new_column.null = None
else:
# the column is an ASCII table column...
if new_column.null is not None:
new_column.null = DEFAULT_ASCII_TNULL
if (new_column.disp is not None and
new_column.disp.upper().startswith('L')):
# ASCII columns may not use the logical data display format;
# for now just drop the TDISPn option for this column as we
# don't have a systematic conversion of boolean data to ASCII
# tables yet
new_column.disp = None
return new_column
def __getattr__(self, name):
"""
Automatically returns the values for the given keyword attribute for
all `Column`s in this list.
Implements for example self.units, self.formats, etc.
"""
cname = name[:-1]
if cname in KEYWORD_ATTRIBUTES and name[-1] == 's':
attr = []
for col in self.columns:
val = getattr(col, cname)
attr.append(val if val is not None else '')
return attr
raise AttributeError(name)
@lazyproperty
def dtype(self):
# Note: This previously returned a dtype that just used the raw field
# widths based on the format's repeat count, and did not incorporate
# field *shapes* as provided by TDIMn keywords.
# Now this incorporates TDIMn from the start, which makes *this* method
# a little more complicated, but simplifies code elsewhere (for example
# fields will have the correct shapes even in the raw recarray).
formats = []
offsets = [0]
for format_, dim in zip(self.formats, self._dims):
dt = format_.dtype
if len(offsets) < len(self.formats):
# Note: the size of the *original* format_ may be greater than
# one would expect from the number of elements determined by
# dim. The FITS format allows this--the rest of the field is
# filled with undefined values.
offsets.append(offsets[-1] + dt.itemsize)
if dim:
if format_.format == 'A':
dt = np.dtype((dt.char + str(dim[-1]), dim[:-1]))
else:
dt = np.dtype((dt.base, dim))
formats.append(dt)
return np.dtype({'names': self.names,
'formats': formats,
'offsets': offsets})
@lazyproperty
def names(self):
return [col.name for col in self.columns]
@lazyproperty
def formats(self):
return [col.format for col in self.columns]
@lazyproperty
def _arrays(self):
return [col.array for col in self.columns]
@lazyproperty
def _recformats(self):
return [fmt.recformat for fmt in self.formats]
@lazyproperty
def _dims(self):
"""Returns the values of the TDIMn keywords parsed into tuples."""
return [col._dims for col in self.columns]
def __getitem__(self, key):
if isinstance(key, str):
key = _get_index(self.names, key)
x = self.columns[key]
if _is_int(key):
return x
else:
return ColDefs(x)
def __len__(self):
return len(self.columns)
def __repr__(self):
rep = 'ColDefs('
if hasattr(self, 'columns') and self.columns:
# The hasattr check is mostly just useful in debugging sessions
# where self.columns may not be defined yet
rep += '\n '
rep += '\n '.join([repr(c) for c in self.columns])
rep += '\n'
rep += ')'
return rep
def __add__(self, other, option='left'):
if isinstance(other, Column):
b = [other]
elif isinstance(other, ColDefs):
b = list(other.columns)
else:
raise TypeError('Wrong type of input.')
if option == 'left':
tmp = list(self.columns) + b
else:
tmp = b + list(self.columns)
return ColDefs(tmp)
def __radd__(self, other):
return self.__add__(other, 'right')
def __sub__(self, other):
if not isinstance(other, (list, tuple)):
other = [other]
_other = [_get_index(self.names, key) for key in other]
indx = list(range(len(self)))
for x in _other:
indx.remove(x)
tmp = [self[i] for i in indx]
return ColDefs(tmp)
def _update_column_attribute_changed(self, column, attr, old_value,
new_value):
"""
Handle column attribute changed notifications from columns that are
members of this `ColDefs`.
`ColDefs` itself does not currently do anything with this, and just
bubbles the notification up to any listening table HDUs that may need
to update their headers, etc. However, this also informs the table of
the numerical index of the column that changed.
"""
idx = 0
for idx, col in enumerate(self.columns):
if col is column:
break
if attr == 'name':
del self.names
elif attr == 'format':
del self.formats
self._notify('column_attribute_changed', column, idx, attr, old_value,
new_value)
def add_col(self, column):
"""
Append one `Column` to the column definition.
"""
if not isinstance(column, Column):
raise AssertionError
self._arrays.append(column.array)
# Obliterate caches of certain things
del self.dtype
del self._recformats
del self._dims
del self.names
del self.formats
self.columns.append(column)
# Listen for changes on the new column
column._add_listener(self)
# If this ColDefs is being tracked by a Table, inform the
# table that its data is now invalid.
self._notify('column_added', self, column)
return self
def del_col(self, col_name):
"""
Delete (the definition of) one `Column`.
col_name : str or int
The column's name or index
"""
indx = _get_index(self.names, col_name)
col = self.columns[indx]
del self._arrays[indx]
# Obliterate caches of certain things
del self.dtype
del self._recformats
del self._dims
del self.names
del self.formats
del self.columns[indx]
col._remove_listener(self)
# If this ColDefs is being tracked by a table HDU, inform the HDU (or
# any other listeners) that the column has been removed
# Just send a reference to self, and the index of the column that was
# removed
self._notify('column_removed', self, indx)
return self
def change_attrib(self, col_name, attrib, new_value):
"""
Change an attribute (in the ``KEYWORD_ATTRIBUTES`` list) of a `Column`.
Parameters
----------
col_name : str or int
The column name or index to change
attrib : str
The attribute name
new_value : object
The new value for the attribute
"""
setattr(self[col_name], attrib, new_value)
def change_name(self, col_name, new_name):
"""
Change a `Column`'s name.
Parameters
----------
col_name : str
The current name of the column
new_name : str
The new name of the column
"""
if new_name != col_name and new_name in self.names:
raise ValueError('New name {} already exists.'.format(new_name))
else:
self.change_attrib(col_name, 'name', new_name)
def change_unit(self, col_name, new_unit):
"""
Change a `Column`'s unit.
Parameters
----------
col_name : str or int
The column name or index
new_unit : str
The new unit for the column
"""
self.change_attrib(col_name, 'unit', new_unit)
def info(self, attrib='all', output=None):
"""
Get attribute(s) information of the column definition.
Parameters
----------
attrib : str
Can be one or more of the attributes listed in
``astropy.io.fits.column.KEYWORD_ATTRIBUTES``. The default is
``"all"`` which will print out all attributes. It forgives plurals
and blanks. If there are two or more attribute names, they must be
separated by comma(s).
output : file, optional
File-like object to output to. Outputs to stdout by default.
If `False`, returns the attributes as a `dict` instead.
Notes
-----
This function doesn't return anything by default; it just prints to
stdout.
"""
if output is None:
output = sys.stdout
if attrib.strip().lower() in ['all', '']:
lst = KEYWORD_ATTRIBUTES
else:
lst = attrib.split(',')
for idx in range(len(lst)):
lst[idx] = lst[idx].strip().lower()
if lst[idx][-1] == 's':
lst[idx] = list[idx][:-1]
ret = {}
for attr in lst:
if output:
if attr not in KEYWORD_ATTRIBUTES:
output.write("'{}' is not an attribute of the column "
"definitions.\n".format(attr))
continue
output.write("{}:\n".format(attr))
output.write(' {}\n'.format(getattr(self, attr + 's')))
else:
ret[attr] = getattr(self, attr + 's')
if not output:
return ret
class _AsciiColDefs(ColDefs):
"""ColDefs implementation for ASCII tables."""
_padding_byte = ' '
_col_format_cls = _AsciiColumnFormat
def __init__(self, input, ascii=True):
super().__init__(input)
# if the format of an ASCII column has no width, add one
if not isinstance(input, _AsciiColDefs):
self._update_field_metrics()
else:
for idx, s in enumerate(input.starts):
self.columns[idx].start = s
self._spans = input.spans
self._width = input._width
@lazyproperty
def dtype(self):
dtype = {}
for j in range(len(self)):
data_type = 'S' + str(self.spans[j])
dtype[self.names[j]] = (data_type, self.starts[j] - 1)
return np.dtype(dtype)
@property
def spans(self):
"""A list of the widths of each field in the table."""
return self._spans
@lazyproperty
def _recformats(self):
if len(self) == 1:
widths = []
else:
widths = [y - x for x, y in pairwise(self.starts)]
# Widths is the width of each field *including* any space between
# fields; this is so that we can map the fields to string records in a
# Numpy recarray
widths.append(self._width - self.starts[-1] + 1)
return ['a' + str(w) for w in widths]
def add_col(self, column):
super().add_col(column)
self._update_field_metrics()
def del_col(self, col_name):
super().del_col(col_name)
self._update_field_metrics()
def _update_field_metrics(self):
"""
Updates the list of the start columns, the list of the widths of each
field, and the total width of each record in the table.
"""
spans = [0] * len(self.columns)
end_col = 0 # Refers to the ASCII text column, not the table col
for idx, col in enumerate(self.columns):
width = col.format.width
# Update the start columns and column span widths taking into
# account the case that the starting column of a field may not
# be the column immediately after the previous field
if not col.start:
col.start = end_col + 1
end_col = col.start + width - 1
spans[idx] = width
self._spans = spans
self._width = end_col
# Utilities
class _VLF(np.ndarray):
"""Variable length field object."""
def __new__(cls, input, dtype='a'):
"""
Parameters
----------
input
a sequence of variable-sized elements.
"""
if dtype == 'a':
try:
# this handles ['abc'] and [['a','b','c']]
# equally, beautiful!
input = [chararray.array(x, itemsize=1) for x in input]
except Exception:
raise ValueError(
'Inconsistent input data array: {0}'.format(input))
a = np.array(input, dtype=object)
self = np.ndarray.__new__(cls, shape=(len(input),), buffer=a,
dtype=object)
self.max = 0
self.element_dtype = dtype
return self
def __array_finalize__(self, obj):
if obj is None:
return
self.max = obj.max
self.element_dtype = obj.element_dtype
def __setitem__(self, key, value):
"""
To make sure the new item has consistent data type to avoid
misalignment.
"""
if isinstance(value, np.ndarray) and value.dtype == self.dtype:
pass
elif isinstance(value, chararray.chararray) and value.itemsize == 1:
pass
elif self.element_dtype == 'a':
value = chararray.array(value, itemsize=1)
else:
value = np.array(value, dtype=self.element_dtype)
np.ndarray.__setitem__(self, key, value)
self.max = max(self.max, len(value))
def _get_index(names, key):
"""
Get the index of the ``key`` in the ``names`` list.
The ``key`` can be an integer or string. If integer, it is the index
in the list. If string,
a. Field (column) names are case sensitive: you can have two
different columns called 'abc' and 'ABC' respectively.
b. When you *refer* to a field (presumably with the field
method), it will try to match the exact name first, so in
the example in (a), field('abc') will get the first field,
and field('ABC') will get the second field.
If there is no exact name matched, it will try to match the
name with case insensitivity. So, in the last example,
field('Abc') will cause an exception since there is no unique
mapping. If there is a field named "XYZ" and no other field
name is a case variant of "XYZ", then field('xyz'),
field('Xyz'), etc. will get this field.
"""
if _is_int(key):
indx = int(key)
elif isinstance(key, str):
# try to find exact match first
try:
indx = names.index(key.rstrip())
except ValueError:
# try to match case-insentively,
_key = key.lower().rstrip()
names = [n.lower().rstrip() for n in names]
count = names.count(_key) # occurrence of _key in names
if count == 1:
indx = names.index(_key)
elif count == 0:
raise KeyError("Key '{}' does not exist.".format(key))
else: # multiple match
raise KeyError("Ambiguous key name '{}'.".format(key))
else:
raise KeyError("Illegal key '{!r}'.".format(key))
return indx
def _unwrapx(input, output, repeat):
"""
Unwrap the X format column into a Boolean array.
Parameters
----------
input
input ``Uint8`` array of shape (`s`, `nbytes`)
output
output Boolean array of shape (`s`, `repeat`)
repeat
number of bits
"""
pow2 = np.array([128, 64, 32, 16, 8, 4, 2, 1], dtype='uint8')
nbytes = ((repeat - 1) // 8) + 1
for i in range(nbytes):
_min = i * 8
_max = min((i + 1) * 8, repeat)
for j in range(_min, _max):
output[..., j] = np.bitwise_and(input[..., i], pow2[j - i * 8])
def _wrapx(input, output, repeat):
"""
Wrap the X format column Boolean array into an ``UInt8`` array.
Parameters
----------
input
input Boolean array of shape (`s`, `repeat`)
output
output ``Uint8`` array of shape (`s`, `nbytes`)
repeat
number of bits
"""
output[...] = 0 # reset the output
nbytes = ((repeat - 1) // 8) + 1
unused = nbytes * 8 - repeat
for i in range(nbytes):
_min = i * 8
_max = min((i + 1) * 8, repeat)
for j in range(_min, _max):
if j != _min:
np.left_shift(output[..., i], 1, output[..., i])
np.add(output[..., i], input[..., j], output[..., i])
# shift the unused bits
np.left_shift(output[..., i], unused, output[..., i])
def _makep(array, descr_output, format, nrows=None):
"""
Construct the P (or Q) format column array, both the data descriptors and
the data. It returns the output "data" array of data type `dtype`.
The descriptor location will have a zero offset for all columns
after this call. The final offset will be calculated when the file
is written.
Parameters
----------
array
input object array
descr_output
output "descriptor" array of data type int32 (for P format arrays) or
int64 (for Q format arrays)--must be nrows long in its first dimension
format
the _FormatP object representing the format of the variable array
nrows : int, optional
number of rows to create in the column; defaults to the number of rows
in the input array
"""
# TODO: A great deal of this is redundant with FITS_rec._convert_p; see if
# we can merge the two somehow.
_offset = 0
if not nrows:
nrows = len(array)
data_output = _VLF([None] * nrows, dtype=format.dtype)
if format.dtype == 'a':
_nbytes = 1
else:
_nbytes = np.array([], dtype=format.dtype).itemsize
for idx in range(nrows):
if idx < len(array):
rowval = array[idx]
else:
if format.dtype == 'a':
rowval = ' ' * data_output.max
else:
rowval = [0] * data_output.max
if format.dtype == 'a':
data_output[idx] = chararray.array(encode_ascii(rowval),
itemsize=1)
else:
data_output[idx] = np.array(rowval, dtype=format.dtype)
descr_output[idx, 0] = len(data_output[idx])
descr_output[idx, 1] = _offset
_offset += len(data_output[idx]) * _nbytes
return data_output
def _parse_tformat(tform):
"""Parse ``TFORMn`` keyword for a binary table into a
``(repeat, format, option)`` tuple.
"""
try:
(repeat, format, option) = TFORMAT_RE.match(tform.strip()).groups()
except Exception:
# TODO: Maybe catch this error use a default type (bytes, maybe?) for
# unrecognized column types. As long as we can determine the correct
# byte width somehow..
raise VerifyError('Format {!r} is not recognized.'.format(tform))
if repeat == '':
repeat = 1
else:
repeat = int(repeat)
return (repeat, format.upper(), option)
def _parse_ascii_tformat(tform, strict=False):
"""
Parse the ``TFORMn`` keywords for ASCII tables into a ``(format, width,
precision)`` tuple (the latter is always zero unless format is one of 'E',
'F', or 'D').
"""
match = TFORMAT_ASCII_RE.match(tform.strip())
if not match:
raise VerifyError('Format {!r} is not recognized.'.format(tform))
# Be flexible on case
format = match.group('format')
if format is None:
# Floating point format
format = match.group('formatf').upper()
width = match.group('widthf')
precision = match.group('precision')
if width is None or precision is None:
if strict:
raise VerifyError('Format {!r} is not unambiguously an ASCII '
'table format.')
else:
width = 0 if width is None else width
precision = 1 if precision is None else precision
else:
format = format.upper()
width = match.group('width')
if width is None:
if strict:
raise VerifyError('Format {!r} is not unambiguously an ASCII '
'table format.')
else:
# Just use a default width of 0 if unspecified
width = 0
precision = 0
def convert_int(val):
msg = ('Format {!r} is not valid--field width and decimal precision '
'must be integers.')
try:
val = int(val)
except (ValueError, TypeError):
raise VerifyError(msg.format(tform))
return val
if width and precision:
# This should only be the case for floating-point formats
width, precision = convert_int(width), convert_int(precision)
elif width:
# Just for integer/string formats; ignore precision
width = convert_int(width)
else:
# For any format, if width was unspecified use the set defaults
width, precision = ASCII_DEFAULT_WIDTHS[format]
if width <= 0:
raise VerifyError("Format {!r} not valid--field width must be a "
"positive integeter.".format(tform))
if precision >= width:
raise VerifyError("Format {!r} not valid--the number of decimal digits "
"must be less than the format's total "
"width {}.".format(tform, width))
return format, width, precision
def _parse_tdim(tdim):
"""Parse the ``TDIM`` value into a tuple (may return an empty tuple if
the value ``TDIM`` value is empty or invalid).
"""
m = tdim and TDIM_RE.match(tdim)
if m:
dims = m.group('dims')
return tuple(int(d.strip()) for d in dims.split(','))[::-1]
# Ignore any dim values that don't specify a multidimensional column
return tuple()
def _scalar_to_format(value):
"""
Given a scalar value or string, returns the minimum FITS column format
that can represent that value. 'minimum' is defined by the order given in
FORMATORDER.
"""
# First, if value is a string, try to convert to the appropriate scalar
# value
for type_ in (int, float, complex):
try:
value = type_(value)
break
except ValueError:
continue
numpy_dtype_str = np.min_scalar_type(value).str
numpy_dtype_str = numpy_dtype_str[1:] # Strip endianness
try:
fits_format = NUMPY2FITS[numpy_dtype_str]
return FITSUPCONVERTERS.get(fits_format, fits_format)
except KeyError:
return "A" + str(len(value))
def _cmp_recformats(f1, f2):
"""
Compares two numpy recformats using the ordering given by FORMATORDER.
"""
if f1[0] == 'a' and f2[0] == 'a':
return cmp(int(f1[1:]), int(f2[1:]))
else:
f1, f2 = NUMPY2FITS[f1], NUMPY2FITS[f2]
return cmp(FORMATORDER.index(f1), FORMATORDER.index(f2))
def _convert_fits2record(format):
"""
Convert FITS format spec to record format spec.
"""
repeat, dtype, option = _parse_tformat(format)
if dtype in FITS2NUMPY:
if dtype == 'A':
output_format = FITS2NUMPY[dtype] + str(repeat)
# to accommodate both the ASCII table and binary table column
# format spec, i.e. A7 in ASCII table is the same as 7A in
# binary table, so both will produce 'a7'.
# Technically the FITS standard does not allow this but it's a very
# common mistake
if format.lstrip()[0] == 'A' and option != '':
# make sure option is integer
output_format = FITS2NUMPY[dtype] + str(int(option))
else:
repeat_str = ''
if repeat != 1:
repeat_str = str(repeat)
output_format = repeat_str + FITS2NUMPY[dtype]
elif dtype == 'X':
output_format = _FormatX(repeat)
elif dtype == 'P':
output_format = _FormatP.from_tform(format)
elif dtype == 'Q':
output_format = _FormatQ.from_tform(format)
elif dtype == 'F':
output_format = 'f8'
else:
raise ValueError('Illegal format `{}`.'.format(format))
return output_format
def _convert_record2fits(format):
"""
Convert record format spec to FITS format spec.
"""
recformat, kind, dtype = _dtype_to_recformat(format)
shape = dtype.shape
itemsize = dtype.base.itemsize
if dtype.char == 'U':
# Unicode dtype--itemsize is 4 times actual ASCII character length,
# which what matters for FITS column formats
# Use dtype.base--dtype may be a multi-dimensional dtype
itemsize = itemsize // 4
option = str(itemsize)
ndims = len(shape)
repeat = 1
if ndims > 0:
nel = np.array(shape, dtype='i8').prod()
if nel > 1:
repeat = nel
if kind == 'a':
# This is a kludge that will place string arrays into a
# single field, so at least we won't lose data. Need to
# use a TDIM keyword to fix this, declaring as (slength,
# dim1, dim2, ...) as mwrfits does
ntot = int(repeat) * int(option)
output_format = str(ntot) + 'A'
elif recformat in NUMPY2FITS: # record format
if repeat != 1:
repeat = str(repeat)
else:
repeat = ''
output_format = repeat + NUMPY2FITS[recformat]
else:
raise ValueError('Illegal format `{}`.'.format(format))
return output_format
def _dtype_to_recformat(dtype):
"""
Utility function for converting a dtype object or string that instantiates
a dtype (e.g. 'float32') into one of the two character Numpy format codes
that have been traditionally used by Astropy.
In particular, use of 'a' to refer to character data is long since
deprecated in Numpy, but Astropy remains heavily invested in its use
(something to try to get away from sooner rather than later).
"""
if not isinstance(dtype, np.dtype):
dtype = np.dtype(dtype)
kind = dtype.base.kind
if kind in ('U', 'S'):
recformat = kind = 'a'
else:
itemsize = dtype.base.itemsize
recformat = kind + str(itemsize)
return recformat, kind, dtype
def _convert_format(format, reverse=False):
"""
Convert FITS format spec to record format spec. Do the opposite if
reverse=True.
"""
if reverse:
return _convert_record2fits(format)
else:
return _convert_fits2record(format)
def _convert_ascii_format(format, reverse=False):
"""Convert ASCII table format spec to record format spec."""
if reverse:
recformat, kind, dtype = _dtype_to_recformat(format)
itemsize = dtype.itemsize
if kind == 'a':
return 'A' + str(itemsize)
elif NUMPY2FITS.get(recformat) == 'L':
# Special case for logical/boolean types--for ASCII tables we
# represent these as single character columns containing 'T' or 'F'
# (a la the storage format for Logical columns in binary tables)
return 'A1'
elif kind == 'i':
# Use for the width the maximum required to represent integers
# of that byte size plus 1 for signs, but use a minimum of the
# default width (to keep with existing behavior)
width = 1 + len(str(2 ** (itemsize * 8)))
width = max(width, ASCII_DEFAULT_WIDTHS['I'][0])
return 'I' + str(width)
elif kind == 'f':
# This is tricky, but go ahead and use D if float-64, and E
# if float-32 with their default widths
if itemsize >= 8:
format = 'D'
else:
format = 'E'
width = '.'.join(str(w) for w in ASCII_DEFAULT_WIDTHS[format])
return format + width
# TODO: There may be reasonable ways to represent other Numpy types so
# let's see what other possibilities there are besides just 'a', 'i',
# and 'f'. If it doesn't have a reasonable ASCII representation then
# raise an exception
else:
format, width, precision = _parse_ascii_tformat(format)
# This gives a sensible "default" dtype for a given ASCII
# format code
recformat = ASCII2NUMPY[format]
# The following logic is taken from CFITSIO:
# For integers, if the width <= 4 we can safely use 16-bit ints for all
# values [for the non-standard J format code just always force 64-bit]
if format == 'I' and width <= 4:
recformat = 'i2'
elif format == 'A':
recformat += str(width)
return recformat
def _parse_tdisp_format(tdisp):
"""
Parse the ``TDISPn`` keywords for ASCII and binary tables into a
``(format, width, precision, exponential)`` tuple (the TDISP values
for ASCII and binary are identical except for 'Lw',
which is only present in BINTABLE extensions
Parameters
----------
tdisp: str
TDISPn FITS Header keyword. Used to specify display formatting.
Returns
-------
formatc: str
The format characters from TDISPn
width: str
The width int value from TDISPn
precision: str
The precision int value from TDISPn
exponential: str
The exponential int value from TDISPn
"""
# Use appropriate regex for format type
tdisp = tdisp.strip()
fmt_key = tdisp[0] if tdisp[0] !='E' or tdisp[1] not in 'NS' else tdisp[:2]
try:
tdisp_re = TDISP_RE_DICT[fmt_key]
except KeyError:
raise VerifyError('Format {} is not recognized.'.format(tdisp))
match = tdisp_re.match(tdisp.strip())
if not match or match.group('formatc') is None:
raise VerifyError('Format {} is not recognized.'.format(tdisp))
formatc = match.group('formatc')
width = match.group('width')
precision = None
exponential = None
# Some formats have precision and exponential
if tdisp[0] in ('I', 'B', 'O', 'Z', 'F', 'E', 'G', 'D'):
precision = match.group('precision')
if precision is None:
precision = 1
if tdisp[0] in ('E', 'D', 'G') and tdisp[1] not in ('N', 'S'):
exponential = match.group('exponential')
if exponential is None:
exponential = 1
# Once parsed, check format dict to do conversion to a formatting string
return formatc, width, precision, exponential
def _fortran_to_python_format(tdisp):
"""
Turn the TDISPn fortran format pieces into a final Python format string.
See the format_type definitions above the TDISP_FMT_DICT. If codes is
changed to take advantage of the exponential specification, will need to
add it as another input parameter.
Parameters
----------
tdisp: str
TDISPn FITS Header keyword. Used to specify display formatting.
Returns
-------
format_string: str
The TDISPn keyword string translated into a Python format string.
"""
format_type, width, precision, exponential = _parse_tdisp_format(tdisp)
try:
fmt = TDISP_FMT_DICT[format_type]
return fmt.format(width=width, precision=precision)
except KeyError:
raise VerifyError('Format {} is not recognized.'.format(format_type))
def python_to_tdisp(format_string, logical_dtype = False):
"""
Turn the Python format string to a TDISP FITS compliant format string. Not
all formats convert. these will cause a Warning and return None.
Parameters
----------
format_string: str
TDISPn FITS Header keyword. Used to specify display formatting.
logical_dtype: bool
True is this format type should be a logical type, 'L'. Needs special
handeling.
Returns
-------
tdsip_string: str
The TDISPn keyword string translated into a Python format string.
"""
fmt_to_tdisp = {'a': 'A', 's': 'A', 'd': 'I', 'b': 'B', 'o': 'O', 'x': 'Z',
'X': 'Z', 'f': 'F', 'F': 'F', 'g': 'G', 'G': 'G', 'e': 'E',
'E': 'E'}
if format_string in [None, "", "{}"]:
return None
# Strip out extra format characters that aren't a type or a width/precision
if format_string[0] == '{' and format_string != "{}":
fmt_str = format_string.lstrip("{:").rstrip('}')
elif format_string[0] == '%':
fmt_str = format_string.lstrip("%")
else:
fmt_str = format_string
precision, sep = '', ''
# Character format, only translate right aligned, and don't take zero fills
if fmt_str[-1].isdigit() and fmt_str[0] == '>' and fmt_str[1] != '0':
ftype = fmt_to_tdisp['a']
width = fmt_str[1:]
elif fmt_str[-1] == 's' and fmt_str != 's':
ftype = fmt_to_tdisp['a']
width = fmt_str[:-1].lstrip('0')
# Number formats, don't take zero fills
elif fmt_str[-1].isalpha() and len(fmt_str) > 1 and fmt_str[0] != '0':
ftype = fmt_to_tdisp[fmt_str[-1]]
fmt_str = fmt_str[:-1]
# If format has a "." split out the width and precision
if '.' in fmt_str:
width, precision = fmt_str.split('.')
sep = '.'
if width == "":
ascii_key = ftype if ftype != 'G' else 'F'
width = str(int(precision) + (ASCII_DEFAULT_WIDTHS[ascii_key][0] -
ASCII_DEFAULT_WIDTHS[ascii_key][1]))
# Otherwise we just have a width
else:
width = fmt_str
else:
warnings.warn('Format {} cannot be mapped to the accepted '
'TDISPn keyword values. Format will not be '
'moved into TDISPn keyword.'.format(format_string),
AstropyUserWarning)
return None
# Catch logical data type, set the format type back to L in this case
if logical_dtype:
ftype = 'L'
return ftype + width + sep + precision
|
cd888a3a4f20cf0c5ce67c859f441c68d412f89a1c39fead86f38a3f44cc2ed1 | # Licensed under a 3-clause BSD style license - see PYFITS.rst
import collections
import copy
import itertools
import re
import warnings
from .card import Card, _pad, KEYWORD_LENGTH, UNDEFINED
from .file import _File
from .util import encode_ascii, decode_ascii, fileobj_closed, fileobj_is_binary
from ._utils import parse_header
from astropy.utils import isiterable
from astropy.utils.exceptions import AstropyUserWarning
from astropy.utils.decorators import deprecated_renamed_argument
BLOCK_SIZE = 2880 # the FITS block size
# This regular expression can match a *valid* END card which just consists of
# the string 'END' followed by all spaces, or an *invalid* end card which
# consists of END, followed by any character that is *not* a valid character
# for a valid FITS keyword (that is, this is not a keyword like 'ENDER' which
# starts with 'END' but is not 'END'), followed by any arbitrary bytes. An
# invalid end card may also consist of just 'END' with no trailing bytes.
HEADER_END_RE = re.compile(encode_ascii(
r'(?:(?P<valid>END {77}) *)|(?P<invalid>END$|END {0,76}[^A-Z0-9_-])'))
# According to the FITS standard the only characters that may appear in a
# header record are the restricted ASCII chars from 0x20 through 0x7E.
VALID_HEADER_CHARS = set(map(chr, range(0x20, 0x7F)))
END_CARD = 'END' + ' ' * 77
__doctest_skip__ = ['Header', 'Header.*']
class Header:
"""
FITS header class. This class exposes both a dict-like interface and a
list-like interface to FITS headers.
The header may be indexed by keyword and, like a dict, the associated value
will be returned. When the header contains cards with duplicate keywords,
only the value of the first card with the given keyword will be returned.
It is also possible to use a 2-tuple as the index in the form (keyword,
n)--this returns the n-th value with that keyword, in the case where there
are duplicate keywords.
For example::
>>> header['NAXIS']
0
>>> header[('FOO', 1)] # Return the value of the second FOO keyword
'foo'
The header may also be indexed by card number::
>>> header[0] # Return the value of the first card in the header
'T'
Commentary keywords such as HISTORY and COMMENT are special cases: When
indexing the Header object with either 'HISTORY' or 'COMMENT' a list of all
the HISTORY/COMMENT values is returned::
>>> header['HISTORY']
This is the first history entry in this header.
This is the second history entry in this header.
...
See the Astropy documentation for more details on working with headers.
"""
def __init__(self, cards=[], copy=False):
"""
Construct a `Header` from an iterable and/or text file.
Parameters
----------
cards : A list of `Card` objects, optional
The cards to initialize the header with. Also allowed are other
`Header` (or `dict`-like) objects.
.. versionchanged:: 1.2
Allowed ``cards`` to be a `dict`-like object.
copy : bool, optional
If ``True`` copies the ``cards`` if they were another `Header`
instance.
Default is ``False``.
