587 lines
16 KiB
Python
587 lines
16 KiB
Python
import numpy as np
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import pytest
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from pandas import (
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NA,
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DataFrame,
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Index,
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NaT,
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Series,
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Timestamp,
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)
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import pandas._testing as tm
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def _assert_almost_equal_both(a, b, **kwargs):
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"""
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Check that two objects are approximately equal.
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This check is performed commutatively.
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Parameters
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----------
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a : object
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The first object to compare.
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b : object
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The second object to compare.
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**kwargs
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The arguments passed to `tm.assert_almost_equal`.
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"""
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tm.assert_almost_equal(a, b, **kwargs)
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tm.assert_almost_equal(b, a, **kwargs)
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def _assert_not_almost_equal(a, b, **kwargs):
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"""
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Check that two objects are not approximately equal.
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Parameters
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----------
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a : object
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The first object to compare.
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b : object
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The second object to compare.
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**kwargs
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The arguments passed to `tm.assert_almost_equal`.
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"""
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try:
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tm.assert_almost_equal(a, b, **kwargs)
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msg = f"{a} and {b} were approximately equal when they shouldn't have been"
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pytest.fail(reason=msg)
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except AssertionError:
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pass
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def _assert_not_almost_equal_both(a, b, **kwargs):
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"""
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Check that two objects are not approximately equal.
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This check is performed commutatively.
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Parameters
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----------
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a : object
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The first object to compare.
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b : object
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The second object to compare.
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**kwargs
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The arguments passed to `tm.assert_almost_equal`.
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"""
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_assert_not_almost_equal(a, b, **kwargs)
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_assert_not_almost_equal(b, a, **kwargs)
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@pytest.mark.parametrize(
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"a,b",
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[
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(1.1, 1.1),
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(1.1, 1.100001),
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(np.int16(1), 1.000001),
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(np.float64(1.1), 1.1),
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(np.uint32(5), 5),
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],
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)
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def test_assert_almost_equal_numbers(a, b):
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_assert_almost_equal_both(a, b)
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@pytest.mark.parametrize(
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"a,b",
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[
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(1.1, 1),
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(1.1, True),
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(1, 2),
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(1.0001, np.int16(1)),
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# The following two examples are not "almost equal" due to tol.
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(0.1, 0.1001),
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(0.0011, 0.0012),
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],
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)
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def test_assert_not_almost_equal_numbers(a, b):
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_assert_not_almost_equal_both(a, b)
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@pytest.mark.parametrize(
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"a,b",
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[
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(1.1, 1.1),
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(1.1, 1.100001),
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(1.1, 1.1001),
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(0.000001, 0.000005),
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(1000.0, 1000.0005),
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# Testing this example, as per #13357
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(0.000011, 0.000012),
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],
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)
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def test_assert_almost_equal_numbers_atol(a, b):
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# Equivalent to the deprecated check_less_precise=True, enforced in 2.0
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_assert_almost_equal_both(a, b, rtol=0.5e-3, atol=0.5e-3)
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@pytest.mark.parametrize("a,b", [(1.1, 1.11), (0.1, 0.101), (0.000011, 0.001012)])
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def test_assert_not_almost_equal_numbers_atol(a, b):
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_assert_not_almost_equal_both(a, b, atol=1e-3)
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@pytest.mark.parametrize(
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"a,b",
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[
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(1.1, 1.1),
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(1.1, 1.100001),
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(1.1, 1.1001),
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(1000.0, 1000.0005),
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(1.1, 1.11),
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(0.1, 0.101),
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],
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)
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def test_assert_almost_equal_numbers_rtol(a, b):
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_assert_almost_equal_both(a, b, rtol=0.05)
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@pytest.mark.parametrize("a,b", [(0.000011, 0.000012), (0.000001, 0.000005)])
