def test_from_sparse_matrix(self):
data = np.array([1, 2, 3, 4, 5, 6])
indices = np.array([0, 2, 2, 0, 1, 2])
indptr = np.array([0, 2, 3, 6])
expected = CSRMatrix(data, indices, indptr, (3, 3))
sps_mat = sps.csr_matrix((data, indices, indptr), shape=(3, 3))
received = CSRMatrix(sps_mat)
self.assertContainerEqual(received, expected, ignore_hdmf_attrs=True)
def test_to_spmat(self):
data = np.array([1, 2, 3, 4, 5, 6])
indices = np.array([0, 2, 2, 0, 1, 2])
indptr = np.array([0, 2, 3, 6])
csr_mat = CSRMatrix(data, indices, indptr, (3, 3))
spmat_array = csr_mat.to_spmat().toarray()
expected = np.asarray([[1, 0, 2], [0, 0, 3], [4, 5, 6]])
np.testing.assert_array_equal(spmat_array, expected)
def test_array_bad_dim(self):
data = np.array([[[1, 2], [3, 4], [5, 6]]])
indices = np.array([0, 2, 2, 0, 1, 2])
indptr = np.array([0, 2, 3, 6])
msg = "'data' argument cannot be ndarray of dimensionality > 2."
with self.assertRaisesWith(ValueError, msg):
CSRMatrix(data, indices, indptr, (3, 3))
def test_constructor_bad_shape(self):
data = np.array([1, 2, 3, 4, 5, 6])
indices = np.array([0, 2, 2, 0, 1, 2])
indptr = np.array([0, 2, 3, 6])
shape = (3, )
msg = "'shape' argument must specify two and only two dimensions."
with self.assertRaisesWith(ValueError, msg):
CSRMatrix(data, indices, indptr, shape)
def test_constructor_bad_indices_dim(self):
data = np.array([1, 2, 3, 4, 5, 6])
indices = np.array([[0, 2, 2, 0, 1, 2]])
indptr = np.array([0, 2, 3, 6])
shape = (3, 3)
msg = "'indices' must be a 1D array of unsigned integers."
with self.assertRaisesWith(ValueError, msg):
CSRMatrix(data, indices, indptr, shape)
def test_constructor_bad_indices(self):
data = np.array([1, 2, 3, 4, 5, 6])
indices = np.array([0, -2, 2, 0, 1, 2])
indptr = np.array([0, 2, 3, 6])
shape = (3, 3)
msg = "Cannot convert 'indices' to an array of unsigned integers."
with self.assertRaisesWith(ValueError, msg):
CSRMatrix(data, indices, indptr, shape)
def test_getattrs(self):
data = np.array([1, 2, 3, 4, 5, 6])
indices = np.array([0, 2, 2, 0, 1, 2], dtype=np.int32)
indptr = np.array([0, 2, 3, 6], dtype=np.int32)
shape = (3, 3)
csr_mat = CSRMatrix(data, indices, indptr, shape)
np.testing.assert_array_equal(data, csr_mat.data)
np.testing.assert_array_equal(indices, csr_mat.indices)
np.testing.assert_array_equal(indptr, csr_mat.indptr)
np.testing.assert_array_equal(shape, csr_mat.shape)
self.assertEqual(csr_mat.indices.dtype.type, np.uint32)
self.assertEqual(csr_mat.indptr.dtype.type, np.uint32)
# NOTE: shape is stored internally in scipy.sparse.spmat as a tuple of ints. this is then converted to ndarray
# but precision differs by OS
self.assertTrue(
np.issubdtype(csr_mat.shape.dtype.type, np.unsignedinteger))
def setUpContainer(self):
data = np.array([1, 2, 3, 4, 5, 6])
indices = np.array([0, 2, 2, 0, 1, 2])
indptr = np.array([0, 2, 3, 6])
return CSRMatrix(data, indices, indptr, (3, 3))
def test_constructor_indices_missing(self):
data = np.array([1, 2, 3, 4, 5, 6])
msg = "Must specify 'indptr', 'indices', and 'shape' arguments when passing data array."
with self.assertRaisesWith(ValueError, msg):
CSRMatrix(data)
def test_2d_data(self):
data = np.array([[1, 0, 2], [0, 0, 3], [4, 5, 6]])
csr_mat = CSRMatrix(data)
sps_mat = sps.csr_matrix(data)
np.testing.assert_array_equal(csr_mat.data, sps_mat.data)