def test_merge(self):
n_blocks = 100
n_rows = 5
n_cols = 10
col_dim = 3
np.random.seed(n_blocks)
data = np.random.random((n_blocks, 2, col_dim))
indices = np.random.randint(0, n_cols, size=n_blocks)
indptr = np.array([0] + np.sort(
np.random.choice(
np.arange(1, n_blocks - 1), size=n_rows -
1, replace=False)).tolist() + [n_blocks])
sbrm = DBSRMatrix()
for i in range(n_rows):
sbrm.append_row(indices[indptr[i]:indptr[i + 1]],
data[indptr[i]:indptr[i + 1]])
np_mat = bsr_matrix((data, indices, indptr)).todense()
pair = np.random.choice(np.arange(n_cols), size=2, replace=False)
sbrm.merge_cols(tuple(pair.tolist()))
dest = min(pair)
src = max(pair)
np_mat[:, col_dim * dest:col_dim * dest +
col_dim] += np_mat[:, col_dim * src:col_dim * src + col_dim]
np_mat = np.delete(np_mat,
np.arange(col_dim * src, col_dim * src + col_dim),
1)
self.assertTrue(np.allclose(np_mat, sbrm.to_bsr().todense()))
def test_merge_cols(self):
nblocks = 13
np.random.seed(nblocks)
data = np.random.random((nblocks, 2, 3))
indices = np.random.randint(0, 6, size=nblocks)
indptr = np.arange(len(indices) + 1)
sbrm = DBSRMatrix()
for i in range(nblocks):
sbrm.append_row(indices[i], data[i])
indices[indices == 2] = 1
indices[indices > 2] += -1
sbrm.merge_cols((1, 2))
bsr = bsr_matrix((data, indices, indptr))
self.assertTrue(np.allclose(bsr.todense(), sbrm.to_bsr().todense()))