.. versionadded:: 1.3
"""
self.clear()
if isinstance(cards, Header):
if copy:
cards = cards.copy()
cards = cards.cards
elif isinstance(cards, dict):
cards = cards.items()
for card in cards:
self.append(card, end=True)
self._modified = False
def __len__(self):
return len(self._cards)
def __iter__(self):
for card in self._cards:
yield card.keyword
def __contains__(self, keyword):
if keyword in self._keyword_indices or keyword in self._rvkc_indices:
# For the most common case (single, standard form keyword lookup)
# this will work and is an O(1) check. If it fails that doesn't
# guarantee absence, just that we have to perform the full set of
# checks in self._cardindex
return True
try:
self._cardindex(keyword)
except (KeyError, IndexError):
return False
return True
def __getitem__(self, key):
if isinstance(key, slice):
return Header([copy.copy(c) for c in self._cards[key]])
elif self._haswildcard(key):
return Header([copy.copy(self._cards[idx])
for idx in self._wildcardmatch(key)])
elif (isinstance(key, str) and
key.upper() in Card._commentary_keywords):
key = key.upper()
# Special case for commentary cards
return _HeaderCommentaryCards(self, key)
if isinstance(key, tuple):
keyword = key[0]
else:
keyword = key
card = self._cards[self._cardindex(key)]
if card.field_specifier is not None and keyword == card.rawkeyword:
# This is RVKC; if only the top-level keyword was specified return
# the raw value, not the parsed out float value
return card.rawvalue
value = card.value
if value == UNDEFINED:
return None
return value
def __setitem__(self, key, value):
if self._set_slice(key, value, self):
return
if isinstance(value, tuple):
if not (0 < len(value) <= 2):
raise ValueError(
'A Header item may be set with either a scalar value, '
'a 1-tuple containing a scalar value, or a 2-tuple '
'containing a scalar value and comment string.')
if len(value) == 1:
value, comment = value[0], None
if value is None:
value = UNDEFINED
elif len(value) == 2:
value, comment = value
if value is None:
value = UNDEFINED
if comment is None:
comment = ''
else:
comment = None
card = None
if isinstance(key, int):
card = self._cards[key]
elif isinstance(key, tuple):
card = self._cards[self._cardindex(key)]
if value is None:
value = UNDEFINED
if card:
card.value = value
if comment is not None:
card.comment = comment
if card._modified:
self._modified = True
else:
# If we get an IndexError that should be raised; we don't allow
# assignment to non-existing indices
self._update((key, value, comment))
def __delitem__(self, key):
if isinstance(key, slice) or self._haswildcard(key):
# This is very inefficient but it's not a commonly used feature.
# If someone out there complains that they make heavy use of slice
# deletions and it's too slow, well, we can worry about it then
# [the solution is not too complicated--it would be wait 'til all
# the cards are deleted before updating _keyword_indices rather
# than updating it once for each card that gets deleted]
if isinstance(key, slice):
indices = range(*key.indices(len(self)))
# If the slice step is backwards we want to reverse it, because
# it will be reversed in a few lines...
if key.step and key.step < 0:
indices = reversed(indices)
else:
indices = self._wildcardmatch(key)
for idx in reversed(indices):
del self[idx]
return
elif isinstance(key, str):
# delete ALL cards with the same keyword name
key = Card.normalize_keyword(key)
indices = self._keyword_indices
if key not in self._keyword_indices:
indices = self._rvkc_indices
if key not in indices:
# if keyword is not present raise KeyError.
# To delete keyword without caring if they were present,
# Header.remove(Keyword) can be used with optional argument ignore_missing as True
raise KeyError("Keyword '{}' not found.".format(key))
for idx in reversed(indices[key]):
# Have to copy the indices list since it will be modified below
del self[idx]
return
idx = self._cardindex(key)
card = self._cards[idx]
keyword = card.keyword
del self._cards[idx]
keyword = Card.normalize_keyword(keyword)
indices = self._keyword_indices[keyword]
indices.remove(idx)
if not indices:
del self._keyword_indices[keyword]
# Also update RVKC indices if necessary :/
if card.field_specifier is not None:
indices = self._rvkc_indices[card.rawkeyword]
indices.remove(idx)
if not indices:
del self._rvkc_indices[card.rawkeyword]
# We also need to update all other indices
self._updateindices(idx, increment=False)
self._modified = True
def __repr__(self):
return self.tostring(sep='\n', endcard=False, padding=False)
def __str__(self):
return self.tostring()
def __eq__(self, other):
"""
Two Headers are equal only if they have the exact same string
representation.
"""
return str(self) == str(other)
def __add__(self, other):
temp = self.copy(strip=False)
temp.extend(other)
return temp
def __iadd__(self, other):
self.extend(other)
return self
def _ipython_key_completions_(self):
return self.__iter__()
@property
def cards(self):
"""
The underlying physical cards that make up this Header; it can be
looked at, but it should not be modified directly.
"""
return _CardAccessor(self)
@property
def comments(self):
"""
View the comments associated with each keyword, if any.
For example, to see the comment on the NAXIS keyword:
>>> header.comments['NAXIS']
number of data axes
Comments can also be updated through this interface:
>>> header.comments['NAXIS'] = 'Number of data axes'
"""
return _HeaderComments(self)
@property
def _modified(self):
"""
Whether or not the header has been modified; this is a property so that
it can also check each card for modifications--cards may have been
modified directly without the header containing it otherwise knowing.
"""
modified_cards = any(c._modified for c in self._cards)
if modified_cards:
# If any cards were modified then by definition the header was
# modified
self.__dict__['_modified'] = True
return self.__dict__['_modified']
@_modified.setter
def _modified(self, val):
self.__dict__['_modified'] = val
@classmethod
def fromstring(cls, data, sep=''):
"""
Creates an HDU header from a byte string containing the entire header
data.
Parameters
----------
data : str
String containing the entire header.
sep : str, optional
The string separating cards from each other, such as a newline. By
default there is no card separator (as is the case in a raw FITS
file).
Returns
-------
header
A new `Header` instance.
"""
cards = []
# If the card separator contains characters that may validly appear in
# a card, the only way to unambiguously distinguish between cards is to
# require that they be Card.length long. However, if the separator
# contains non-valid characters (namely \n) the cards may be split
# immediately at the separator
require_full_cardlength = set(sep).issubset(VALID_HEADER_CHARS)
# Split the header into individual cards
idx = 0
image = []
while idx < len(data):
if require_full_cardlength:
end_idx = idx + Card.length
else:
try:
end_idx = data.index(sep, idx)
except ValueError:
end_idx = len(data)
next_image = data[idx:end_idx]
idx = end_idx + len(sep)
if image:
if next_image[:8] == 'CONTINUE':
image.append(next_image)
continue
cards.append(Card.fromstring(''.join(image)))
if require_full_cardlength:
if next_image == END_CARD:
image = []
break
else:
if next_image.split(sep)[0].rstrip() == 'END':
image = []
break
image = [next_image]
# Add the last image that was found before the end, if any
if image:
cards.append(Card.fromstring(''.join(image)))
return cls._fromcards(cards)
@classmethod
def fromfile(cls, fileobj, sep='', endcard=True, padding=True):
"""
Similar to :meth:`Header.fromstring`, but reads the header string from
a given file-like object or filename.
Parameters
----------
fileobj : str, file-like
A filename or an open file-like object from which a FITS header is
to be read. For open file handles the file pointer must be at the
beginning of the header.
sep : str, optional
The string separating cards from each other, such as a newline. By
default there is no card separator (as is the case in a raw FITS
file).
endcard : bool, optional
If True (the default) the header must end with an END card in order
to be considered valid. If an END card is not found an
`OSError` is raised.
padding : bool, optional
If True (the default) the header will be required to be padded out
to a multiple of 2880, the FITS header block size. Otherwise any
padding, or lack thereof, is ignored.
Returns
-------
header
A new `Header` instance.
"""
close_file = False
if isinstance(fileobj, str):
# Open in text mode by default to support newline handling; if a
# binary-mode file object is passed in, the user is on their own
# with respect to newline handling
fileobj = open(fileobj, 'r')
close_file = True
try:
is_binary = fileobj_is_binary(fileobj)
def block_iter(nbytes):
while True:
data = fileobj.read(nbytes)
if data:
yield data
else:
break
return cls._from_blocks(block_iter, is_binary, sep, endcard,
padding)[1]
finally:
if close_file:
fileobj.close()
@classmethod
def _fromcards(cls, cards):
header = cls()
for idx, card in enumerate(cards):
header._cards.append(card)
keyword = Card.normalize_keyword(card.keyword)
header._keyword_indices[keyword].append(idx)
if card.field_specifier is not None:
header._rvkc_indices[card.rawkeyword].append(idx)
header._modified = False
return header
@classmethod
def _from_blocks(cls, block_iter, is_binary, sep, endcard, padding):
"""
The meat of `Header.fromfile`; in a separate method so that
`Header.fromfile` itself is just responsible for wrapping file
handling. Also used by `_BaseHDU.fromstring`.
``block_iter`` should be a callable which, given a block size n
(typically 2880 bytes as used by the FITS standard) returns an iterator
of byte strings of that block size.
``is_binary`` specifies whether the returned blocks are bytes or text
Returns both the entire header *string*, and the `Header` object
returned by Header.fromstring on that string.
"""
actual_block_size = _block_size(sep)
clen = Card.length + len(sep)
blocks = block_iter(actual_block_size)
# Read the first header block.
try:
block = next(blocks)
except StopIteration:
raise EOFError()
if not is_binary:
# TODO: There needs to be error handling at *this* level for
# non-ASCII characters; maybe at this stage decoding latin-1 might
# be safer
block = encode_ascii(block)
read_blocks = []
is_eof = False
end_found = False
# continue reading header blocks until END card or EOF is reached
while True:
# find the END card
end_found, block = cls._find_end_card(block, clen)
read_blocks.append(decode_ascii(block))
if end_found:
break
try:
block = next(blocks)
except StopIteration:
is_eof = True
break
if not block:
is_eof = True
break
if not is_binary:
block = encode_ascii(block)
if not end_found and is_eof and endcard:
# TODO: Pass this error to validation framework as an ERROR,
# rather than raising an exception
raise OSError('Header missing END card.')
header_str = ''.join(read_blocks)
_check_padding(header_str, actual_block_size, is_eof,
check_block_size=padding)
return header_str, cls.fromstring(header_str, sep=sep)
@classmethod
def _find_end_card(cls, block, card_len):
"""
Utility method to search a header block for the END card and handle
invalid END cards.
This method can also returned a modified copy of the input header block
in case an invalid end card needs to be sanitized.
"""
for mo in HEADER_END_RE.finditer(block):
# Ensure the END card was found, and it started on the
# boundary of a new card (see ticket #142)
if mo.start() % card_len != 0:
continue
# This must be the last header block, otherwise the
# file is malformatted
if mo.group('invalid'):
offset = mo.start()
trailing = block[offset + 3:offset + card_len - 3].rstrip()
if trailing:
trailing = repr(trailing).lstrip('ub')
# TODO: Pass this warning up to the validation framework
warnings.warn(
'Unexpected bytes trailing END keyword: {0}; these '
'bytes will be replaced with spaces on write.'.format(
trailing), AstropyUserWarning)
else:
# TODO: Pass this warning up to the validation framework
warnings.warn(
'Missing padding to end of the FITS block after the '
'END keyword; additional spaces will be appended to '
'the file upon writing to pad out to {0} '
'bytes.'.format(BLOCK_SIZE), AstropyUserWarning)
# Sanitize out invalid END card now that the appropriate
# warnings have been issued
block = (block[:offset] + encode_ascii(END_CARD) +
block[offset + len(END_CARD):])
return True, block
return False, block
def tostring(self, sep='', endcard=True, padding=True):
r"""
Returns a string representation of the header.
By default this uses no separator between cards, adds the END card, and
pads the string with spaces to the next multiple of 2880 bytes. That
is, it returns the header exactly as it would appear in a FITS file.
Parameters
----------
sep : str, optional
The character or string with which to separate cards. By default
there is no separator, but one could use ``'\\n'``, for example, to
separate each card with a new line
endcard : bool, optional
If True (default) adds the END card to the end of the header
string
padding : bool, optional
If True (default) pads the string with spaces out to the next
multiple of 2880 characters
Returns
-------
s : str
A string representing a FITS header.
"""
lines = []
for card in self._cards:
s = str(card)
# Cards with CONTINUE cards may be longer than 80 chars; so break
# them into multiple lines
while s:
lines.append(s[:Card.length])
s = s[Card.length:]
s = sep.join(lines)
if endcard:
s += sep + _pad('END')
if padding:
s += ' ' * _pad_length(len(s))
return s
@deprecated_renamed_argument('clobber', 'overwrite', '2.0')
def tofile(self, fileobj, sep='', endcard=True, padding=True,
overwrite=False):
r"""
Writes the header to file or file-like object.
By default this writes the header exactly as it would be written to a
FITS file, with the END card included and padding to the next multiple
of 2880 bytes. However, aspects of this may be controlled.
Parameters
----------
fileobj : str, file, optional
Either the pathname of a file, or an open file handle or file-like
object
sep : str, optional
The character or string with which to separate cards. By default
there is no separator, but one could use ``'\\n'``, for example, to
separate each card with a new line
endcard : bool, optional
If `True` (default) adds the END card to the end of the header
string
padding : bool, optional
If `True` (default) pads the string with spaces out to the next
multiple of 2880 characters
overwrite : bool, optional
If ``True``, overwrite the output file if it exists. Raises an
``OSError`` if ``False`` and the output file exists. Default is
``False``.
.. versionchanged:: 1.3
``overwrite`` replaces the deprecated ``clobber`` argument.
"""
close_file = fileobj_closed(fileobj)
if not isinstance(fileobj, _File):
fileobj = _File(fileobj, mode='ostream', overwrite=overwrite)
try:
blocks = self.tostring(sep=sep, endcard=endcard, padding=padding)
actual_block_size = _block_size(sep)
if padding and len(blocks) % actual_block_size != 0:
raise OSError(
'Header size ({}) is not a multiple of block '
'size ({}).'.format(
len(blocks) - actual_block_size + BLOCK_SIZE,
BLOCK_SIZE))
if not fileobj.simulateonly:
fileobj.flush()
try:
offset = fileobj.tell()
except (AttributeError, OSError):
offset = 0
fileobj.write(blocks.encode('ascii'))
fileobj.flush()
finally:
if close_file:
fileobj.close()
@classmethod
def fromtextfile(cls, fileobj, endcard=False):
"""
Read a header from a simple text file or file-like object.
Equivalent to::
>>> Header.fromfile(fileobj, sep='\\n', endcard=False,
... padding=False)
See Also
--------
fromfile
"""
return cls.fromfile(fileobj, sep='\n', endcard=endcard, padding=False)
@deprecated_renamed_argument('clobber', 'overwrite', '2.0')
def totextfile(self, fileobj, endcard=False, overwrite=False):
"""
Write the header as text to a file or a file-like object.
Equivalent to::
>>> Header.tofile(fileobj, sep='\\n', endcard=False,
... padding=False, overwrite=overwrite)
.. versionchanged:: 1.3
``overwrite`` replaces the deprecated ``clobber`` argument.
See Also
--------
tofile
"""
self.tofile(fileobj, sep='\n', endcard=endcard, padding=False,
overwrite=overwrite)
def clear(self):
"""
Remove all cards from the header.
"""
self._cards = []
self._keyword_indices = collections.defaultdict(list)
self._rvkc_indices = collections.defaultdict(list)
def copy(self, strip=False):
"""
Make a copy of the :class:`Header`.
.. versionchanged:: 1.3
`copy.copy` and `copy.deepcopy` on a `Header` will call this
method.
Parameters
----------
strip : bool, optional
If `True`, strip any headers that are specific to one of the
standard HDU types, so that this header can be used in a different
HDU.
Returns
-------
header
A new :class:`Header` instance.
"""
tmp = Header((copy.copy(card) for card in self._cards))
if strip:
tmp._strip()
return tmp
def __copy__(self):
return self.copy()
def __deepcopy__(self, *args, **kwargs):
return self.copy()
@classmethod
def fromkeys(cls, iterable, value=None):
"""
Similar to :meth:`dict.fromkeys`--creates a new `Header` from an
iterable of keywords and an optional default value.
This method is not likely to be particularly useful for creating real
world FITS headers, but it is useful for testing.
Parameters
----------
iterable
Any iterable that returns strings representing FITS keywords.
value : optional
A default value to assign to each keyword; must be a valid type for
FITS keywords.
Returns
-------
header
A new `Header` instance.
"""
d = cls()
if not isinstance(value, tuple):
value = (value,)
for key in iterable:
d.append((key,) + value)
return d
def get(self, key, default=None):
"""
Similar to :meth:`dict.get`--returns the value associated with keyword
in the header, or a default value if the keyword is not found.
Parameters
----------
key : str
A keyword that may or may not be in the header.
default : optional
A default value to return if the keyword is not found in the
header.
Returns
-------
value
The value associated with the given keyword, or the default value
if the keyword is not in the header.
"""
try:
return self[key]
except (KeyError, IndexError):
return default
def set(self, keyword, value=None, comment=None, before=None, after=None):
"""
Set the value and/or comment and/or position of a specified keyword.
If the keyword does not already exist in the header, a new keyword is
created in the specified position, or appended to the end of the header
if no position is specified.
This method is similar to :meth:`Header.update` prior to Astropy v0.1.
.. note::
It should be noted that ``header.set(keyword, value)`` and
``header.set(keyword, value, comment)`` are equivalent to
``header[keyword] = value`` and
``header[keyword] = (value, comment)`` respectively.
New keywords can also be inserted relative to existing keywords
using, for example::
>>> header.insert('NAXIS1', ('NAXIS', 2, 'Number of axes'))
to insert before an existing keyword, or::
>>> header.insert('NAXIS', ('NAXIS1', 4096), after=True)
to insert after an existing keyword.
The only advantage of using :meth:`Header.set` is that it
easily replaces the old usage of :meth:`Header.update` both
conceptually and in terms of function signature.
Parameters
----------
keyword : str
A header keyword
value : str, optional
The value to set for the given keyword; if None the existing value
is kept, but '' may be used to set a blank value
comment : str, optional
The comment to set for the given keyword; if None the existing
comment is kept, but ``''`` may be used to set a blank comment
before : str, int, optional
Name of the keyword, or index of the `Card` before which this card
should be located in the header. The argument ``before`` takes
precedence over ``after`` if both specified.
after : str, int, optional
Name of the keyword, or index of the `Card` after which this card
should be located in the header.
"""
# Create a temporary card that looks like the one being set; if the
# temporary card turns out to be a RVKC this will make it easier to
# deal with the idiosyncrasies thereof
# Don't try to make a temporary card though if they keyword looks like
# it might be a HIERARCH card or is otherwise invalid--this step is
# only for validating RVKCs.
if (len(keyword) <= KEYWORD_LENGTH and
Card._keywd_FSC_RE.match(keyword) and
keyword not in self._keyword_indices):
new_card = Card(keyword, value, comment)
new_keyword = new_card.keyword
else:
new_keyword = keyword
if (new_keyword not in Card._commentary_keywords and
new_keyword in self):
if comment is None:
comment = self.comments[keyword]
if value is None:
value = self[keyword]
self[keyword] = (value, comment)
if before is not None or after is not None:
card = self._cards[self._cardindex(keyword)]
self._relativeinsert(card, before=before, after=after,
replace=True)
elif before is not None or after is not None:
self._relativeinsert((keyword, value, comment), before=before,
after=after)
else:
self[keyword] = (value, comment)
def items(self):
"""Like :meth:`dict.items`."""
for card in self._cards:
yield (card.keyword, card.value)
def keys(self):
"""
Like :meth:`dict.keys`--iterating directly over the `Header`
instance has the same behavior.
"""
for card in self._cards:
yield card.keyword
def values(self):
"""Like :meth:`dict.values`."""
for card in self._cards:
yield card.value
def pop(self, *args):
"""
Works like :meth:`list.pop` if no arguments or an index argument are
supplied; otherwise works like :meth:`dict.pop`.
"""
if len(args) > 2:
raise TypeError('Header.pop expected at most 2 arguments, got '
'{}'.format(len(args)))
if len(args) == 0:
key = -1
else:
key = args[0]
try:
value = self[key]
except (KeyError, IndexError):
if len(args) == 2:
return args[1]
raise
del self[key]
return value
def popitem(self):
"""Similar to :meth:`dict.popitem`."""
try:
k, v = next(self.items())
except StopIteration:
raise KeyError('Header is empty')
del self[k]
return k, v
def setdefault(self, key, default=None):
"""Similar to :meth:`dict.setdefault`."""
try:
return self[key]
except (KeyError, IndexError):
self[key] = default
return default
def update(self, *args, **kwargs):
"""
Update the Header with new keyword values, updating the values of
existing keywords and appending new keywords otherwise; similar to
`dict.update`.
`update` accepts either a dict-like object or an iterable. In the
former case the keys must be header keywords and the values may be
either scalar values or (value, comment) tuples. In the case of an
iterable the items must be (keyword, value) tuples or (keyword, value,
comment) tuples.
Arbitrary arguments are also accepted, in which case the update() is
called again with the kwargs dict as its only argument. That is,
::
>>> header.update(NAXIS1=100, NAXIS2=100)
is equivalent to::
header.update({'NAXIS1': 100, 'NAXIS2': 100})
.. warning::
As this method works similarly to `dict.update` it is very
different from the ``Header.update()`` method in Astropy v0.1.
Use of the old API was
**deprecated** for a long time and is now removed. Most uses of the
old API can be replaced as follows:
* Replace ::
header.update(keyword, value)
with ::
header[keyword] = value
* Replace ::
header.update(keyword, value, comment=comment)
with ::
header[keyword] = (value, comment)
* Replace ::
header.update(keyword, value, before=before_keyword)
with ::
header.insert(before_keyword, (keyword, value))
* Replace ::
header.update(keyword, value, after=after_keyword)
with ::
header.insert(after_keyword, (keyword, value),
after=True)
See also :meth:`Header.set` which is a new method that provides an
interface similar to the old ``Header.update()`` and may help make
transition a little easier.
"""
if args:
other = args[0]
else:
other = None
def update_from_dict(k, v):
if not isinstance(v, tuple):
card = Card(k, v)
elif 0 < len(v) <= 2:
card = Card(*((k,) + v))
else:
raise ValueError(
'Header update value for key %r is invalid; the '
'value must be either a scalar, a 1-tuple '
'containing the scalar value, or a 2-tuple '
'containing the value and a comment string.' % k)
self._update(card)
if other is None:
pass
elif hasattr(other, 'items'):
for k, v in other.items():
update_from_dict(k, v)
elif hasattr(other, 'keys'):
for k in other.keys():
update_from_dict(k, other[k])
else:
for idx, card in enumerate(other):
if isinstance(card, Card):
self._update(card)
elif isinstance(card, tuple) and (1 < len(card) <= 3):
self._update(Card(*card))
else:
raise ValueError(
'Header update sequence item #{} is invalid; '
'the item must either be a 2-tuple containing '
'a keyword and value, or a 3-tuple containing '
'a keyword, value, and comment string.'.format(idx))
if kwargs:
self.update(kwargs)
def append(self, card=None, useblanks=True, bottom=False, end=False):
"""
Appends a new keyword+value card to the end of the Header, similar
to `list.append`.
By default if the last cards in the Header have commentary keywords,
this will append the new keyword before the commentary (unless the new
keyword is also commentary).
Also differs from `list.append` in that it can be called with no
arguments: In this case a blank card is appended to the end of the
Header. In the case all the keyword arguments are ignored.
Parameters
----------
card : str, tuple
A keyword or a (keyword, value, [comment]) tuple representing a
single header card; the comment is optional in which case a
2-tuple may be used
useblanks : bool, optional
If there are blank cards at the end of the Header, replace the
first blank card so that the total number of cards in the Header
does not increase. Otherwise preserve the number of blank cards.
bottom : bool, optional
If True, instead of appending after the last non-commentary card,
append after the last non-blank card.
end : bool, optional
If True, ignore the useblanks and bottom options, and append at the
very end of the Header.
"""
if isinstance(card, str):
card = Card(card)
elif isinstance(card, tuple):
card = Card(*card)
elif card is None:
card = Card()
elif not isinstance(card, Card):
raise ValueError(
'The value appended to a Header must be either a keyword or '
'(keyword, value, [comment]) tuple; got: {!r}'.format(card))
if not end and card.is_blank:
# Blank cards should always just be appended to the end
end = True
if end:
self._cards.append(card)
idx = len(self._cards) - 1
else:
idx = len(self._cards) - 1
while idx >= 0 and self._cards[idx].is_blank:
idx -= 1
if not bottom and card.keyword not in Card._commentary_keywords:
while (idx >= 0 and
self._cards[idx].keyword in Card._commentary_keywords):
idx -= 1
idx += 1
self._cards.insert(idx, card)
self._updateindices(idx)
keyword = Card.normalize_keyword(card.keyword)
self._keyword_indices[keyword].append(idx)
if card.field_specifier is not None:
self._rvkc_indices[card.rawkeyword].append(idx)
if not end:
# If the appended card was a commentary card, and it was appended
# before existing cards with the same keyword, the indices for
# cards with that keyword may have changed
if not bottom and card.keyword in Card._commentary_keywords:
self._keyword_indices[keyword].sort()
# Finally, if useblanks, delete a blank cards from the end
if useblanks and self._countblanks():
# Don't do this unless there is at least one blanks at the end
# of the header; we need to convert the card to its string
# image to see how long it is. In the vast majority of cases
# this will just be 80 (Card.length) but it may be longer for
# CONTINUE cards
self._useblanks(len(str(card)) // Card.length)
self._modified = True
def extend(self, cards, strip=True, unique=False, update=False,
update_first=False, useblanks=True, bottom=False, end=False):
"""
Appends multiple keyword+value cards to the end of the header, similar
to `list.extend`.
Parameters
----------
cards : iterable
An iterable of (keyword, value, [comment]) tuples; see
`Header.append`.
strip : bool, optional
Remove any keywords that have meaning only to specific types of
HDUs, so that only more general keywords are added from extension
Header or Card list (default: `True`).
unique : bool, optional
If `True`, ensures that no duplicate keywords are appended;
keywords already in this header are simply discarded. The
exception is commentary keywords (COMMENT, HISTORY, etc.): they are
only treated as duplicates if their values match.
update : bool, optional
If `True`, update the current header with the values and comments
from duplicate keywords in the input header. This supersedes the
``unique`` argument. Commentary keywords are treated the same as
if ``unique=True``.
update_first : bool, optional
If the first keyword in the header is 'SIMPLE', and the first
keyword in the input header is 'XTENSION', the 'SIMPLE' keyword is
replaced by the 'XTENSION' keyword. Likewise if the first keyword
in the header is 'XTENSION' and the first keyword in the input
header is 'SIMPLE', the 'XTENSION' keyword is replaced by the
'SIMPLE' keyword. This behavior is otherwise dumb as to whether or
not the resulting header is a valid primary or extension header.
This is mostly provided to support backwards compatibility with the
old ``Header.fromTxtFile`` method, and only applies if
``update=True``.
useblanks, bottom, end : bool, optional
These arguments are passed to :meth:`Header.append` while appending
new cards to the header.
"""
temp = Header(cards)
if strip:
temp._strip()
if len(self):
first = self._cards[0].keyword
else:
first = None
# We don't immediately modify the header, because first we need to sift
# out any duplicates in the new header prior to adding them to the
# existing header, but while *allowing* duplicates from the header
# being extended from (see ticket #156)
extend_cards = []
for idx, card in enumerate(temp.cards):
keyword = card.keyword
if keyword not in Card._commentary_keywords:
if unique and not update and keyword in self:
continue
elif update:
if idx == 0 and update_first:
# Dumbly update the first keyword to either SIMPLE or
# XTENSION as the case may be, as was in the case in
# Header.fromTxtFile
if ((keyword == 'SIMPLE' and first == 'XTENSION') or
(keyword == 'XTENSION' and first == 'SIMPLE')):
del self[0]
self.insert(0, card)
else:
self[keyword] = (card.value, card.comment)
elif keyword in self:
self[keyword] = (card.value, card.comment)
else:
extend_cards.append(card)
else:
extend_cards.append(card)
else:
if (unique or update) and keyword in self:
if card.is_blank:
extend_cards.append(card)
continue
for value in self[keyword]:
if value == card.value:
break
else:
extend_cards.append(card)
else:
extend_cards.append(card)
for card in extend_cards:
self.append(card, useblanks=useblanks, bottom=bottom, end=end)
def count(self, keyword):
"""
Returns the count of the given keyword in the header, similar to
`list.count` if the Header object is treated as a list of keywords.
Parameters
----------
keyword : str
The keyword to count instances of in the header
"""
keyword = Card.normalize_keyword(keyword)
# We have to look before we leap, since otherwise _keyword_indices,
# being a defaultdict, will create an entry for the nonexistent keyword
if keyword not in self._keyword_indices:
raise KeyError("Keyword {!r} not found.".format(keyword))
return len(self._keyword_indices[keyword])
def index(self, keyword, start=None, stop=None):
"""
Returns the index if the first instance of the given keyword in the
header, similar to `list.index` if the Header object is treated as a
list of keywords.
Parameters
----------
keyword : str
The keyword to look up in the list of all keywords in the header
start : int, optional
The lower bound for the index
stop : int, optional
The upper bound for the index
"""
if start is None:
start = 0
if stop is None:
stop = len(self._cards)
if stop < start:
step = -1
else:
step = 1
norm_keyword = Card.normalize_keyword(keyword)
for idx in range(start, stop, step):
if self._cards[idx].keyword.upper() == norm_keyword:
return idx
else:
raise ValueError('The keyword {!r} is not in the '
' header.'.format(keyword))
def insert(self, key, card, useblanks=True, after=False):
"""
Inserts a new keyword+value card into the Header at a given location,
similar to `list.insert`.
Parameters
----------
key : int, str, or tuple
The index into the list of header keywords before which the
new keyword should be inserted, or the name of a keyword before
which the new keyword should be inserted. Can also accept a
(keyword, index) tuple for inserting around duplicate keywords.
card : str, tuple
A keyword or a (keyword, value, [comment]) tuple; see
`Header.append`
useblanks : bool, optional
If there are blank cards at the end of the Header, replace the
first blank card so that the total number of cards in the Header
does not increase. Otherwise preserve the number of blank cards.
after : bool, optional
If set to `True`, insert *after* the specified index or keyword,
rather than before it. Defaults to `False`.
"""
if not isinstance(key, int):
# Don't pass through ints to _cardindex because it will not take
# kindly to indices outside the existing number of cards in the
# header, which insert needs to be able to support (for example
# when inserting into empty headers)
idx = self._cardindex(key)
else:
idx = key
if after:
if idx == -1:
idx = len(self._cards)
else:
idx += 1
if idx >= len(self._cards):
# This is just an append (Though it must be an append absolutely to
# the bottom, ignoring blanks, etc.--the point of the insert method
# is that you get exactly what you asked for with no surprises)
self.append(card, end=True)
return
if isinstance(card, str):
card = Card(card)
elif isinstance(card, tuple):
card = Card(*card)
elif not isinstance(card, Card):
raise ValueError(
'The value inserted into a Header must be either a keyword or '
'(keyword, value, [comment]) tuple; got: {!r}'.format(card))
self._cards.insert(idx, card)
keyword = card.keyword
# If idx was < 0, determine the actual index according to the rules
# used by list.insert()
if idx < 0:
idx += len(self._cards) - 1
if idx < 0:
idx = 0
# All the keyword indices above the insertion point must be updated
self._updateindices(idx)
keyword = Card.normalize_keyword(keyword)
self._keyword_indices[keyword].append(idx)
count = len(self._keyword_indices[keyword])
if count > 1:
# There were already keywords with this same name
if keyword not in Card._commentary_keywords:
warnings.warn(
'A {!r} keyword already exists in this header. Inserting '
'duplicate keyword.'.format(keyword), AstropyUserWarning)
self._keyword_indices[keyword].sort()
if card.field_specifier is not None:
# Update the index of RVKC as well
rvkc_indices = self._rvkc_indices[card.rawkeyword]
rvkc_indices.append(idx)
rvkc_indices.sort()
if useblanks:
self._useblanks(len(str(card)) // Card.length)
self._modified = True
def remove(self, keyword, ignore_missing=False, remove_all=False):
"""
Removes the first instance of the given keyword from the header similar
to `list.remove` if the Header object is treated as a list of keywords.
Parameters
----------
keyword : str
The keyword of which to remove the first instance in the header.
ignore_missing : bool, optional
When True, ignores missing keywords. Otherwise, if the keyword
is not present in the header a KeyError is raised.
remove_all : bool, optional
When True, all instances of keyword will be removed.
Otherwise only the first instance of the given keyword is removed.
"""
keyword = Card.normalize_keyword(keyword)
if keyword in self._keyword_indices:
del self[self._keyword_indices[keyword][0]]
if remove_all:
while keyword in self._keyword_indices:
del self[self._keyword_indices[keyword][0]]
elif not ignore_missing:
raise KeyError("Keyword '{}' not found.".format(keyword))
def rename_keyword(self, oldkeyword, newkeyword, force=False):
"""
Rename a card's keyword in the header.
Parameters
----------
oldkeyword : str or int
Old keyword or card index
newkeyword : str
New keyword
force : bool, optional
When `True`, if the new keyword already exists in the header, force
the creation of a duplicate keyword. Otherwise a
`ValueError` is raised.
"""
oldkeyword = Card.normalize_keyword(oldkeyword)
newkeyword = Card.normalize_keyword(newkeyword)
if newkeyword == 'CONTINUE':
raise ValueError('Can not rename to CONTINUE')
if (newkeyword in Card._commentary_keywords or
oldkeyword in Card._commentary_keywords):
if not (newkeyword in Card._commentary_keywords and
oldkeyword in Card._commentary_keywords):
raise ValueError('Regular and commentary keys can not be '
'renamed to each other.')
elif not force and newkeyword in self:
raise ValueError('Intended keyword {} already exists in header.'
.format(newkeyword))
idx = self.index(oldkeyword)
card = self._cards[idx]
del self[idx]
self.insert(idx, (newkeyword, card.value, card.comment))
def add_history(self, value, before=None, after=None):
"""
Add a ``HISTORY`` card.
Parameters
----------
value : str
History text to be added.
before : str or int, optional
Same as in `Header.update`
after : str or int, optional
Same as in `Header.update`
"""
self._add_commentary('HISTORY', value, before=before, after=after)
def add_comment(self, value, before=None, after=None):
"""
Add a ``COMMENT`` card.
Parameters
----------
value : str
Text to be added.
before : str or int, optional
Same as in `Header.update`
after : str or int, optional
Same as in `Header.update`
"""
self._add_commentary('COMMENT', value, before=before, after=after)
def add_blank(self, value='', before=None, after=None):
"""
Add a blank card.