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def test_assert_not_almost_equal_numbers_rtol(a, b):
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_assert_not_almost_equal_both(a, b, rtol=0.05)
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@pytest.mark.parametrize(
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"a,b,rtol",
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[
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(1.00001, 1.00005, 0.001),
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(-0.908356 + 0.2j, -0.908358 + 0.2j, 1e-3),
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(0.1 + 1.009j, 0.1 + 1.006j, 0.1),
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(0.1001 + 2.0j, 0.1 + 2.001j, 0.01),
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],
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)
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def test_assert_almost_equal_complex_numbers(a, b, rtol):
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_assert_almost_equal_both(a, b, rtol=rtol)
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_assert_almost_equal_both(np.complex64(a), np.complex64(b), rtol=rtol)
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_assert_almost_equal_both(np.complex128(a), np.complex128(b), rtol=rtol)
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@pytest.mark.parametrize(
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"a,b,rtol",
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[
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(0.58310768, 0.58330768, 1e-7),
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(-0.908 + 0.2j, -0.978 + 0.2j, 0.001),
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(0.1 + 1j, 0.1 + 2j, 0.01),
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(-0.132 + 1.001j, -0.132 + 1.005j, 1e-5),
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(0.58310768j, 0.58330768j, 1e-9),
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],
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)
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def test_assert_not_almost_equal_complex_numbers(a, b, rtol):
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_assert_not_almost_equal_both(a, b, rtol=rtol)
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_assert_not_almost_equal_both(np.complex64(a), np.complex64(b), rtol=rtol)
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_assert_not_almost_equal_both(np.complex128(a), np.complex128(b), rtol=rtol)
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@pytest.mark.parametrize("a,b", [(0, 0), (0, 0.0), (0, np.float64(0)), (0.00000001, 0)])
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def test_assert_almost_equal_numbers_with_zeros(a, b):
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_assert_almost_equal_both(a, b)
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@pytest.mark.parametrize("a,b", [(0.001, 0), (1, 0)])
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def test_assert_not_almost_equal_numbers_with_zeros(a, b):
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_assert_not_almost_equal_both(a, b)
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@pytest.mark.parametrize("a,b", [(1, "abc"), (1, [1]), (1, object())])
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def test_assert_not_almost_equal_numbers_with_mixed(a, b):
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_assert_not_almost_equal_both(a, b)
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@pytest.mark.parametrize(
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"left_dtype", ["M8[ns]", "m8[ns]", "float64", "int64", "object"]
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)
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@pytest.mark.parametrize(
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"right_dtype", ["M8[ns]", "m8[ns]", "float64", "int64", "object"]
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)
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def test_assert_almost_equal_edge_case_ndarrays(left_dtype, right_dtype):
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# Empty compare.
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_assert_almost_equal_both(
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np.array([], dtype=left_dtype),
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np.array([], dtype=right_dtype),
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check_dtype=False,
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)
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def test_assert_almost_equal_sets():
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# GH#51727
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_assert_almost_equal_both({1, 2, 3}, {1, 2, 3})
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def test_assert_almost_not_equal_sets():
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# GH#51727
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msg = r"{1, 2, 3} != {1, 2, 4}"
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with pytest.raises(AssertionError, match=msg):
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_assert_almost_equal_both({1, 2, 3}, {1, 2, 4})
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def test_assert_almost_equal_dicts():
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_assert_almost_equal_both({"a": 1, "b": 2}, {"a": 1, "b": 2})
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@pytest.mark.parametrize(
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"a,b",
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[
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({"a": 1, "b": 2}, {"a": 1, "b": 3}),
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({"a": 1, "b": 2}, {"a": 1, "b": 2, "c": 3}),
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({"a": 1}, 1),
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({"a": 1}, "abc"),
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({"a": 1}, [1]),
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],
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)
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def test_assert_not_almost_equal_dicts(a, b):
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_assert_not_almost_equal_both(a, b)
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@pytest.mark.parametrize("val", [1, 2])
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def test_assert_almost_equal_dict_like_object(val):
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dict_val = 1
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real_dict = {"a": val}
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class DictLikeObj:
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def keys(self):
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return ("a",)
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def __getitem__(self, item):
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if item == "a":
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return dict_val
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func = (
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_assert_almost_equal_both if val == dict_val else _assert_not_almost_equal_both
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)
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func(real_dict, DictLikeObj(), check_dtype=False)
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def test_assert_almost_equal_strings():
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_assert_almost_equal_both("abc", "abc")
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@pytest.mark.parametrize(
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"a,b", [("abc", "abcd"), ("abc", "abd"), ("abc", 1), ("abc", [1])]
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)
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def test_assert_not_almost_equal_strings(a, b):
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_assert_not_almost_equal_both(a, b)
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@pytest.mark.parametrize(
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"a,b", [([1, 2, 3], [1, 2, 3]), (np.array([1, 2, 3]), np.array([1, 2, 3]))]
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)
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def test_assert_almost_equal_iterables(a, b):
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_assert_almost_equal_both(a, b)
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@pytest.mark.parametrize(
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"a,b",
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[
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# Class is different.
