def test_is_symmetric_dense(self):
m = self.block00.toarray()
self.assertTrue(is_symmetric_dense(m))
self.assertTrue(is_symmetric_dense(2))
with self.assertRaises(Exception) as context:
self.assertTrue(is_symmetric_dense(self.block00))
def test_is_symmetric_dense(self):
m = self.block00.toarray()
self.assertTrue(is_symmetric_dense(m))
self.assertTrue(is_symmetric_dense(2))
with self.assertRaises(Exception) as context:
self.assertTrue(is_symmetric_dense(self.block00))
def test_is_symmetric_dense(self):
test_m = np.array([[2., 0., 0., 1.], [0., 3., 0., 0.],
[0., 0., 4., 0.], [1., 0., 0., 5.]])
flag = is_symmetric_dense(test_m)
self.assertTrue(flag)
usm = self.basic_m.toarray()
flag = is_symmetric_dense(usm)
self.assertFalse(flag)
def __init__(self, arg1, shape=None, dtype=None, copy=False, **kwargs):
# check if dense matrix is symmetric
if isinstance(arg1, np.ndarray):
if not is_symmetric_dense(arg1):
raise RuntimeError("ndarray is not symmetric")
# keep only lower triangular
arg1 = np.tril(arg1)
# symmetric matrices don't expand symmetry
expand_symmetry = kwargs.pop('expand_symmetry', False)
error_msg = "Symmetric matrices only store lower triangular"
assert not expand_symmetry, error_msg
super(CSCSymMatrix, self).__init__(arg1,
shape=shape,
dtype=dtype,
copy=copy,
expand_symmetry=expand_symmetry,
**kwargs)
# add check to verify square matrix
if self.shape[0] != self.shape[1]:
raise RuntimeError('A rectangular matrix is not symmetric')
# check nnz is less than the full lower triangular
if self.nnz > self.shape[0] * (self.shape[0] + 1) / 2:
raise RuntimeError(
'CSCSymMatrix only store lower triangular entries. Too many nnz'
)
# TODO: check only lower triangular entries
# makes sparse matrix symmetric
self._symmetric = True
