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111 lines
3.9 KiB
Python
111 lines
3.9 KiB
Python
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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dtypes = [
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"int64",
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"Int64",
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{"A": "int64", "B": "Int64"},
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]
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@pytest.mark.parametrize("dtype", dtypes)
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def test_unary_unary(dtype):
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# unary input, unary output
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values = np.array([[-1, -1], [1, 1]], dtype="int64")
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df = pd.DataFrame(values, columns=["A", "B"], index=["a", "b"]).astype(dtype=dtype)
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result = np.positive(df)
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expected = pd.DataFrame(
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np.positive(values), index=df.index, columns=df.columns
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).astype(dtype)
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tm.assert_frame_equal(result, expected)
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@pytest.mark.parametrize("dtype", dtypes)
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def test_unary_binary(dtype):
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# unary input, binary output
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if pd.api.types.is_extension_array_dtype(dtype) or isinstance(dtype, dict):
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pytest.xfail(reason="Extension / mixed with multiple outuputs not implemented.")
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values = np.array([[-1, -1], [1, 1]], dtype="int64")
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df = pd.DataFrame(values, columns=["A", "B"], index=["a", "b"]).astype(dtype=dtype)
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result_pandas = np.modf(df)
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assert isinstance(result_pandas, tuple)
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assert len(result_pandas) == 2
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expected_numpy = np.modf(values)
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for result, b in zip(result_pandas, expected_numpy):
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expected = pd.DataFrame(b, index=df.index, columns=df.columns)
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tm.assert_frame_equal(result, expected)
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@pytest.mark.parametrize("dtype", dtypes)
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def test_binary_input_dispatch_binop(dtype):
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# binop ufuncs are dispatched to our dunder methods.
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values = np.array([[-1, -1], [1, 1]], dtype="int64")
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df = pd.DataFrame(values, columns=["A", "B"], index=["a", "b"]).astype(dtype=dtype)
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result = np.add(df, df)
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expected = pd.DataFrame(
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np.add(values, values), index=df.index, columns=df.columns
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).astype(dtype)
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tm.assert_frame_equal(result, expected)
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@pytest.mark.parametrize("dtype_a", dtypes)
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@pytest.mark.parametrize("dtype_b", dtypes)
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def test_binary_input_aligns_columns(dtype_a, dtype_b):
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if (
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pd.api.types.is_extension_array_dtype(dtype_a)
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or isinstance(dtype_a, dict)
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or pd.api.types.is_extension_array_dtype(dtype_b)
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or isinstance(dtype_b, dict)
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):
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pytest.xfail(reason="Extension / mixed with multiple inputs not implemented.")
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df1 = pd.DataFrame({"A": [1, 2], "B": [3, 4]}).astype(dtype_a)
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if isinstance(dtype_a, dict) and isinstance(dtype_b, dict):
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dtype_b["C"] = dtype_b.pop("B")
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df2 = pd.DataFrame({"A": [1, 2], "C": [3, 4]}).astype(dtype_b)
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result = np.heaviside(df1, df2)
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expected = np.heaviside(
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np.array([[1, 3, np.nan], [2, 4, np.nan]]),
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np.array([[1, np.nan, 3], [2, np.nan, 4]]),
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)
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expected = pd.DataFrame(expected, index=[0, 1], columns=["A", "B", "C"])
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tm.assert_frame_equal(result, expected)
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@pytest.mark.parametrize("dtype", dtypes)
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def test_binary_input_aligns_index(dtype):
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if pd.api.types.is_extension_array_dtype(dtype) or isinstance(dtype, dict):
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pytest.xfail(reason="Extension / mixed with multiple inputs not implemented.")
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df1 = pd.DataFrame({"A": [1, 2], "B": [3, 4]}, index=["a", "b"]).astype(dtype)
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df2 = pd.DataFrame({"A": [1, 2], "B": [3, 4]}, index=["a", "c"]).astype(dtype)
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result = np.heaviside(df1, df2)
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expected = np.heaviside(
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np.array([[1, 3], [3, 4], [np.nan, np.nan]]),
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np.array([[1, 3], [np.nan, np.nan], [3, 4]]),
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)
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# TODO(FloatArray): this will be Float64Dtype.
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expected = pd.DataFrame(expected, index=["a", "b", "c"], columns=["A", "B"])
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tm.assert_frame_equal(result, expected)
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def test_binary_frame_series_raises():
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# We don't currently implement
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df = pd.DataFrame({"A": [1, 2]})
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with pytest.raises(NotImplementedError, match="logaddexp"):
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np.logaddexp(df, df["A"])
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with pytest.raises(NotImplementedError, match="logaddexp"):
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np.logaddexp(df["A"], df)
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def test_frame_outer_deprecated():
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df = pd.DataFrame({"A": [1, 2]})
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with tm.assert_produces_warning(FutureWarning):
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np.subtract.outer(df, df)
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