Parameters
----------
value : str, optional
Text to be added.
before : str or int, optional
Same as in `Header.update`
after : str or int, optional
Same as in `Header.update`
"""
self._add_commentary('', value, before=before, after=after)
def _update(self, card):
"""
The real update code. If keyword already exists, its value and/or
comment will be updated. Otherwise a new card will be appended.
This will not create a duplicate keyword except in the case of
commentary cards. The only other way to force creation of a duplicate
is to use the insert(), append(), or extend() methods.
"""
keyword, value, comment = card
# Lookups for existing/known keywords are case-insensitive
keyword = keyword.upper()
if keyword.startswith('HIERARCH '):
keyword = keyword[9:]
if (keyword not in Card._commentary_keywords and
keyword in self._keyword_indices):
# Easy; just update the value/comment
idx = self._keyword_indices[keyword][0]
existing_card = self._cards[idx]
existing_card.value = value
if comment is not None:
# '' should be used to explicitly blank a comment
existing_card.comment = comment
if existing_card._modified:
self._modified = True
elif keyword in Card._commentary_keywords:
cards = self._splitcommentary(keyword, value)
if keyword in self._keyword_indices:
# Append after the last keyword of the same type
idx = self.index(keyword, start=len(self) - 1, stop=-1)
isblank = not (keyword or value or comment)
for c in reversed(cards):
self.insert(idx + 1, c, useblanks=(not isblank))
else:
for c in cards:
self.append(c, bottom=True)
else:
# A new keyword! self.append() will handle updating _modified
self.append(card)
def _cardindex(self, key):
"""Returns an index into the ._cards list given a valid lookup key."""
# This used to just set key = (key, 0) and then go on to act as if the
# user passed in a tuple, but it's much more common to just be given a
# string as the key, so optimize more for that case
if isinstance(key, str):
keyword = key
n = 0
elif isinstance(key, int):
# If < 0, determine the actual index
if key < 0:
key += len(self._cards)
if key < 0 or key >= len(self._cards):
raise IndexError('Header index out of range.')
return key
elif isinstance(key, slice):
return key
elif isinstance(key, tuple):
if (len(key) != 2 or not isinstance(key[0], str) or
not isinstance(key[1], int)):
raise ValueError(
'Tuple indices must be 2-tuples consisting of a '
'keyword string and an integer index.')
keyword, n = key
else:
raise ValueError(
'Header indices must be either a string, a 2-tuple, or '
'an integer.')
keyword = Card.normalize_keyword(keyword)
# Returns the index into _cards for the n-th card with the given
# keyword (where n is 0-based)
indices = self._keyword_indices.get(keyword, None)
if keyword and not indices:
if len(keyword) > KEYWORD_LENGTH or '.' in keyword:
raise KeyError("Keyword {!r} not found.".format(keyword))
else:
# Maybe it's a RVKC?
indices = self._rvkc_indices.get(keyword, None)
if not indices:
raise KeyError("Keyword {!r} not found.".format(keyword))
try:
return indices[n]
except IndexError:
raise IndexError('There are only {} {!r} cards in the '
'header.'.format(len(indices), keyword))
def _keyword_from_index(self, idx):
"""
Given an integer index, return the (keyword, repeat) tuple that index
refers to. For most keywords the repeat will always be zero, but it
may be greater than zero for keywords that are duplicated (especially
commentary keywords).
In a sense this is the inverse of self.index, except that it also
supports duplicates.
"""
if idx < 0:
idx += len(self._cards)
keyword = self._cards[idx].keyword
keyword = Card.normalize_keyword(keyword)
repeat = self._keyword_indices[keyword].index(idx)
return keyword, repeat
def _relativeinsert(self, card, before=None, after=None, replace=False):
"""
Inserts a new card before or after an existing card; used to
implement support for the legacy before/after keyword arguments to
Header.update().
If replace=True, move an existing card with the same keyword.
"""
if before is None:
insertionkey = after
else:
insertionkey = before
def get_insertion_idx():
if not (isinstance(insertionkey, int) and
insertionkey >= len(self._cards)):
idx = self._cardindex(insertionkey)
else:
idx = insertionkey
if before is None:
idx += 1
return idx
if replace:
# The card presumably already exists somewhere in the header.
# Check whether or not we actually have to move it; if it does need
# to be moved we just delete it and then it will be reinserted
# below
old_idx = self._cardindex(card.keyword)
insertion_idx = get_insertion_idx()
if (insertion_idx >= len(self._cards) and
old_idx == len(self._cards) - 1):
# The card would be appended to the end, but it's already at
# the end
return
if before is not None:
if old_idx == insertion_idx - 1:
return
elif after is not None and old_idx == insertion_idx:
return
del self[old_idx]
# Even if replace=True, the insertion idx may have changed since the
# old card was deleted
idx = get_insertion_idx()
if card[0] in Card._commentary_keywords:
cards = reversed(self._splitcommentary(card[0], card[1]))
else:
cards = [card]
for c in cards:
self.insert(idx, c)
def _updateindices(self, idx, increment=True):
"""
For all cards with index above idx, increment or decrement its index
value in the keyword_indices dict.
"""
if idx > len(self._cards):
# Save us some effort
return
increment = 1 if increment else -1
for index_sets in (self._keyword_indices, self._rvkc_indices):
for indices in index_sets.values():
for jdx, keyword_index in enumerate(indices):
if keyword_index >= idx:
indices[jdx] += increment
def _countblanks(self):
"""Returns the number of blank cards at the end of the Header."""
for idx in range(1, len(self._cards)):
if not self._cards[-idx].is_blank:
return idx - 1
return 0
def _useblanks(self, count):
for _ in range(count):
if self._cards[-1].is_blank:
del self[-1]
else:
break
def _haswildcard(self, keyword):
"""Return `True` if the input keyword contains a wildcard pattern."""
return (isinstance(keyword, str) and
(keyword.endswith('...') or '*' in keyword or '?' in keyword))
def _wildcardmatch(self, pattern):
"""
Returns a list of indices of the cards matching the given wildcard
pattern.
* '*' matches 0 or more characters
* '?' matches a single character
* '...' matches 0 or more of any non-whitespace character
"""
pattern = pattern.replace('*', r'.*').replace('?', r'.')
pattern = pattern.replace('...', r'\S*') + '$'
pattern_re = re.compile(pattern, re.I)
return [idx for idx, card in enumerate(self._cards)
if pattern_re.match(card.keyword)]
def _set_slice(self, key, value, target):
"""
Used to implement Header.__setitem__ and CardAccessor.__setitem__.
"""
if isinstance(key, slice) or self._haswildcard(key):
if isinstance(key, slice):
indices = range(*key.indices(len(target)))
else:
indices = self._wildcardmatch(key)
if isinstance(value, str) or not isiterable(value):
value = itertools.repeat(value, len(indices))
for idx, val in zip(indices, value):
target[idx] = val
return True
return False
def _splitcommentary(self, keyword, value):
"""
Given a commentary keyword and value, returns a list of the one or more
cards needed to represent the full value. This is primarily used to
create the multiple commentary cards needed to represent a long value
that won't fit into a single commentary card.
"""
# The maximum value in each card can be the maximum card length minus
# the maximum key length (which can include spaces if they key length
# less than 8
maxlen = Card.length - KEYWORD_LENGTH
valuestr = str(value)
if len(valuestr) <= maxlen:
# The value can fit in a single card
cards = [Card(keyword, value)]
else:
# The value must be split across multiple consecutive commentary
# cards
idx = 0
cards = []
while idx < len(valuestr):
cards.append(Card(keyword, valuestr[idx:idx + maxlen]))
idx += maxlen
return cards
def _strip(self):
"""
Strip cards specific to a certain kind of header.
Strip cards like ``SIMPLE``, ``BITPIX``, etc. so the rest of
the header can be used to reconstruct another kind of header.
"""
# TODO: Previously this only deleted some cards specific to an HDU if
# _hdutype matched that type. But it seemed simple enough to just
# delete all desired cards anyways, and just ignore the KeyErrors if
# they don't exist.
# However, it might be desirable to make this extendable somehow--have
# a way for HDU classes to specify some headers that are specific only
# to that type, and should be removed otherwise.
if 'NAXIS' in self:
naxis = self['NAXIS']
else:
naxis = 0
if 'TFIELDS' in self:
tfields = self['TFIELDS']
else:
tfields = 0
for idx in range(naxis):
try:
del self['NAXIS' + str(idx + 1)]
except KeyError:
pass
for name in ('TFORM', 'TSCAL', 'TZERO', 'TNULL', 'TTYPE',
'TUNIT', 'TDISP', 'TDIM', 'THEAP', 'TBCOL'):
for idx in range(tfields):
try:
del self[name + str(idx + 1)]
except KeyError:
pass
for name in ('SIMPLE', 'XTENSION', 'BITPIX', 'NAXIS', 'EXTEND',
'PCOUNT', 'GCOUNT', 'GROUPS', 'BSCALE', 'BZERO',
'TFIELDS'):
try:
del self[name]
except KeyError:
pass
def _add_commentary(self, key, value, before=None, after=None):
"""
Add a commentary card.
If ``before`` and ``after`` are `None`, add to the last occurrence
of cards of the same name (except blank card). If there is no
card (or blank card), append at the end.
"""
if before is not None or after is not None:
self._relativeinsert((key, value), before=before,
after=after)
else:
self[key] = value
collections.abc.MutableSequence.register(Header)
collections.abc.MutableMapping.register(Header)
class _DelayedHeader:
"""
Descriptor used to create the Header object from the header string that
was stored in HDU._header_str when parsing the file.
"""
def __get__(self, obj, owner=None):
try:
return obj.__dict__['_header']
except KeyError:
if obj._header_str is not None:
hdr = Header.fromstring(obj._header_str)
obj._header_str = None
else:
raise AttributeError("'{}' object has no attribute '_header'"
.format(obj.__class__.__name__))
obj.__dict__['_header'] = hdr
return hdr
def __set__(self, obj, val):
obj.__dict__['_header'] = val
def __delete__(self, obj):
del obj.__dict__['_header']
class _BasicHeaderCards:
"""
This class allows to access cards with the _BasicHeader.cards attribute.
This is needed because during the HDU class detection, some HDUs uses
the .cards interface. Cards cannot be modified here as the _BasicHeader
object will be deleted once the HDU object is created.
"""
def __init__(self, header):
self.header = header
def __getitem__(self, key):
# .cards is a list of cards, so key here is an integer.
# get the keyword name from its index.
key = self.header._keys[key]
# then we get the card from the _BasicHeader._cards list, or parse it
# if needed.
try:
return self.header._cards[key]
except KeyError:
cardstr = self.header._raw_cards[key]
card = Card.fromstring(cardstr)
self.header._cards[key] = card
return card
class _BasicHeader(collections.abc.Mapping):
"""This class provides a fast header parsing, without all the additional
features of the Header class. Here only standard keywords are parsed, no
support for CONTINUE, HIERARCH, COMMENT, HISTORY, or rvkc.
The raw card images are stored and parsed only if needed. The idea is that
to create the HDU objects, only a small subset of standard cards is needed.
Once a card is parsed, which is deferred to the Card class, the Card object
is kept in a cache. This is useful because a small subset of cards is used
a lot in the HDU creation process (NAXIS, XTENSION, ...).
"""
def __init__(self, cards):
# dict of (keywords, card images)
self._raw_cards = cards
self._keys = list(cards.keys())
# dict of (keyword, Card object) storing the parsed cards
self._cards = {}
# the _BasicHeaderCards object allows to access Card objects from
# keyword indices
self.cards = _BasicHeaderCards(self)
self._modified = False
def __getitem__(self, key):
if isinstance(key, int):
key = self._keys[key]
try:
return self._cards[key].value
except KeyError:
# parse the Card and store it
cardstr = self._raw_cards[key]
self._cards[key] = card = Card.fromstring(cardstr)
return card.value
def __len__(self):
return len(self._raw_cards)
def __iter__(self):
return iter(self._raw_cards)
def index(self, keyword):
return self._keys.index(keyword)
@classmethod
def fromfile(cls, fileobj):
"""The main method to parse a FITS header from a file. The parsing is
done with the parse_header function implemented in Cython."""
close_file = False
if isinstance(fileobj, str):
fileobj = open(fileobj, 'rb')
close_file = True
try:
header_str, cards = parse_header(fileobj)
_check_padding(header_str, BLOCK_SIZE, False)
return header_str, cls(cards)
finally:
if close_file:
fileobj.close()
class _CardAccessor:
"""
This is a generic class for wrapping a Header in such a way that you can
use the header's slice/filtering capabilities to return a subset of cards
and do something with them.
This is sort of the opposite notion of the old CardList class--whereas
Header used to use CardList to get lists of cards, this uses Header to get
lists of cards.
"""
# TODO: Consider giving this dict/list methods like Header itself
def __init__(self, header):
self._header = header
def __repr__(self):
return '\n'.join(repr(c) for c in self._header._cards)
def __len__(self):
return len(self._header._cards)
def __iter__(self):
return iter(self._header._cards)
def __eq__(self, other):
# If the `other` item is a scalar we will still treat it as equal if
# this _CardAccessor only contains one item
if not isiterable(other) or isinstance(other, str):
if len(self) == 1:
other = [other]
else:
return False
for a, b in itertools.zip_longest(self, other):
if a != b:
return False
else:
return True
def __ne__(self, other):
return not (self == other)
def __getitem__(self, item):
if isinstance(item, slice) or self._header._haswildcard(item):
return self.__class__(self._header[item])
idx = self._header._cardindex(item)
return self._header._cards[idx]
def _setslice(self, item, value):
"""
Helper for implementing __setitem__ on _CardAccessor subclasses; slices
should always be handled in this same way.
"""
if isinstance(item, slice) or self._header._haswildcard(item):
if isinstance(item, slice):
indices = range(*item.indices(len(self)))
else:
indices = self._header._wildcardmatch(item)
if isinstance(value, str) or not isiterable(value):
value = itertools.repeat(value, len(indices))
for idx, val in zip(indices, value):
self[idx] = val
return True
return False
collections.abc.Mapping.register(_CardAccessor)
collections.abc.Sequence.register(_CardAccessor)
class _HeaderComments(_CardAccessor):
"""
A class used internally by the Header class for the Header.comments
attribute access.
This object can be used to display all the keyword comments in the Header,
or look up the comments on specific keywords. It allows all the same forms
of keyword lookup as the Header class itself, but returns comments instead
of values.
"""
def __iter__(self):
for card in self._header._cards:
yield card.comment
def __repr__(self):
"""Returns a simple list of all keywords and their comments."""
keyword_length = KEYWORD_LENGTH
for card in self._header._cards:
keyword_length = max(keyword_length, len(card.keyword))
return '\n'.join('{:>{len}} {}'.format(c.keyword, c.comment,
len=keyword_length)
for c in self._header._cards)
def __getitem__(self, item):
"""
Slices and filter strings return a new _HeaderComments containing the
returned cards. Otherwise the comment of a single card is returned.
"""
item = super().__getitem__(item)
if isinstance(item, _HeaderComments):
# The item key was a slice
return item
return item.comment
def __setitem__(self, item, comment):
"""
Set/update the comment on specified card or cards.
Slice/filter updates work similarly to how Header.__setitem__ works.
"""
if self._header._set_slice(item, comment, self):
return
# In this case, key/index errors should be raised; don't update
# comments of nonexistent cards
idx = self._header._cardindex(item)
value = self._header[idx]
self._header[idx] = (value, comment)
class _HeaderCommentaryCards(_CardAccessor):
"""
This is used to return a list-like sequence over all the values in the
header for a given commentary keyword, such as HISTORY.
"""
def __init__(self, header, keyword=''):
super().__init__(header)
self._keyword = keyword
self._count = self._header.count(self._keyword)
self._indices = slice(self._count).indices(self._count)
# __len__ and __iter__ need to be overridden from the base class due to the
# different approach this class has to take for slicing
def __len__(self):
return len(range(*self._indices))
def __iter__(self):
for idx in range(*self._indices):
yield self._header[(self._keyword, idx)]
def __repr__(self):
return '\n'.join(self)
def __getitem__(self, idx):
if isinstance(idx, slice):
n = self.__class__(self._header, self._keyword)
n._indices = idx.indices(self._count)
return n
elif not isinstance(idx, int):
raise ValueError('{} index must be an integer'.format(self._keyword))
idx = list(range(*self._indices))[idx]
return self._header[(self._keyword, idx)]
def __setitem__(self, item, value):
"""
Set the value of a specified commentary card or cards.
Slice/filter updates work similarly to how Header.__setitem__ works.
"""
if self._header._set_slice(item, value, self):
return
# In this case, key/index errors should be raised; don't update
# comments of nonexistent cards
self._header[(self._keyword, item)] = value
def _block_size(sep):
"""
Determine the size of a FITS header block if a non-blank separator is used
between cards.
"""
return BLOCK_SIZE + (len(sep) * (BLOCK_SIZE // Card.length - 1))
def _pad_length(stringlen):
"""Bytes needed to pad the input stringlen to the next FITS block."""
return (BLOCK_SIZE - (stringlen % BLOCK_SIZE)) % BLOCK_SIZE
def _check_padding(header_str, block_size, is_eof, check_block_size=True):
# Strip any zero-padding (see ticket #106)
if header_str and header_str[-1] == '\0':
if is_eof and header_str.strip('\0') == '':
# TODO: Pass this warning to validation framework
warnings.warn(
'Unexpected extra padding at the end of the file. This '
'padding may not be preserved when saving changes.',
AstropyUserWarning)
raise EOFError()
else:
# Replace the illegal null bytes with spaces as required by
# the FITS standard, and issue a nasty warning
# TODO: Pass this warning to validation framework
warnings.warn(
'Header block contains null bytes instead of spaces for '
'padding, and is not FITS-compliant. Nulls may be '
'replaced with spaces upon writing.', AstropyUserWarning)
header_str.replace('\0', ' ')
if check_block_size and (len(header_str) % block_size) != 0:
# This error message ignores the length of the separator for
# now, but maybe it shouldn't?
actual_len = len(header_str) - block_size + BLOCK_SIZE
# TODO: Pass this error to validation framework
raise ValueError('Header size is not multiple of {0}: {1}'
.format(BLOCK_SIZE, actual_len))
|
f310e6a4f73ee5cdfa2037c9a0253f43f1b23396d1be77ee03c018ad784bd17c | # Licensed under a 3-clause BSD style license - see PYFITS.rst
import copy
import operator
import warnings
import weakref
from contextlib import suppress
from functools import reduce
import numpy as np
from numpy import char as chararray
from .column import (ASCIITNULL, FITS2NUMPY, ASCII2NUMPY, ASCII2STR, ColDefs,
_AsciiColDefs, _FormatX, _FormatP, _VLF, _get_index,
_wrapx, _unwrapx, _makep, Delayed)
from .util import decode_ascii, encode_ascii, _rstrip_inplace
from astropy.utils import lazyproperty
class FITS_record:
"""
FITS record class.
`FITS_record` is used to access records of the `FITS_rec` object.
This will allow us to deal with scaled columns. It also handles
conversion/scaling of columns in ASCII tables. The `FITS_record`
class expects a `FITS_rec` object as input.
"""
def __init__(self, input, row=0, start=None, end=None, step=None,
base=None, **kwargs):
"""
Parameters
----------
input : array
The array to wrap.
row : int, optional
The starting logical row of the array.
start : int, optional
The starting column in the row associated with this object.
Used for subsetting the columns of the `FITS_rec` object.
end : int, optional
The ending column in the row associated with this object.
Used for subsetting the columns of the `FITS_rec` object.
"""
self.array = input
self.row = row
if base:
width = len(base)
else:
width = self.array._nfields
s = slice(start, end, step).indices(width)
self.start, self.end, self.step = s
self.base = base
def __getitem__(self, key):
if isinstance(key, str):
indx = _get_index(self.array.names, key)
if indx < self.start or indx > self.end - 1:
raise KeyError("Key '{}' does not exist.".format(key))
elif isinstance(key, slice):
return type(self)(self.array, self.row, key.start, key.stop,
key.step, self)
else:
indx = self._get_index(key)
if indx > self.array._nfields - 1:
raise IndexError('Index out of bounds')
return self.array.field(indx)[self.row]
def __setitem__(self, key, value):
if isinstance(key, str):
indx = _get_index(self.array.names, key)
if indx < self.start or indx > self.end - 1:
raise KeyError("Key '{}' does not exist.".format(key))
elif isinstance(key, slice):
for indx in range(slice.start, slice.stop, slice.step):
indx = self._get_indx(indx)
self.array.field(indx)[self.row] = value
else:
indx = self._get_index(key)
if indx > self.array._nfields - 1:
raise IndexError('Index out of bounds')
self.array.field(indx)[self.row] = value
def __len__(self):
return len(range(self.start, self.end, self.step))
def __repr__(self):
"""
Display a single row.
"""
outlist = []
for idx in range(len(self)):
outlist.append(repr(self[idx]))
return '({})'.format(', '.join(outlist))
def field(self, field):
"""
Get the field data of the record.
"""
return self.__getitem__(field)
def setfield(self, field, value):
"""
Set the field data of the record.
"""
self.__setitem__(field, value)
@lazyproperty
def _bases(self):
bases = [weakref.proxy(self)]
base = self.base
while base:
bases.append(base)
base = base.base
return bases
def _get_index(self, indx):
indices = np.ogrid[:self.array._nfields]
for base in reversed(self._bases):
if base.step < 1:
s = slice(base.start, None, base.step)
else:
s = slice(base.start, base.end, base.step)
indices = indices[s]
return indices[indx]
class FITS_rec(np.recarray):
"""
FITS record array class.
`FITS_rec` is the data part of a table HDU's data part. This is a layer
over the `~numpy.recarray`, so we can deal with scaled columns.
It inherits all of the standard methods from `numpy.ndarray`.
"""
_record_type = FITS_record
_character_as_bytes = False
def __new__(subtype, input):
"""
Construct a FITS record array from a recarray.
"""
# input should be a record array
if input.dtype.subdtype is None:
self = np.recarray.__new__(subtype, input.shape, input.dtype,
buf=input.data)
else:
self = np.recarray.__new__(subtype, input.shape, input.dtype,
buf=input.data, strides=input.strides)
self._init()
if self.dtype.fields:
self._nfields = len(self.dtype.fields)
return self
def __setstate__(self, state):
meta = state[-1]
column_state = state[-2]
state = state[:-2]
super().__setstate__(state)
self._col_weakrefs = weakref.WeakSet()
for attr, value in zip(meta, column_state):
setattr(self, attr, value)
def __reduce__(self):
"""
Return a 3-tuple for pickling a FITS_rec. Use the super-class
functionality but then add in a tuple of FITS_rec-specific
values that get used in __setstate__.
"""
reconst_func, reconst_func_args, state = super().__reduce__()
# Define FITS_rec-specific attrs that get added to state
column_state = []
meta = []
for attrs in ['_converted', '_heapoffset', '_heapsize', '_nfields',
'_gap', '_uint', 'parnames', '_coldefs']:
with suppress(AttributeError):
# _coldefs can be Delayed, and file objects cannot be
# picked, it needs to be deepcopied first
if attrs == '_coldefs':
column_state.append(self._coldefs.__deepcopy__(None))
else:
column_state.append(getattr(self, attrs))
meta.append(attrs)
state = state + (column_state, meta)
return reconst_func, reconst_func_args, state
def __array_finalize__(self, obj):
if obj is None:
return
if isinstance(obj, FITS_rec):
self._character_as_bytes = obj._character_as_bytes
if isinstance(obj, FITS_rec) and obj.dtype == self.dtype:
self._converted = obj._converted
self._heapoffset = obj._heapoffset
self._heapsize = obj._heapsize
self._col_weakrefs = obj._col_weakrefs
self._coldefs = obj._coldefs
self._nfields = obj._nfields
self._gap = obj._gap
self._uint = obj._uint
elif self.dtype.fields is not None:
# This will allow regular ndarrays with fields, rather than
# just other FITS_rec objects
self._nfields = len(self.dtype.fields)
self._converted = {}
self._heapoffset = getattr(obj, '_heapoffset', 0)
self._heapsize = getattr(obj, '_heapsize', 0)
self._gap = getattr(obj, '_gap', 0)
self._uint = getattr(obj, '_uint', False)
self._col_weakrefs = weakref.WeakSet()
self._coldefs = ColDefs(self)
# Work around chicken-egg problem. Column.array relies on the
# _coldefs attribute to set up ref back to parent FITS_rec; however
# in the above line the self._coldefs has not been assigned yet so
# this fails. This patches that up...
for col in self._coldefs:
del col.array
col._parent_fits_rec = weakref.ref(self)
else:
self._init()
def _init(self):
"""Initializes internal attributes specific to FITS-isms."""
self._nfields = 0
self._converted = {}
self._heapoffset = 0
self._heapsize = 0
self._col_weakrefs = weakref.WeakSet()
self._coldefs = None
self._gap = 0
self._uint = False
@classmethod
def from_columns(cls, columns, nrows=0, fill=False, character_as_bytes=False):
"""
Given a `ColDefs` object of unknown origin, initialize a new `FITS_rec`
object.
.. note::
This was originally part of the ``new_table`` function in the table
module but was moved into a class method since most of its
functionality always had more to do with initializing a `FITS_rec`
object than anything else, and much of it also overlapped with
``FITS_rec._scale_back``.
Parameters
----------
columns : sequence of `Column` or a `ColDefs`
The columns from which to create the table data. If these
columns have data arrays attached that data may be used in
initializing the new table. Otherwise the input columns
will be used as a template for a new table with the requested
number of rows.
nrows : int
Number of rows in the new table. If the input columns have data
associated with them, the size of the largest input column is used.
Otherwise the default is 0.
fill : bool
If `True`, will fill all cells with zeros or blanks. If
`False`, copy the data from input, undefined cells will still
be filled with zeros/blanks.
"""
if not isinstance(columns, ColDefs):
columns = ColDefs(columns)
# read the delayed data
for column in columns:
arr = column.array
if isinstance(arr, Delayed):
if arr.hdu.data is None:
column.array = None
else:
column.array = _get_recarray_field(arr.hdu.data,
arr.field)
# Reset columns._arrays (which we may want to just do away with
# altogether
del columns._arrays
# use the largest column shape as the shape of the record
if nrows == 0:
for arr in columns._arrays:
if arr is not None:
dim = arr.shape[0]
else:
dim = 0
if dim > nrows:
nrows = dim
raw_data = np.empty(columns.dtype.itemsize * nrows, dtype=np.uint8)
raw_data.fill(ord(columns._padding_byte))
data = np.recarray(nrows, dtype=columns.dtype, buf=raw_data).view(cls)
data._character_as_bytes = character_as_bytes
# Make sure the data is a listener for changes to the columns
columns._add_listener(data)
# Previously this assignment was made from hdu.columns, but that's a
# bug since if a _TableBaseHDU has a FITS_rec in its .data attribute
# the _TableBaseHDU.columns property is actually returned from
# .data._coldefs, so this assignment was circular! Don't make that
# mistake again.
# All of this is an artifact of the fragility of the FITS_rec class,
# and that it can't just be initialized by columns...
data._coldefs = columns
# If fill is True we don't copy anything from the column arrays. We're
# just using them as a template, and returning a table filled with
# zeros/blanks
if fill:
return data
# Otherwise we have to fill the recarray with data from the input
# columns
for idx, column in enumerate(columns):
# For each column in the ColDef object, determine the number of
# rows in that column. This will be either the number of rows in
# the ndarray associated with the column, or the number of rows
# given in the call to this function, which ever is smaller. If
# the input FILL argument is true, the number of rows is set to
# zero so that no data is copied from the original input data.
arr = column.array
if arr is None:
array_size = 0
else:
array_size = len(arr)
n = min(array_size, nrows)
# TODO: At least *some* of this logic is mostly redundant with the
# _convert_foo methods in this class; see if we can eliminate some
# of that duplication.
if not n:
# The input column had an empty array, so just use the fill
# value
continue
field = _get_recarray_field(data, idx)
name = column.name
fitsformat = column.format
recformat = fitsformat.recformat
outarr = field[:n]
inarr = arr[:n]
if isinstance(recformat, _FormatX):
# Data is a bit array
if inarr.shape[-1] == recformat.repeat:
_wrapx(inarr, outarr, recformat.repeat)
continue
elif isinstance(recformat, _FormatP):
data._cache_field(name, _makep(inarr, field, recformat,
nrows=nrows))
continue
# TODO: Find a better way of determining that the column is meant
# to be FITS L formatted
elif recformat[-2:] == FITS2NUMPY['L'] and inarr.dtype == bool:
# column is boolean
# The raw data field should be filled with either 'T' or 'F'
# (not 0). Use 'F' as a default
field[:] = ord('F')
# Also save the original boolean array in data._converted so
# that it doesn't have to be re-converted
converted = np.zeros(field.shape, dtype=bool)
converted[:n] = inarr
data._cache_field(name, converted)
# TODO: Maybe this step isn't necessary at all if _scale_back
# will handle it?
inarr = np.where(inarr == np.False_, ord('F'), ord('T'))
elif (columns[idx]._physical_values and
columns[idx]._pseudo_unsigned_ints):
# Temporary hack...
bzero = column.bzero
converted = np.zeros(field.shape, dtype=inarr.dtype)
converted[:n] = inarr
data._cache_field(name, converted)
if n < nrows:
# Pre-scale rows below the input data
field[n:] = -bzero
inarr = inarr - bzero
elif isinstance(columns, _AsciiColDefs):
# Regardless whether the format is character or numeric, if the
# input array contains characters then it's already in the raw
# format for ASCII tables
if fitsformat._pseudo_logical:
# Hack to support converting from 8-bit T/F characters
# Normally the column array is a chararray of 1 character
# strings, but we need to view it as a normal ndarray of
# 8-bit ints to fill it with ASCII codes for 'T' and 'F'
outarr = field.view(np.uint8, np.ndarray)[:n]
elif arr.dtype.kind not in ('S', 'U'):
# Set up views of numeric columns with the appropriate
# numeric dtype
# Fill with the appropriate blanks for the column format
data._cache_field(name, np.zeros(nrows, dtype=arr.dtype))
outarr = data._converted[name][:n]
outarr[:] = inarr
continue
if inarr.shape != outarr.shape:
if (inarr.dtype.kind == outarr.dtype.kind and
inarr.dtype.kind in ('U', 'S') and
inarr.dtype != outarr.dtype):
inarr_rowsize = inarr[0].size
inarr = inarr.flatten().view(outarr.dtype)
# This is a special case to handle input arrays with
# non-trivial TDIMn.
# By design each row of the outarray is 1-D, while each row of
# the input array may be n-D
if outarr.ndim > 1:
# The normal case where the first dimension is the rows
inarr_rowsize = inarr[0].size
inarr = inarr.reshape(n, inarr_rowsize)
outarr[:, :inarr_rowsize] = inarr
else:
# Special case for strings where the out array only has one
# dimension (the second dimension is rolled up into the
# strings
outarr[:n] = inarr.ravel()
else:
outarr[:] = inarr
# Now replace the original column array references with the new
# fields
# This is required to prevent the issue reported in
# https://github.com/spacetelescope/PyFITS/issues/99
for idx in range(len(columns)):
columns._arrays[idx] = data.field(idx)
return data
def __repr__(self):
# Force use of the normal ndarray repr (rather than the new
# one added for recarray in Numpy 1.10) for backwards compat
return np.ndarray.__repr__(self)
def __getitem__(self, key):
if self._coldefs is None:
return super().__getitem__(key)
if isinstance(key, str):
return self.field(key)
# Have to view as a recarray then back as a FITS_rec, otherwise the
# circular reference fix/hack in FITS_rec.field() won't preserve
# the slice.
out = self.view(np.recarray)[key]
if type(out) is not np.recarray:
# Oops, we got a single element rather than a view. In that case,
# return a Record, which has no __getstate__ and is more efficient.
return self._record_type(self, key)
# We got a view; change it back to our class, and add stuff
out = out.view(type(self))
out._coldefs = ColDefs(self._coldefs)
arrays = []
out._converted = {}
for idx, name in enumerate(self._coldefs.names):
#
# Store the new arrays for the _coldefs object
#
arrays.append(self._coldefs._arrays[idx][key])
# Ensure that the sliced FITS_rec will view the same scaled
# columns as the original; this is one of the few cases where
# it is not necessary to use _cache_field()
if name in self._converted:
dummy = self._converted[name]
field = np.ndarray.__getitem__(dummy, key)
out._converted[name] = field
out._coldefs._arrays = arrays
return out
def __setitem__(self, key, value):
if self._coldefs is None:
return super().__setitem__(key, value)
if isinstance(key, str):
self[key][:] = value
return
if isinstance(key, slice):
end = min(len(self), key.stop or len(self))
end = max(0, end)
start = max(0, key.start or 0)
end = min(end, start + len(value))
for idx in range(start, end):
self.__setitem__(idx, value[idx - start])
return
if isinstance(value, FITS_record):
for idx in range(self._nfields):
self.field(self.names[idx])[key] = value.field(self.names[idx])
elif isinstance(value, (tuple, list, np.void)):
if self._nfields == len(value):
for idx in range(self._nfields):
self.field(idx)[key] = value[idx]
else:
raise ValueError('Input tuple or list required to have {} '
'elements.'.format(self._nfields))
else:
raise TypeError('Assignment requires a FITS_record, tuple, or '
'list as input.')
def _ipython_key_completions_(self):
return self.names
def copy(self, order='C'):
"""
The Numpy documentation lies; `numpy.ndarray.copy` is not equivalent to
`numpy.copy`. Differences include that it re-views the copied array as
self's ndarray subclass, as though it were taking a slice; this means
``__array_finalize__`` is called and the copy shares all the array
attributes (including ``._converted``!). So we need to make a deep
copy of all those attributes so that the two arrays truly do not share
any data.