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(np.array([1, 2, 3]), [1, 2, 3]),
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# Dtype is different.
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(np.array([1, 2, 3]), np.array([1.0, 2.0, 3.0])),
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# Can't compare generators.
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(iter([1, 2, 3]), [1, 2, 3]),
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([1, 2, 3], [1, 2, 4]),
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([1, 2, 3], [1, 2, 3, 4]),
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([1, 2, 3], 1),
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],
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)
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def test_assert_not_almost_equal_iterables(a, b):
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_assert_not_almost_equal(a, b)
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def test_assert_almost_equal_null():
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_assert_almost_equal_both(None, None)
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@pytest.mark.parametrize("a,b", [(None, np.nan), (None, 0), (np.nan, 0)])
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def test_assert_not_almost_equal_null(a, b):
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_assert_not_almost_equal(a, b)
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@pytest.mark.parametrize(
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"a,b",
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[
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(np.inf, np.inf),
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(np.inf, float("inf")),
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(np.array([np.inf, np.nan, -np.inf]), np.array([np.inf, np.nan, -np.inf])),
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],
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)
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def test_assert_almost_equal_inf(a, b):
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_assert_almost_equal_both(a, b)
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objs = [NA, np.nan, NaT, None, np.datetime64("NaT"), np.timedelta64("NaT")]
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@pytest.mark.parametrize("left", objs)
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@pytest.mark.parametrize("right", objs)
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def test_mismatched_na_assert_almost_equal_deprecation(left, right):
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left_arr = np.array([left], dtype=object)
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right_arr = np.array([right], dtype=object)
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msg = "Mismatched null-like values"
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if left is right:
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_assert_almost_equal_both(left, right, check_dtype=False)
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tm.assert_numpy_array_equal(left_arr, right_arr)
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tm.assert_index_equal(
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Index(left_arr, dtype=object), Index(right_arr, dtype=object)
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)
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tm.assert_series_equal(
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Series(left_arr, dtype=object), Series(right_arr, dtype=object)
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)
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tm.assert_frame_equal(
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DataFrame(left_arr, dtype=object), DataFrame(right_arr, dtype=object)
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)
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else:
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with tm.assert_produces_warning(FutureWarning, match=msg):
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_assert_almost_equal_both(left, right, check_dtype=False)
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# TODO: to get the same deprecation in assert_numpy_array_equal we need
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# to change/deprecate the default for strict_nan to become True
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# TODO: to get the same deprecation in assert_index_equal we need to
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# change/deprecate array_equivalent_object to be stricter, as
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# assert_index_equal uses Index.equal which uses array_equivalent.
