Merge pull request scipy#2768 from argriffing/lax-fractional-matrix-power-singularity

TST: mark a fractional_matrix_power test as knownfail

Author: Ralf Gommers

scipy/linalg/_matfuncs_inv_ssq.py

@@ -627,9 +627,12 @@ def _remainder_matrix_power(A, t):
            32 (3). pp. 1056-1078. ISSN 0895-4798
 
     """
+    # This code block is copied from numpy.matrix_power().
     A = np.asarray(A)
     if len(A.shape) != 2 or A.shape[0] != A.shape[1]:
-        raise ValueError('expected a square matrix')
+        raise ValueError('input must be a square array')
+
+    # Get the number of rows and columns.
     n, n = A.shape
 
     # Triangularize the matrix if necessary,

scipy/linalg/tests/test_matfuncs.py

@@ -509,21 +509,16 @@ def test_type_conversion_mixed_sign_or_complex_spectrum(self):
                 A_power = fractional_matrix_power(A, p)
                 assert_(A_power.dtype.char in complex_dtype_chars)
 
+    @decorators.knownfailureif(True, 'Too unstable across LAPACKs.')
     def test_singular(self):
         # Negative fractional powers do not work with singular matrices.
-        # Neither do non-integer fractional powers,
-        # because the scaling and squaring cannot deal with it.
         for matrix_as_list in (
                 [[0, 0], [0, 0]],
                 [[1, 1], [1, 1]],
                 [[1, 2], [3, 6]],
                 [[0, 0, 0], [0, 1, 1], [0, -1, 1]]):
 
-            # check that the spectrum has the expected properties
-            W = scipy.linalg.eigvals(matrix_as_list)
-            assert_(np.sum(W != 0) < len(W))
-
-            # check fractional powers both for float and for complex types
+            # Check fractional powers both for float and for complex types.
             for newtype in (float, complex):
                 A = np.array(matrix_as_list, dtype=newtype)
                 for p in (-0.7, -0.9, -2.4, -1.3):