"""
new = super().copy(order=order)
new.__dict__ = copy.deepcopy(self.__dict__)
return new
@property
def columns(self):
"""
A user-visible accessor for the coldefs.
See https://aeon.stsci.edu/ssb/trac/pyfits/ticket/44
"""
return self._coldefs
@property
def _coldefs(self):
# This used to be a normal internal attribute, but it was changed to a
# property as a quick and transparent way to work around the reference
# leak bug fixed in https://github.com/astropy/astropy/pull/4539
#
# See the long comment in the Column.array property for more details
# on this. But in short, FITS_rec now has a ._col_weakrefs attribute
# which is a WeakSet of weakrefs to each Column in _coldefs.
#
# So whenever ._coldefs is set we also add each Column in the ColDefs
# to the weakrefs set. This is an easy way to find out if a Column has
# any references to it external to the FITS_rec (i.e. a user assigned a
# column to a variable). If the column is still in _col_weakrefs then
# there are other references to it external to this FITS_rec. We use
# that information in __del__ to save off copies of the array data
# for those columns to their Column.array property before our memory
# is freed.
return self.__dict__.get('_coldefs')
@_coldefs.setter
def _coldefs(self, cols):
self.__dict__['_coldefs'] = cols
if isinstance(cols, ColDefs):
for col in cols.columns:
self._col_weakrefs.add(col)
@_coldefs.deleter
def _coldefs(self):
try:
del self.__dict__['_coldefs']
except KeyError as exc:
raise AttributeError(exc.args[0])
def __del__(self):
try:
del self._coldefs
if self.dtype.fields is not None:
for col in self._col_weakrefs:
if col.array is not None:
col.array = col.array.copy()
# See issues #4690 and #4912
except (AttributeError, TypeError): # pragma: no cover
pass
@property
def names(self):
"""List of column names."""
if self.dtype.fields:
return list(self.dtype.names)
elif getattr(self, '_coldefs', None) is not None:
return self._coldefs.names
else:
return None
@property
def formats(self):
"""List of column FITS formats."""
if getattr(self, '_coldefs', None) is not None:
return self._coldefs.formats
return None
@property
def _raw_itemsize(self):
"""
Returns the size of row items that would be written to the raw FITS
file, taking into account the possibility of unicode columns being
compactified.
Currently for internal use only.
"""
if _has_unicode_fields(self):
total_itemsize = 0
for field in self.dtype.fields.values():
itemsize = field[0].itemsize
if field[0].kind == 'U':
itemsize = itemsize // 4
total_itemsize += itemsize
return total_itemsize
else:
# Just return the normal itemsize
return self.itemsize
def field(self, key):
"""
A view of a `Column`'s data as an array.
"""
# NOTE: The *column* index may not be the same as the field index in
# the recarray, if the column is a phantom column
column = self.columns[key]
name = column.name
format = column.format
if format.dtype.itemsize == 0:
warnings.warn(
'Field {!r} has a repeat count of 0 in its format code, '
'indicating an empty field.'.format(key))
return np.array([], dtype=format.dtype)
# If field's base is a FITS_rec, we can run into trouble because it
# contains a reference to the ._coldefs object of the original data;
# this can lead to a circular reference; see ticket #49
base = self
while (isinstance(base, FITS_rec) and
isinstance(base.base, np.recarray)):
base = base.base
# base could still be a FITS_rec in some cases, so take care to
# use rec.recarray.field to avoid a potential infinite
# recursion
field = _get_recarray_field(base, name)
if name not in self._converted:
recformat = format.recformat
# TODO: If we're now passing the column to these subroutines, do we
# really need to pass them the recformat?
if isinstance(recformat, _FormatP):
# for P format
converted = self._convert_p(column, field, recformat)
else:
# Handle all other column data types which are fixed-width
# fields
converted = self._convert_other(column, field, recformat)
# Note: Never assign values directly into the self._converted dict;
# always go through self._cache_field; this way self._converted is
# only used to store arrays that are not already direct views of
# our own data.
self._cache_field(name, converted)
return converted
return self._converted[name]
def _cache_field(self, name, field):
"""
Do not store fields in _converted if one of its bases is self,
or if it has a common base with self.
This results in a reference cycle that cannot be broken since
ndarrays do not participate in cyclic garbage collection.
"""
base = field
while True:
self_base = self
while True:
if self_base is base:
return
if getattr(self_base, 'base', None) is not None:
self_base = self_base.base
else:
break
if getattr(base, 'base', None) is not None:
base = base.base
else:
break
self._converted[name] = field
def _update_column_attribute_changed(self, column, idx, attr, old_value,
new_value):
"""
Update how the data is formatted depending on changes to column
attributes initiated by the user through the `Column` interface.
Dispatches column attribute change notifications to individual methods
for each attribute ``_update_column_<attr>``
"""
method_name = '_update_column_{0}'.format(attr)
if hasattr(self, method_name):
# Right now this is so we can be lazy and not implement updaters
# for every attribute yet--some we may not need at all, TBD
getattr(self, method_name)(column, idx, old_value, new_value)
def _update_column_name(self, column, idx, old_name, name):
"""Update the dtype field names when a column name is changed."""
dtype = self.dtype
# Updating the names on the dtype should suffice
dtype.names = dtype.names[:idx] + (name,) + dtype.names[idx + 1:]
def _convert_x(self, field, recformat):
"""Convert a raw table column to a bit array as specified by the
FITS X format.
"""
dummy = np.zeros(self.shape + (recformat.repeat,), dtype=np.bool_)
_unwrapx(field, dummy, recformat.repeat)
return dummy
def _convert_p(self, column, field, recformat):
"""Convert a raw table column of FITS P or Q format descriptors
to a VLA column with the array data returned from the heap.
"""
dummy = _VLF([None] * len(self), dtype=recformat.dtype)
raw_data = self._get_raw_data()
if raw_data is None:
raise OSError(
"Could not find heap data for the {!r} variable-length "
"array column.".format(column.name))
for idx in range(len(self)):
offset = field[idx, 1] + self._heapoffset
count = field[idx, 0]
if recformat.dtype == 'a':
dt = np.dtype(recformat.dtype + str(1))
arr_len = count * dt.itemsize
da = raw_data[offset:offset + arr_len].view(dt)
da = np.char.array(da.view(dtype=dt), itemsize=count)
dummy[idx] = decode_ascii(da)
else:
dt = np.dtype(recformat.dtype)
arr_len = count * dt.itemsize
dummy[idx] = raw_data[offset:offset + arr_len].view(dt)
dummy[idx].dtype = dummy[idx].dtype.newbyteorder('>')
# Each array in the field may now require additional
# scaling depending on the other scaling parameters
# TODO: The same scaling parameters apply to every
# array in the column so this is currently very slow; we
# really only need to check once whether any scaling will
# be necessary and skip this step if not
# TODO: Test that this works for X format; I don't think
# that it does--the recformat variable only applies to the P
# format not the X format
dummy[idx] = self._convert_other(column, dummy[idx],
recformat)
return dummy
def _convert_ascii(self, column, field):
"""
Special handling for ASCII table columns to convert columns containing
numeric types to actual numeric arrays from the string representation.
"""
format = column.format
recformat = ASCII2NUMPY[format[0]]
# if the string = TNULL, return ASCIITNULL
nullval = str(column.null).strip().encode('ascii')
if len(nullval) > format.width:
nullval = nullval[:format.width]
# Before using .replace make sure that any trailing bytes in each
# column are filled with spaces, and *not*, say, nulls; this causes
# functions like replace to potentially leave gibberish bytes in the
# array buffer.
dummy = np.char.ljust(field, format.width)
dummy = np.char.replace(dummy, encode_ascii('D'), encode_ascii('E'))
null_fill = encode_ascii(str(ASCIITNULL).rjust(format.width))
# Convert all fields equal to the TNULL value (nullval) to empty fields.
# TODO: These fields really should be conerted to NaN or something else undefined.
# Currently they are converted to empty fields, which are then set to zero.
dummy = np.where(np.char.strip(dummy) == nullval, null_fill, dummy)
# always replace empty fields, see https://github.com/astropy/astropy/pull/5394
if nullval != b'':
dummy = np.where(np.char.strip(dummy) == b'', null_fill, dummy)
try:
dummy = np.array(dummy, dtype=recformat)
except ValueError as exc:
indx = self.names.index(column.name)
raise ValueError(
'{}; the header may be missing the necessary TNULL{} '
'keyword or the table contains invalid data'.format(
exc, indx + 1))
return dummy
def _convert_other(self, column, field, recformat):
"""Perform conversions on any other fixed-width column data types.
This may not perform any conversion at all if it's not necessary, in
which case the original column array is returned.
"""
if isinstance(recformat, _FormatX):
# special handling for the X format
return self._convert_x(field, recformat)
(_str, _bool, _number, _scale, _zero, bscale, bzero, dim) = \
self._get_scale_factors(column)
indx = self.names.index(column.name)
# ASCII table, convert strings to numbers
# TODO:
# For now, check that these are ASCII columns by checking the coldefs
# type; in the future all columns (for binary tables, ASCII tables, or
# otherwise) should "know" what type they are already and how to handle
# converting their data from FITS format to native format and vice
# versa...
if not _str and isinstance(self._coldefs, _AsciiColDefs):
field = self._convert_ascii(column, field)
# Test that the dimensions given in dim are sensible; otherwise
# display a warning and ignore them
if dim:
# See if the dimensions already match, if not, make sure the
# number items will fit in the specified dimensions
if field.ndim > 1:
actual_shape = field.shape[1:]
if _str:
actual_shape = actual_shape + (field.itemsize,)
else:
actual_shape = field.shape[0]
if dim == actual_shape:
# The array already has the correct dimensions, so we
# ignore dim and don't convert
dim = None
else:
nitems = reduce(operator.mul, dim)
if _str:
actual_nitems = field.itemsize
elif len(field.shape) == 1: # No repeat count in TFORMn, equivalent to 1
actual_nitems = 1
else:
actual_nitems = field.shape[1]
if nitems > actual_nitems:
warnings.warn(
'TDIM{} value {:d} does not fit with the size of '
'the array items ({:d}). TDIM{:d} will be ignored.'
.format(indx + 1, self._coldefs[indx].dims,
actual_nitems, indx + 1))
dim = None
# further conversion for both ASCII and binary tables
# For now we've made columns responsible for *knowing* whether their
# data has been scaled, but we make the FITS_rec class responsible for
# actually doing the scaling
# TODO: This also needs to be fixed in the effort to make Columns
# responsible for scaling their arrays to/from FITS native values
if not column.ascii and column.format.p_format:
format_code = column.format.p_format
else:
# TODO: Rather than having this if/else it might be nice if the
# ColumnFormat class had an attribute guaranteed to give the format
# of actual values in a column regardless of whether the true
# format is something like P or Q
format_code = column.format.format
if (_number and (_scale or _zero) and not column._physical_values):
# This is to handle pseudo unsigned ints in table columns
# TODO: For now this only really works correctly for binary tables
# Should it work for ASCII tables as well?
if self._uint:
if bzero == 2**15 and format_code == 'I':
field = np.array(field, dtype=np.uint16)
elif bzero == 2**31 and format_code == 'J':
field = np.array(field, dtype=np.uint32)
elif bzero == 2**63 and format_code == 'K':
field = np.array(field, dtype=np.uint64)
bzero64 = np.uint64(2 ** 63)
else:
field = np.array(field, dtype=np.float64)
else:
field = np.array(field, dtype=np.float64)
if _scale:
np.multiply(field, bscale, field)
if _zero:
if self._uint and format_code == 'K':
# There is a chance of overflow, so be careful
test_overflow = field.copy()
try:
test_overflow += bzero64
except OverflowError:
warnings.warn(
"Overflow detected while applying TZERO{0:d}. "
"Returning unscaled data.".format(indx + 1))
else:
field = test_overflow
else:
field += bzero
# mark the column as scaled
column._physical_values = True
elif _bool and field.dtype != bool:
field = np.equal(field, ord('T'))
elif _str:
if not self._character_as_bytes:
with suppress(UnicodeDecodeError):
field = decode_ascii(field)
if dim:
# Apply the new field item dimensions
nitems = reduce(operator.mul, dim)
if field.ndim > 1:
field = field[:, :nitems]
if _str:
fmt = field.dtype.char
dtype = ('|{}{}'.format(fmt, dim[-1]), dim[:-1])
field.dtype = dtype
else:
field.shape = (field.shape[0],) + dim
return field
def _get_heap_data(self):
"""
Returns a pointer into the table's raw data to its heap (if present).
This is returned as a numpy byte array.
"""
if self._heapsize:
raw_data = self._get_raw_data().view(np.ubyte)
heap_end = self._heapoffset + self._heapsize
return raw_data[self._heapoffset:heap_end]
else:
return np.array([], dtype=np.ubyte)
def _get_raw_data(self):
"""
Returns the base array of self that "raw data array" that is the
array in the format that it was first read from a file before it was
sliced or viewed as a different type in any way.
This is determined by walking through the bases until finding one that
has at least the same number of bytes as self, plus the heapsize. This
may be the immediate .base but is not always. This is used primarily
for variable-length array support which needs to be able to find the
heap (the raw data *may* be larger than nbytes + heapsize if it
contains a gap or padding).
May return ``None`` if no array resembling the "raw data" according to
the stated criteria can be found.
"""
raw_data_bytes = self.nbytes + self._heapsize
base = self
while hasattr(base, 'base') and base.base is not None:
base = base.base
if hasattr(base, 'nbytes') and base.nbytes >= raw_data_bytes:
return base
def _get_scale_factors(self, column):
"""Get all the scaling flags and factors for one column."""
# TODO: Maybe this should be a method/property on Column? Or maybe
# it's not really needed at all...
_str = column.format.format == 'A'
_bool = column.format.format == 'L'
_number = not (_bool or _str)
bscale = column.bscale
bzero = column.bzero
_scale = bscale not in ('', None, 1)
_zero = bzero not in ('', None, 0)
# ensure bscale/bzero are numbers
if not _scale:
bscale = 1
if not _zero:
bzero = 0
# column._dims gives a tuple, rather than column.dim which returns the
# original string format code from the FITS header...
dim = column._dims
return (_str, _bool, _number, _scale, _zero, bscale, bzero, dim)
def _scale_back(self, update_heap_pointers=True):
"""
Update the parent array, using the (latest) scaled array.
If ``update_heap_pointers`` is `False`, this will leave all the heap
pointers in P/Q columns as they are verbatim--it only makes sense to do
this if there is already data on the heap and it can be guaranteed that
that data has not been modified, and there is not new data to add to
the heap. Currently this is only used as an optimization for
CompImageHDU that does its own handling of the heap.
"""
# Running total for the new heap size
heapsize = 0
for indx, name in enumerate(self.dtype.names):
column = self._coldefs[indx]
recformat = column.format.recformat
raw_field = _get_recarray_field(self, indx)
# add the location offset of the heap area for each
# variable length column
if isinstance(recformat, _FormatP):
# Irritatingly, this can return a different dtype than just
# doing np.dtype(recformat.dtype); but this returns the results
# that we want. For example if recformat.dtype is 'a' we want
# an array of characters.
dtype = np.array([], dtype=recformat.dtype).dtype
if update_heap_pointers and name in self._converted:
# The VLA has potentially been updated, so we need to
# update the array descriptors
raw_field[:] = 0 # reset
npts = [len(arr) for arr in self._converted[name]]
raw_field[:len(npts), 0] = npts
raw_field[1:, 1] = (np.add.accumulate(raw_field[:-1, 0]) *
dtype.itemsize)
raw_field[:, 1][:] += heapsize
heapsize += raw_field[:, 0].sum() * dtype.itemsize
# Even if this VLA has not been read or updated, we need to
# include the size of its constituent arrays in the heap size
# total
if isinstance(recformat, _FormatX) and name in self._converted:
_wrapx(self._converted[name], raw_field, recformat.repeat)
continue
_str, _bool, _number, _scale, _zero, bscale, bzero, _ = \
self._get_scale_factors(column)
field = self._converted.get(name, raw_field)
# conversion for both ASCII and binary tables
if _number or _str:
if _number and (_scale or _zero) and column._physical_values:
dummy = field.copy()
if _zero:
dummy -= bzero
if _scale:
dummy /= bscale
# This will set the raw values in the recarray back to
# their non-physical storage values, so the column should
# be mark is not scaled
column._physical_values = False
elif _str or isinstance(self._coldefs, _AsciiColDefs):
dummy = field
else:
continue
# ASCII table, convert numbers to strings
if isinstance(self._coldefs, _AsciiColDefs):
self._scale_back_ascii(indx, dummy, raw_field)
# binary table string column
elif isinstance(raw_field, chararray.chararray):
self._scale_back_strings(indx, dummy, raw_field)
# all other binary table columns
else:
if len(raw_field) and isinstance(raw_field[0],
np.integer):
dummy = np.around(dummy)
if raw_field.shape == dummy.shape:
raw_field[:] = dummy
else:
# Reshaping the data is necessary in cases where the
# TDIMn keyword was used to shape a column's entries
# into arrays
raw_field[:] = dummy.ravel().view(raw_field.dtype)
del dummy
# ASCII table does not have Boolean type
elif _bool and name in self._converted:
choices = (np.array([ord('F')], dtype=np.int8)[0],
np.array([ord('T')], dtype=np.int8)[0])
raw_field[:] = np.choose(field, choices)
# Store the updated heapsize
self._heapsize = heapsize
def _scale_back_strings(self, col_idx, input_field, output_field):
# There are a few possibilities this has to be able to handle properly
# The input_field, which comes from the _converted column is of dtype
# 'Un' so that elements read out of the array are normal str
# objects (i.e. unicode strings)
#
# At the other end the *output_field* may also be of type 'S' or of
# type 'U'. It will *usually* be of type 'S' because when reading
# an existing FITS table the raw data is just ASCII strings, and
# represented in Numpy as an S array. However, when a user creates
# a new table from scratch, they *might* pass in a column containing
# unicode strings (dtype 'U'). Therefore the output_field of the
# raw array is actually a unicode array. But we still want to make
# sure the data is encodable as ASCII. Later when we write out the
# array we use, in the dtype 'U' case, a different write routine
# that writes row by row and encodes any 'U' columns to ASCII.
# If the output_field is non-ASCII we will worry about ASCII encoding
# later when writing; otherwise we can do it right here
if input_field.dtype.kind == 'U' and output_field.dtype.kind == 'S':
try:
_ascii_encode(input_field, out=output_field)
except _UnicodeArrayEncodeError as exc:
raise ValueError(
"Could not save column '{0}': Contains characters that "
"cannot be encoded as ASCII as required by FITS, starting "
"at the index {1!r} of the column, and the index {2} of "
"the string at that location.".format(
self._coldefs[col_idx].name,
exc.index[0] if len(exc.index) == 1 else exc.index,
exc.start))
else:
# Otherwise go ahead and do a direct copy into--if both are type
# 'U' we'll handle encoding later
input_field = input_field.flatten().view(output_field.dtype)
output_field.flat[:] = input_field
# Ensure that blanks at the end of each string are
# converted to nulls instead of spaces, see Trac #15
# and #111
_rstrip_inplace(output_field)
def _scale_back_ascii(self, col_idx, input_field, output_field):
"""
Convert internal array values back to ASCII table representation.
The ``input_field`` is the internal representation of the values, and
the ``output_field`` is the character array representing the ASCII
output that will be written.
"""
starts = self._coldefs.starts[:]
spans = self._coldefs.spans
format = self._coldefs[col_idx].format
# The the index of the "end" column of the record, beyond
# which we can't write
end = super().field(-1).itemsize
starts.append(end + starts[-1])
if col_idx > 0:
lead = starts[col_idx] - starts[col_idx - 1] - spans[col_idx - 1]
else:
lead = 0
if lead < 0:
warnings.warn('Column {!r} starting point overlaps the previous '
'column.'.format(col_idx + 1))
trail = starts[col_idx + 1] - starts[col_idx] - spans[col_idx]
if trail < 0:
warnings.warn('Column {!r} ending point overlaps the next '
'column.'.format(col_idx + 1))
# TODO: It would be nice if these string column formatting
# details were left to a specialized class, as is the case
# with FormatX and FormatP
if 'A' in format:
_pc = '{:'
else:
_pc = '{:>'
fmt = ''.join([_pc, format[1:], ASCII2STR[format[0]], '}',
(' ' * trail)])
# Even if the format precision is 0, we should output a decimal point
# as long as there is space to do so--not including a decimal point in
# a float value is discouraged by the FITS Standard
trailing_decimal = (format.precision == 0 and
format.format in ('F', 'E', 'D'))
# not using numarray.strings's num2char because the
# result is not allowed to expand (as C/Python does).
for jdx, value in enumerate(input_field):
value = fmt.format(value)
if len(value) > starts[col_idx + 1] - starts[col_idx]:
raise ValueError(
"Value {!r} does not fit into the output's itemsize of "
"{}.".format(value, spans[col_idx]))
if trailing_decimal and value[0] == ' ':
# We have some extra space in the field for the trailing
# decimal point
value = value[1:] + '.'
output_field[jdx] = value
# Replace exponent separator in floating point numbers
if 'D' in format:
output_field[:] = output_field.replace(b'E', b'D')
def _get_recarray_field(array, key):
"""
Compatibility function for using the recarray base class's field method.
This incorporates the legacy functionality of returning string arrays as
Numeric-style chararray objects.
"""
# Numpy >= 1.10.dev recarray no longer returns chararrays for strings
# This is currently needed for backwards-compatibility and for
# automatic truncation of trailing whitespace
field = np.recarray.field(array, key)
if (field.dtype.char in ('S', 'U') and
not isinstance(field, chararray.chararray)):
field = field.view(chararray.chararray)
return field
class _UnicodeArrayEncodeError(UnicodeEncodeError):
def __init__(self, encoding, object_, start, end, reason, index):
super().__init__(encoding, object_, start, end, reason)
self.index = index
def _ascii_encode(inarray, out=None):
"""
Takes a unicode array and fills the output string array with the ASCII
encodings (if possible) of the elements of the input array. The two arrays
must be the same size (though not necessarily the same shape).
This is like an inplace version of `np.char.encode` though simpler since
it's only limited to ASCII, and hence the size of each character is
guaranteed to be 1 byte.
If any strings are non-ASCII an UnicodeArrayEncodeError is raised--this is
just a `UnicodeEncodeError` with an additional attribute for the index of
the item that couldn't be encoded.
"""
out_dtype = np.dtype(('S{0}'.format(inarray.dtype.itemsize // 4),
inarray.dtype.shape))
if out is not None:
out = out.view(out_dtype)
op_dtypes = [inarray.dtype, out_dtype]
op_flags = [['readonly'], ['writeonly', 'allocate']]
it = np.nditer([inarray, out], op_dtypes=op_dtypes,
op_flags=op_flags, flags=['zerosize_ok'])
try:
for initem, outitem in it:
outitem[...] = initem.item().encode('ascii')
except UnicodeEncodeError as exc:
index = np.unravel_index(it.iterindex, inarray.shape)
raise _UnicodeArrayEncodeError(*(exc.args + (index,)))
return it.operands[1]
def _has_unicode_fields(array):
"""
Returns True if any fields in a structured array have Unicode dtype.
"""
dtypes = (d[0] for d in array.dtype.fields.values())
return any(d.kind == 'U' for d in dtypes)
|
ab2289acbc429bbd99de6472642cff4e4ad57f6e0ec7ed87cd92551373012a11 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import re
import warnings
from collections import defaultdict, OrderedDict
import numpy as np
from . import Header, Card
from astropy import units as u
from astropy.coordinates import EarthLocation
from astropy.table import Column
from astropy.time import Time, TimeDelta
from astropy.time.core import BARYCENTRIC_SCALES
from astropy.time.formats import FITS_DEPRECATED_SCALES
from astropy.utils.exceptions import AstropyUserWarning
# The following is based on the FITS WCS Paper IV, "Representations of time
# coordinates in FITS".
# http://adsabs.harvard.edu/abs/2015A%26A...574A..36R
# FITS WCS standard specified "4-3" form for non-linear coordinate types
TCTYP_RE_TYPE = re.compile(r'(?P<type>[A-Z]+)[-]+')
TCTYP_RE_ALGO = re.compile(r'(?P<algo>[A-Z]+)\s*')
# FITS Time standard specified time units
FITS_TIME_UNIT = ['s', 'd', 'a', 'cy', 'min', 'h', 'yr', 'ta', 'Ba']
# Global time reference coordinate keywords
TIME_KEYWORDS = ('TIMESYS', 'MJDREF', 'JDREF', 'DATEREF',
'TREFPOS', 'TREFDIR', 'TIMEUNIT', 'TIMEOFFS',
'OBSGEO-X', 'OBSGEO-Y', 'OBSGEO-Z',
'OBSGEO-L', 'OBSGEO-B', 'OBSGEO-H', 'DATE',
'DATE-OBS', 'DATE-AVG', 'DATE-BEG', 'DATE-END',
'MJD-OBS', 'MJD-AVG', 'MJD-BEG', 'MJD-END')
# Column-specific time override keywords
COLUMN_TIME_KEYWORDS = ('TCTYP', 'TCUNI', 'TRPOS')
# Column-specific keywords regex
COLUMN_TIME_KEYWORD_REGEXP = '({0})[0-9]+'.format(
'|'.join(COLUMN_TIME_KEYWORDS))
def is_time_column_keyword(keyword):
"""
Check if the FITS header keyword is a time column-specific keyword.
Parameters
----------
keyword : str
FITS keyword.
"""
return re.match(COLUMN_TIME_KEYWORD_REGEXP, keyword) is not None
# Set astropy time global information
GLOBAL_TIME_INFO = {'TIMESYS': ('UTC', 'Default time scale'),
'JDREF': (0.0, 'Time columns are jd = jd1 + jd2'),
'TREFPOS': ('TOPOCENTER', 'Time reference position')}
def _verify_global_info(global_info):
"""
Given the global time reference frame information, verify that
each global time coordinate attribute will be given a valid value.
Parameters
----------
global_info : dict
Global time reference frame information.
"""
# Translate FITS deprecated scale into astropy scale, or else just convert
# to lower case for further checks.
global_info['scale'] = FITS_DEPRECATED_SCALES.get(global_info['TIMESYS'],
global_info['TIMESYS'].lower())
# Verify global time scale
if global_info['scale'] not in Time.SCALES:
# 'GPS' and 'LOCAL' are FITS recognized time scale values
# but are not supported by astropy.
if global_info['scale'] == 'gps':
warnings.warn(
'Global time scale (TIMESYS) has a FITS recognized time scale '
'value "GPS". In Astropy, "GPS" is a time from epoch format '
'which runs synchronously with TAI; GPS is approximately 19 s '
'ahead of TAI. Hence, this format will be used.', AstropyUserWarning)
# Assume that the values are in GPS format
global_info['scale'] = 'tai'
global_info['format'] = 'gps'
if global_info['scale'] == 'local':
warnings.warn(
'Global time scale (TIMESYS) has a FITS recognized time scale '
'value "LOCAL". However, the standard states that "LOCAL" should be '
'tied to one of the existing scales because it is intrinsically '
'unreliable and/or ill-defined. Astropy will thus use the default '
'global time scale "UTC" instead of "LOCAL".', AstropyUserWarning)
# Default scale 'UTC'
global_info['scale'] = 'utc'
global_info['format'] = None
else:
raise AssertionError(
'Global time scale (TIMESYS) should have a FITS recognized '
'time scale value (got {!r}). The FITS standard states that '
'the use of local time scales should be restricted to alternate '
'coordinates.'.format(global_info['TIMESYS']))
else:
# Scale is already set
global_info['format'] = None
# Check if geocentric global location is specified
obs_geo = [global_info[attr] for attr in ('OBSGEO-X', 'OBSGEO-Y', 'OBSGEO-Z')
if attr in global_info]
# Location full specification is (X, Y, Z)
if len(obs_geo) == 3:
global_info['location'] = EarthLocation.from_geocentric(*obs_geo, unit=u.m)
else:
# Check if geodetic global location is specified (since geocentric failed)
# First warn the user if geocentric location is partially specified
if obs_geo:
warnings.warn(
'The geocentric observatory location {} is not completely '
'specified (X, Y, Z) and will be ignored.'.format(obs_geo),
AstropyUserWarning)
# Check geodetic location
obs_geo = [global_info[attr] for attr in ('OBSGEO-L', 'OBSGEO-B', 'OBSGEO-H')
if attr in global_info]
if len(obs_geo) == 3:
global_info['location'] = EarthLocation.from_geodetic(*obs_geo)
else:
# Since both geocentric and geodetic locations are not specified,
# location will be None.
# Warn the user if geodetic location is partially specified
if obs_geo:
warnings.warn(
'The geodetic observatory location {} is not completely '
'specified (lon, lat, alt) and will be ignored.'.format(obs_geo),
AstropyUserWarning)
global_info['location'] = None
# Get global time reference
# Keywords are listed in order of precedence, as stated by the standard
for key, format_ in (('MJDREF', 'mjd'), ('JDREF', 'jd'), ('DATEREF', 'fits')):
if key in global_info:
global_info['ref_time'] = {'val': global_info[key], 'format': format_}
break
else:
# If none of the three keywords is present, MJDREF = 0.0 must be assumed
global_info['ref_time'] = {'val': 0, 'format': 'mjd'}
def _verify_column_info(column_info, global_info):
"""
Given the column-specific time reference frame information, verify that
each column-specific time coordinate attribute has a valid value.
Return True if the coordinate column is time, or else return False.
Parameters
----------
global_info : dict
Global time reference frame information.
column_info : dict
Column-specific time reference frame override information.
"""
scale = column_info.get('TCTYP', None)
unit = column_info.get('TCUNI', None)
location = column_info.get('TRPOS', None)
if scale is not None:
# Non-linear coordinate types have "4-3" form and are not time coordinates
if TCTYP_RE_TYPE.match(scale[:5]) and TCTYP_RE_ALGO.match(scale[5:]):
return False
elif scale.lower() in Time.SCALES:
column_info['scale'] = scale.lower()
column_info['format'] = None
elif scale in FITS_DEPRECATED_SCALES.keys():
column_info['scale'] = FITS_DEPRECATED_SCALES[scale]
column_info['format'] = None
# TCTYPn (scale) = 'TIME' indicates that the column scale is
# controlled by the global scale.
elif scale == 'TIME':
column_info['scale'] = global_info['scale']
column_info['format'] = global_info['format']
elif scale == 'GPS':
warnings.warn(
'Table column "{}" has a FITS recognized time scale value "GPS". '
'In Astropy, "GPS" is a time from epoch format which runs '
'synchronously with TAI; GPS runs ahead of TAI approximately '
'by 19 s. Hence, this format will be used.'.format(column_info),
AstropyUserWarning)
column_info['scale'] = 'tai'
column_info['format'] = 'gps'
elif scale == 'LOCAL':
warnings.warn(
'Table column "{}" has a FITS recognized time scale value "LOCAL". '
'However, the standard states that "LOCAL" should be tied to one '
'of the existing scales because it is intrinsically unreliable '
'and/or ill-defined. Astropy will thus use the global time scale '
'(TIMESYS) as the default.'. format(column_info),
AstropyUserWarning)
column_info['scale'] = global_info['scale']
column_info['format'] = global_info['format']
else:
# Coordinate type is either an unrecognized local time scale
# or a linear coordinate type
return False
# If TCUNIn is a time unit or TRPOSn is specified, the column is a time
# coordinate. This has to be tested since TCTYP (scale) is not specified.
elif (unit is not None and unit in FITS_TIME_UNIT) or location is not None:
column_info['scale'] = global_info['scale']
column_info['format'] = global_info['format']
# None of the conditions for time coordinate columns is satisfied
else:
return False
# Check if column-specific reference position TRPOSn is specified
if location is not None:
# Observatory position (location) needs to be specified only
# for 'TOPOCENTER'.
if location == 'TOPOCENTER':
column_info['location'] = global_info['location']
if column_info['location'] is None:
warnings.warn(
'Time column reference position "TRPOSn" value is "TOPOCENTER". '
'However, the observatory position is not properly specified. '
'The FITS standard does not support this and hence reference '
'position will be ignored.', AstropyUserWarning)
else:
column_info['location'] = None
# Since TRPOSn is not specified, global reference position is
# considered.
elif global_info['TREFPOS'] == 'TOPOCENTER':
column_info['location'] = global_info['location']
if column_info['location'] is None:
warnings.warn(
'Time column reference position "TRPOSn" is not specified. The '
'default value for it is "TOPOCENTER", but due to unspecified '
'observatory position, reference position will be ignored.',
AstropyUserWarning)
else:
column_info['location'] = None
# Get reference time
column_info['ref_time'] = global_info['ref_time']
return True
def _get_info_if_time_column(col, global_info):
"""
Check if a column without corresponding time column keywords in the
FITS header represents time or not. If yes, return the time column
information needed for its conversion to Time.
