Merge pull request #3313 from tadeu/approx-array-scalar
Add support for `pytest.approx` comparisons between array and scalar
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86d6804e60
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@ -31,6 +31,10 @@ class ApproxBase(object):
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or sequences of numbers.
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"""
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# Tell numpy to use our `__eq__` operator instead of its
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__array_ufunc__ = None
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__array_priority__ = 100
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def __init__(self, expected, rel=None, abs=None, nan_ok=False):
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self.expected = expected
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self.abs = abs
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@ -69,14 +73,13 @@ class ApproxNumpy(ApproxBase):
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Perform approximate comparisons for numpy arrays.
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"""
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# Tell numpy to use our `__eq__` operator instead of its.
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__array_priority__ = 100
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def __repr__(self):
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# It might be nice to rewrite this function to account for the
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# shape of the array...
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import numpy as np
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return "approx({0!r})".format(list(
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self._approx_scalar(x) for x in self.expected))
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self._approx_scalar(x) for x in np.asarray(self.expected)))
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if sys.version_info[0] == 2:
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__cmp__ = _cmp_raises_type_error
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@ -84,12 +87,15 @@ class ApproxNumpy(ApproxBase):
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def __eq__(self, actual):
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import numpy as np
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try:
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actual = np.asarray(actual)
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except: # noqa
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raise TypeError("cannot compare '{0}' to numpy.ndarray".format(actual))
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# self.expected is supposed to always be an array here
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if actual.shape != self.expected.shape:
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if not np.isscalar(actual):
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try:
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actual = np.asarray(actual)
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except: # noqa
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raise TypeError("cannot compare '{0}' to numpy.ndarray".format(actual))
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if not np.isscalar(actual) and actual.shape != self.expected.shape:
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return False
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return ApproxBase.__eq__(self, actual)
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@ -97,11 +103,16 @@ class ApproxNumpy(ApproxBase):
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def _yield_comparisons(self, actual):
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import numpy as np
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# We can be sure that `actual` is a numpy array, because it's
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# casted in `__eq__` before being passed to `ApproxBase.__eq__`,
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# which is the only method that calls this one.
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for i in np.ndindex(self.expected.shape):
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yield actual[i], self.expected[i]
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# `actual` can either be a numpy array or a scalar, it is treated in
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# `__eq__` before being passed to `ApproxBase.__eq__`, which is the
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# only method that calls this one.
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if np.isscalar(actual):
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for i in np.ndindex(self.expected.shape):
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yield actual, np.asscalar(self.expected[i])
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else:
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for i in np.ndindex(self.expected.shape):
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yield np.asscalar(actual[i]), np.asscalar(self.expected[i])
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class ApproxMapping(ApproxBase):
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@ -131,9 +142,6 @@ class ApproxSequence(ApproxBase):
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Perform approximate comparisons for sequences of numbers.
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"""
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# Tell numpy to use our `__eq__` operator instead of its.
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__array_priority__ = 100
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def __repr__(self):
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seq_type = type(self.expected)
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if seq_type not in (tuple, list, set):
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@ -189,6 +197,8 @@ class ApproxScalar(ApproxBase):
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Return true if the given value is equal to the expected value within
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the pre-specified tolerance.
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"""
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if _is_numpy_array(actual):
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return ApproxNumpy(actual, self.abs, self.rel, self.nan_ok) == self.expected
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# Short-circuit exact equality.
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if actual == self.expected:
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@ -308,12 +318,18 @@ def approx(expected, rel=None, abs=None, nan_ok=False):
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>>> {'a': 0.1 + 0.2, 'b': 0.2 + 0.4} == approx({'a': 0.3, 'b': 0.6})
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True
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And ``numpy`` arrays::
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``numpy`` arrays::
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>>> import numpy as np # doctest: +SKIP
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>>> np.array([0.1, 0.2]) + np.array([0.2, 0.4]) == approx(np.array([0.3, 0.6])) # doctest: +SKIP
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True
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And for a ``numpy`` array against a scalar::
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>>> import numpy as np # doctest: +SKIP
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>>> np.array([0.1, 0.2]) + np.array([0.2, 0.1]) == approx(0.3) # doctest: +SKIP
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True
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By default, ``approx`` considers numbers within a relative tolerance of
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``1e-6`` (i.e. one part in a million) of its expected value to be equal.
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This treatment would lead to surprising results if the expected value was
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@ -0,0 +1 @@
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``pytest.approx`` now accepts comparing a numpy array with a scalar.
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@ -391,3 +391,25 @@ class TestApprox(object):
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"""
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with pytest.raises(TypeError):
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op(1, approx(1, rel=1e-6, abs=1e-12))
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def test_numpy_array_with_scalar(self):
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np = pytest.importorskip('numpy')
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actual = np.array([1 + 1e-7, 1 - 1e-8])
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expected = 1.0
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assert actual == approx(expected, rel=5e-7, abs=0)
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assert actual != approx(expected, rel=5e-8, abs=0)
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assert approx(expected, rel=5e-7, abs=0) == actual
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assert approx(expected, rel=5e-8, abs=0) != actual
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def test_numpy_scalar_with_array(self):
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np = pytest.importorskip('numpy')
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actual = 1.0
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expected = np.array([1 + 1e-7, 1 - 1e-8])
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assert actual == approx(expected, rel=5e-7, abs=0)
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assert actual != approx(expected, rel=5e-8, abs=0)
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assert approx(expected, rel=5e-7, abs=0) == actual
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assert approx(expected, rel=5e-8, abs=0) != actual
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