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import operator
import numpy as np
import pytest
from pandas import (
DataFrame,
Index,
Series,
)
import pandas._testing as tm
class TestMatMul:
def test_matmul(self):
# matmul test is for GH#10259
a = DataFrame(
np.random.default_rng(2).standard_normal((3, 4)),
index=["a", "b", "c"],
columns=["p", "q", "r", "s"],
)
b = DataFrame(
np.random.default_rng(2).standard_normal((4, 2)),
index=["p", "q", "r", "s"],
columns=["one", "two"],
)
# DataFrame @ DataFrame
result = operator.matmul(a, b)
expected = DataFrame(
np.dot(a.values, b.values), index=["a", "b", "c"], columns=["one", "two"]
)
tm.assert_frame_equal(result, expected)
# DataFrame @ Series
result = operator.matmul(a, b.one)
expected = Series(np.dot(a.values, b.one.values), index=["a", "b", "c"])
tm.assert_series_equal(result, expected)
# np.array @ DataFrame
result = operator.matmul(a.values, b)
assert isinstance(result, DataFrame)
assert result.columns.equals(b.columns)
assert result.index.equals(Index(range(3)))
expected = np.dot(a.values, b.values)
tm.assert_almost_equal(result.values, expected)
# nested list @ DataFrame (__rmatmul__)
result = operator.matmul(a.values.tolist(), b)
expected = DataFrame(
np.dot(a.values, b.values), index=["a", "b", "c"], columns=["one", "two"]
)
tm.assert_almost_equal(result.values, expected.values)
# mixed dtype DataFrame @ DataFrame
a["q"] = a.q.round().astype(int)
result = operator.matmul(a, b)
expected = DataFrame(
np.dot(a.values, b.values), index=["a", "b", "c"], columns=["one", "two"]
)
tm.assert_frame_equal(result, expected)
# different dtypes DataFrame @ DataFrame
a = a.astype(int)
result = operator.matmul(a, b)
expected = DataFrame(
np.dot(a.values, b.values), index=["a", "b", "c"], columns=["one", "two"]
)
tm.assert_frame_equal(result, expected)
# unaligned
df = DataFrame(
np.random.default_rng(2).standard_normal((3, 4)),
index=[1, 2, 3],
columns=range(4),
)
df2 = DataFrame(
np.random.default_rng(2).standard_normal((5, 3)),
index=range(5),
columns=[1, 2, 3],
)
with pytest.raises(ValueError, match="aligned"):
operator.matmul(df, df2)
def test_matmul_message_shapes(self):
# GH#21581 exception message should reflect original shapes,
# not transposed shapes
a = np.random.default_rng(2).random((10, 4))
b = np.random.default_rng(2).random((5, 3))
df = DataFrame(b)
msg = r"shapes \(10, 4\) and \(5, 3\) not aligned"
with pytest.raises(ValueError, match=msg):
a @ df
with pytest.raises(ValueError, match=msg):
a.tolist() @ df