Fixes bug

thewalrus/decompositions.py

@@ -194,7 +194,7 @@ def takagi(A, svd_order=True):
         # If the matrix A is real one can be more clever and use its eigendecomposition
         ls, U = np.linalg.eigh(A)
         vals = np.abs(ls)  # These are the Takagi eigenvalues
-        signs = (-1) ** (1 + np.heaviside(vals, 1))
+        signs = (-1) ** (1 + np.heaviside(ls, 1))
         phases = np.sqrt(np.complex128(signs))
         Uc = U * phases  # One needs to readjust the phases
         # Find the permutation to sort in decreasing order

thewalrus/tests/test_decompositions.py

@@ -281,11 +281,14 @@ def test_takagi(n, datatype, svd_order):
 @pytest.mark.parametrize("half_rank", [0, 1])
 @pytest.mark.parametrize("phase", [0, 1])
 @pytest.mark.parametrize("null_space", [0, 5, 10])
-def test_degenerate(n, datatype, svd_order, half_rank, phase, null_space):
+@pytest.mark.parametrize("offset", [0, 0.5])
+def test_degenerate(n, datatype, svd_order, half_rank, phase, null_space, offset):
     """Tests Takagi produces the correct result for very degenerate cases"""
     nhalf = n // 2
     diags = (
-        [half_rank * np.random.rand()] * nhalf + [np.random.rand()] * (n - nhalf) + [0] * null_space
+        [half_rank * np.random.rand()] * nhalf
+        + [np.random.rand() - offset] * (n - nhalf)
+        + [0] * null_space
     )
     if datatype is np.complex128:
         U = haar_measure(n + null_space)