This is only applicable to the special-case where a column has the
name 'TIME' and a time unit.
"""
# Column with TTYPEn = 'TIME' and lacking any TC*n or time
# specific keywords will be controlled by the global keywords.
if col.info.name.upper() == 'TIME' and col.info.unit in FITS_TIME_UNIT:
column_info = {'scale': global_info['scale'],
'format': global_info['format'],
'ref_time': global_info['ref_time'],
'location': None}
if global_info['TREFPOS'] == 'TOPOCENTER':
column_info['location'] = global_info['location']
if column_info['location'] is None:
warnings.warn(
'Time column "{}" reference position will be ignored '
'due to unspecified observatory position.'.format(col.info.name),
AstropyUserWarning)
return column_info
return None
def _convert_global_time(table, global_info):
"""
Convert the table metadata for time informational keywords
to astropy Time.
Parameters
----------
table : `~astropy.table.Table`
The table whose time metadata is to be converted.
global_info : dict
Global time reference frame information.
"""
# Read in Global Informational keywords as Time
for key, value in global_info.items():
# FITS uses a subset of ISO-8601 for DATE-xxx
if key.startswith('DATE'):
if key not in table.meta:
scale = 'utc' if key == 'DATE' else global_info['scale']
try:
precision = len(value.split('.')[-1]) if '.' in value else 0
value = Time(value, format='fits', scale=scale,
precision=precision)
except ValueError:
pass
table.meta[key] = value
# MJD-xxx in MJD according to TIMESYS
elif key.startswith('MJD-'):
if key not in table.meta:
try:
value = Time(value, format='mjd',
scale=global_info['scale'])
except ValueError:
pass
table.meta[key] = value
def _convert_time_column(col, column_info):
"""
Convert time columns to astropy Time columns.
Parameters
----------
col : `~astropy.table.Column`
The time coordinate column to be converted to Time.
column_info : dict
Column-specific time reference frame override information.
"""
# The code might fail while attempting to read FITS files not written by astropy.
try:
# ISO-8601 is the only string representation of time in FITS
if col.info.dtype.kind in ['S', 'U']:
# [+/-C]CCYY-MM-DD[Thh:mm:ss[.s...]] where the number of characters
# from index 20 to the end of string represents the precision
precision = max(int(col.info.dtype.str[2:]) - 20, 0)
return Time(col, format='fits', scale=column_info['scale'],
precision=precision,
location=column_info['location'])
if column_info['format'] == 'gps':
return Time(col, format='gps', location=column_info['location'])
# If reference value is 0 for JD or MJD, the column values can be
# directly converted to Time, as they are absolute (relative
# to a globally accepted zero point).
if (column_info['ref_time']['val'] == 0 and
column_info['ref_time']['format'] in ['jd', 'mjd']):
# (jd1, jd2) where jd = jd1 + jd2
if col.shape[-1] == 2 and col.ndim > 1:
return Time(col[..., 0], col[..., 1], scale=column_info['scale'],
format=column_info['ref_time']['format'],
location=column_info['location'])
else:
return Time(col, scale=column_info['scale'],
format=column_info['ref_time']['format'],
location=column_info['location'])
# Reference time
ref_time = Time(column_info['ref_time']['val'], scale=column_info['scale'],
format=column_info['ref_time']['format'],
location=column_info['location'])
# Elapsed time since reference time
if col.shape[-1] == 2 and col.ndim > 1:
delta_time = TimeDelta(col[..., 0], col[..., 1])
else:
delta_time = TimeDelta(col)
return ref_time + delta_time
except Exception as err:
warnings.warn(
'The exception "{}" was encountered while trying to convert the time '
'column "{}" to Astropy Time.'.format(err, col.info.name),
AstropyUserWarning)
return col
def fits_to_time(hdr, table):
"""
Read FITS binary table time columns as `~astropy.time.Time`.
This method reads the metadata associated with time coordinates, as
stored in a FITS binary table header, converts time columns into
`~astropy.time.Time` columns and reads global reference times as
`~astropy.time.Time` instances.
Parameters
----------
hdr : `~astropy.io.fits.header.Header`
FITS Header
table : `~astropy.table.Table`
The table whose time columns are to be read as Time
Returns
-------
hdr : `~astropy.io.fits.header.Header`
Modified FITS Header (time metadata removed)
"""
# Set defaults for global time scale, reference, etc.
global_info = {'TIMESYS': 'UTC',
'TREFPOS': 'TOPOCENTER'}
# Set default dictionary for time columns
time_columns = defaultdict(OrderedDict)
# Make a "copy" (not just a view) of the input header, since it
# may get modified. the data is still a "view" (for now)
hcopy = hdr.copy(strip=True)
# Scan the header for global and column-specific time keywords
for key, value, comment in hdr.cards:
if key in TIME_KEYWORDS:
global_info[key] = value
hcopy.remove(key)
elif is_time_column_keyword(key):
base, idx = re.match(r'([A-Z]+)([0-9]+)', key).groups()
time_columns[int(idx)][base] = value
hcopy.remove(key)
elif (value in ('OBSGEO-X', 'OBSGEO-Y', 'OBSGEO-Z') and
re.match('TTYPE[0-9]+', key)):
global_info[value] = table[value]
# Verify and get the global time reference frame information
_verify_global_info(global_info)
_convert_global_time(table, global_info)
# Columns with column-specific time (coordinate) keywords
if time_columns:
for idx, column_info in time_columns.items():
# Check if the column is time coordinate (not spatial)
if _verify_column_info(column_info, global_info):
colname = table.colnames[idx - 1]
# Convert to Time
table[colname] = _convert_time_column(table[colname],
column_info)
# Check for special-cases of time coordinate columns
for idx, colname in enumerate(table.colnames):
if (idx + 1) not in time_columns:
column_info = _get_info_if_time_column(table[colname], global_info)
if column_info:
table[colname] = _convert_time_column(table[colname], column_info)
return hcopy
def time_to_fits(table):
"""
Replace Time columns in a Table with non-mixin columns containing
each element as a vector of two doubles (jd1, jd2) and return a FITS
header with appropriate time coordinate keywords.
jd = jd1 + jd2 represents time in the Julian Date format with
high-precision.
Parameters
----------
table : `~astropy.table.Table`
The table whose Time columns are to be replaced.
Returns
-------
table : `~astropy.table.Table`
The table with replaced Time columns
hdr : `~astropy.io.fits.header.Header`
Header containing global time reference frame FITS keywords
"""
# Shallow copy of the input table
newtable = table.copy(copy_data=False)
# Global time coordinate frame keywords
hdr = Header([Card(keyword=key, value=val[0], comment=val[1])
for key, val in GLOBAL_TIME_INFO.items()])
# Store coordinate column-specific metadata
newtable.meta['__coordinate_columns__'] = defaultdict(OrderedDict)
coord_meta = newtable.meta['__coordinate_columns__']
time_cols = table.columns.isinstance(Time)
# Geocentric location
location = None
for col in time_cols:
# By default, Time objects are written in full precision, i.e. we store both
# jd1 and jd2 (serialize_method['fits'] = 'jd1_jd2'). Formatted values for
# Time can be stored if the user explicitly chooses to do so.
if col.info.serialize_method['fits'] == 'formatted_value':
newtable.replace_column(col.info.name, Column(col.value))
continue
# The following is necessary to deal with multi-dimensional ``Time`` objects
# (i.e. where Time.shape is non-trivial).
jd12 = np.array([col.jd1, col.jd2])
# Roll the 0th (innermost) axis backwards, until it lies in the last position
# (jd12.ndim)
jd12 = np.rollaxis(jd12, 0, jd12.ndim)
newtable.replace_column(col.info.name, Column(jd12, unit='d'))
# Get column position(index)
n = table.colnames.index(col.info.name) + 1
# Time column-specific override keywords
coord_meta[col.info.name]['coord_type'] = col.scale.upper()
coord_meta[col.info.name]['coord_unit'] = 'd'
# Time column reference position
if getattr(col, 'location') is None:
if location is not None:
warnings.warn(
'Time Column "{}" has no specified location, but global Time '
'Position is present, which will be the default for this column '
'in FITS specification.'.format(col.info.name),
AstropyUserWarning)
else:
coord_meta[col.info.name]['time_ref_pos'] = 'TOPOCENTER'
# Compatibility of Time Scales and Reference Positions
if col.scale in BARYCENTRIC_SCALES:
warnings.warn(
'Earth Location "TOPOCENTER" for Time Column "{}" is incompatabile '
'with scale "{}".'.format(col.info.name, col.scale.upper()),
AstropyUserWarning)
if location is None:
# Set global geocentric location
location = col.location
if location.size > 1:
for dim in ('x', 'y', 'z'):
newtable.add_column(Column(getattr(location, dim).to_value(u.m)),
name='OBSGEO-{}'.format(dim.upper()))
else:
hdr.extend([Card(keyword='OBSGEO-{}'.format(dim.upper()),
value=getattr(location, dim).to_value(u.m))
for dim in ('x', 'y', 'z')])
elif location != col.location:
raise ValueError('Multiple Time Columns with different geocentric '
'observatory locations ({}, {}) encountered.'
'This is not supported by the FITS standard.'
.format(location, col.location))
return newtable, hdr
|
e27e499ce980e1131b4831d0071095781384a3a28b15a8758c56c192d9d01c95 | # Licensed under a 3-clause BSD style license - see PYFITS.rst
"""
Convenience functions
=====================
The functions in this module provide shortcuts for some of the most basic
operations on FITS files, such as reading and updating the header. They are
included directly in the 'astropy.io.fits' namespace so that they can be used
like::
astropy.io.fits.getheader(...)
These functions are primarily for convenience when working with FITS files in
the command-line interpreter. If performing several operations on the same
file, such as in a script, it is better to *not* use these functions, as each
one must open and re-parse the file. In such cases it is better to use
:func:`astropy.io.fits.open` and work directly with the
:class:`astropy.io.fits.HDUList` object and underlying HDU objects.
Several of the convenience functions, such as `getheader` and `getdata` support
special arguments for selecting which extension HDU to use when working with a
multi-extension FITS file. There are a few supported argument formats for
selecting the extension. See the documentation for `getdata` for an
explanation of all the different formats.
.. warning::
All arguments to convenience functions other than the filename that are
*not* for selecting the extension HDU should be passed in as keyword
arguments. This is to avoid ambiguity and conflicts with the
extension arguments. For example, to set NAXIS=1 on the Primary HDU:
Wrong::
astropy.io.fits.setval('myimage.fits', 'NAXIS', 1)
The above example will try to set the NAXIS value on the first extension
HDU to blank. That is, the argument '1' is assumed to specify an extension
HDU.
Right::
astropy.io.fits.setval('myimage.fits', 'NAXIS', value=1)
This will set the NAXIS keyword to 1 on the primary HDU (the default). To
specify the first extension HDU use::
astropy.io.fits.setval('myimage.fits', 'NAXIS', value=1, ext=1)
This complexity arises out of the attempt to simultaneously support
multiple argument formats that were used in past versions of PyFITS.
Unfortunately, it is not possible to support all formats without
introducing some ambiguity. A future Astropy release may standardize
around a single format and officially deprecate the other formats.
"""
import operator
import os
import warnings
import numpy as np
from .diff import FITSDiff, HDUDiff
from .file import FILE_MODES, _File
from .hdu.base import _BaseHDU, _ValidHDU
from .hdu.hdulist import fitsopen, HDUList
from .hdu.image import PrimaryHDU, ImageHDU
from .hdu.table import BinTableHDU
from .header import Header
from .util import fileobj_closed, fileobj_name, fileobj_mode, _is_int
from astropy.utils.exceptions import AstropyUserWarning
from astropy.utils.decorators import deprecated_renamed_argument
__all__ = ['getheader', 'getdata', 'getval', 'setval', 'delval', 'writeto',
'append', 'update', 'info', 'tabledump', 'tableload',
'table_to_hdu', 'printdiff']
def getheader(filename, *args, **kwargs):
"""
Get the header from an extension of a FITS file.
Parameters
----------
filename : file path, file object, or file like object
File to get header from. If an opened file object, its mode
must be one of the following rb, rb+, or ab+).
ext, extname, extver
The rest of the arguments are for extension specification. See the
`getdata` documentation for explanations/examples.
kwargs
Any additional keyword arguments to be passed to
`astropy.io.fits.open`.
Returns
-------
header : `Header` object
"""
mode, closed = _get_file_mode(filename)
hdulist, extidx = _getext(filename, mode, *args, **kwargs)
try:
hdu = hdulist[extidx]
header = hdu.header
finally:
hdulist.close(closed=closed)
return header
def getdata(filename, *args, header=None, lower=None, upper=None, view=None,
**kwargs):
"""
Get the data from an extension of a FITS file (and optionally the
header).
Parameters
----------
filename : file path, file object, or file like object
File to get data from. If opened, mode must be one of the
following rb, rb+, or ab+.
ext
The rest of the arguments are for extension specification.
They are flexible and are best illustrated by examples.
No extra arguments implies the primary header::
getdata('in.fits')
By extension number::
getdata('in.fits', 0) # the primary header
getdata('in.fits', 2) # the second extension
getdata('in.fits', ext=2) # the second extension
By name, i.e., ``EXTNAME`` value (if unique)::
getdata('in.fits', 'sci')
getdata('in.fits', extname='sci') # equivalent
Note ``EXTNAME`` values are not case sensitive
By combination of ``EXTNAME`` and EXTVER`` as separate
arguments or as a tuple::
getdata('in.fits', 'sci', 2) # EXTNAME='SCI' & EXTVER=2
getdata('in.fits', extname='sci', extver=2) # equivalent
getdata('in.fits', ('sci', 2)) # equivalent
Ambiguous or conflicting specifications will raise an exception::
getdata('in.fits', ext=('sci',1), extname='err', extver=2)
header : bool, optional
If `True`, return the data and the header of the specified HDU as a
tuple.
lower, upper : bool, optional
If ``lower`` or ``upper`` are `True`, the field names in the
returned data object will be converted to lower or upper case,
respectively.
view : ndarray, optional
When given, the data will be returned wrapped in the given ndarray
subclass by calling::
data.view(view)
kwargs
Any additional keyword arguments to be passed to
`astropy.io.fits.open`.
Returns
-------
array : array, record array or groups data object
Type depends on the type of the extension being referenced.
If the optional keyword ``header`` is set to `True`, this
function will return a (``data``, ``header``) tuple.
"""
mode, closed = _get_file_mode(filename)
hdulist, extidx = _getext(filename, mode, *args, **kwargs)
try:
hdu = hdulist[extidx]
data = hdu.data
if data is None and extidx == 0:
try:
hdu = hdulist[1]
data = hdu.data
except IndexError:
raise IndexError('No data in this HDU.')
if data is None:
raise IndexError('No data in this HDU.')
if header:
hdr = hdu.header
finally:
hdulist.close(closed=closed)
# Change case of names if requested
trans = None
if lower:
trans = operator.methodcaller('lower')
elif upper:
trans = operator.methodcaller('upper')
if trans:
if data.dtype.names is None:
# this data does not have fields
return
if data.dtype.descr[0][0] == '':
# this data does not have fields
return
data.dtype.names = [trans(n) for n in data.dtype.names]
# allow different views into the underlying ndarray. Keep the original
# view just in case there is a problem
if isinstance(view, type) and issubclass(view, np.ndarray):
data = data.view(view)
if header:
return data, hdr
else:
return data
def getval(filename, keyword, *args, **kwargs):
"""
Get a keyword's value from a header in a FITS file.
Parameters
----------
filename : file path, file object, or file like object
Name of the FITS file, or file object (if opened, mode must be
one of the following rb, rb+, or ab+).
keyword : str
Keyword name
ext, extname, extver
The rest of the arguments are for extension specification.
See `getdata` for explanations/examples.
kwargs
Any additional keyword arguments to be passed to
`astropy.io.fits.open`.
*Note:* This function automatically specifies ``do_not_scale_image_data
= True`` when opening the file so that values can be retrieved from the
unmodified header.
Returns
-------
keyword value : str, int, or float
"""
if 'do_not_scale_image_data' not in kwargs:
kwargs['do_not_scale_image_data'] = True
hdr = getheader(filename, *args, **kwargs)
return hdr[keyword]
def setval(filename, keyword, *args, value=None, comment=None, before=None,
after=None, savecomment=False, **kwargs):
"""
Set a keyword's value from a header in a FITS file.
If the keyword already exists, it's value/comment will be updated.
If it does not exist, a new card will be created and it will be
placed before or after the specified location. If no ``before`` or
``after`` is specified, it will be appended at the end.
When updating more than one keyword in a file, this convenience
function is a much less efficient approach compared with opening
the file for update, modifying the header, and closing the file.
Parameters
----------
filename : file path, file object, or file like object
Name of the FITS file, or file object If opened, mode must be update
(rb+). An opened file object or `~gzip.GzipFile` object will be closed
upon return.
keyword : str
Keyword name
value : str, int, float, optional
Keyword value (default: `None`, meaning don't modify)
comment : str, optional
Keyword comment, (default: `None`, meaning don't modify)
before : str, int, optional
Name of the keyword, or index of the card before which the new card
will be placed. The argument ``before`` takes precedence over
``after`` if both are specified (default: `None`).
after : str, int, optional
Name of the keyword, or index of the card after which the new card will
be placed. (default: `None`).
savecomment : bool, optional
When `True`, preserve the current comment for an existing keyword. The
argument ``savecomment`` takes precedence over ``comment`` if both
specified. If ``comment`` is not specified then the current comment
will automatically be preserved (default: `False`).
ext, extname, extver
The rest of the arguments are for extension specification.
See `getdata` for explanations/examples.
kwargs
Any additional keyword arguments to be passed to
`astropy.io.fits.open`.
*Note:* This function automatically specifies ``do_not_scale_image_data
= True`` when opening the file so that values can be retrieved from the
unmodified header.
"""
if 'do_not_scale_image_data' not in kwargs:
kwargs['do_not_scale_image_data'] = True
closed = fileobj_closed(filename)
hdulist, extidx = _getext(filename, 'update', *args, **kwargs)
try:
if keyword in hdulist[extidx].header and savecomment:
comment = None
hdulist[extidx].header.set(keyword, value, comment, before, after)
finally:
hdulist.close(closed=closed)
def delval(filename, keyword, *args, **kwargs):
"""
Delete all instances of keyword from a header in a FITS file.
Parameters
----------
filename : file path, file object, or file like object
Name of the FITS file, or file object If opened, mode must be update
(rb+). An opened file object or `~gzip.GzipFile` object will be closed
upon return.
keyword : str, int
Keyword name or index
ext, extname, extver
The rest of the arguments are for extension specification.
See `getdata` for explanations/examples.
kwargs
Any additional keyword arguments to be passed to
`astropy.io.fits.open`.
*Note:* This function automatically specifies ``do_not_scale_image_data
= True`` when opening the file so that values can be retrieved from the
unmodified header.
"""
if 'do_not_scale_image_data' not in kwargs:
kwargs['do_not_scale_image_data'] = True
closed = fileobj_closed(filename)
hdulist, extidx = _getext(filename, 'update', *args, **kwargs)
try:
del hdulist[extidx].header[keyword]
finally:
hdulist.close(closed=closed)
@deprecated_renamed_argument('clobber', 'overwrite', '2.0')
def writeto(filename, data, header=None, output_verify='exception',
overwrite=False, checksum=False):
"""
Create a new FITS file using the supplied data/header.
Parameters
----------
filename : file path, file object, or file like object
File to write to. If opened, must be opened in a writeable binary
mode such as 'wb' or 'ab+'.
data : array, record array, or groups data object
data to write to the new file
header : `Header` object, optional
the header associated with ``data``. If `None`, a header
of the appropriate type is created for the supplied data. This
argument is optional.
output_verify : str
Output verification option. Must be one of ``"fix"``, ``"silentfix"``,
``"ignore"``, ``"warn"``, or ``"exception"``. May also be any
combination of ``"fix"`` or ``"silentfix"`` with ``"+ignore"``,
``+warn``, or ``+exception" (e.g. ``"fix+warn"``). See :ref:`verify`
for more info.
overwrite : bool, optional
If ``True``, overwrite the output file if it exists. Raises an
``OSError`` if ``False`` and the output file exists. Default is
``False``.
.. versionchanged:: 1.3
``overwrite`` replaces the deprecated ``clobber`` argument.
checksum : bool, optional
If `True`, adds both ``DATASUM`` and ``CHECKSUM`` cards to the
headers of all HDU's written to the file.
"""
hdu = _makehdu(data, header)
if hdu.is_image and not isinstance(hdu, PrimaryHDU):
hdu = PrimaryHDU(data, header=header)
hdu.writeto(filename, overwrite=overwrite, output_verify=output_verify,
checksum=checksum)
def table_to_hdu(table, character_as_bytes=False):
"""
Convert an `~astropy.table.Table` object to a FITS
`~astropy.io.fits.BinTableHDU`.
Parameters
----------
table : astropy.table.Table
The table to convert.
character_as_bytes : bool
Whether to return bytes for string columns when accessed from the HDU.
By default this is `False` and (unicode) strings are returned, but for
large tables this may use up a lot of memory.
Returns
-------
table_hdu : `~astropy.io.fits.BinTableHDU`
The FITS binary table HDU.
"""
# Avoid circular imports
from .connect import is_column_keyword, REMOVE_KEYWORDS
from .column import python_to_tdisp
# Header to store Time related metadata
hdr = None
# Not all tables with mixin columns are supported
if table.has_mixin_columns:
# Import is done here, in order to avoid it at build time as erfa is not
# yet available then.
from astropy.table.column import BaseColumn
from astropy.time import Time
from astropy.units import Quantity
from .fitstime import time_to_fits
# Only those columns which are instances of BaseColumn, Quantity or Time can
# be written
unsupported_cols = table.columns.not_isinstance((BaseColumn, Quantity, Time))
if unsupported_cols:
unsupported_names = [col.info.name for col in unsupported_cols]
raise ValueError('cannot write table with mixin column(s) {0}'
.format(unsupported_names))
time_cols = table.columns.isinstance(Time)
if time_cols:
table, hdr = time_to_fits(table)
# Create a new HDU object
if table.masked:
# float column's default mask value needs to be Nan
for column in table.columns.values():
fill_value = column.get_fill_value()
if column.dtype.kind == 'f' and np.allclose(fill_value, 1e20):
column.set_fill_value(np.nan)
# TODO: it might be better to construct the FITS table directly from
# the Table columns, rather than go via a structured array.
table_hdu = BinTableHDU.from_columns(np.array(table.filled()), header=hdr, character_as_bytes=True)
for col in table_hdu.columns:
# Binary FITS tables support TNULL *only* for integer data columns
# TODO: Determine a schema for handling non-integer masked columns
# in FITS (if at all possible)
int_formats = ('B', 'I', 'J', 'K')
if not (col.format in int_formats or
col.format.p_format in int_formats):
continue
# The astype is necessary because if the string column is less
# than one character, the fill value will be N/A by default which
# is too long, and so no values will get masked.
fill_value = table[col.name].get_fill_value()
col.null = fill_value.astype(table[col.name].dtype)
else:
table_hdu = BinTableHDU.from_columns(np.array(table.filled()), header=hdr, character_as_bytes=character_as_bytes)
# Set units and format display for output HDU
for col in table_hdu.columns:
if table[col.name].info.format is not None:
# check for boolean types, special format case
logical = table[col.name].info.dtype == bool
tdisp_format = python_to_tdisp(table[col.name].info.format,
logical_dtype=logical)
if tdisp_format is not None:
col.disp = tdisp_format
unit = table[col.name].unit
if unit is not None:
# Local imports to avoid importing units when it is not required,
# e.g. for command-line scripts
from astropy.units import Unit
from astropy.units.format.fits import UnitScaleError
try:
col.unit = unit.to_string(format='fits')
except UnitScaleError:
scale = unit.scale
raise UnitScaleError(
"The column '{0}' could not be stored in FITS format "
"because it has a scale '({1})' that "
"is not recognized by the FITS standard. Either scale "
"the data or change the units.".format(col.name, str(scale)))
except ValueError:
warnings.warn(
"The unit '{0}' could not be saved to FITS format".format(
unit.to_string()), AstropyUserWarning)
# Try creating a Unit to issue a warning if the unit is not FITS compliant
Unit(col.unit, format='fits', parse_strict='warn')
# Column-specific override keywords for coordinate columns
coord_meta = table.meta.pop('__coordinate_columns__', {})
for col_name, col_info in coord_meta.items():
col = table_hdu.columns[col_name]
# Set the column coordinate attributes from data saved earlier.
# Note: have to set all three, even if we have no data.
for attr in 'coord_type', 'coord_unit', 'time_ref_pos':
setattr(col, attr, col_info.get(attr, None))
for key, value in table.meta.items():
if is_column_keyword(key.upper()) or key.upper() in REMOVE_KEYWORDS:
warnings.warn(
"Meta-data keyword {0} will be ignored since it conflicts "
"with a FITS reserved keyword".format(key), AstropyUserWarning)
# Convert to FITS format
if key == 'comments':
key = 'comment'
if isinstance(value, list):
for item in value:
try:
table_hdu.header.append((key, item))
except ValueError:
warnings.warn(
"Attribute `{0}` of type {1} cannot be added to "
"FITS Header - skipping".format(key, type(value)),
AstropyUserWarning)
else:
try:
table_hdu.header[key] = value
except ValueError:
warnings.warn(
"Attribute `{0}` of type {1} cannot be added to FITS "
"Header - skipping".format(key, type(value)),
AstropyUserWarning)
return table_hdu
def append(filename, data, header=None, checksum=False, verify=True, **kwargs):
"""
Append the header/data to FITS file if filename exists, create if not.
If only ``data`` is supplied, a minimal header is created.
Parameters
----------
filename : file path, file object, or file like object
File to write to. If opened, must be opened for update (rb+) unless it
is a new file, then it must be opened for append (ab+). A file or
`~gzip.GzipFile` object opened for update will be closed after return.
data : array, table, or group data object
the new data used for appending
header : `Header` object, optional
The header associated with ``data``. If `None`, an appropriate header
will be created for the data object supplied.
checksum : bool, optional
When `True` adds both ``DATASUM`` and ``CHECKSUM`` cards to the header
of the HDU when written to the file.
verify : bool, optional
When `True`, the existing FITS file will be read in to verify it for
correctness before appending. When `False`, content is simply appended
to the end of the file. Setting ``verify`` to `False` can be much
faster.
kwargs
Additional arguments are passed to:
- `~astropy.io.fits.writeto` if the file does not exist or is empty.
In this case ``output_verify`` is the only possible argument.
- `~astropy.io.fits.open` if ``verify`` is True or if ``filename``
is a file object.
- Otherwise no additional arguments can be used.
"""
name, closed, noexist_or_empty = _stat_filename_or_fileobj(filename)
if noexist_or_empty:
#
# The input file or file like object either doesn't exits or is
# empty. Use the writeto convenience function to write the
# output to the empty object.
#
writeto(filename, data, header, checksum=checksum, **kwargs)
else:
hdu = _makehdu(data, header)
if isinstance(hdu, PrimaryHDU):
hdu = ImageHDU(data, header)
if verify or not closed:
f = fitsopen(filename, mode='append', **kwargs)
try:
f.append(hdu)
# Set a flag in the HDU so that only this HDU gets a checksum
# when writing the file.
hdu._output_checksum = checksum
finally:
f.close(closed=closed)
else:
f = _File(filename, mode='append')
try:
hdu._output_checksum = checksum
hdu._writeto(f)
finally:
f.close()
def update(filename, data, *args, **kwargs):
"""
Update the specified extension with the input data/header.
Parameters
----------
filename : file path, file object, or file like object
File to update. If opened, mode must be update (rb+). An opened file
object or `~gzip.GzipFile` object will be closed upon return.
data : array, table, or group data object
the new data used for updating
header : `Header` object, optional
The header associated with ``data``. If `None`, an appropriate header
will be created for the data object supplied.
ext, extname, extver
The rest of the arguments are flexible: the 3rd argument can be the
header associated with the data. If the 3rd argument is not a
`Header`, it (and other positional arguments) are assumed to be the
extension specification(s). Header and extension specs can also be
keyword arguments. For example::
update(file, dat, hdr, 'sci') # update the 'sci' extension
update(file, dat, 3) # update the 3rd extension
update(file, dat, hdr, 3) # update the 3rd extension
update(file, dat, 'sci', 2) # update the 2nd SCI extension
update(file, dat, 3, header=hdr) # update the 3rd extension
update(file, dat, header=hdr, ext=5) # update the 5th extension
kwargs
Any additional keyword arguments to be passed to
`astropy.io.fits.open`.
"""
# The arguments to this function are a bit trickier to deal with than others
# in this module, since the documentation has promised that the header
# argument can be an optional positional argument.
if args and isinstance(args[0], Header):
header = args[0]
args = args[1:]
else:
header = None
# The header can also be a keyword argument--if both are provided the
# keyword takes precedence
header = kwargs.pop('header', header)
new_hdu = _makehdu(data, header)
closed = fileobj_closed(filename)
hdulist, _ext = _getext(filename, 'update', *args, **kwargs)
try:
hdulist[_ext] = new_hdu
finally:
hdulist.close(closed=closed)
def info(filename, output=None, **kwargs):
"""
Print the summary information on a FITS file.
This includes the name, type, length of header, data shape and type
for each extension.
Parameters
----------
filename : file path, file object, or file like object
FITS file to obtain info from. If opened, mode must be one of
the following: rb, rb+, or ab+ (i.e. the file must be readable).
output : file, bool, optional
A file-like object to write the output to. If ``False``, does not
output to a file and instead returns a list of tuples representing the
HDU info. Writes to ``sys.stdout`` by default.
kwargs
Any additional keyword arguments to be passed to
`astropy.io.fits.open`.
*Note:* This function sets ``ignore_missing_end=True`` by default.
"""
mode, closed = _get_file_mode(filename, default='readonly')
# Set the default value for the ignore_missing_end parameter
if 'ignore_missing_end' not in kwargs:
kwargs['ignore_missing_end'] = True
f = fitsopen(filename, mode=mode, **kwargs)
try:
ret = f.info(output=output)
finally:
if closed:
f.close()
return ret
def printdiff(inputa, inputb, *args, **kwargs):
"""
Compare two parts of a FITS file, including entire FITS files,
FITS `HDUList` objects and FITS ``HDU`` objects.
Parameters
----------
inputa : str, `HDUList` object, or ``HDU`` object
The filename of a FITS file, `HDUList`, or ``HDU``
object to compare to ``inputb``.
inputb : str, `HDUList` object, or ``HDU`` object
The filename of a FITS file, `HDUList`, or ``HDU``
object to compare to ``inputa``.
ext, extname, extver
Additional positional arguments are for extension specification if your
inputs are string filenames (will not work if
``inputa`` and ``inputb`` are ``HDU`` objects or `HDUList` objects).
They are flexible and are best illustrated by examples. In addition
to using these arguments positionally you can directly call the
keyword parameters ``ext``, ``extname``.
