class TestDistArrayCreation(IpclusterTestCase):
"""Test distarray creation methods"""
def setUp(self):
self.context = Context(self.client)
def test_zeros(self):
shape = (16, 16)
zero_distarray = self.context.zeros(shape)
zero_ndarray = numpy.zeros(shape)
assert_array_equal(zero_distarray.tondarray(), zero_ndarray)
def test_ones(self):
shape = (16, 16)
one_distarray = self.context.ones(shape)
one_ndarray = numpy.ones(shape)
assert_array_equal(one_distarray.tondarray(), one_ndarray)
def test_empty(self):
shape = (16, 16)
empty_distarray = self.context.empty(shape)
self.assertEqual(empty_distarray.shape, shape)
def test_fromndarray(self):
ndarr = numpy.arange(16).reshape(4, 4)
distarr = self.context.fromndarray(ndarr)
for (i, j), val in numpy.ndenumerate(ndarr):
self.assertEqual(distarr[i, j], ndarr[i, j])
class TestDistArrayCreation(unittest.TestCase):
"""Test distarray creation methods"""
def setUp(self):
self.context = Context()
def tearDown(self):
self.context.close()
def test___init__(self):
shape = (100, 100)
distribution = Distribution.from_shape(self.context, shape, ('b', 'c'))
da = DistArray(distribution, dtype=int)
da.fill(42)
nda = numpy.empty(shape, dtype=int)
nda.fill(42)
assert_array_equal(da.tondarray(), nda)
def test_zeros(self):
shape = (16, 16)
zero_distarray = self.context.zeros(shape)
zero_ndarray = numpy.zeros(shape)
assert_array_equal(zero_distarray.tondarray(), zero_ndarray)
def test_ones(self):
shape = (16, 16)
one_distarray = self.context.ones(shape)
one_ndarray = numpy.ones(shape)
assert_array_equal(one_distarray.tondarray(), one_ndarray)
def test_empty(self):
shape = (16, 16)
empty_distarray = self.context.empty(shape)
self.assertEqual(empty_distarray.shape, shape)
def test_fromndarray(self):
ndarr = numpy.arange(16).reshape(4, 4)
distarr = self.context.fromndarray(ndarr)
for (i, j), val in numpy.ndenumerate(ndarr):
self.assertEqual(distarr[i, j], ndarr[i, j])
def test_grid_rank(self):
# regression test for issue #235
a = self.context.empty((4, 4, 4), dist=('b', 'n', 'b'),
grid_shape=(1, 1, 4))
self.assertEqual(a.grid_shape, (1, 1, 4))
def test_fromfunction(self):
fn = lambda i, j: i + j
shape = (7, 9)
expected = numpy.fromfunction(fn, shape, dtype=int)
result = self.context.fromfunction(fn, shape, dtype=int)
assert_array_equal(expected, result.tondarray())
class TestDistArray(unittest.TestCase):
def setUp(self):
self.dac = Context()
def tearDown(self):
self.dac.close()
def test_set_and_getitem_block_dist(self):
size = 10
dap = self.dac.empty((size,), dist={0: 'b'})
for val in range(size):
dap[val] = val
for val in range(size):
self.assertEqual(dap[val], val)
for i in range(1, size + 1):
dap[-i] = i
self.assertEqual(dap[-i], i)
def test_set_and_getitem_nd_block_dist(self):
size = 5
dap = self.dac.empty((size, size), dist={0: 'b', 1: 'b'})
for row in range(size):
for col in range(size):
val = size*row + col
dap[row, col] = val
self.assertEqual(dap[row, col], val)
for row in range(1 ,size + 1):
for col in range(1, size + 1):
dap[-row, -col] = row + col
self.assertEqual(dap[-row, -col], row + col)
def test_set_and_getitem_cyclic_dist(self):
size = 10
dap = self.dac.empty((size,), dist={0: 'c'})
