Voice et bot modif

venv/lib/python3.12/site-packages/numpy/linalg/tests/test_linalg.py

@@ -745,6 +745,12 @@ class SVDHermitianCases(HermitianTestCase, HermitianGeneralizedTestCase):
 class TestSVDHermitian(SVDHermitianCases, SVDBaseTests):
     hermitian = True
 
+    def test_singular(self):
+        x = np.array([[1, 0], [0, 0]])
+        u, _, vh = linalg.svd(x, hermitian=self.hermitian)
+        assert_allclose(u @ u.T.conj(), np.eye(2), rtol=1e-14)
+        assert_allclose(vh @ vh.T.conj(), np.eye(2), rtol=1e-14)
+
 
 class CondCases(LinalgSquareTestCase, LinalgGeneralizedSquareTestCase):
     # cond(x, p) for p in (None, 2, -2)
@@ -2440,3 +2446,22 @@ def test_vector_norm_empty():
         assert_equal(np.linalg.vector_norm(x, ord=1), 0)
         assert_equal(np.linalg.vector_norm(x, ord=2), 0)
         assert_equal(np.linalg.vector_norm(x, ord=np.inf), 0)
+
+def test_empty_matrix_rank():
+    assert_equal(matrix_rank(np.zeros((0, 0))), 0)
+    assert_equal(matrix_rank(np.zeros((0, 5))), 0)
+    assert_equal(matrix_rank(np.zeros((5, 0))), 0)
+
+    result = matrix_rank(np.zeros((0, 5, 5)))
+    assert_equal(result.shape, (0,))
+    assert_equal(result.dtype, np.intp)
+
+    result = matrix_rank(np.zeros((3, 0, 5)))
+    assert_equal(result, np.array([0, 0, 0]))
+
+    result = matrix_rank(np.zeros((2, 5, 0)))
+    assert_equal(result, np.array([0, 0]))
+
+    result = matrix_rank(np.zeros((2, 3, 0, 4)))
+    assert_equal(result.shape, (2, 3))
+    assert_equal(result, np.zeros((2, 3), dtype=np.intp))

venv/lib/python3.12/site-packages/numpy/linalg/tests/test_regression.py

@@ -7,6 +7,7 @@ import numpy as np
 from numpy import arange, array, dot, float64, linalg, transpose
 from numpy.testing import (
     assert_,
+    assert_almost_equal,
     assert_array_almost_equal,
     assert_array_equal,
     assert_array_less,
@@ -180,3 +181,10 @@ class TestRegression:
             if mismatches != 0:
                 assert False, ("unexpected result from matmul, "
                     "probably due to OpenBLAS threading issues")
+
+    def test_norm_linux_arm(self):
+        # gh-30816
+        a = np.arange(20000) / 50000
+        b = a + 1j * np.roll(np.flip(a), 12345)
+        norm = np.linalg.norm(b)
+        assert_almost_equal(norm, 46.18628948075393)