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test_numpy.py
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135 lines (113 loc) · 3.49 KB
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# Copyright 2023 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
import pandas as pd
import pytest
@pytest.mark.parametrize(
("opname",),
[
("sin",),
("cos",),
("tan",),
("arcsin",),
("arccos",),
("arctan",),
("sinh",),
("cosh",),
("tanh",),
("arcsinh",),
("arccosh",),
("arctanh",),
("exp",),
("log",),
("log10",),
("sqrt",),
("abs",),
],
)
def test_series_ufuncs(floats_pd, floats_bf, opname):
bf_result = getattr(np, opname)(floats_bf).to_pandas()
pd_result = getattr(np, opname)(floats_pd)
pd.testing.assert_series_equal(bf_result, pd_result)
@pytest.mark.parametrize(
("opname",),
[
("sin",),
("cos",),
("tan",),
("log",),
("log10",),
("sqrt",),
("abs",),
],
)
def test_df_ufuncs(scalars_dfs, opname):
scalars_df, scalars_pandas_df = scalars_dfs
bf_result = getattr(np, opname)(
scalars_df[["float64_col", "int64_col"]]
).to_pandas()
pd_result = getattr(np, opname)(scalars_pandas_df[["float64_col", "int64_col"]])
pd.testing.assert_frame_equal(bf_result, pd_result)
@pytest.mark.parametrize(
("opname",),
[
("add",),
("subtract",),
("multiply",),
("divide",),
("power",),
],
)
def test_series_binary_ufuncs(floats_product_pd, floats_product_bf, opname):
bf_result = getattr(np, opname)(
floats_product_bf.float64_col_x, floats_product_bf.float64_col_y
).to_pandas()
pd_result = getattr(np, opname)(
floats_product_pd.float64_col_x, floats_product_pd.float64_col_y
)
pd.testing.assert_series_equal(bf_result, pd_result)
@pytest.mark.parametrize(
("opname",),
[
("add",),
("subtract",),
("multiply",),
("divide",),
("power",),
],
)
def test_df_binary_ufuncs(scalars_dfs, opname):
scalars_df, scalars_pandas_df = scalars_dfs
bf_result = getattr(np, opname)(
scalars_df[["float64_col", "int64_col"]], 5.1
).to_pandas()
pd_result = getattr(np, opname)(
scalars_pandas_df[["float64_col", "int64_col"]], 5.1
)
pd.testing.assert_frame_equal(bf_result, pd_result)
def test_series_binary_ufuncs_reverse(scalars_dfs):
scalars_df, scalars_pandas_df = scalars_dfs
# Could be any non-symmetric binary op
bf_result = np.subtract(5.1, scalars_df["int64_col"]).to_pandas()
pd_result = np.subtract(5.1, scalars_pandas_df["int64_col"])
pd.testing.assert_series_equal(bf_result, pd_result)
def test_df_binary_ufuncs_reverse(scalars_dfs):
scalars_df, scalars_pandas_df = scalars_dfs
# Could be any non-symmetric binary op
bf_result = np.subtract(5.1, scalars_df[["float64_col", "int64_col"]]).to_pandas()
pd_result = np.subtract(
5.1,
scalars_pandas_df[["float64_col", "int64_col"]],
)
pd.testing.assert_frame_equal(bf_result, pd_result)