By extension number::
printdiff('inA.fits', 'inB.fits', 0) # the primary HDU
printdiff('inA.fits', 'inB.fits', 2) # the second extension
printdiff('inA.fits', 'inB.fits', ext=2) # the second extension
By name, i.e., ``EXTNAME`` value (if unique). ``EXTNAME`` values are
not case sensitive:
printdiff('inA.fits', 'inB.fits', 'sci')
printdiff('inA.fits', 'inB.fits', extname='sci') # equivalent
By combination of ``EXTNAME`` and ``EXTVER`` as separate
arguments or as a tuple::
printdiff('inA.fits', 'inB.fits', 'sci', 2) # EXTNAME='SCI'
# & EXTVER=2
printdiff('inA.fits', 'inB.fits', extname='sci', extver=2)
# equivalent
printdiff('inA.fits', 'inB.fits', ('sci', 2)) # equivalent
Ambiguous or conflicting specifications will raise an exception::
printdiff('inA.fits', 'inB.fits',
ext=('sci', 1), extname='err', extver=2)
kwargs
Any additional keyword arguments to be passed to
`~astropy.io.fits.FITSDiff`.
Notes
-----
The primary use for the `printdiff` function is to allow quick print out
of a FITS difference report and will write to ``sys.stdout``.
To save the diff report to a file please use `~astropy.io.fits.FITSDiff`
directly.
"""
# Pop extension keywords
extension = {key: kwargs.pop(key) for key in ['ext', 'extname', 'extver']
if key in kwargs}
has_extensions = args or extension
if isinstance(inputa, str) and has_extensions:
# Use handy _getext to interpret any ext keywords, but
# will need to close a if fails
modea, closeda = _get_file_mode(inputa)
modeb, closedb = _get_file_mode(inputb)
hdulista, extidxa = _getext(inputa, modea, *args, **extension)
# Have to close a if b doesn't make it
try:
hdulistb, extidxb = _getext(inputb, modeb, *args, **extension)
except Exception:
hdulista.close(closed=closeda)
raise
try:
hdua = hdulista[extidxa]
hdub = hdulistb[extidxb]
# See below print for note
print(HDUDiff(hdua, hdub, **kwargs).report())
finally:
hdulista.close(closed=closeda)
hdulistb.close(closed=closedb)
# If input is not a string, can feed HDU objects or HDUList directly,
# but can't currently handle extensions
elif isinstance(inputa, _ValidHDU) and has_extensions:
raise ValueError("Cannot use extension keywords when providing an "
"HDU object.")
elif isinstance(inputa, _ValidHDU) and not has_extensions:
print(HDUDiff(inputa, inputb, **kwargs).report())
elif isinstance(inputa, HDUList) and has_extensions:
raise NotImplementedError("Extension specification with HDUList "
"objects not implemented.")
# This function is EXCLUSIVELY for printing the diff report to screen
# in a one-liner call, hence the use of print instead of logging
else:
print(FITSDiff(inputa, inputb, **kwargs).report())
@deprecated_renamed_argument('clobber', 'overwrite', '2.0')
def tabledump(filename, datafile=None, cdfile=None, hfile=None, ext=1,
overwrite=False):
"""
Dump a table HDU to a file in ASCII format. The table may be
dumped in three separate files, one containing column definitions,
one containing header parameters, and one for table data.
Parameters
----------
filename : file path, file object or file-like object
Input fits file.
datafile : file path, file object or file-like object, optional
Output data file. The default is the root name of the input
fits file appended with an underscore, followed by the
extension number (ext), followed by the extension ``.txt``.
cdfile : file path, file object or file-like object, optional
Output column definitions file. The default is `None`,
no column definitions output is produced.
hfile : file path, file object or file-like object, optional
Output header parameters file. The default is `None`,
no header parameters output is produced.
ext : int
The number of the extension containing the table HDU to be
dumped.
overwrite : bool, optional
If ``True``, overwrite the output file if it exists. Raises an
``OSError`` if ``False`` and the output file exists. Default is
``False``.
.. versionchanged:: 1.3
``overwrite`` replaces the deprecated ``clobber`` argument.
Notes
-----
The primary use for the `tabledump` function is to allow editing in a
standard text editor of the table data and parameters. The
`tableload` function can be used to reassemble the table from the
three ASCII files.
"""
# allow file object to already be opened in any of the valid modes
# and leave the file in the same state (opened or closed) as when
# the function was called
mode, closed = _get_file_mode(filename, default='readonly')
f = fitsopen(filename, mode=mode)
# Create the default data file name if one was not provided
try:
if not datafile:
root, tail = os.path.splitext(f._file.name)
datafile = root + '_' + repr(ext) + '.txt'
# Dump the data from the HDU to the files
f[ext].dump(datafile, cdfile, hfile, overwrite)
finally:
if closed:
f.close()
if isinstance(tabledump.__doc__, str):
tabledump.__doc__ += BinTableHDU._tdump_file_format.replace('\n', '\n ')
def tableload(datafile, cdfile, hfile=None):
"""
Create a table from the input ASCII files. The input is from up
to three separate files, one containing column definitions, one
containing header parameters, and one containing column data. The
header parameters file is not required. When the header
parameters file is absent a minimal header is constructed.
Parameters
----------
datafile : file path, file object or file-like object
Input data file containing the table data in ASCII format.
cdfile : file path, file object or file-like object
Input column definition file containing the names, formats,
display formats, physical units, multidimensional array
dimensions, undefined values, scale factors, and offsets
associated with the columns in the table.
hfile : file path, file object or file-like object, optional
Input parameter definition file containing the header
parameter definitions to be associated with the table.
If `None`, a minimal header is constructed.
Notes
-----
The primary use for the `tableload` function is to allow the input of
ASCII data that was edited in a standard text editor of the table
data and parameters. The tabledump function can be used to create the
initial ASCII files.
"""
return BinTableHDU.load(datafile, cdfile, hfile, replace=True)
if isinstance(tableload.__doc__, str):
tableload.__doc__ += BinTableHDU._tdump_file_format.replace('\n', '\n ')
def _getext(filename, mode, *args, ext=None, extname=None, extver=None,
**kwargs):
"""
Open the input file, return the `HDUList` and the extension.
This supports several different styles of extension selection. See the
:func:`getdata()` documentation for the different possibilities.
"""
err_msg = ('Redundant/conflicting extension arguments(s): {}'.format(
{'args': args, 'ext': ext, 'extname': extname,
'extver': extver}))
# This code would be much simpler if just one way of specifying an
# extension were picked. But now we need to support all possible ways for
# the time being.
if len(args) == 1:
# Must be either an extension number, an extension name, or an
# (extname, extver) tuple
if _is_int(args[0]) or (isinstance(ext, tuple) and len(ext) == 2):
if ext is not None or extname is not None or extver is not None:
raise TypeError(err_msg)
ext = args[0]
elif isinstance(args[0], str):
# The first arg is an extension name; it could still be valid
# to provide an extver kwarg
if ext is not None or extname is not None:
raise TypeError(err_msg)
extname = args[0]
else:
# Take whatever we have as the ext argument; we'll validate it
# below
ext = args[0]
elif len(args) == 2:
# Must be an extname and extver
if ext is not None or extname is not None or extver is not None:
raise TypeError(err_msg)
extname = args[0]
extver = args[1]
elif len(args) > 2:
raise TypeError('Too many positional arguments.')
if (ext is not None and
not (_is_int(ext) or
(isinstance(ext, tuple) and len(ext) == 2 and
isinstance(ext[0], str) and _is_int(ext[1])))):
raise ValueError(
'The ext keyword must be either an extension number '
'(zero-indexed) or a (extname, extver) tuple.')
if extname is not None and not isinstance(extname, str):
raise ValueError('The extname argument must be a string.')
if extver is not None and not _is_int(extver):
raise ValueError('The extver argument must be an integer.')
if ext is None and extname is None and extver is None:
ext = 0
elif ext is not None and (extname is not None or extver is not None):
raise TypeError(err_msg)
elif extname:
if extver:
ext = (extname, extver)
else:
ext = (extname, 1)
elif extver and extname is None:
raise TypeError('extver alone cannot specify an extension.')
hdulist = fitsopen(filename, mode=mode, **kwargs)
return hdulist, ext
def _makehdu(data, header):
if header is None:
header = Header()
hdu = _BaseHDU(data, header)
if hdu.__class__ in (_BaseHDU, _ValidHDU):
# The HDU type was unrecognized, possibly due to a
# nonexistent/incomplete header
if ((isinstance(data, np.ndarray) and data.dtype.fields is not None) or
isinstance(data, np.recarray)):
hdu = BinTableHDU(data, header=header)
elif isinstance(data, np.ndarray):
hdu = ImageHDU(data, header=header)
else:
raise KeyError('Data must be a numpy array.')
return hdu
def _stat_filename_or_fileobj(filename):
closed = fileobj_closed(filename)
name = fileobj_name(filename) or ''
try:
loc = filename.tell()
except AttributeError:
loc = 0
noexist_or_empty = ((name and
(not os.path.exists(name) or
(os.path.getsize(name) == 0)))
or (not name and loc == 0))
return name, closed, noexist_or_empty
def _get_file_mode(filename, default='readonly'):
"""
Allow file object to already be opened in any of the valid modes and
and leave the file in the same state (opened or closed) as when
the function was called.
"""
mode = default
closed = fileobj_closed(filename)
fmode = fileobj_mode(filename)
if fmode is not None:
mode = FILE_MODES.get(fmode)
if mode is None:
raise OSError(
"File mode of the input file object ({!r}) cannot be used to "
"read/write FITS files.".format(fmode))
return mode, closed
|
84966053fae3e007c4c48a4d32aac54facbc325bf4441541d9e4fee4b46e77da | # Licensed under a 3-clause BSD style license - see PYFITS.rst
import os
from distutils.core import Extension
from glob import glob
from astropy_helpers import setup_helpers
from astropy_helpers.distutils_helpers import get_distutils_build_option
def _get_compression_extension():
# 'numpy' will be replaced with the proper path to the numpy includes
cfg = setup_helpers.DistutilsExtensionArgs()
cfg['include_dirs'].append('numpy')
cfg['sources'].append(os.path.join(os.path.dirname(__file__), 'src',
'compressionmodule.c'))
if not setup_helpers.use_system_library('cfitsio'):
if setup_helpers.get_compiler_option() == 'msvc':
# These come from the CFITSIO vcc makefile, except the last
# which ensures on windows we do not include unistd.h (in regular
# compilation of cfitsio, an empty file would be generated)
cfg['extra_compile_args'].extend(
['/D', '"WIN32"',
'/D', '"_WINDOWS"',
'/D', '"_MBCS"',
'/D', '"_USRDLL"',
'/D', '"_CRT_SECURE_NO_DEPRECATE"',
'/D', '"FF_NO_UNISTD_H"'])
else:
cfg['extra_compile_args'].extend([
'-Wno-declaration-after-statement'
])
if not get_distutils_build_option('debug'):
# these switches are to silence warnings from compiling CFITSIO
# For full silencing, some are added that only are used in
# later versions of gcc (versions approximate; see #6474)
cfg['extra_compile_args'].extend([
'-Wno-strict-prototypes',
'-Wno-unused',
'-Wno-uninitialized',
'-Wno-unused-result', # gcc >~4.8
'-Wno-misleading-indentation', # gcc >~7.2
'-Wno-format-overflow', # gcc >~7.2
])
cfitsio_lib_path = os.path.join('cextern', 'cfitsio', 'lib')
cfitsio_zlib_path = os.path.join('cextern', 'cfitsio', 'zlib')
cfitsio_files = glob(os.path.join(cfitsio_lib_path, '*.c'))
cfitsio_zlib_files = glob(os.path.join(cfitsio_zlib_path, '*.c'))
cfg['include_dirs'].append(cfitsio_lib_path)
cfg['include_dirs'].append(cfitsio_zlib_path)
cfg['sources'].extend(cfitsio_files)
cfg['sources'].extend(cfitsio_zlib_files)
else:
cfg.update(setup_helpers.pkg_config(['cfitsio'], ['cfitsio']))
return Extension('astropy.io.fits.compression', **cfg)
def get_extensions():
return [_get_compression_extension()]
def get_external_libraries():
return ['cfitsio']
|
8005b0253f9f3b0c34b34f5e3e62b46b27d9062392d895b4b8100a3368ad9519 | # Licensed under a 3-clause BSD style license - see PYFITS.rst
import gzip
import itertools
import io
import mmap
import operator
import os
import platform
import signal
import sys
import tempfile
import textwrap
import threading
import warnings
import weakref
from contextlib import contextmanager, suppress
from functools import wraps
from astropy.utils import data
from distutils.version import LooseVersion
import numpy as np
from astropy.utils.exceptions import AstropyUserWarning
cmp = lambda a, b: (a > b) - (a < b)
all_integer_types = (int, np.integer)
class NotifierMixin:
"""
Mixin class that provides services by which objects can register
listeners to changes on that object.
All methods provided by this class are underscored, since this is intended
for internal use to communicate between classes in a generic way, and is
not machinery that should be exposed to users of the classes involved.
Use the ``_add_listener`` method to register a listener on an instance of
the notifier. This registers the listener with a weak reference, so if
no other references to the listener exist it is automatically dropped from
the list and does not need to be manually removed.
Call the ``_notify`` method on the notifier to update all listeners
upon changes. ``_notify('change_type', *args, **kwargs)`` results
in calling ``listener._update_change_type(*args, **kwargs)`` on all
listeners subscribed to that notifier.
If a particular listener does not have the appropriate update method
it is ignored.
Examples
--------
>>> class Widget(NotifierMixin):
... state = 1
... def __init__(self, name):
... self.name = name
... def update_state(self):
... self.state += 1
... self._notify('widget_state_changed', self)
...
>>> class WidgetListener:
... def _update_widget_state_changed(self, widget):
... print('Widget {0} changed state to {1}'.format(
... widget.name, widget.state))
...
>>> widget = Widget('fred')
>>> listener = WidgetListener()
>>> widget._add_listener(listener)
>>> widget.update_state()
Widget fred changed state to 2
"""
_listeners = None
def _add_listener(self, listener):
"""
Add an object to the list of listeners to notify of changes to this
object. This adds a weakref to the list of listeners that is
removed from the listeners list when the listener has no other
references to it.
"""
if self._listeners is None:
self._listeners = weakref.WeakValueDictionary()
self._listeners[id(listener)] = listener
def _remove_listener(self, listener):
"""
Removes the specified listener from the listeners list. This relies
on object identity (i.e. the ``is`` operator).
"""
if self._listeners is None:
return
with suppress(KeyError):
del self._listeners[id(listener)]
def _notify(self, notification, *args, **kwargs):
"""
Notify all listeners of some particular state change by calling their
``_update_<notification>`` method with the given ``*args`` and
``**kwargs``.
The notification does not by default include the object that actually
changed (``self``), but it certainly may if required.
"""
if self._listeners is None:
return
method_name = '_update_{0}'.format(notification)
for listener in self._listeners.valuerefs():
# Use valuerefs instead of itervaluerefs; see
# https://github.com/astropy/astropy/issues/4015
listener = listener() # dereference weakref
if listener is None:
continue
if hasattr(listener, method_name):
method = getattr(listener, method_name)
if callable(method):
method(*args, **kwargs)
def __getstate__(self):
"""
Exclude listeners when saving the listener's state, since they may be
ephemeral.
"""
# TODO: This hasn't come up often, but if anyone needs to pickle HDU
# objects it will be necessary when HDU objects' states are restored to
# re-register themselves as listeners on their new column instances.
try:
state = super().__getstate__()
except AttributeError:
# Chances are the super object doesn't have a getstate
state = self.__dict__.copy()
state['_listeners'] = None
return state
def first(iterable):
"""
Returns the first item returned by iterating over an iterable object.
Example:
>>> a = [1, 2, 3]
>>> first(a)
1
"""
return next(iter(iterable))
def itersubclasses(cls, _seen=None):
"""
Generator over all subclasses of a given class, in depth first order.
>>> class A: pass
>>> class B(A): pass
>>> class C(A): pass
>>> class D(B,C): pass
>>> class E(D): pass
>>>
>>> for cls in itersubclasses(A):
... print(cls.__name__)
B
D
E
C
>>> # get ALL classes currently defined
>>> [cls.__name__ for cls in itersubclasses(object)]
[...'tuple', ...'type', ...]
From http://code.activestate.com/recipes/576949/
"""
if _seen is None:
_seen = set()
try:
subs = cls.__subclasses__()
except TypeError: # fails only when cls is type
subs = cls.__subclasses__(cls)
for sub in sorted(subs, key=operator.attrgetter('__name__')):
if sub not in _seen:
_seen.add(sub)
yield sub
for sub in itersubclasses(sub, _seen):
yield sub
def ignore_sigint(func):
"""
This decorator registers a custom SIGINT handler to catch and ignore SIGINT
until the wrapped function is completed.
"""
@wraps(func)
def wrapped(*args, **kwargs):
# Get the name of the current thread and determine if this is a single
# threaded application
curr_thread = threading.currentThread()
single_thread = (threading.activeCount() == 1 and
curr_thread.getName() == 'MainThread')
class SigintHandler:
def __init__(self):
self.sigint_received = False
def __call__(self, signum, frame):
warnings.warn('KeyboardInterrupt ignored until {} is '
'complete!'.format(func.__name__),
AstropyUserWarning)
self.sigint_received = True
sigint_handler = SigintHandler()
# Define new signal interput handler
if single_thread:
# Install new handler
old_handler = signal.signal(signal.SIGINT, sigint_handler)
try:
func(*args, **kwargs)
finally:
if single_thread:
if old_handler is not None:
signal.signal(signal.SIGINT, old_handler)
else:
signal.signal(signal.SIGINT, signal.SIG_DFL)
if sigint_handler.sigint_received:
raise KeyboardInterrupt
return wrapped
def pairwise(iterable):
"""Return the items of an iterable paired with its next item.
Ex: s -> (s0,s1), (s1,s2), (s2,s3), ....
"""
a, b = itertools.tee(iterable)
for _ in b:
# Just a little trick to advance b without having to catch
# StopIter if b happens to be empty
break
return zip(a, b)
def encode_ascii(s):
if isinstance(s, str):
return s.encode('ascii')
elif (isinstance(s, np.ndarray) and
issubclass(s.dtype.type, np.str_)):
ns = np.char.encode(s, 'ascii').view(type(s))
if ns.dtype.itemsize != s.dtype.itemsize / 4:
ns = ns.astype((np.bytes_, s.dtype.itemsize / 4))
return ns
elif (isinstance(s, np.ndarray) and
not issubclass(s.dtype.type, np.bytes_)):
raise TypeError('string operation on non-string array')
return s
def decode_ascii(s):
if isinstance(s, bytes):
try:
return s.decode('ascii')
except UnicodeDecodeError:
warnings.warn('non-ASCII characters are present in the FITS '
'file header and have been replaced by "?" '
'characters', AstropyUserWarning)
s = s.decode('ascii', errors='replace')
return s.replace(u'\ufffd', '?')
elif (isinstance(s, np.ndarray) and
issubclass(s.dtype.type, np.bytes_)):
# np.char.encode/decode annoyingly don't preserve the type of the
# array, hence the view() call
# It also doesn't necessarily preserve widths of the strings,
# hence the astype()
if s.size == 0:
# Numpy apparently also has a bug that if a string array is
# empty calling np.char.decode on it returns an empty float64
# array wth
dt = s.dtype.str.replace('S', 'U')
ns = np.array([], dtype=dt).view(type(s))
else:
ns = np.char.decode(s, 'ascii').view(type(s))
if ns.dtype.itemsize / 4 != s.dtype.itemsize:
ns = ns.astype((np.str_, s.dtype.itemsize))
return ns
elif (isinstance(s, np.ndarray) and
not issubclass(s.dtype.type, np.str_)):
# Don't silently pass through on non-string arrays; we don't want
# to hide errors where things that are not stringy are attempting
# to be decoded
raise TypeError('string operation on non-string array')
return s
def isreadable(f):
"""
Returns True if the file-like object can be read from. This is a common-
sense approximation of io.IOBase.readable.
"""
if hasattr(f, 'readable'):
return f.readable()
if hasattr(f, 'closed') and f.closed:
# This mimics the behavior of io.IOBase.readable
raise ValueError('I/O operation on closed file')
if not hasattr(f, 'read'):
return False
if hasattr(f, 'mode') and not any(c in f.mode for c in 'r+'):
return False
# Not closed, has a 'read()' method, and either has no known mode or a
# readable mode--should be good enough to assume 'readable'
return True
def iswritable(f):
"""
Returns True if the file-like object can be written to. This is a common-
sense approximation of io.IOBase.writable.
"""
if hasattr(f, 'writable'):
return f.writable()
if hasattr(f, 'closed') and f.closed:
# This mimics the behavior of io.IOBase.writable
raise ValueError('I/O operation on closed file')
if not hasattr(f, 'write'):
return False
if hasattr(f, 'mode') and not any(c in f.mode for c in 'wa+'):
return False
# Note closed, has a 'write()' method, and either has no known mode or a
# mode that supports writing--should be good enough to assume 'writable'
return True
def isfile(f):
"""
Returns True if the given object represents an OS-level file (that is,
``isinstance(f, file)``).
On Python 3 this also returns True if the given object is higher level
wrapper on top of a FileIO object, such as a TextIOWrapper.
"""
if isinstance(f, io.FileIO):
return True
elif hasattr(f, 'buffer'):
return isfile(f.buffer)
elif hasattr(f, 'raw'):
return isfile(f.raw)
return False
def fileobj_open(filename, mode):
"""
A wrapper around the `open()` builtin.
This exists because `open()` returns an `io.BufferedReader` by default.
This is bad, because `io.BufferedReader` doesn't support random access,
which we need in some cases. We must call open with buffering=0 to get
a raw random-access file reader.
"""
return open(filename, mode, buffering=0)
def fileobj_name(f):
"""
Returns the 'name' of file-like object f, if it has anything that could be
called its name. Otherwise f's class or type is returned. If f is a
string f itself is returned.
"""
if isinstance(f, str):
return f
elif isinstance(f, gzip.GzipFile):
# The .name attribute on GzipFiles does not always represent the name
# of the file being read/written--it can also represent the original
# name of the file being compressed
# See the documentation at
# https://docs.python.org/3/library/gzip.html#gzip.GzipFile
# As such, for gzip files only return the name of the underlying
# fileobj, if it exists
return fileobj_name(f.fileobj)
elif hasattr(f, 'name'):
return f.name
elif hasattr(f, 'filename'):
return f.filename
elif hasattr(f, '__class__'):
return str(f.__class__)
else:
return str(type(f))
def fileobj_closed(f):
"""
Returns True if the given file-like object is closed or if f is a string
(and assumed to be a pathname).
Returns False for all other types of objects, under the assumption that
they are file-like objects with no sense of a 'closed' state.
"""
if isinstance(f, str):
return True
if hasattr(f, 'closed'):
return f.closed
elif hasattr(f, 'fileobj') and hasattr(f.fileobj, 'closed'):
return f.fileobj.closed
elif hasattr(f, 'fp') and hasattr(f.fp, 'closed'):
return f.fp.closed
else:
return False
def fileobj_mode(f):
"""
Returns the 'mode' string of a file-like object if such a thing exists.
Otherwise returns None.
"""
# Go from most to least specific--for example gzip objects have a 'mode'
# attribute, but it's not analogous to the file.mode attribute
# gzip.GzipFile -like
if hasattr(f, 'fileobj') and hasattr(f.fileobj, 'mode'):
fileobj = f.fileobj
# astropy.io.fits._File -like, doesn't need additional checks because it's
# already validated
elif hasattr(f, 'fileobj_mode'):
return f.fileobj_mode
# PIL-Image -like investigate the fp (filebuffer)
elif hasattr(f, 'fp') and hasattr(f.fp, 'mode'):
fileobj = f.fp
# FILEIO -like (normal open(...)), keep as is.
elif hasattr(f, 'mode'):
fileobj = f
# Doesn't look like a file-like object, for example strings, urls or paths.
else:
return None
return _fileobj_normalize_mode(fileobj)
def _fileobj_normalize_mode(f):
"""Takes care of some corner cases in Python where the mode string
is either oddly formatted or does not truly represent the file mode.
"""
mode = f.mode
# Special case: Gzip modes:
if isinstance(f, gzip.GzipFile):
# GzipFiles can be either readonly or writeonly
if mode == gzip.READ:
return 'rb'
elif mode == gzip.WRITE:
return 'wb'
else:
return None # This shouldn't happen?
# Sometimes Python can produce modes like 'r+b' which will be normalized
# here to 'rb+'
if '+' in mode:
mode = mode.replace('+', '')
mode += '+'
return mode
def fileobj_is_binary(f):
"""
Returns True if the give file or file-like object has a file open in binary
mode. When in doubt, returns True by default.
"""
# This is kind of a hack for this to work correctly with _File objects,
# which, for the time being, are *always* binary
if hasattr(f, 'binary'):
return f.binary
if isinstance(f, io.TextIOBase):
return False
mode = fileobj_mode(f)
if mode:
return 'b' in mode
else:
return True
def translate(s, table, deletechars):
if deletechars:
table = table.copy()
for c in deletechars:
table[ord(c)] = None
return s.translate(table)
def fill(text, width, **kwargs):
"""
Like :func:`textwrap.wrap` but preserves existing paragraphs which
:func:`textwrap.wrap` does not otherwise handle well. Also handles section
headers.
"""
paragraphs = text.split('\n\n')
def maybe_fill(t):
if all(len(l) < width for l in t.splitlines()):
return t
else:
return textwrap.fill(t, width, **kwargs)
return '\n\n'.join(maybe_fill(p) for p in paragraphs)
# On MacOS X 10.8 and earlier, there is a bug that causes numpy.fromfile to
# fail when reading over 2Gb of data. If we detect these versions of MacOS X,
# we can instead read the data in chunks. To avoid performance penalties at
# import time, we defer the setting of this global variable until the first
# time it is needed.
CHUNKED_FROMFILE = None
def _array_from_file(infile, dtype, count):
"""Create a numpy array from a file or a file-like object."""
if isfile(infile):
global CHUNKED_FROMFILE
if CHUNKED_FROMFILE is None:
if (sys.platform == 'darwin' and
LooseVersion(platform.mac_ver()[0]) < LooseVersion('10.9')):
CHUNKED_FROMFILE = True
else:
CHUNKED_FROMFILE = False
if CHUNKED_FROMFILE:
chunk_size = int(1024 ** 3 / dtype.itemsize) # 1Gb to be safe
if count < chunk_size:
return np.fromfile(infile, dtype=dtype, count=count)
else:
array = np.empty(count, dtype=dtype)
for beg in range(0, count, chunk_size):
end = min(count, beg + chunk_size)
array[beg:end] = np.fromfile(infile, dtype=dtype, count=end - beg)
return array
else:
return np.fromfile(infile, dtype=dtype, count=count)
else:
# treat as file-like object with "read" method; this includes gzip file
# objects, because numpy.fromfile just reads the compressed bytes from
# their underlying file object, instead of the decompressed bytes
read_size = np.dtype(dtype).itemsize * count
s = infile.read(read_size)
array = np.frombuffer(s, dtype=dtype, count=count)
# copy is needed because np.frombuffer returns a read-only view of the
# underlying buffer
array = array.copy()
return array
_OSX_WRITE_LIMIT = (2 ** 32) - 1
_WIN_WRITE_LIMIT = (2 ** 31) - 1
def _array_to_file(arr, outfile):
"""
Write a numpy array to a file or a file-like object.
Parameters
----------
arr : `~numpy.ndarray`
The Numpy array to write.
outfile : file-like
A file-like object such as a Python file object, an `io.BytesIO`, or
anything else with a ``write`` method. The file object must support
the buffer interface in its ``write``.
If writing directly to an on-disk file this delegates directly to
`ndarray.tofile`. Otherwise a slower Python implementation is used.
"""
if isfile(outfile) and not isinstance(outfile, io.BufferedIOBase):
write = lambda a, f: a.tofile(f)
else:
write = _array_to_file_like
# Implements a workaround for a bug deep in OSX's stdlib file writing
# functions; on 64-bit OSX it is not possible to correctly write a number
# of bytes greater than 2 ** 32 and divisible by 4096 (or possibly 8192--
# whatever the default blocksize for the filesystem is).
# This issue should have a workaround in Numpy too, but hasn't been
# implemented there yet: https://github.com/astropy/astropy/issues/839
#
# Apparently Windows has its own fwrite bug:
# https://github.com/numpy/numpy/issues/2256
if (sys.platform == 'darwin' and arr.nbytes >= _OSX_WRITE_LIMIT + 1 and
arr.nbytes % 4096 == 0):
# chunksize is a count of elements in the array, not bytes
chunksize = _OSX_WRITE_LIMIT // arr.itemsize
elif sys.platform.startswith('win'):
chunksize = _WIN_WRITE_LIMIT // arr.itemsize
else:
# Just pass the whole array to the write routine
return write(arr, outfile)
# Write one chunk at a time for systems whose fwrite chokes on large
# writes.
idx = 0
arr = arr.view(np.ndarray).flatten()
while idx < arr.nbytes:
write(arr[idx:idx + chunksize], outfile)
idx += chunksize
def _array_to_file_like(arr, fileobj):
"""
Write a `~numpy.ndarray` to a file-like object (which is not supported by
`numpy.ndarray.tofile`).
"""
# If the array is empty, we can simply take a shortcut and return since
# there is nothing to write.
if len(arr) == 0:
return
if arr.flags.contiguous:
# It suffices to just pass the underlying buffer directly to the
# fileobj's write (assuming it supports the buffer interface). If
# it does not have the buffer interface, a TypeError should be returned
# in which case we can fall back to the other methods.
try:
fileobj.write(arr.data)
except TypeError:
pass
else:
return
if hasattr(np, 'nditer'):
# nditer version for non-contiguous arrays
for item in np.nditer(arr, order='C'):
fileobj.write(item.tostring())
else:
# Slower version for Numpy versions without nditer;
# The problem with flatiter is it doesn't preserve the original
# byteorder
byteorder = arr.dtype.byteorder
if ((sys.byteorder == 'little' and byteorder == '>')
or (sys.byteorder == 'big' and byteorder == '<')):
for item in arr.flat:
fileobj.write(item.byteswap().tostring())
else:
for item in arr.flat:
fileobj.write(item.tostring())
def _write_string(f, s):
"""
Write a string to a file, encoding to ASCII if the file is open in binary
mode, or decoding if the file is open in text mode.
"""
# Assume if the file object doesn't have a specific mode, that the mode is
# binary
binmode = fileobj_is_binary(f)
if binmode and isinstance(s, str):
s = encode_ascii(s)
elif not binmode and not isinstance(f, str):
s = decode_ascii(s)
f.write(s)
def _convert_array(array, dtype):
"""
Converts an array to a new dtype--if the itemsize of the new dtype is
the same as the old dtype and both types are not numeric, a view is
returned. Otherwise a new array must be created.
"""
if array.dtype == dtype:
return array
elif (array.dtype.itemsize == dtype.itemsize and not
(np.issubdtype(array.dtype, np.number) and
np.issubdtype(dtype, np.number))):
# Includes a special case when both dtypes are at least numeric to
# account for ticket #218: https://aeon.stsci.edu/ssb/trac/pyfits/ticket/218
return array.view(dtype)
else:
return array.astype(dtype)
def _unsigned_zero(dtype):
"""
Given a numpy dtype, finds its "zero" point, which is exactly in the
middle of its range.
"""
assert dtype.kind == 'u'
return 1 << (dtype.itemsize * 8 - 1)
def _is_pseudo_unsigned(dtype):
return dtype.kind == 'u' and dtype.itemsize >= 2
def _is_int(val):
return isinstance(val, all_integer_types)
def _str_to_num(val):
"""Converts a given string to either an int or a float if necessary."""
try:
num = int(val)
except ValueError:
# If this fails then an exception should be raised anyways
num = float(val)
return num
def _words_group(input, strlen):
"""
Split a long string into parts where each part is no longer
than ``strlen`` and no word is cut into two pieces. But if
there is one single word which is longer than ``strlen``, then
it will be split in the middle of the word.
"""
words = []
nblanks = input.count(' ')
nmax = max(nblanks, len(input) // strlen + 1)
arr = np.frombuffer((input + ' ').encode('utf8'), dtype=(bytes, 1))
# locations of the blanks
blank_loc = np.nonzero(arr == b' ')[0]
offset = 0
xoffset = 0
for idx in range(nmax):
try:
loc = np.nonzero(blank_loc >= strlen + offset)[0][0]
offset = blank_loc[loc - 1] + 1
if loc == 0:
offset = -1
except Exception:
offset = len(input)
# check for one word longer than strlen, break in the middle
if offset <= xoffset:
offset = xoffset + strlen
# collect the pieces in a list
words.append(input[xoffset:offset])
if len(input) == offset:
break
xoffset = offset
return words
def _tmp_name(input):
"""
Create a temporary file name which should not already exist. Use the
directory of the input file as the base name of the mkstemp() output.
"""
if input is not None:
input = os.path.dirname(input)
f, fn = tempfile.mkstemp(dir=input)
os.close(f)
return fn
def _get_array_mmap(array):
"""
If the array has an mmap.mmap at base of its base chain, return the mmap
object; otherwise return None.
