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())
def test_vectorize(self):
"""Test the @vectorize decorator for parity with NumPy's"""
context = Context()
a = numpy.arange(16).reshape(4, 4)
da = context.fromndarray(a)
@vectorize
def da_fn(a, b, c):
return a**2 + b + c
@numpy.vectorize
def a_fn(a, b, c):
return a**2 + b + c
a = a_fn(a, a, 6)
db = da_fn(da, da, 6)
assert_array_equal(db.toarray(), a)