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with tm.assert_produces_warning(FutureWarning, match=msg):
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tm.assert_series_equal(
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Series(left_arr, dtype=object), Series(right_arr, dtype=object)
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)
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with tm.assert_produces_warning(FutureWarning, match=msg):
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tm.assert_frame_equal(
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DataFrame(left_arr, dtype=object), DataFrame(right_arr, dtype=object)
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)
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def test_assert_not_almost_equal_inf():
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_assert_not_almost_equal_both(np.inf, 0)
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@pytest.mark.parametrize(
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"a,b",
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[
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(Index([1.0, 1.1]), Index([1.0, 1.100001])),
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(Series([1.0, 1.1]), Series([1.0, 1.100001])),
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(np.array([1.1, 2.000001]), np.array([1.1, 2.0])),
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(DataFrame({"a": [1.0, 1.1]}), DataFrame({"a": [1.0, 1.100001]})),
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],
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)
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def test_assert_almost_equal_pandas(a, b):
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_assert_almost_equal_both(a, b)
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def test_assert_almost_equal_object():
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a = [Timestamp("2011-01-01"), Timestamp("2011-01-01")]
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b = [Timestamp("2011-01-01"), Timestamp("2011-01-01")]
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_assert_almost_equal_both(a, b)
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def test_assert_almost_equal_value_mismatch():
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msg = "expected 2\\.00000 but got 1\\.00000, with rtol=1e-05, atol=1e-08"
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with pytest.raises(AssertionError, match=msg):
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tm.assert_almost_equal(1, 2)
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@pytest.mark.parametrize(
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"a,b,klass1,klass2",
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[(np.array([1]), 1, "ndarray", "int"), (1, np.array([1]), "int", "ndarray")],
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)
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def test_assert_almost_equal_class_mismatch(a, b, klass1, klass2):
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msg = f"""numpy array are different
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numpy array classes are different
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\\[left\\]: {klass1}
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\\[right\\]: {klass2}"""
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with pytest.raises(AssertionError, match=msg):
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tm.assert_almost_equal(a, b)
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def test_assert_almost_equal_value_mismatch1():
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msg = """numpy array are different
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numpy array values are different \\(66\\.66667 %\\)
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\\[left\\]: \\[nan, 2\\.0, 3\\.0\\]
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\\[right\\]: \\[1\\.0, nan, 3\\.0\\]"""
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with pytest.raises(AssertionError, match=msg):
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tm.assert_almost_equal(np.array([np.nan, 2, 3]), np.array([1, np.nan, 3]))
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def test_assert_almost_equal_value_mismatch2():
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msg = """numpy array are different
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numpy array values are different \\(50\\.0 %\\)
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\\[left\\]: \\[1, 2\\]
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\\[right\\]: \\[1, 3\\]"""
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with pytest.raises(AssertionError, match=msg):
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tm.assert_almost_equal(np.array([1, 2]), np.array([1, 3]))
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def test_assert_almost_equal_value_mismatch3():
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msg = """numpy array are different
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numpy array values are different \\(16\\.66667 %\\)
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\\[left\\]: \\[\\[1, 2\\], \\[3, 4\\], \\[5, 6\\]\\]
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\\[right\\]: \\[\\[1, 3\\], \\[3, 4\\], \\[5, 6\\]\\]"""
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with pytest.raises(AssertionError, match=msg):
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tm.assert_almost_equal(
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np.array([[1, 2], [3, 4], [5, 6]]), np.array([[1, 3], [3, 4], [5, 6]])
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)
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def test_assert_almost_equal_value_mismatch4():
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msg = """numpy array are different
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numpy array values are different \\(25\\.0 %\\)
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\\[left\\]: \\[\\[1, 2\\], \\[3, 4\\]\\]
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\\[right\\]: \\[\\[1, 3\\], \\[3, 4\\]\\]"""
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with pytest.raises(AssertionError, match=msg):
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tm.assert_almost_equal(np.array([[1, 2], [3, 4]]), np.array([[1, 3], [3, 4]]))
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def test_assert_almost_equal_shape_mismatch_override():
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msg = """Index are different
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Index shapes are different
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\\[left\\]: \\(2L*,\\)
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\\[right\\]: \\(3L*,\\)"""
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with pytest.raises(AssertionError, match=msg):
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tm.assert_almost_equal(np.array([1, 2]), np.array([3, 4, 5]), obj="Index")
