264 lines
6.6 KiB
Python
264 lines
6.6 KiB
Python
import numpy as np
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import pytest
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import pandas as pd
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from pandas import (
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Index,
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MultiIndex,
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date_range,
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period_range,
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)
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import pandas._testing as tm
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def test_infer_objects(idx):
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with pytest.raises(NotImplementedError, match="to_frame"):
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idx.infer_objects()
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def test_shift(idx):
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# GH8083 test the base class for shift
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msg = (
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"This method is only implemented for DatetimeIndex, PeriodIndex and "
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"TimedeltaIndex; Got type MultiIndex"
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)
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with pytest.raises(NotImplementedError, match=msg):
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idx.shift(1)
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with pytest.raises(NotImplementedError, match=msg):
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idx.shift(1, 2)
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def test_groupby(idx):
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groups = idx.groupby(np.array([1, 1, 1, 2, 2, 2]))
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labels = idx.tolist()
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exp = {1: labels[:3], 2: labels[3:]}
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tm.assert_dict_equal(groups, exp)
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# GH5620
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groups = idx.groupby(idx)
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exp = {key: [key] for key in idx}
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tm.assert_dict_equal(groups, exp)
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def test_truncate_multiindex():
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# GH 34564 for MultiIndex level names check
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major_axis = Index(list(range(4)))
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minor_axis = Index(list(range(2)))
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major_codes = np.array([0, 0, 1, 2, 3, 3])
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minor_codes = np.array([0, 1, 0, 1, 0, 1])
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index = MultiIndex(
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levels=[major_axis, minor_axis],
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codes=[major_codes, minor_codes],
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names=["L1", "L2"],
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)
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result = index.truncate(before=1)
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assert "foo" not in result.levels[0]
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assert 1 in result.levels[0]
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assert index.names == result.names
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result = index.truncate(after=1)
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assert 2 not in result.levels[0]
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assert 1 in result.levels[0]
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assert index.names == result.names
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result = index.truncate(before=1, after=2)
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assert len(result.levels[0]) == 2
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assert index.names == result.names
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msg = "after < before"
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with pytest.raises(ValueError, match=msg):
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index.truncate(3, 1)
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# TODO: reshape
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def test_reorder_levels(idx):
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# this blows up
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with pytest.raises(IndexError, match="^Too many levels"):
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idx.reorder_levels([2, 1, 0])
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def test_numpy_repeat():
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reps = 2
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numbers = [1, 2, 3]
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names = np.array(["foo", "bar"])
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m = MultiIndex.from_product([numbers, names], names=names)
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expected = MultiIndex.from_product([numbers, names.repeat(reps)], names=names)
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tm.assert_index_equal(np.repeat(m, reps), expected)
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msg = "the 'axis' parameter is not supported"
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with pytest.raises(ValueError, match=msg):
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np.repeat(m, reps, axis=1)
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def test_append_mixed_dtypes():
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# GH 13660
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dti = date_range("2011-01-01", freq="ME", periods=3)
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dti_tz = date_range("2011-01-01", freq="ME", periods=3, tz="US/Eastern")
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pi = period_range("2011-01", freq="M", periods=3)
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mi = MultiIndex.from_arrays(
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[[1, 2, 3], [1.1, np.nan, 3.3], ["a", "b", "c"], dti, dti_tz, pi]
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)
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assert mi.nlevels == 6
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res = mi.append(mi)
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exp = MultiIndex.from_arrays(
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[
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[1, 2, 3, 1, 2, 3],
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[1.1, np.nan, 3.3, 1.1, np.nan, 3.3],
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["a", "b", "c", "a", "b", "c"],
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dti.append(dti),
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dti_tz.append(dti_tz),
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pi.append(pi),
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]
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)
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tm.assert_index_equal(res, exp)
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other = MultiIndex.from_arrays(
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[
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["x", "y", "z"],
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["x", "y", "z"],
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["x", "y", "z"],
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["x", "y", "z"],
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["x", "y", "z"],
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["x", "y", "z"],
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]
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)
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res = mi.append(other)
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exp = MultiIndex.from_arrays(
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[
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[1, 2, 3, "x", "y", "z"],
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[1.1, np.nan, 3.3, "x", "y", "z"],
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["a", "b", "c", "x", "y", "z"],
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dti.append(Index(["x", "y", "z"])),
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dti_tz.append(Index(["x", "y", "z"])),
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pi.append(Index(["x", "y", "z"])),
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]
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)
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tm.assert_index_equal(res, exp)
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def test_iter(idx):
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result = list(idx)
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expected = [
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("foo", "one"),
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("foo", "two"),
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("bar", "one"),
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("baz", "two"),
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("qux", "one"),
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("qux", "two"),
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]
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assert result == expected
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def test_sub(idx):
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first = idx
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# - now raises (previously was set op difference)
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msg = "cannot perform __sub__ with this index type: MultiIndex"
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with pytest.raises(TypeError, match=msg):
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first - idx[-3:]
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with pytest.raises(TypeError, match=msg):
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idx[-3:] - first
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with pytest.raises(TypeError, match=msg):
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idx[-3:] - first.tolist()
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msg = "cannot perform __rsub__ with this index type: MultiIndex"
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with pytest.raises(TypeError, match=msg):
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first.tolist() - idx[-3:]
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def test_map(idx):
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# callable
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index = idx
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result = index.map(lambda x: x)
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tm.assert_index_equal(result, index)
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@pytest.mark.parametrize(
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"mapper",
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[
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lambda values, idx: {i: e for e, i in zip(values, idx)},
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lambda values, idx: pd.Series(values, idx),
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],
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)
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def test_map_dictlike(idx, mapper):
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identity = mapper(idx.values, idx)
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# we don't infer to uint64 dtype for a dict
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if idx.dtype == np.uint64 and isinstance(identity, dict):
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expected = idx.astype("int64")
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else:
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expected = idx
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result = idx.map(identity)
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tm.assert_index_equal(result, expected)
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# empty mappable
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expected = Index([np.nan] * len(idx))
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result = idx.map(mapper(expected, idx))
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tm.assert_index_equal(result, expected)
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@pytest.mark.parametrize(
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"func",
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[
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np.exp,
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np.exp2,
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np.expm1,
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np.log,
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np.log2,
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np.log10,
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np.log1p,
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np.sqrt,
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np.sin,
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np.cos,
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np.tan,
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np.arcsin,
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np.arccos,
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np.arctan,
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np.sinh,
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np.cosh,
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np.tanh,
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np.arcsinh,
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np.arccosh,
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np.arctanh,
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np.deg2rad,
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np.rad2deg,
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],
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ids=lambda func: func.__name__,
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)
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def test_numpy_ufuncs(idx, func):
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# test ufuncs of numpy. see:
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# https://numpy.org/doc/stable/reference/ufuncs.html
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expected_exception = TypeError
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msg = (
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"loop of ufunc does not support argument 0 of type tuple which "
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f"has no callable {func.__name__} method"
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)
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with pytest.raises(expected_exception, match=msg):
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func(idx)
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@pytest.mark.parametrize(
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"func",
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[np.isfinite, np.isinf, np.isnan, np.signbit],
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ids=lambda func: func.__name__,
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)
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def test_numpy_type_funcs(idx, func):
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msg = (
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f"ufunc '{func.__name__}' not supported for the input types, and the inputs "
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"could not be safely coerced to any supported types according to "
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"the casting rule ''safe''"
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)
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with pytest.raises(TypeError, match=msg):
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func(idx)
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