def test_pmat_neighbors_invalid_input(self):
np.random.seed(12)
pmat = np.random.random_sample((20, 20))
np.fill_diagonal(pmat, 0.5)
# Too large filter_shape
pmat_neigh = asset._PMatNeighbors(filter_shape=(11, 3), n_largest=3)
self.assertRaises(ValueError, pmat_neigh.compute, pmat)
pmat_neigh = asset._PMatNeighbors(filter_shape=(21, 3), n_largest=3)
np.fill_diagonal(pmat, 0.0)
self.assertRaises(ValueError, pmat_neigh.compute, pmat)
pmat_neigh = asset._PMatNeighbors(filter_shape=(11, 3), n_largest=3,
max_chunk_size=10)
if HAVE_PYOPENCL:
# max_chunk_size > filter_shape
self.assertRaises(ValueError, pmat_neigh.pyopencl, pmat)
if HAVE_CUDA:
# max_chunk_size > filter_shape
self.assertRaises(ValueError, pmat_neigh.pycuda, pmat)
# Too small filter_shape
self.assertRaises(ValueError, asset._PMatNeighbors,
filter_shape=(11, 3), n_largest=100)
# w >= l
self.assertRaises(ValueError, asset._PMatNeighbors,
filter_shape=(9, 9), n_largest=3)
# not centered
self.assertWarns(UserWarning, asset._PMatNeighbors,
filter_shape=(10, 6), n_largest=3)
def test_pmat_neighbors_gpu_overlapped_chunks(self):
# The pmat is chunked as follows:
# [(0, 11), (11, 22), (22, 33), (29, 40)]
# Two last chunks overlap.
np.random.seed(12)
pmat = np.random.random_sample((50, 50)).astype(np.float32)
pmat_neigh = asset._PMatNeighbors(filter_shape=(11, 5), n_largest=3,
max_chunk_size=12)
lmat_true = pmat_neigh.cpu(pmat)
if HAVE_PYOPENCL:
lmat_opencl = pmat_neigh.pyopencl(pmat)
assert_array_almost_equal(lmat_opencl, lmat_true)
if HAVE_CUDA:
lmat_cuda = pmat_neigh.pycuda(pmat)
assert_array_almost_equal(lmat_cuda, lmat_true)
def test_pmat_neighbors_gpu_chunked(self):
np.random.seed(12)
filter_shape = (7, 3)
n_largest = 3
pmat1 = np.random.random_sample((40, 40)).astype(np.float32)
np.fill_diagonal(pmat1, 0.5)
pmat2 = np.random.random_sample((70, 27)).astype(np.float32)
pmat3 = np.random.random_sample((41, 80)).astype(np.float32)
for pmat in (pmat1, pmat2, pmat3):
pmat_neigh = asset._PMatNeighbors(filter_shape=filter_shape,
n_largest=n_largest)
lmat_true = pmat_neigh.cpu(pmat)
for max_chunk_size in (17, 20, 29):
pmat_neigh.max_chunk_size = max_chunk_size
if HAVE_PYOPENCL:
lmat_opencl = pmat_neigh.pyopencl(pmat)
assert_array_almost_equal(lmat_opencl, lmat_true)
if HAVE_CUDA:
lmat_cuda = pmat_neigh.pycuda(pmat)
assert_array_almost_equal(lmat_cuda, lmat_true)
def test_pmat_neighbors_gpu(self):
np.random.seed(12)
n_largest = 3
pmat1 = np.random.random_sample((40, 40)).astype(np.float32)
np.fill_diagonal(pmat1, 0.5)
pmat2 = np.random.random_sample((70, 23)).astype(np.float32)
pmat3 = np.random.random_sample((27, 93)).astype(np.float32)
for pmat in (pmat1, pmat2, pmat3):
for filter_size in (4, 8, 11):
filter_shape = (filter_size, 3)
with warnings.catch_warnings():
# ignore even filter sizes
warnings.simplefilter('ignore', UserWarning)
pmat_neigh = asset._PMatNeighbors(
filter_shape=filter_shape, n_largest=n_largest)
lmat_true = pmat_neigh.cpu(pmat)
if HAVE_PYOPENCL:
lmat_opencl = pmat_neigh.pyopencl(pmat)
assert_array_almost_equal(lmat_opencl, lmat_true)
if HAVE_CUDA:
lmat_cuda = pmat_neigh.pycuda(pmat)
assert_array_almost_equal(lmat_cuda, lmat_true)