ai-content-maker/.venv/Lib/site-packages/numpy/lib/tests/test_mixins.py

217 lines
6.9 KiB
Python

import numbers
import operator
import numpy as np
from numpy.testing import assert_, assert_equal, assert_raises
# NOTE: This class should be kept as an exact copy of the example from the
# docstring for NDArrayOperatorsMixin.
class ArrayLike(np.lib.mixins.NDArrayOperatorsMixin):
def __init__(self, value):
self.value = np.asarray(value)
# One might also consider adding the built-in list type to this
# list, to support operations like np.add(array_like, list)
_HANDLED_TYPES = (np.ndarray, numbers.Number)
def __array_ufunc__(self, ufunc, method, *inputs, **kwargs):
out = kwargs.get('out', ())
for x in inputs + out:
# Only support operations with instances of _HANDLED_TYPES.
# Use ArrayLike instead of type(self) for isinstance to
# allow subclasses that don't override __array_ufunc__ to
# handle ArrayLike objects.
if not isinstance(x, self._HANDLED_TYPES + (ArrayLike,)):
return NotImplemented
# Defer to the implementation of the ufunc on unwrapped values.
inputs = tuple(x.value if isinstance(x, ArrayLike) else x
for x in inputs)
if out:
kwargs['out'] = tuple(
x.value if isinstance(x, ArrayLike) else x
for x in out)
result = getattr(ufunc, method)(*inputs, **kwargs)
if type(result) is tuple:
# multiple return values
return tuple(type(self)(x) for x in result)
elif method == 'at':
# no return value
return None
else:
# one return value
return type(self)(result)
def __repr__(self):
return '%s(%r)' % (type(self).__name__, self.value)
def wrap_array_like(result):
if type(result) is tuple:
return tuple(ArrayLike(r) for r in result)
else:
return ArrayLike(result)
def _assert_equal_type_and_value(result, expected, err_msg=None):
assert_equal(type(result), type(expected), err_msg=err_msg)
if isinstance(result, tuple):
assert_equal(len(result), len(expected), err_msg=err_msg)
for result_item, expected_item in zip(result, expected):
_assert_equal_type_and_value(result_item, expected_item, err_msg)
else:
assert_equal(result.value, expected.value, err_msg=err_msg)
assert_equal(getattr(result.value, 'dtype', None),
getattr(expected.value, 'dtype', None), err_msg=err_msg)
_ALL_BINARY_OPERATORS = [
operator.lt,
operator.le,
operator.eq,
operator.ne,
operator.gt,
operator.ge,
operator.add,
operator.sub,
operator.mul,
operator.truediv,
operator.floordiv,
operator.mod,
divmod,
pow,
operator.lshift,
operator.rshift,
operator.and_,
operator.xor,
operator.or_,
]
class TestNDArrayOperatorsMixin:
def test_array_like_add(self):
def check(result):
_assert_equal_type_and_value(result, ArrayLike(0))
check(ArrayLike(0) + 0)
check(0 + ArrayLike(0))
check(ArrayLike(0) + np.array(0))
check(np.array(0) + ArrayLike(0))
check(ArrayLike(np.array(0)) + 0)
check(0 + ArrayLike(np.array(0)))
check(ArrayLike(np.array(0)) + np.array(0))
check(np.array(0) + ArrayLike(np.array(0)))
def test_inplace(self):
array_like = ArrayLike(np.array([0]))
array_like += 1
_assert_equal_type_and_value(array_like, ArrayLike(np.array([1])))
array = np.array([0])
array += ArrayLike(1)
_assert_equal_type_and_value(array, ArrayLike(np.array([1])))
def test_opt_out(self):
class OptOut:
"""Object that opts out of __array_ufunc__."""
__array_ufunc__ = None
def __add__(self, other):
return self
def __radd__(self, other):
return self
array_like = ArrayLike(1)
opt_out = OptOut()
# supported operations
assert_(array_like + opt_out is opt_out)
assert_(opt_out + array_like is opt_out)
# not supported
with assert_raises(TypeError):
# don't use the Python default, array_like = array_like + opt_out
array_like += opt_out
with assert_raises(TypeError):
array_like - opt_out
with assert_raises(TypeError):
opt_out - array_like
def test_subclass(self):
class SubArrayLike(ArrayLike):
"""Should take precedence over ArrayLike."""
x = ArrayLike(0)
y = SubArrayLike(1)
_assert_equal_type_and_value(x + y, y)
_assert_equal_type_and_value(y + x, y)
def test_object(self):
x = ArrayLike(0)
obj = object()
with assert_raises(TypeError):
x + obj
with assert_raises(TypeError):
obj + x
with assert_raises(TypeError):
x += obj
def test_unary_methods(self):
array = np.array([-1, 0, 1, 2])
array_like = ArrayLike(array)
for op in [operator.neg,
operator.pos,
abs,
operator.invert]:
_assert_equal_type_and_value(op(array_like), ArrayLike(op(array)))
def test_forward_binary_methods(self):
array = np.array([-1, 0, 1, 2])
array_like = ArrayLike(array)
for op in _ALL_BINARY_OPERATORS:
expected = wrap_array_like(op(array, 1))
actual = op(array_like, 1)
err_msg = 'failed for operator {}'.format(op)
_assert_equal_type_and_value(expected, actual, err_msg=err_msg)
def test_reflected_binary_methods(self):
for op in _ALL_BINARY_OPERATORS:
expected = wrap_array_like(op(2, 1))
actual = op(2, ArrayLike(1))
err_msg = 'failed for operator {}'.format(op)
_assert_equal_type_and_value(expected, actual, err_msg=err_msg)
def test_matmul(self):
array = np.array([1, 2], dtype=np.float64)
array_like = ArrayLike(array)
expected = ArrayLike(np.float64(5))
_assert_equal_type_and_value(expected, np.matmul(array_like, array))
_assert_equal_type_and_value(
expected, operator.matmul(array_like, array))
_assert_equal_type_and_value(
expected, operator.matmul(array, array_like))
def test_ufunc_at(self):
array = ArrayLike(np.array([1, 2, 3, 4]))
assert_(np.negative.at(array, np.array([0, 1])) is None)
_assert_equal_type_and_value(array, ArrayLike([-1, -2, 3, 4]))
def test_ufunc_two_outputs(self):
mantissa, exponent = np.frexp(2 ** -3)
expected = (ArrayLike(mantissa), ArrayLike(exponent))
_assert_equal_type_and_value(
np.frexp(ArrayLike(2 ** -3)), expected)
_assert_equal_type_and_value(
np.frexp(ArrayLike(np.array(2 ** -3))), expected)