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def test_assert_almost_equal_unicode():
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# see gh-20503
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msg = """numpy array are different
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numpy array values are different \\(33\\.33333 %\\)
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\\[left\\]: \\[á, à, ä\\]
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\\[right\\]: \\[á, à, å\\]"""
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with pytest.raises(AssertionError, match=msg):
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tm.assert_almost_equal(np.array(["á", "à", "ä"]), np.array(["á", "à", "å"]))
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def test_assert_almost_equal_timestamp():
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a = np.array([Timestamp("2011-01-01"), Timestamp("2011-01-01")])
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b = np.array([Timestamp("2011-01-01"), Timestamp("2011-01-02")])
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msg = """numpy array are different
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numpy array values are different \\(50\\.0 %\\)
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\\[left\\]: \\[2011-01-01 00:00:00, 2011-01-01 00:00:00\\]
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\\[right\\]: \\[2011-01-01 00:00:00, 2011-01-02 00:00:00\\]"""
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with pytest.raises(AssertionError, match=msg):
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tm.assert_almost_equal(a, b)
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def test_assert_almost_equal_iterable_length_mismatch():
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msg = """Iterable are different
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Iterable length are different
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\\[left\\]: 2
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\\[right\\]: 3"""
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with pytest.raises(AssertionError, match=msg):
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tm.assert_almost_equal([1, 2], [3, 4, 5])
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def test_assert_almost_equal_iterable_values_mismatch():
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msg = """Iterable are different
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|
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|
Iterable values are different \\(50\\.0 %\\)
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\\[left\\]: \\[1, 2\\]
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\\[right\\]: \\[1, 3\\]"""
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|
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with pytest.raises(AssertionError, match=msg):
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tm.assert_almost_equal([1, 2], [1, 3])
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subarr = np.empty(2, dtype=object)
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subarr[:] = [np.array([None, "b"], dtype=object), np.array(["c", "d"], dtype=object)]
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NESTED_CASES = [
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# nested array
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(
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np.array([np.array([50, 70, 90]), np.array([20, 30])], dtype=object),
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np.array([np.array([50, 70, 90]), np.array([20, 30])], dtype=object),
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),
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# >1 level of nesting
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|
(
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|
np.array(
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|
[
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|
np.array([np.array([50, 70]), np.array([90])], dtype=object),
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np.array([np.array([20, 30])], dtype=object),
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|
],
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|
dtype=object,
|
|
),
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|
np.array(
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|
[
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|
np.array([np.array([50, 70]), np.array([90])], dtype=object),
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|
np.array([np.array([20, 30])], dtype=object),
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],
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|
dtype=object,
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|
),
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|
),
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|
# lists
|
|
(
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|
np.array([[50, 70, 90], [20, 30]], dtype=object),
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|
np.array([[50, 70, 90], [20, 30]], dtype=object),
|
|
),
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|
# mixed array/list
|
|
(
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|
np.array([np.array([1, 2, 3]), np.array([4, 5])], dtype=object),
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|
np.array([[1, 2, 3], [4, 5]], dtype=object),
|
|
),
|
|
(
|
|
np.array(
|
|
[
|
|
np.array([np.array([1, 2, 3]), np.array([4, 5])], dtype=object),
|
|
np.array(
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|
[np.array([6]), np.array([7, 8]), np.array([9])], dtype=object
|
|
),
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|
],
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|
dtype=object,
|
|
),
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|
np.array([[[1, 2, 3], [4, 5]], [[6], [7, 8], [9]]], dtype=object),
|
|
),
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|
# same-length lists
|
|
(
|
|
np.array([subarr, None], dtype=object),
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|
np.array([[[None, "b"], ["c", "d"]], None], dtype=object),
|
|
),
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|
# dicts
|
|
(
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|
np.array([{"f1": 1, "f2": np.array(["a", "b"], dtype=object)}], dtype=object),
|
|
np.array([{"f1": 1, "f2": np.array(["a", "b"], dtype=object)}], dtype=object),
|
|
),
|
|
(
|
|
np.array([{"f1": 1, "f2": np.array(["a", "b"], dtype=object)}], dtype=object),
|
|
np.array([{"f1": 1, "f2": ["a", "b"]}], dtype=object),
|
|
),
|
|
# array/list of dicts
|
|
(
|
|
np.array(
|
|
[
|
|
np.array(
|
|
[{"f1": 1, "f2": np.array(["a", "b"], dtype=object)}], dtype=object
|
|
),
|
|
np.array([], dtype=object),
|
|
],
|
|
dtype=object,
|
|
),
|
|
np.array([[{"f1": 1, "f2": ["a", "b"]}], []], dtype=object),
|
|
),
|
|
]
|
|
|
|
|
|
@pytest.mark.filterwarnings("ignore:elementwise comparison failed:DeprecationWarning")
|
|
@pytest.mark.parametrize("a,b", NESTED_CASES)
|
|
def test_assert_almost_equal_array_nested(a, b):
|
|
_assert_almost_equal_both(a, b)
|