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- import numpy as np
- import pytest
- import pandas as pd
- from pandas import (
- DatetimeIndex,
- Index,
- )
- import pandas._testing as tm
- dtlike_dtypes = [
- np.dtype("timedelta64[ns]"),
- np.dtype("datetime64[ns]"),
- pd.DatetimeTZDtype("ns", "Asia/Tokyo"),
- pd.PeriodDtype("ns"),
- ]
- @pytest.mark.parametrize("ldtype", dtlike_dtypes)
- @pytest.mark.parametrize("rdtype", dtlike_dtypes)
- def test_get_indexer_non_unique_wrong_dtype(ldtype, rdtype):
- vals = np.tile(3600 * 10**9 * np.arange(3), 2)
- def construct(dtype):
- if dtype is dtlike_dtypes[-1]:
- # PeriodArray will try to cast ints to strings
- return DatetimeIndex(vals).astype(dtype)
- return Index(vals, dtype=dtype)
- left = construct(ldtype)
- right = construct(rdtype)
- result = left.get_indexer_non_unique(right)
- if ldtype is rdtype:
- ex1 = np.array([0, 3, 1, 4, 2, 5] * 2, dtype=np.intp)
- ex2 = np.array([], dtype=np.intp)
- tm.assert_numpy_array_equal(result[0], ex1)
- tm.assert_numpy_array_equal(result[1], ex2)
- else:
- no_matches = np.array([-1] * 6, dtype=np.intp)
- missing = np.arange(6, dtype=np.intp)
- tm.assert_numpy_array_equal(result[0], no_matches)
- tm.assert_numpy_array_equal(result[1], missing)
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