108 lines
2.9 KiB
Python
108 lines
2.9 KiB
Python
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import operator
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import numpy as np
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import pytest
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import pandas as pd
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import pandas._testing as tm
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from pandas.arrays import FloatingArray
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@pytest.fixture
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def data():
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return pd.array(
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[True, False] * 4 + [np.nan] + [True, False] * 44 + [np.nan] + [True, False],
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dtype="boolean",
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)
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@pytest.fixture
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def left_array():
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return pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean")
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@pytest.fixture
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def right_array():
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return pd.array([True, False, None] * 3, dtype="boolean")
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# Basic test for the arithmetic array ops
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# -----------------------------------------------------------------------------
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@pytest.mark.parametrize(
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"opname, exp",
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[
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("add", [True, True, None, True, False, None, None, None, None]),
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("mul", [True, False, None, False, False, None, None, None, None]),
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],
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ids=["add", "mul"],
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)
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def test_add_mul(left_array, right_array, opname, exp):
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op = getattr(operator, opname)
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result = op(left_array, right_array)
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expected = pd.array(exp, dtype="boolean")
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tm.assert_extension_array_equal(result, expected)
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def test_sub(left_array, right_array):
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with pytest.raises(TypeError):
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# numpy points to ^ operator or logical_xor function instead
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left_array - right_array
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def test_div(left_array, right_array):
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result = left_array / right_array
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expected = FloatingArray(
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np.array(
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[1.0, np.inf, np.nan, 0.0, np.nan, np.nan, np.nan, np.nan, np.nan],
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dtype="float64",
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),
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np.array([False, False, True, False, False, True, True, True, True]),
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)
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tm.assert_extension_array_equal(result, expected)
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@pytest.mark.parametrize(
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"opname",
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[
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pytest.param(
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"floordiv",
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marks=pytest.mark.xfail(reason="NumpyDev GH#40874", strict=False),
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),
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"mod",
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pytest.param(
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"pow", marks=pytest.mark.xfail(reason="TODO follow int8 behaviour? GH34686")
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),
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],
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)
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def test_op_int8(left_array, right_array, opname):
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op = getattr(operator, opname)
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result = op(left_array, right_array)
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expected = op(left_array.astype("Int8"), right_array.astype("Int8"))
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tm.assert_extension_array_equal(result, expected)
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# Test generic characteristics / errors
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# -----------------------------------------------------------------------------
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def test_error_invalid_values(data, all_arithmetic_operators):
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# invalid ops
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op = all_arithmetic_operators
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s = pd.Series(data)
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ops = getattr(s, op)
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# invalid scalars
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with pytest.raises(TypeError):
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ops("foo")
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with pytest.raises(TypeError):
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ops(pd.Timestamp("20180101"))
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# invalid array-likes
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if op not in ("__mul__", "__rmul__"):
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# TODO(extension) numpy's mul with object array sees booleans as numbers
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with pytest.raises(TypeError):
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ops(pd.Series("foo", index=s.index))
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