"""
if isinstance(array, mmap.mmap):
return array
base = array
while hasattr(base, 'base') and base.base is not None:
if isinstance(base.base, mmap.mmap):
return base.base
base = base.base
@contextmanager
def _free_space_check(hdulist, dirname=None):
try:
yield
except OSError as exc:
error_message = ''
if not isinstance(hdulist, list):
hdulist = [hdulist, ]
if dirname is None:
dirname = os.path.dirname(hdulist._file.name)
if os.path.isdir(dirname):
free_space = data.get_free_space_in_dir(dirname)
hdulist_size = sum(hdu.size for hdu in hdulist)
if free_space < hdulist_size:
error_message = ("Not enough space on disk: requested {}, "
"available {}. ".format(hdulist_size, free_space))
for hdu in hdulist:
hdu._close()
raise OSError(error_message + str(exc))
def _extract_number(value, default):
"""
Attempts to extract an integer number from the given value. If the
extraction fails, the value of the 'default' argument is returned.
"""
try:
# The _str_to_num method converts the value to string/float
# so we need to perform one additional conversion to int on top
return int(_str_to_num(value))
except (TypeError, ValueError):
return default
def get_testdata_filepath(filename):
"""
Return a string representing the path to the file requested from the
io.fits test data set.
.. versionadded:: 2.0.3
Parameters
----------
filename : str
The filename of the test data file.
Returns
-------
filepath : str
The path to the requested file.
"""
return data.get_pkg_data_filename(
'io/fits/tests/data/{}'.format(filename), 'astropy')
def _rstrip_inplace(array):
"""
Performs an in-place rstrip operation on string arrays. This is necessary
since the built-in `np.char.rstrip` in Numpy does not perform an in-place
calculation.
"""
# The following implementation convert the string to unsigned integers of
# the right length. Trailing spaces (which are represented as 32) are then
# converted to null characters (represented as zeros). To avoid creating
# large temporary mask arrays, we loop over chunks (attempting to do that
# on a 1-D version of the array; large memory may still be needed in the
# unlikely case that a string array has small first dimension and cannot
# be represented as a contiguous 1-D array in memory).
dt = array.dtype
if dt.kind not in 'SU':
raise TypeError("This function can only be used on string arrays")
# View the array as appropriate integers. The last dimension will
# equal the number of characters in each string.
bpc = 1 if dt.kind == 'S' else 4
dt_int = "{0}{1}u{2}".format(dt.itemsize // bpc, dt.byteorder, bpc)
b = array.view(dt_int, np.ndarray)
# For optimal speed, work in chunks of the internal ufunc buffer size.
bufsize = np.getbufsize()
# Attempt to have the strings as a 1-D array to give the chunk known size.
# Note: the code will work if this fails; the chunks will just be larger.
if b.ndim > 2:
try:
b.shape = -1, b.shape[-1]
except AttributeError: # can occur for non-contiguous arrays
pass
for j in range(0, b.shape[0], bufsize):
c = b[j:j + bufsize]
# Mask which will tell whether we're in a sequence of trailing spaces.
mask = np.ones(c.shape[:-1], dtype=bool)
# Loop over the characters in the strings, in reverse order. We process
# the i-th character of all strings in the chunk at the same time. If
# the character is 32, this corresponds to a space, and we then change
# this to 0. We then construct a new mask to find rows where the
# i-th character is 0 (null) and the i-1-th is 32 (space) and repeat.
for i in range(-1, -c.shape[-1], -1):
mask &= c[..., i] == 32
c[..., i][mask] = 0
mask = c[..., i] == 0
return array
|
5412cc3d84284b0256863c121b59c6dba6ebe9484ef210ffcb0f168ca11a93e3 | # Licensed under a 3-clause BSD style license - see PYFITS.rst
import re
import warnings
import numpy as np
from .util import _str_to_num, _is_int, translate, _words_group
from .verify import _Verify, _ErrList, VerifyError, VerifyWarning
from . import conf
from astropy.utils.exceptions import AstropyUserWarning
__all__ = ['Card', 'Undefined']
FIX_FP_TABLE = str.maketrans('de', 'DE')
FIX_FP_TABLE2 = str.maketrans('dD', 'eE')
CARD_LENGTH = 80
BLANK_CARD = ' ' * CARD_LENGTH
KEYWORD_LENGTH = 8 # The max length for FITS-standard keywords
VALUE_INDICATOR = '= ' # The standard FITS value indicator
VALUE_INDICATOR_LEN = len(VALUE_INDICATOR)
HIERARCH_VALUE_INDICATOR = '=' # HIERARCH cards may use a shortened indicator
class Undefined:
"""Undefined value."""
def __init__(self):
# This __init__ is required to be here for Sphinx documentation
pass
UNDEFINED = Undefined()
class Card(_Verify):
length = CARD_LENGTH
"""The length of a Card image; should always be 80 for valid FITS files."""
# String for a FITS standard compliant (FSC) keyword.
_keywd_FSC_RE = re.compile(r'^[A-Z0-9_-]{0,%d}$' % KEYWORD_LENGTH)
# This will match any printable ASCII character excluding '='
_keywd_hierarch_RE = re.compile(r'^(?:HIERARCH +)?(?:^[ -<>-~]+ ?)+$',
re.I)
# A number sub-string, either an integer or a float in fixed or
# scientific notation. One for FSC and one for non-FSC (NFSC) format:
# NFSC allows lower case of DE for exponent, allows space between sign,
# digits, exponent sign, and exponents
_digits_FSC = r'(\.\d+|\d+(\.\d*)?)([DE][+-]?\d+)?'
_digits_NFSC = r'(\.\d+|\d+(\.\d*)?) *([deDE] *[+-]? *\d+)?'
_numr_FSC = r'[+-]?' + _digits_FSC
_numr_NFSC = r'[+-]? *' + _digits_NFSC
# This regex helps delete leading zeros from numbers, otherwise
# Python might evaluate them as octal values (this is not-greedy, however,
# so it may not strip leading zeros from a float, which is fine)
_number_FSC_RE = re.compile(r'(?P<sign>[+-])?0*?(?P<digt>{})'.format(
_digits_FSC))
_number_NFSC_RE = re.compile(r'(?P<sign>[+-])? *0*?(?P<digt>{})'.format(
_digits_NFSC))
# FSC commentary card string which must contain printable ASCII characters.
# Note: \Z matches the end of the string without allowing newlines
_ascii_text_re = re.compile(r'[ -~]*\Z')
# Checks for a valid value/comment string. It returns a match object
# for a valid value/comment string.
# The valu group will return a match if a FITS string, boolean,
# number, or complex value is found, otherwise it will return
# None, meaning the keyword is undefined. The comment field will
# return a match if the comment separator is found, though the
# comment maybe an empty string.
_value_FSC_RE = re.compile(
r'(?P<valu_field> *'
r'(?P<valu>'
# The <strg> regex is not correct for all cases, but
# it comes pretty darn close. It appears to find the
# end of a string rather well, but will accept
# strings with an odd number of single quotes,
# instead of issuing an error. The FITS standard
# appears vague on this issue and only states that a
# string should not end with two single quotes,
# whereas it should not end with an even number of
# quotes to be precise.
#
# Note that a non-greedy match is done for a string,
# since a greedy match will find a single-quote after
# the comment separator resulting in an incorrect
# match.
r'\'(?P<strg>([ -~]+?|\'\'|)) *?\'(?=$|/| )|'
r'(?P<bool>[FT])|'
r'(?P<numr>' + _numr_FSC + r')|'
r'(?P<cplx>\( *'
r'(?P<real>' + _numr_FSC + r') *, *'
r'(?P<imag>' + _numr_FSC + r') *\))'
r')? *)'
r'(?P<comm_field>'
r'(?P<sepr>/ *)'
r'(?P<comm>[!-~][ -~]*)?'
r')?$')
_value_NFSC_RE = re.compile(
r'(?P<valu_field> *'
r'(?P<valu>'
r'\'(?P<strg>([ -~]+?|\'\'|) *?)\'(?=$|/| )|'
r'(?P<bool>[FT])|'
r'(?P<numr>' + _numr_NFSC + r')|'
r'(?P<cplx>\( *'
r'(?P<real>' + _numr_NFSC + r') *, *'
r'(?P<imag>' + _numr_NFSC + r') *\))'
r')? *)'
r'(?P<comm_field>'
r'(?P<sepr>/ *)'
r'(?P<comm>(.|\n)*)'
r')?$')
_rvkc_identifier = r'[a-zA-Z_]\w*'
_rvkc_field = _rvkc_identifier + r'(\.\d+)?'
_rvkc_field_specifier_s = r'{}(\.{})*'.format(_rvkc_field, _rvkc_field)
_rvkc_field_specifier_val = (r'(?P<keyword>{}): (?P<val>{})'.format(
_rvkc_field_specifier_s, _numr_FSC))
_rvkc_keyword_val = r'\'(?P<rawval>{})\''.format(_rvkc_field_specifier_val)
_rvkc_keyword_val_comm = (r' *{} *(/ *(?P<comm>[ -~]*))?$'.format(
_rvkc_keyword_val))
_rvkc_field_specifier_val_RE = re.compile(_rvkc_field_specifier_val + '$')
# regular expression to extract the key and the field specifier from a
# string that is being used to index into a card list that contains
# record value keyword cards (ex. 'DP1.AXIS.1')
_rvkc_keyword_name_RE = (
re.compile(r'(?P<keyword>{})\.(?P<field_specifier>{})$'.format(
_rvkc_identifier, _rvkc_field_specifier_s)))
# regular expression to extract the field specifier and value and comment
# from the string value of a record value keyword card
# (ex "'AXIS.1: 1' / a comment")
_rvkc_keyword_val_comm_RE = re.compile(_rvkc_keyword_val_comm)
_commentary_keywords = {'', 'COMMENT', 'HISTORY', 'END'}
_special_keywords = _commentary_keywords.union(['CONTINUE'])
# The default value indicator; may be changed if required by a convention
# (namely HIERARCH cards)
_value_indicator = VALUE_INDICATOR
def __init__(self, keyword=None, value=None, comment=None, **kwargs):
# For backwards compatibility, support the 'key' keyword argument:
if keyword is None and 'key' in kwargs:
keyword = kwargs['key']
self._keyword = None
self._value = None
self._comment = None
self._valuestring = None
self._image = None
# This attribute is set to False when creating the card from a card
# image to ensure that the contents of the image get verified at some
# point
self._verified = True
# A flag to conveniently mark whether or not this was a valid HIERARCH
# card
self._hierarch = False
# If the card could not be parsed according the the FITS standard or
# any recognized non-standard conventions, this will be True
self._invalid = False
self._field_specifier = None
# These are used primarily only by RVKCs
self._rawkeyword = None
self._rawvalue = None
if not (keyword is not None and value is not None and
self._check_if_rvkc(keyword, value)):
# If _check_if_rvkc passes, it will handle setting the keyword and
# value
if keyword is not None:
self.keyword = keyword
if value is not None:
self.value = value
if comment is not None:
self.comment = comment
self._modified = False
self._valuemodified = False
def __repr__(self):
return repr((self.keyword, self.value, self.comment))
def __str__(self):
return self.image
def __len__(self):
return 3
def __getitem__(self, index):
return (self.keyword, self.value, self.comment)[index]
@property
def keyword(self):
"""Returns the keyword name parsed from the card image."""
if self._keyword is not None:
return self._keyword
elif self._image:
self._keyword = self._parse_keyword()
return self._keyword
else:
self.keyword = ''
return ''
@keyword.setter
def keyword(self, keyword):
"""Set the key attribute; once set it cannot be modified."""
if self._keyword is not None:
raise AttributeError(
'Once set, the Card keyword may not be modified')
elif isinstance(keyword, str):
# Be nice and remove trailing whitespace--some FITS code always
# pads keywords out with spaces; leading whitespace, however,
# should be strictly disallowed.
keyword = keyword.rstrip()
keyword_upper = keyword.upper()
if (len(keyword) <= KEYWORD_LENGTH and
self._keywd_FSC_RE.match(keyword_upper)):
# For keywords with length > 8 they will be HIERARCH cards,
# and can have arbitrary case keywords
if keyword_upper == 'END':
raise ValueError("Keyword 'END' not allowed.")
keyword = keyword_upper
elif self._keywd_hierarch_RE.match(keyword):
# In prior versions of PyFITS (*) HIERARCH cards would only be
# created if the user-supplied keyword explicitly started with
# 'HIERARCH '. Now we will create them automatically for long
# keywords, but we still want to support the old behavior too;
# the old behavior makes it possible to create HEIRARCH cards
# that would otherwise be recognized as RVKCs
# (*) This has never affected Astropy, because it was changed
# before PyFITS was merged into Astropy!
self._hierarch = True
self._value_indicator = HIERARCH_VALUE_INDICATOR
if keyword_upper[:9] == 'HIERARCH ':
# The user explicitly asked for a HIERARCH card, so don't
# bug them about it...
keyword = keyword[9:].strip()
else:
# We'll gladly create a HIERARCH card, but a warning is
# also displayed
warnings.warn(
'Keyword name {!r} is greater than 8 characters or '
'contains characters not allowed by the FITS '
'standard; a HIERARCH card will be created.'.format(
keyword), VerifyWarning)
else:
raise ValueError('Illegal keyword name: {!r}.'.format(keyword))
self._keyword = keyword
self._modified = True
else:
raise ValueError('Keyword name {!r} is not a string.'.format(keyword))
@property
def value(self):
"""The value associated with the keyword stored in this card."""
if self.field_specifier:
return float(self._value)
if self._value is not None:
value = self._value
elif self._valuestring is not None or self._image:
value = self._value = self._parse_value()
else:
if self._keyword == '':
self._value = value = ''
else:
self._value = value = UNDEFINED
if conf.strip_header_whitespace and isinstance(value, str):
value = value.rstrip()
return value
@value.setter
def value(self, value):
if self._invalid:
raise ValueError(
'The value of invalid/unparseable cards cannot set. Either '
'delete this card from the header or replace it.')
if value is None:
value = UNDEFINED
try:
oldvalue = self.value
except VerifyError:
# probably a parsing error, falling back to the internal _value
# which should be None. This may happen while calling _fix_value.
oldvalue = self._value
if oldvalue is None:
oldvalue = UNDEFINED
if not isinstance(value,
(str, int, float, complex, bool, Undefined,
np.floating, np.integer, np.complexfloating,
np.bool_)):
raise ValueError('Illegal value: {!r}.'.format(value))
if isinstance(value, float) and (np.isnan(value) or np.isinf(value)):
raise ValueError("Floating point {!r} values are not allowed "
"in FITS headers.".format(value))
elif isinstance(value, str):
m = self._ascii_text_re.match(value)
if not m:
raise ValueError(
'FITS header values must contain standard printable ASCII '
'characters; {!r} contains characters not representable in '
'ASCII or non-printable characters.'.format(value))
elif isinstance(value, bytes):
# Allow str, but only if they can be decoded to ASCII text; note
# this is not even allowed on Python 3 since the `bytes` type is
# not included in `str`. Presently we simply don't
# allow bytes to be assigned to headers, as doing so would too
# easily mask potential user error
valid = True
try:
text_value = value.decode('ascii')
except UnicodeDecodeError:
valid = False
else:
# Check against the printable characters regexp as well
m = self._ascii_text_re.match(text_value)
valid = m is not None
if not valid:
raise ValueError(
'FITS header values must contain standard printable ASCII '
'characters; {!r} contains characters/bytes that do not '
'represent printable characters in ASCII.'.format(value))
elif isinstance(value, np.bool_):
value = bool(value)
if (conf.strip_header_whitespace and
(isinstance(oldvalue, str) and isinstance(value, str))):
# Ignore extra whitespace when comparing the new value to the old
different = oldvalue.rstrip() != value.rstrip()
elif isinstance(oldvalue, bool) or isinstance(value, bool):
different = oldvalue is not value
else:
different = (oldvalue != value or
not isinstance(value, type(oldvalue)))
if different:
self._value = value
self._rawvalue = None
self._modified = True
self._valuestring = None
self._valuemodified = True
if self.field_specifier:
try:
self._value = _int_or_float(self._value)
except ValueError:
raise ValueError('value {} is not a float'.format(
self._value))
@value.deleter
def value(self):
if self._invalid:
raise ValueError(
'The value of invalid/unparseable cards cannot deleted. '
'Either delete this card from the header or replace it.')
if not self.field_specifier:
self.value = ''
else:
raise AttributeError('Values cannot be deleted from record-valued '
'keyword cards')
@property
def rawkeyword(self):
"""On record-valued keyword cards this is the name of the standard <= 8
character FITS keyword that this RVKC is stored in. Otherwise it is
the card's normal keyword.
"""
if self._rawkeyword is not None:
return self._rawkeyword
elif self.field_specifier is not None:
self._rawkeyword = self.keyword.split('.', 1)[0]
return self._rawkeyword
else:
return self.keyword
@property
def rawvalue(self):
"""On record-valued keyword cards this is the raw string value in
the ``<field-specifier>: <value>`` format stored in the card in order
to represent a RVKC. Otherwise it is the card's normal value.
"""
if self._rawvalue is not None:
return self._rawvalue
elif self.field_specifier is not None:
self._rawvalue = '{}: {}'.format(self.field_specifier, self.value)
return self._rawvalue
else:
return self.value
@property
def comment(self):
"""Get the comment attribute from the card image if not already set."""
if self._comment is not None:
return self._comment
elif self._image:
self._comment = self._parse_comment()
return self._comment
else:
self._comment = ''
return ''
@comment.setter
def comment(self, comment):
if self._invalid:
raise ValueError(
'The comment of invalid/unparseable cards cannot set. Either '
'delete this card from the header or replace it.')
if comment is None:
comment = ''
if isinstance(comment, str):
m = self._ascii_text_re.match(comment)
if not m:
raise ValueError(
'FITS header comments must contain standard printable '
'ASCII characters; {!r} contains characters not '
'representable in ASCII or non-printable characters.'
.format(comment))
try:
oldcomment = self.comment
except VerifyError:
# probably a parsing error, falling back to the internal _comment
# which should be None.
oldcomment = self._comment
if oldcomment is None:
oldcomment = ''
if comment != oldcomment:
self._comment = comment
self._modified = True
@comment.deleter
def comment(self):
if self._invalid:
raise ValueError(
'The comment of invalid/unparseable cards cannot deleted. '
'Either delete this card from the header or replace it.')
self.comment = ''
@property
def field_specifier(self):
"""
The field-specifier of record-valued keyword cards; always `None` on
normal cards.
"""
# Ensure that the keyword exists and has been parsed--the will set the
# internal _field_specifier attribute if this is a RVKC.
if self.keyword:
return self._field_specifier
else:
return None
@field_specifier.setter
def field_specifier(self, field_specifier):
if not field_specifier:
raise ValueError('The field-specifier may not be blank in '
'record-valued keyword cards.')
elif not self.field_specifier:
raise AttributeError('Cannot coerce cards to be record-valued '
'keyword cards by setting the '
'field_specifier attribute')
elif field_specifier != self.field_specifier:
self._field_specifier = field_specifier
# The keyword need also be updated
keyword = self._keyword.split('.', 1)[0]
self._keyword = '.'.join([keyword, field_specifier])
self._modified = True
@field_specifier.deleter
def field_specifier(self):
raise AttributeError('The field_specifier attribute may not be '
'deleted from record-valued keyword cards.')
@property
def image(self):
"""
The card "image", that is, the 80 byte character string that represents
this card in an actual FITS header.
"""
if self._image and not self._verified:
self.verify('fix+warn')
if self._image is None or self._modified:
self._image = self._format_image()
return self._image
@property
def is_blank(self):
"""
`True` if the card is completely blank--that is, it has no keyword,
value, or comment. It appears in the header as 80 spaces.
Returns `False` otherwise.
"""
if not self._verified:
# The card image has not been parsed yet; compare directly with the
# string representation of a blank card
return self._image == BLANK_CARD
# If the keyword, value, and comment are all empty (for self.value
# explicitly check that it is a string value, since a blank value is
# returned as '')
return (not self.keyword and
(isinstance(self.value, str) and not self.value) and
not self.comment)
@classmethod
def fromstring(cls, image):
"""
Construct a `Card` object from a (raw) string. It will pad the string
if it is not the length of a card image (80 columns). If the card
image is longer than 80 columns, assume it contains ``CONTINUE``
card(s).
"""
card = cls()
card._image = _pad(image)
card._verified = False
return card
@classmethod
def normalize_keyword(cls, keyword):
"""
`classmethod` to convert a keyword value that may contain a
field-specifier to uppercase. The effect is to raise the key to
uppercase and leave the field specifier in its original case.
Parameters
----------
keyword : or str
A keyword value or a ``keyword.field-specifier`` value
"""
# Test first for the most common case: a standard FITS keyword provided
# in standard all-caps
if (len(keyword) <= KEYWORD_LENGTH and
cls._keywd_FSC_RE.match(keyword)):
return keyword
# Test if this is a record-valued keyword
match = cls._rvkc_keyword_name_RE.match(keyword)
if match:
return '.'.join((match.group('keyword').strip().upper(),
match.group('field_specifier')))
elif len(keyword) > 9 and keyword[:9].upper() == 'HIERARCH ':
# Remove 'HIERARCH' from HIERARCH keywords; this could lead to
# ambiguity if there is actually a keyword card containing
# "HIERARCH HIERARCH", but shame on you if you do that.
return keyword[9:].strip().upper()
else:
# A normal FITS keyword, but provided in non-standard case
return keyword.strip().upper()
def _check_if_rvkc(self, *args):
"""
Determine whether or not the card is a record-valued keyword card.
If one argument is given, that argument is treated as a full card image
and parsed as such. If two arguments are given, the first is treated
as the card keyword (including the field-specifier if the card is
intended as a RVKC), and the second as the card value OR the first value
can be the base keyword, and the second value the 'field-specifier:
value' string.
If the check passes the ._keyword, ._value, and .field_specifier
keywords are set.
Examples
--------
::
self._check_if_rvkc('DP1', 'AXIS.1: 2')
self._check_if_rvkc('DP1.AXIS.1', 2)
self._check_if_rvkc('DP1 = AXIS.1: 2')
"""
if not conf.enable_record_valued_keyword_cards:
return False
if len(args) == 1:
return self._check_if_rvkc_image(*args)
elif len(args) == 2:
keyword, value = args
if not isinstance(keyword, str):
return False
if keyword in self._commentary_keywords:
return False
match = self._rvkc_keyword_name_RE.match(keyword)
if match and isinstance(value, (int, float)):
self._init_rvkc(match.group('keyword'),
match.group('field_specifier'), None, value)
return True
# Testing for ': ' is a quick way to avoid running the full regular
# expression, speeding this up for the majority of cases
if isinstance(value, str) and value.find(': ') > 0:
match = self._rvkc_field_specifier_val_RE.match(value)
if match and self._keywd_FSC_RE.match(keyword):
self._init_rvkc(keyword, match.group('keyword'), value,
match.group('val'))
return True
def _check_if_rvkc_image(self, *args):
"""
Implements `Card._check_if_rvkc` for the case of an unparsed card
image. If given one argument this is the full intact image. If given
two arguments the card has already been split between keyword and
value+comment at the standard value indicator '= '.
"""
if len(args) == 1:
image = args[0]
eq_idx = image.find(VALUE_INDICATOR)
if eq_idx < 0 or eq_idx > 9:
return False
keyword = image[:eq_idx]
rest = image[eq_idx + VALUE_INDICATOR_LEN:]
else:
keyword, rest = args
rest = rest.lstrip()
# This test allows us to skip running the full regular expression for
# the majority of cards that do not contain strings or that definitely
# do not contain RVKC field-specifiers; it's very much a
# micro-optimization but it does make a measurable difference
if not rest or rest[0] != "'" or rest.find(': ') < 2:
return False
match = self._rvkc_keyword_val_comm_RE.match(rest)
if match:
self._init_rvkc(keyword, match.group('keyword'),
match.group('rawval'), match.group('val'))
return True
def _init_rvkc(self, keyword, field_specifier, field, value):
"""
Sort of addendum to Card.__init__ to set the appropriate internal
attributes if the card was determined to be a RVKC.
"""
keyword_upper = keyword.upper()
self._keyword = '.'.join((keyword_upper, field_specifier))
self._rawkeyword = keyword_upper
self._field_specifier = field_specifier
self._value = _int_or_float(value)
self._rawvalue = field
def _parse_keyword(self):
keyword = self._image[:KEYWORD_LENGTH].strip()
keyword_upper = keyword.upper()
if keyword_upper in self._special_keywords:
return keyword_upper
elif (keyword_upper == 'HIERARCH' and self._image[8] == ' ' and
HIERARCH_VALUE_INDICATOR in self._image):
# This is valid HIERARCH card as described by the HIERARCH keyword
# convention:
# http://fits.gsfc.nasa.gov/registry/hierarch_keyword.html
self._hierarch = True
self._value_indicator = HIERARCH_VALUE_INDICATOR
keyword = self._image.split(HIERARCH_VALUE_INDICATOR, 1)[0][9:]
return keyword.strip()
else:
val_ind_idx = self._image.find(VALUE_INDICATOR)
if 0 <= val_ind_idx <= KEYWORD_LENGTH:
# The value indicator should appear in byte 8, but we are
# flexible and allow this to be fixed
if val_ind_idx < KEYWORD_LENGTH:
keyword = keyword[:val_ind_idx]
keyword_upper = keyword_upper[:val_ind_idx]
rest = self._image[val_ind_idx + VALUE_INDICATOR_LEN:]
# So far this looks like a standard FITS keyword; check whether
# the value represents a RVKC; if so then we pass things off to
# the RVKC parser
if self._check_if_rvkc_image(keyword, rest):
return self._keyword
return keyword_upper
else:
warnings.warn(
'The following header keyword is invalid or follows an '
'unrecognized non-standard convention:\n{}'
.format(self._image), AstropyUserWarning)
self._invalid = True
return keyword
def _parse_value(self):
"""Extract the keyword value from the card image."""
# for commentary cards, no need to parse further
# Likewise for invalid cards
if self.keyword.upper() in self._commentary_keywords or self._invalid:
return self._image[KEYWORD_LENGTH:].rstrip()
if self._check_if_rvkc(self._image):
return self._value
if len(self._image) > self.length:
values = []
for card in self._itersubcards():
value = card.value.rstrip().replace("''", "'")
if value and value[-1] == '&':
value = value[:-1]
values.append(value)
value = ''.join(values)
self._valuestring = value
return value
m = self._value_NFSC_RE.match(self._split()[1])
if m is None:
raise VerifyError("Unparsable card ({}), fix it first with "
".verify('fix').".format(self.keyword))
if m.group('bool') is not None:
value = m.group('bool') == 'T'
elif m.group('strg') is not None:
value = re.sub("''", "'", m.group('strg'))
elif m.group('numr') is not None:
# Check for numbers with leading 0s.
numr = self._number_NFSC_RE.match(m.group('numr'))
digt = translate(numr.group('digt'), FIX_FP_TABLE2, ' ')
if numr.group('sign') is None:
sign = ''
else:
sign = numr.group('sign')
value = _str_to_num(sign + digt)
elif m.group('cplx') is not None:
# Check for numbers with leading 0s.
real = self._number_NFSC_RE.match(m.group('real'))
rdigt = translate(real.group('digt'), FIX_FP_TABLE2, ' ')
if real.group('sign') is None:
rsign = ''
else:
rsign = real.group('sign')
value = _str_to_num(rsign + rdigt)
imag = self._number_NFSC_RE.match(m.group('imag'))
idigt = translate(imag.group('digt'), FIX_FP_TABLE2, ' ')
if imag.group('sign') is None:
isign = ''
else:
isign = imag.group('sign')
value += _str_to_num(isign + idigt) * 1j
else:
value = UNDEFINED
if not self._valuestring:
self._valuestring = m.group('valu')
return value
def _parse_comment(self):
"""Extract the keyword value from the card image."""
# for commentary cards, no need to parse further
# likewise for invalid/unparseable cards
if self.keyword in Card._commentary_keywords or self._invalid:
return ''
if len(self._image) > self.length:
comments = []
for card in self._itersubcards():
if card.comment:
comments.append(card.comment)
comment = '/ ' + ' '.join(comments).rstrip()
m = self._value_NFSC_RE.match(comment)
else:
m = self._value_NFSC_RE.match(self._split()[1])
if m is not None:
comment = m.group('comm')
if comment:
return comment.rstrip()
return ''
def _split(self):
"""
Split the card image between the keyword and the rest of the card.
"""
if self._image is not None:
# If we already have a card image, don't try to rebuild a new card
# image, which self.image would do
image = self._image
else:
image = self.image
if self.keyword in self._special_keywords:
keyword, valuecomment = image.split(' ', 1)
else:
try:
delim_index = image.index(self._value_indicator)
except ValueError:
delim_index = None
# The equal sign may not be any higher than column 10; anything
# past that must be considered part of the card value
if delim_index is None:
keyword = image[:KEYWORD_LENGTH]
valuecomment = image[KEYWORD_LENGTH:]
elif delim_index > 10 and image[:9] != 'HIERARCH ':
keyword = image[:8]
valuecomment = image[8:]
else:
keyword, valuecomment = image.split(self._value_indicator, 1)
return keyword.strip(), valuecomment.strip()
def _fix_keyword(self):
if self.field_specifier:
keyword, field_specifier = self._keyword.split('.', 1)
self._keyword = '.'.join([keyword.upper(), field_specifier])
else:
self._keyword = self._keyword.upper()
self._modified = True
def _fix_value(self):
"""Fix the card image for fixable non-standard compliance."""
value = None
keyword, valuecomment = self._split()
m = self._value_NFSC_RE.match(valuecomment)
# for the unparsable case
if m is None:
try:
value, comment = valuecomment.split('/', 1)
self.value = value.strip()
self.comment = comment.strip()
except (ValueError, IndexError):
self.value = valuecomment
self._valuestring = self._value
return
elif m.group('numr') is not None:
numr = self._number_NFSC_RE.match(m.group('numr'))
value = translate(numr.group('digt'), FIX_FP_TABLE, ' ')
if numr.group('sign') is not None:
value = numr.group('sign') + value
elif m.group('cplx') is not None:
real = self._number_NFSC_RE.match(m.group('real'))
rdigt = translate(real.group('digt'), FIX_FP_TABLE, ' ')
if real.group('sign') is not None:
rdigt = real.group('sign') + rdigt
imag = self._number_NFSC_RE.match(m.group('imag'))
idigt = translate(imag.group('digt'), FIX_FP_TABLE, ' ')
if imag.group('sign') is not None:
idigt = imag.group('sign') + idigt
value = '({}, {})'.format(rdigt, idigt)
self._valuestring = value
# The value itself has not been modified, but its serialized
# representation (as stored in self._valuestring) has been changed, so
# still set this card as having been modified (see ticket #137)
self._modified = True
def _format_keyword(self):
if self.keyword:
if self.field_specifier:
return '{:{len}}'.format(self.keyword.split('.', 1)[0],
len=KEYWORD_LENGTH)
elif self._hierarch:
return 'HIERARCH {} '.format(self.keyword)
else:
return '{:{len}}'.format(self.keyword, len=KEYWORD_LENGTH)
else:
return ' ' * KEYWORD_LENGTH
def _format_value(self):
# value string
float_types = (float, np.floating, complex, np.complexfloating)
# Force the value to be parsed out first
value = self.value
# But work with the underlying raw value instead (to preserve
# whitespace, for now...)
value = self._value
if self.keyword in self._commentary_keywords:
# The value of a commentary card must be just a raw unprocessed
# string
value = str(value)
elif (self._valuestring and not self._valuemodified and
isinstance(self.value, float_types)):
# Keep the existing formatting for float/complex numbers
value = '{:>20}'.format(self._valuestring)
elif self.field_specifier:
value = _format_value(self._value).strip()
value = "'{}: {}'".format(self.field_specifier, value)
else:
value = _format_value(value)
# For HIERARCH cards the value should be shortened to conserve space
if not self.field_specifier and len(self.keyword) > KEYWORD_LENGTH:
value = value.strip()
return value
def _format_comment(self):
if not self.comment:
return ''
else:
return ' / {}'.format(self._comment)
def _format_image(self):
keyword = self._format_keyword()
value = self._format_value()
is_commentary = keyword.strip() in self._commentary_keywords
if is_commentary:
comment = ''
else:
comment = self._format_comment()
# equal sign string
# by default use the standard value indicator even for HIERARCH cards;
# later we may abbreviate it if necessary
delimiter = VALUE_INDICATOR
if is_commentary:
delimiter = ''
# put all parts together
output = ''.join([keyword, delimiter, value, comment])
# For HIERARCH cards we can save a bit of space if necessary by
# removing the space between the keyword and the equals sign; I'm
# guessing this is part of the HIEARCH card specification
keywordvalue_length = len(keyword) + len(delimiter) + len(value)
if (keywordvalue_length > self.length and
keyword.startswith('HIERARCH')):
if (keywordvalue_length == self.length + 1 and keyword[-1] == ' '):
output = ''.join([keyword[:-1], delimiter, value, comment])
else:
# I guess the HIERARCH card spec is incompatible with CONTINUE
# cards
raise ValueError('The header keyword {!r} with its value is '
'too long'.format(self.keyword))
if len(output) <= self.length:
output = '{:80}'.format(output)
else:
# longstring case (CONTINUE card)
# try not to use CONTINUE if the string value can fit in one line.
# Instead, just truncate the comment
if (isinstance(self.value, str) and
len(value) > (self.length - 10)):
output = self._format_long_image()
else:
warnings.warn('Card is too long, comment will be truncated.',
VerifyWarning)
output = output[:Card.length]
return output
def _format_long_image(self):
"""
Break up long string value/comment into ``CONTINUE`` cards.
