Updated script that can be controled by Nodejs web app

lib/python3.13/site-packages/pandas/tests/series/methods/test_matmul.py

@@ -0,0 +1,82 @@
+import operator
+
+import numpy as np
+import pytest
+
+from pandas import (
+    DataFrame,
+    Series,
+)
+import pandas._testing as tm
+
+
+class TestMatmul:
+    def test_matmul(self):
+        # matmul test is for GH#10259
+        a = Series(
+            np.random.default_rng(2).standard_normal(4), index=["p", "q", "r", "s"]
+        )
+        b = DataFrame(
+            np.random.default_rng(2).standard_normal((3, 4)),
+            index=["1", "2", "3"],
+            columns=["p", "q", "r", "s"],
+        ).T
+
+        # Series @ DataFrame -> Series
+        result = operator.matmul(a, b)
+        expected = Series(np.dot(a.values, b.values), index=["1", "2", "3"])
+        tm.assert_series_equal(result, expected)
+
+        # DataFrame @ Series -> Series
+        result = operator.matmul(b.T, a)
+        expected = Series(np.dot(b.T.values, a.T.values), index=["1", "2", "3"])
+        tm.assert_series_equal(result, expected)
+
+        # Series @ Series -> scalar
+        result = operator.matmul(a, a)
+        expected = np.dot(a.values, a.values)
+        tm.assert_almost_equal(result, expected)
+
+        # GH#21530
+        # vector (1D np.array) @ Series (__rmatmul__)
+        result = operator.matmul(a.values, a)
+        expected = np.dot(a.values, a.values)
+        tm.assert_almost_equal(result, expected)
+
+        # GH#21530
+        # vector (1D list) @ Series (__rmatmul__)
+        result = operator.matmul(a.values.tolist(), a)
+        expected = np.dot(a.values, a.values)
+        tm.assert_almost_equal(result, expected)
+
+        # GH#21530
+        # matrix (2D np.array) @ Series (__rmatmul__)
+        result = operator.matmul(b.T.values, a)
+        expected = np.dot(b.T.values, a.values)
+        tm.assert_almost_equal(result, expected)
+
+        # GH#21530
+        # matrix (2D nested lists) @ Series (__rmatmul__)
+        result = operator.matmul(b.T.values.tolist(), a)
+        expected = np.dot(b.T.values, a.values)
+        tm.assert_almost_equal(result, expected)
+
+        # mixed dtype DataFrame @ Series
+        a["p"] = int(a.p)
+        result = operator.matmul(b.T, a)
+        expected = Series(np.dot(b.T.values, a.T.values), index=["1", "2", "3"])
+        tm.assert_series_equal(result, expected)
+
+        # different dtypes DataFrame @ Series
+        a = a.astype(int)
+        result = operator.matmul(b.T, a)
+        expected = Series(np.dot(b.T.values, a.T.values), index=["1", "2", "3"])
+        tm.assert_series_equal(result, expected)
+
+        msg = r"Dot product shape mismatch, \(4,\) vs \(3,\)"
+        # exception raised is of type Exception
+        with pytest.raises(Exception, match=msg):
+            a.dot(a.values[:3])
+        msg = "matrices are not aligned"
+        with pytest.raises(ValueError, match=msg):
+            a.dot(b.T)