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42 lines
1.4 KiB
42 lines
1.4 KiB
1 year ago
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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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class BaseAccumulateTests:
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"""
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Accumulation specific tests. Generally these only
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make sense for numeric/boolean operations.
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"""
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def _supports_accumulation(self, ser: pd.Series, op_name: str) -> bool:
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# Do we expect this accumulation to be supported for this dtype?
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# We default to assuming "no"; subclass authors should override here.
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return False
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def check_accumulate(self, ser: pd.Series, op_name: str, skipna: bool):
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alt = ser.astype("float64")
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result = getattr(ser, op_name)(skipna=skipna)
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if result.dtype == pd.Float32Dtype() and op_name == "cumprod" and skipna:
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# TODO: avoid special-casing here
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pytest.skip(
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f"Float32 precision lead to large differences with op {op_name} "
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f"and skipna={skipna}"
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)
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expected = getattr(alt, op_name)(skipna=skipna)
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tm.assert_series_equal(result, expected, check_dtype=False)
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@pytest.mark.parametrize("skipna", [True, False])
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def test_accumulate_series(self, data, all_numeric_accumulations, skipna):
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op_name = all_numeric_accumulations
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ser = pd.Series(data)
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if self._supports_accumulation(ser, op_name):
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self.check_accumulate(ser, op_name, skipna)
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else:
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with pytest.raises(NotImplementedError):
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getattr(ser, op_name)(skipna=skipna)
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