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venv/Lib/site-packages/pandas/tests/frame/methods/test_matmul.py

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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