for val in range(size):
dap[val] = val
self.assertEqual(dap[val], val)
for i in range(1, size + 1):
dap[-i] = i
self.assertEqual(dap[-i], i)
def test_get_index_error(self):
dap = self.dac.empty((10,), dist={0: 'c'})
with self.assertRaises(IndexError):
dap[11]
with self.assertRaises(IndexError):
dap[-11]
def test_set_index_error(self):
dap = self.dac.empty((10,), dist={0: 'c'})
with self.assertRaises(IndexError):
dap[11] = 55
with self.assertRaises(IndexError):
dap[-11] = 55
def test_iteration(self):
size = 10
dap = self.dac.empty((size,), dist={0: 'c'})
dap.fill(10)
for val in dap:
self.assertEqual(val, 10)
def test_tondarray(self):
dap = self.dac.empty((3, 3))
ndarr = numpy.arange(9).reshape(3, 3)
for (i, j), val in numpy.ndenumerate(ndarr):
dap[i, j] = ndarr[i, j]
numpy.testing.assert_array_equal(dap.tondarray(), ndarr)
def test_global_tolocal_bug(self):
# gh-issue #154
dap = self.dac.zeros((3, 3), dist=('n', 'b'))
ndarr = numpy.zeros((3, 3))
numpy.testing.assert_array_equal(dap.tondarray(), ndarr)
class TestDistArray(IpclusterTestCase):
def setUp(self):
self.dac = Context(self.client)
def test_set_and_getitem_block_dist(self):
size = 10
dap = self.dac.empty((size,), dist={0: 'b'})
for val in range(size):
dap[val] = val
for val in range(size):
self.assertEqual(dap[val], val)
def test_set_and_getitem_nd_block_dist(self):
size = 5
dap = self.dac.empty((size, size), dist={0: 'b', 1: 'b'})
for row in range(size):
for col in range(size):
val = size*row + col
dap[row, col] = val
for row in range(size):
for col in range(size):
val = size*row + col
self.assertEqual(dap[row, col], val)
def test_set_and_getitem_cyclic_dist(self):
size = 10
dap = self.dac.empty((size,), dist={0: 'c'})
for val in range(size):
dap[val] = val
for val in range(size):
self.assertEqual(dap[val], val)
@unittest.skip("Slicing not yet implemented.")
def test_slice_in_getitem_block_dist(self):
dap = self.dac.empty((100,), dist={0: 'b'})
self.assertIsInstance(dap[20:40], DistArray)
@unittest.skip("Slicing not yet implemented.")
def test_slice_in_setitem_raises_valueerror(self):
dap = self.dac.empty((100,), dist={0: 'b'})
vals = numpy.random.random(20)
with self.assertRaises(NotImplementedError):
dap[20:40] = vals
@unittest.skip('Slice assignment not yet implemented.')
def test_slice_size_error(self):
dap = self.dac.empty((100,), dist={0: 'c'})
with self.assertRaises(NotImplementedError):
dap[20:40] = (11, 12)
def test_get_index_error(self):
dap = self.dac.empty((10,), dist={0: 'c'})
with self.assertRaises(IndexError):
dap[11]
def test_set_index_error(self):
dap = self.dac.empty((10,), dist={0: 'c'})
with self.assertRaises(IndexError):
dap[11] = 55
def test_iteration(self):
size = 10
dap = self.dac.empty((size,), dist={0: 'c'})
dap.fill(10)
for val in dap:
self.assertEqual(val, 10)
def test_tondarray(self):
dap = self.dac.empty((3, 3))
ndarr = numpy.arange(9).reshape(3, 3)
for (i, j), val in numpy.ndenumerate(ndarr):
dap[i, j] = ndarr[i, j]
numpy.testing.assert_array_equal(dap.tondarray(), ndarr)
def test_global_tolocal_bug(self):
# gh-issue #154
dap = self.dac.zeros((3, 3), dist=('n', 'b'))
ndarr = numpy.zeros((3, 3))
numpy.testing.assert_array_equal(dap.tondarray(), ndarr)