This is a primitive implementation: it will put the value
string in one block and the comment string in another. Also,
it does not break at the blank space between words. So it may
not look pretty.
"""
if self.keyword in Card._commentary_keywords:
return self._format_long_commentary_image()
value_length = 67
comment_length = 64
output = []
# do the value string
value = self._value.replace("'", "''")
words = _words_group(value, value_length)
for idx, word in enumerate(words):
if idx == 0:
headstr = '{:{len}}= '.format(self.keyword, len=KEYWORD_LENGTH)
else:
headstr = 'CONTINUE '
# If this is the final CONTINUE remove the '&'
if not self.comment and idx == len(words) - 1:
value_format = "'{}'"
else:
value_format = "'{}&'"
value = value_format.format(word)
output.append('{:80}'.format(headstr + value))
# do the comment string
comment_format = "{}"
if self.comment:
words = _words_group(self.comment, comment_length)
for idx, word in enumerate(words):
# If this is the final CONTINUE remove the '&'
if idx == len(words) - 1:
headstr = "CONTINUE '' / "
else:
headstr = "CONTINUE '&' / "
comment = headstr + comment_format.format(word)
output.append('{:80}'.format(comment))
return ''.join(output)
def _format_long_commentary_image(self):
"""
If a commentary card's value is too long to fit on a single card, this
will render the card as multiple consecutive commentary card of the
same type.
"""
maxlen = Card.length - KEYWORD_LENGTH
value = self._format_value()
output = []
idx = 0
while idx < len(value):
output.append(str(Card(self.keyword, value[idx:idx + maxlen])))
idx += maxlen
return ''.join(output)
def _verify(self, option='warn'):
self._verified = True
errs = _ErrList([])
fix_text = ('Fixed {!r} card to meet the FITS '
'standard.'.format(self.keyword))
# Don't try to verify cards that already don't meet any recognizable
# standard
if self._invalid:
return errs
# verify the equal sign position
if (self.keyword not in self._commentary_keywords and
(self._image and self._image[:9].upper() != 'HIERARCH ' and
self._image.find('=') != 8)):
errs.append(self.run_option(
option,
err_text='Card {!r} is not FITS standard (equal sign not '
'at column 8).'.format(self.keyword),
fix_text=fix_text,
fix=self._fix_value))
# verify the key, it is never fixable
# always fix silently the case where "=" is before column 9,
# since there is no way to communicate back to the _keys.
if ((self._image and self._image[:8].upper() == 'HIERARCH') or
self._hierarch):
pass
else:
if self._image:
# PyFITS will auto-uppercase any standard keyword, so lowercase
# keywords can only occur if they came from the wild
keyword = self._split()[0]
if keyword != keyword.upper():
# Keyword should be uppercase unless it's a HIERARCH card
errs.append(self.run_option(
option,
err_text='Card keyword {!r} is not upper case.'.format(
keyword),
fix_text=fix_text,
fix=self._fix_keyword))
keyword = self.keyword
if self.field_specifier:
keyword = keyword.split('.', 1)[0]
if not self._keywd_FSC_RE.match(keyword):
errs.append(self.run_option(
option,
err_text='Illegal keyword name {!r}'.format(keyword),
fixable=False))
# verify the value, it may be fixable
keyword, valuecomment = self._split()
if self.keyword in self._commentary_keywords:
# For commentary keywords all that needs to be ensured is that it
# contains only printable ASCII characters
if not self._ascii_text_re.match(valuecomment):
errs.append(self.run_option(
option,
err_text='Unprintable string {!r}; commentary cards may '
'only contain printable ASCII characters'.format(
valuecomment),
fixable=False))
else:
m = self._value_FSC_RE.match(valuecomment)
if not m:
errs.append(self.run_option(
option,
err_text='Card {!r} is not FITS standard (invalid value '
'string: {!r}).'.format(self.keyword, valuecomment),
fix_text=fix_text,
fix=self._fix_value))
# verify the comment (string), it is never fixable
m = self._value_NFSC_RE.match(valuecomment)
if m is not None:
comment = m.group('comm')
if comment is not None:
if not self._ascii_text_re.match(comment):
errs.append(self.run_option(
option,
err_text=('Unprintable string {!r}; header comments '
'may only contain printable ASCII '
'characters'.format(comment)),
fixable=False))
return errs
def _itersubcards(self):
"""
If the card image is greater than 80 characters, it should consist of a
normal card followed by one or more CONTINUE card. This method returns
the subcards that make up this logical card.
"""
ncards = len(self._image) // Card.length
for idx in range(0, Card.length * ncards, Card.length):
card = Card.fromstring(self._image[idx:idx + Card.length])
if idx > 0 and card.keyword.upper() != 'CONTINUE':
raise VerifyError(
'Long card images must have CONTINUE cards after '
'the first card.')
if not isinstance(card.value, str):
raise VerifyError('CONTINUE cards must have string values.')
yield card
def _int_or_float(s):
"""
Converts an a string to an int if possible, or to a float.
If the string is neither a string or a float a value error is raised.
"""
if isinstance(s, float):
# Already a float so just pass through
return s
try:
return int(s)
except (ValueError, TypeError):
try:
return float(s)
except (ValueError, TypeError) as e:
raise ValueError(str(e))
def _format_value(value):
"""
Converts a card value to its appropriate string representation as
defined by the FITS format.
"""
# string value should occupies at least 8 columns, unless it is
# a null string
if isinstance(value, str):
if value == '':
return "''"
else:
exp_val_str = value.replace("'", "''")
val_str = "'{:8}'".format(exp_val_str)
return '{:20}'.format(val_str)
# must be before int checking since bool is also int
elif isinstance(value, (bool, np.bool_)):
return '{:>20}'.format(repr(value)[0]) # T or F
elif _is_int(value):
return '{:>20d}'.format(value)
elif isinstance(value, (float, np.floating)):
return '{:>20}'.format(_format_float(value))
elif isinstance(value, (complex, np.complexfloating)):
val_str = '({}, {})'.format(_format_float(value.real),
_format_float(value.imag))
return '{:>20}'.format(val_str)
elif isinstance(value, Undefined):
return ''
else:
return ''
def _format_float(value):
"""Format a floating number to make sure it gets the decimal point."""
value_str = '{:.16G}'.format(value)
if '.' not in value_str and 'E' not in value_str:
value_str += '.0'
elif 'E' in value_str:
# On some Windows builds of Python (and possibly other platforms?) the
# exponent is zero-padded out to, it seems, three digits. Normalize
# the format to pad only to two digits.
significand, exponent = value_str.split('E')
if exponent[0] in ('+', '-'):
sign = exponent[0]
exponent = exponent[1:]
else:
sign = ''
value_str = '{}E{}{:02d}'.format(significand, sign, int(exponent))
# Limit the value string to at most 20 characters.
str_len = len(value_str)
if str_len > 20:
idx = value_str.find('E')
if idx < 0:
value_str = value_str[:20]
else:
value_str = value_str[:20 - (str_len - idx)] + value_str[idx:]
return value_str
def _pad(input):
"""Pad blank space to the input string to be multiple of 80."""
_len = len(input)
if _len == Card.length:
return input
elif _len > Card.length:
strlen = _len % Card.length
if strlen == 0:
return input
else:
return input + ' ' * (Card.length - strlen)
# minimum length is 80
else:
strlen = _len % Card.length
return input + ' ' * (Card.length - strlen)
|
c5b2a7e48d3d693294ae49082db4e3697bf30397ca74faf24987423a57c00b21 | # Licensed under a 3-clause BSD style license - see PYFITS.rst
import operator
import warnings
from astropy.utils import indent
from astropy.utils.exceptions import AstropyUserWarning
class VerifyError(Exception):
"""
Verify exception class.
"""
class VerifyWarning(AstropyUserWarning):
"""
Verify warning class.
"""
VERIFY_OPTIONS = ['ignore', 'warn', 'exception', 'fix', 'silentfix',
'fix+ignore', 'fix+warn', 'fix+exception',
'silentfix+ignore', 'silentfix+warn', 'silentfix+exception']
class _Verify:
"""
Shared methods for verification.
"""
def run_option(self, option='warn', err_text='', fix_text='Fixed.',
fix=None, fixable=True):
"""
Execute the verification with selected option.
"""
text = err_text
if option in ['warn', 'exception']:
fixable = False
# fix the value
elif not fixable:
text = 'Unfixable error: {}'.format(text)
else:
if fix:
fix()
text += ' ' + fix_text
return (fixable, text)
def verify(self, option='warn'):
"""
Verify all values in the instance.
Parameters
----------
option : str
Output verification option. Must be one of ``"fix"``,
``"silentfix"``, ``"ignore"``, ``"warn"``, or
``"exception"``. May also be any combination of ``"fix"`` or
``"silentfix"`` with ``"+ignore"``, ``+warn``, or ``+exception"
(e.g. ``"fix+warn"``). See :ref:`verify` for more info.
"""
opt = option.lower()
if opt not in VERIFY_OPTIONS:
raise ValueError('Option {!r} not recognized.'.format(option))
if opt == 'ignore':
return
errs = self._verify(opt)
# Break the verify option into separate options related to reporting of
# errors, and fixing of fixable errors
if '+' in opt:
fix_opt, report_opt = opt.split('+')
elif opt in ['fix', 'silentfix']:
# The original default behavior for 'fix' and 'silentfix' was to
# raise an exception for unfixable errors
fix_opt, report_opt = opt, 'exception'
else:
fix_opt, report_opt = None, opt
if fix_opt == 'silentfix' and report_opt == 'ignore':
# Fixable errors were fixed, but don't report anything
return
if fix_opt == 'silentfix':
# Don't print out fixable issues; the first element of each verify
# item is a boolean indicating whether or not the issue was fixable
line_filter = lambda x: not x[0]
elif fix_opt == 'fix' and report_opt == 'ignore':
# Don't print *unfixable* issues, but do print fixed issues; this
# is probably not very useful but the option exists for
# completeness
line_filter = operator.itemgetter(0)
else:
line_filter = None
unfixable = False
messages = []
for fixable, message in errs.iter_lines(filter=line_filter):
if fixable is not None:
unfixable = not fixable
messages.append(message)
if messages:
messages.insert(0, 'Verification reported errors:')
messages.append('Note: astropy.io.fits uses zero-based indexing.\n')
if fix_opt == 'silentfix' and not unfixable:
return
elif report_opt == 'warn' or (fix_opt == 'fix' and not unfixable):
for line in messages:
warnings.warn(line, VerifyWarning)
else:
raise VerifyError('\n' + '\n'.join(messages))
class _ErrList(list):
"""
Verification errors list class. It has a nested list structure
constructed by error messages generated by verifications at
different class levels.
"""
def __init__(self, val=(), unit='Element'):
super().__init__(val)
self.unit = unit
def __str__(self):
return '\n'.join(item[1] for item in self.iter_lines())
def iter_lines(self, filter=None, shift=0):
"""
Iterate the nested structure as a list of strings with appropriate
indentations for each level of structure.
"""
element = 0
# go through the list twice, first time print out all top level
# messages
for item in self:
if not isinstance(item, _ErrList):
if filter is None or filter(item):
yield item[0], indent(item[1], shift=shift)
# second time go through the next level items, each of the next level
# must present, even it has nothing.
for item in self:
if isinstance(item, _ErrList):
next_lines = item.iter_lines(filter=filter, shift=shift + 1)
try:
first_line = next(next_lines)
except StopIteration:
first_line = None
if first_line is not None:
if self.unit:
# This line is sort of a header for the next level in
# the hierarchy
yield None, indent('{} {}:'.format(self.unit, element),
shift=shift)
yield first_line
for line in next_lines:
yield line
element += 1
|
ecb86193458442f2ecabb14b8c24ee172aa8705c1af3fc88b9474698acd70d0d | # Licensed under a 3-clause BSD style license - see LICENSE.rst
"""An extensible ASCII table reader and writer.
cds.py:
Classes to read CDS / Vizier table format
:Copyright: Smithsonian Astrophysical Observatory (2011)
:Author: Tom Aldcroft ([email protected])
"""
import fnmatch
import itertools
import re
import os
from contextlib import suppress
from . import core
from . import fixedwidth
from astropy.units import Unit
__doctest_skip__ = ['*']
class CdsHeader(core.BaseHeader):
col_type_map = {'e': core.FloatType,
'f': core.FloatType,
'i': core.IntType,
'a': core.StrType}
'The ReadMe file to construct header from.'
readme = None
def get_type_map_key(self, col):
match = re.match(r'\d*(\S)', col.raw_type.lower())
if not match:
raise ValueError('Unrecognized CDS format "{}" for column "{}"'.format(
col.raw_type, col.name))
return match.group(1)
def get_cols(self, lines):
"""
Initialize the header Column objects from the table ``lines`` for a CDS
header.
Parameters
----------
lines : list
List of table lines
"""
# Read header block for the table ``self.data.table_name`` from the read
# me file ``self.readme``.
if self.readme and self.data.table_name:
in_header = False
readme_inputter = core.BaseInputter()
f = readme_inputter.get_lines(self.readme)
# Header info is not in data lines but in a separate file.
lines = []
comment_lines = 0
for line in f:
line = line.strip()
if in_header:
lines.append(line)
if line.startswith(('------', '=======')):
comment_lines += 1
if comment_lines == 3:
break
else:
match = re.match(r'Byte-by-byte Description of file: (?P<name>.+)$',
line, re.IGNORECASE)
if match:
# Split 'name' in case in contains multiple files
names = [s for s in re.split('[, ]+', match.group('name'))
if s]
# Iterate on names to find if one matches the tablename
# including wildcards.
for pattern in names:
if fnmatch.fnmatch(self.data.table_name, pattern):
in_header = True
lines.append(line)
break
else:
raise core.InconsistentTableError("Can't find table {0} in {1}".format(
self.data.table_name, self.readme))
found_line = False
for i_col_def, line in enumerate(lines):
if re.match(r'Byte-by-byte Description', line, re.IGNORECASE):
found_line = True
elif found_line: # First line after list of file descriptions
i_col_def -= 1 # Set i_col_def to last description line
break
re_col_def = re.compile(r"""\s*
(?P<start> \d+ \s* -)? \s*
(?P<end> \d+) \s+
(?P<format> [\w.]+) \s+
(?P<units> \S+) \s+
(?P<name> \S+)
(\s+ (?P<descr> \S.*))?""",
re.VERBOSE)
cols = []
for line in itertools.islice(lines, i_col_def+4, None):
if line.startswith(('------', '=======')):
break
match = re_col_def.match(line)
if match:
col = core.Column(name=match.group('name'))
col.start = int(re.sub(r'[-\s]', '',
match.group('start') or match.group('end'))) - 1
col.end = int(match.group('end'))
unit = match.group('units')
if unit == '---':
col.unit = None # "---" is the marker for no unit in CDS table
else:
col.unit = Unit(unit, format='cds', parse_strict='warn')
col.description = (match.group('descr') or '').strip()
col.raw_type = match.group('format')
col.type = self.get_col_type(col)
match = re.match(
r'\? (?P<equal> =)? (?P<nullval> \S*) (\s+ (?P<descriptiontext> \S.*))?', col.description, re.VERBOSE)
if match:
col.description = (match.group('descriptiontext') or '').strip()
if issubclass(col.type, core.FloatType):
fillval = 'nan'
else:
fillval = '0'
if match.group('nullval') == '-':
col.null = '---'
# CDS tables can use -, --, ---, or ---- to mark missing values
# see https://github.com/astropy/astropy/issues/1335
for i in [1, 2, 3, 4]:
self.data.fill_values.append(('-'*i, fillval, col.name))
else:
col.null = match.group('nullval')
self.data.fill_values.append((col.null, fillval, col.name))
cols.append(col)
else: # could be a continuation of the previous col's description
if cols:
cols[-1].description += line.strip()
else:
raise ValueError('Line "{}" not parsable as CDS header'.format(line))
self.names = [x.name for x in cols]
self.cols = cols
class CdsData(core.BaseData):
"""CDS table data reader
"""
splitter_class = fixedwidth.FixedWidthSplitter
def process_lines(self, lines):
"""Skip over CDS header by finding the last section delimiter"""
# If the header has a ReadMe and data has a filename
# then no need to skip, as the data lines do not have header
# info. The ``read`` method adds the table_name to the ``data``
# attribute.
if self.header.readme and self.table_name:
return lines
i_sections = [i for i, x in enumerate(lines)
if x.startswith(('------', '======='))]
if not i_sections:
raise core.InconsistentTableError('No CDS section delimiter found')
return lines[i_sections[-1]+1:]
class Cds(core.BaseReader):
"""CDS format table.
See: http://vizier.u-strasbg.fr/doc/catstd.htx
Example::
Table: Table name here
= ==============================================================================
Catalog reference paper
Bibliography info here
================================================================================
ADC_Keywords: Keyword ; Another keyword ; etc
Description:
Catalog description here.
================================================================================
Byte-by-byte Description of file: datafile3.txt
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 3 I3 --- Index Running identification number
5- 6 I2 h RAh Hour of Right Ascension (J2000)
8- 9 I2 min RAm Minute of Right Ascension (J2000)
11- 15 F5.2 s RAs Second of Right Ascension (J2000)
--------------------------------------------------------------------------------
Note (1): A CDS file can contain sections with various metadata.
Notes can be multiple lines.
Note (2): Another note.
--------------------------------------------------------------------------------
1 03 28 39.09
2 04 18 24.11
**About parsing the CDS format**
The CDS format consists of a table description and the table data. These
can be in separate files as a ``ReadMe`` file plus data file(s), or
combined in a single file. Different subsections within the description
are separated by lines of dashes or equal signs ("------" or "======").
The table which specifies the column information must be preceded by a line
starting with "Byte-by-byte Description of file:".
In the case where the table description is combined with the data values,
the data must be in the last section and must be preceded by a section
delimiter line (dashes or equal signs only).
**Basic usage**
Use the ``ascii.read()`` function as normal, with an optional ``readme``
parameter indicating the CDS ReadMe file. If not supplied it is assumed that
the header information is at the top of the given table. Examples::
>>> from astropy.io import ascii
>>> table = ascii.read("data/cds.dat")
>>> table = ascii.read("data/vizier/table1.dat", readme="data/vizier/ReadMe")
>>> table = ascii.read("data/cds/multi/lhs2065.dat", readme="data/cds/multi/ReadMe")
>>> table = ascii.read("data/cds/glob/lmxbrefs.dat", readme="data/cds/glob/ReadMe")
The table name and the CDS ReadMe file can be entered as URLs. This can be used
to directly load tables from the Internet. For example, Vizier tables from the
CDS::
>>> table = ascii.read("ftp://cdsarc.u-strasbg.fr/pub/cats/VII/253/snrs.dat",
... readme="ftp://cdsarc.u-strasbg.fr/pub/cats/VII/253/ReadMe")
If the header (ReadMe) and data are stored in a single file and there
is content between the header and the data (for instance Notes), then the
parsing process may fail. In this case you can instruct the reader to
guess the actual start of the data by supplying ``data_start='guess'`` in the
call to the ``ascii.read()`` function. You should verify that the output
data table matches expectation based on the input CDS file.
**Using a reader object**
When ``Cds`` reader object is created with a ``readme`` parameter
passed to it at initialization, then when the ``read`` method is
executed with a table filename, the header information for the
specified table is taken from the ``readme`` file. An
``InconsistentTableError`` is raised if the ``readme`` file does not
have header information for the given table.
>>> readme = "data/vizier/ReadMe"
>>> r = ascii.get_reader(ascii.Cds, readme=readme)
>>> table = r.read("data/vizier/table1.dat")
>>> # table5.dat has the same ReadMe file
>>> table = r.read("data/vizier/table5.dat")
If no ``readme`` parameter is specified, then the header
information is assumed to be at the top of the given table.
>>> r = ascii.get_reader(ascii.Cds)
>>> table = r.read("data/cds.dat")
>>> #The following gives InconsistentTableError, since no
>>> #readme file was given and table1.dat does not have a header.
>>> table = r.read("data/vizier/table1.dat")
Traceback (most recent call last):
...
InconsistentTableError: No CDS section delimiter found
Caveats:
* The Units and Explanations are available in the column ``unit`` and
``description`` attributes, respectively.
* The other metadata defined by this format is not available in the output table.
"""
_format_name = 'cds'
_io_registry_format_aliases = ['cds']
_io_registry_can_write = False
_description = 'CDS format table'
data_class = CdsData
header_class = CdsHeader
def __init__(self, readme=None):
super().__init__()
self.header.readme = readme
def write(self, table=None):
"""Not available for the Cds class (raises NotImplementedError)"""
raise NotImplementedError
def read(self, table):
# If the read kwarg `data_start` is 'guess' then the table may have extraneous
# lines between the end of the header and the beginning of data.
if self.data.start_line == 'guess':
# Replicate the first part of BaseReader.read up to the point where
# the table lines are initially read in.
with suppress(TypeError):
# For strings only
if os.linesep not in table + '':
self.data.table_name = os.path.basename(table)
self.data.header = self.header
self.header.data = self.data
# Get a list of the lines (rows) in the table
lines = self.inputter.get_lines(table)
# Now try increasing data.start_line by one until the table reads successfully.
# For efficiency use the in-memory list of lines instead of `table`, which
# could be a file.
for data_start in range(len(lines)):
self.data.start_line = data_start
with suppress(Exception):
table = super().read(lines)
return table
else:
return super().read(table)
|
25dced53fc9413ff52387ed96b2e163e3addb792decaf775184e5eb049741ccc | # Licensed under a 3-clause BSD style license - see LICENSE.rst
"""An extensible ASCII table reader and writer.
basic.py:
Basic table read / write functionality for simple character
delimited files with various options for column header definition.
:Copyright: Smithsonian Astrophysical Observatory (2011)
:Author: Tom Aldcroft ([email protected])
"""
import re
from . import core
class BasicHeader(core.BaseHeader):
"""
Basic table Header Reader
Set a few defaults for common ascii table formats
(start at line 0, comments begin with ``#`` and possibly white space)
"""
start_line = 0
comment = r'\s*#'
write_comment = '# '
class BasicData(core.BaseData):
"""
Basic table Data Reader
Set a few defaults for common ascii table formats
(start at line 1, comments begin with ``#`` and possibly white space)
"""
start_line = 1
comment = r'\s*#'
write_comment = '# '
class Basic(core.BaseReader):
r"""Character-delimited table with a single header line at the top.
Lines beginning with a comment character (default='#') as the first
non-whitespace character are comments.
Example table::
# Column definition is the first uncommented line
# Default delimiter is the space character.
apples oranges pears
# Data starts after the header column definition, blank lines ignored
1 2 3
4 5 6
"""
_format_name = 'basic'
_description = 'Basic table with custom delimiters'
_io_registry_format_aliases = ['ascii']
header_class = BasicHeader
data_class = BasicData
class NoHeaderHeader(BasicHeader):
"""
Reader for table header without a header
Set the start of header line number to `None`, which tells the basic
reader there is no header line.
"""
start_line = None
class NoHeaderData(BasicData):
"""
Reader for table data without a header
Data starts at first uncommented line since there is no header line.
"""
start_line = 0
class NoHeader(Basic):
"""Character-delimited table with no header line.
When reading, columns are autonamed using header.auto_format which defaults
to "col%d". Otherwise this reader the same as the :class:`Basic` class
from which it is derived. Example::
# Table data
1 2 "hello there"
3 4 world
"""
_format_name = 'no_header'
_description = 'Basic table with no headers'
header_class = NoHeaderHeader
data_class = NoHeaderData
class CommentedHeaderHeader(BasicHeader):
"""
Header class for which the column definition line starts with the
comment character. See the :class:`CommentedHeader` class for an example.
"""
def process_lines(self, lines):
"""
Return only lines that start with the comment regexp. For these
lines strip out the matching characters.
"""
re_comment = re.compile(self.comment)
for line in lines:
match = re_comment.match(line)
if match:
yield line[match.end():]
def write(self, lines):
lines.append(self.write_comment + self.splitter.join(self.colnames))
class CommentedHeader(Basic):
"""Character-delimited table with column names in a comment line.
When reading, ``header_start`` can be used to specify the
line index of column names, and it can be a negative index (for example -1
for the last commented line). The default delimiter is the <space>
character.
Example::
# col1 col2 col3
# Comment line
1 2 3
4 5 6
"""
_format_name = 'commented_header'
_description = 'Column names in a commented line'
header_class = CommentedHeaderHeader
data_class = NoHeaderData
def read(self, table):
"""
Read input data (file-like object, filename, list of strings, or
single string) into a Table and return the result.
"""
out = super().read(table)
# Strip off the comment line set as the header line for
# commented_header format (first by default).
if 'comments' in out.meta:
idx = self.header.start_line
if idx < 0:
idx = len(out.meta['comments']) + idx
out.meta['comments'] = out.meta['comments'][:idx] + out.meta['comments'][idx+1:]
if not out.meta['comments']:
del out.meta['comments']
return out
def write_header(self, lines, meta):
"""
Write comment lines after, rather than before, the header.
"""
self.header.write(lines)
self.header.write_comments(lines, meta)
class TabHeaderSplitter(core.DefaultSplitter):
"""Split lines on tab and do not remove whitespace"""
delimiter = '\t'
process_line = None
class TabDataSplitter(TabHeaderSplitter):
"""
Don't strip data value whitespace since that is significant in TSV tables
"""
process_val = None
skipinitialspace = False
class TabHeader(BasicHeader):
"""
Reader for header of tables with tab separated header
"""
splitter_class = TabHeaderSplitter
class TabData(BasicData):
"""
Reader for data of tables with tab separated data
"""
splitter_class = TabDataSplitter
class Tab(Basic):
"""Tab-separated table.
Unlike the :class:`Basic` reader, whitespace is not stripped from the
beginning and end of either lines or individual column values.
Example::
col1 <tab> col2 <tab> col3
# Comment line
1 <tab> 2 <tab> 5
"""
_format_name = 'tab'
_description = 'Basic table with tab-separated values'
header_class = TabHeader
data_class = TabData
class CsvSplitter(core.DefaultSplitter):
"""
Split on comma for CSV (comma-separated-value) tables
"""
delimiter = ','
class CsvHeader(BasicHeader):
"""
Header that uses the :class:`astropy.io.ascii.basic.CsvSplitter`
"""
splitter_class = CsvSplitter
comment = None
write_comment = None
class CsvData(BasicData):
"""
Data that uses the :class:`astropy.io.ascii.basic.CsvSplitter`
"""
splitter_class = CsvSplitter
fill_values = [(core.masked, '')]
comment = None
write_comment = None
class Csv(Basic):
"""CSV (comma-separated-values) table.
This file format may contain rows with fewer entries than the number of
columns, a situation that occurs in output from some spreadsheet editors.
The missing entries are marked as masked in the output table.
Masked values (indicated by an empty '' field value when reading) are
written out in the same way with an empty ('') field. This is different
from the typical default for `astropy.io.ascii` in which missing values are
indicated by ``--``.
Example::
num,ra,dec,radius,mag
1,32.23222,10.1211
2,38.12321,-88.1321,2.2,17.0
"""
_format_name = 'csv'
_io_registry_format_aliases = ['csv']
_io_registry_can_write = True
_io_registry_suffix = '.csv'
_description = 'Comma-separated-values'
header_class = CsvHeader
data_class = CsvData
def inconsistent_handler(self, str_vals, ncols):
"""
Adjust row if it is too short.
If a data row is shorter than the header, add empty values to make it the
right length.
Note that this will *not* be called if the row already matches the header.
Parameters
----------
str_vals : list
A list of value strings from the current row of the table.
ncols : int
The expected number of entries from the table header.
Returns
-------
str_vals : list
List of strings to be parsed into data entries in the output table.
"""
if len(str_vals) < ncols:
str_vals.extend((ncols - len(str_vals)) * [''])
return str_vals
class RdbHeader(TabHeader):
"""
Header for RDB tables
"""
col_type_map = {'n': core.NumType,
's': core.StrType}
def get_type_map_key(self, col):
return col.raw_type[-1]
def get_cols(self, lines):
"""
Initialize the header Column objects from the table ``lines``.
This is a specialized get_cols for the RDB type:
Line 0: RDB col names
Line 1: RDB col definitions
Line 2+: RDB data rows
Parameters
----------
lines : list
List of table lines
Returns
-------
None
"""
header_lines = self.process_lines(lines) # this is a generator
header_vals_list = [hl for _, hl in zip(range(2), self.splitter(header_lines))]
if len(header_vals_list) != 2:
raise ValueError('RDB header requires 2 lines')
self.names, raw_types = header_vals_list
if len(self.names) != len(raw_types):
raise core.InconsistentTableError('RDB header mismatch between number of column names and column types.')
if any(not re.match(r'\d*(N|S)$', x, re.IGNORECASE) for x in raw_types):
raise core.InconsistentTableError('RDB types definitions do not all match [num](N|S): {}'.format(raw_types))
self._set_cols_from_names()
for col, raw_type in zip(self.cols, raw_types):
col.raw_type = raw_type
col.type = self.get_col_type(col)
def write(self, lines):
lines.append(self.splitter.join(self.colnames))
rdb_types = []
for col in self.cols:
# Check if dtype.kind is string or unicode. See help(np.core.numerictypes)
rdb_type = 'S' if col.info.dtype.kind in ('S', 'U') else 'N'
rdb_types.append(rdb_type)
lines.append(self.splitter.join(rdb_types))
class RdbData(TabData):
"""
Data reader for RDB data. Starts reading at line 2.
"""
start_line = 2
class Rdb(Tab):
"""Tab-separated file with an extra line after the column definition line that
specifies either numeric (N) or string (S) data.
See: https://compbio.soe.ucsc.edu/rdb/
Example::
col1 <tab> col2 <tab> col3
N <tab> S <tab> N
1 <tab> 2 <tab> 5
"""
_format_name = 'rdb'
_io_registry_format_aliases = ['rdb']
_io_registry_suffix = '.rdb'
_description = 'Tab-separated with a type definition header line'
header_class = RdbHeader
data_class = RdbData
|
b0b93d39226e24b3eb6d6b3eb31d287491985ecc2538c837281cc5684d7393b1 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
# This file connects the readers/writers to the astropy.table.Table class
import re
import functools
from astropy.io import registry as io_registry
from astropy.table import Table
__all__ = []
def io_read(format, filename, **kwargs):
from .ui import read
if format != 'ascii':
format = re.sub(r'^ascii\.', '', format)
kwargs['format'] = format
return read(filename, **kwargs)
def io_write(format, table, filename, **kwargs):
from .ui import write
if format != 'ascii':
format = re.sub(r'^ascii\.', '', format)
kwargs['format'] = format
return write(table, filename, **kwargs)
def io_identify(suffix, origin, filepath, fileobj, *args, **kwargs):
return filepath is not None and filepath.endswith(suffix)
def _get_connectors_table():
from .core import FORMAT_CLASSES
rows = []
rows.append(('ascii', '', 'Yes', 'ASCII table in any supported format (uses guessing)'))
for format in sorted(FORMAT_CLASSES):
cls = FORMAT_CLASSES[format]
io_format = 'ascii.' + cls._format_name
description = getattr(cls, '_description', '')
class_link = ':class:`~{0}.{1}`'.format(cls.__module__, cls.__name__)
suffix = getattr(cls, '_io_registry_suffix', '')
can_write = 'Yes' if getattr(cls, '_io_registry_can_write', True) else ''
rows.append((io_format, suffix, can_write,
'{0}: {1}'.format(class_link, description)))
out = Table(list(zip(*rows)), names=('Format', 'Suffix', 'Write', 'Description'))
for colname in ('Format', 'Description'):
width = max(len(x) for x in out[colname])
out[colname].format = '%-{0}s'.format(width)
return out
|
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