def check_op(self, op):
"""Check unary operation for success.
Check the one- and two-arg ufunc versions as well as the method
version attached to a LocalArray.
"""
d = Distribution.from_shape(comm=self.comm,
shape=(16, 16), dist=('b', 'n'))
x = localarray.ones(d)
y = localarray.ones(d)
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=RuntimeWarning)
result0 = op(x, casting='unsafe') # standard form
op(x, y=y, casting='unsafe') # two-arg form
assert_array_equal(result0.ndarray, y.ndarray)
def test_ones(self):
size = self.comm_size
nrows = size * 3
d = Distribution.from_shape(comm=self.comm, shape=(nrows, 20))
a = localarray.ones(d)
expected = np.ones((nrows // size, 20))
assert_array_equal(a.ndarray, expected)
def test_slicing(self):
distribution = Distribution.from_shape(self.comm,
(16, 16),
dist=('b', 'n'))
a = ones(distribution)
if self.comm.Get_rank() == 0:
dd00 = {"dist_type": 'b',
"size": 5,
"start": 0,
"stop": 3,
"proc_grid_size": 2,
"proc_grid_rank": 0}
dd01 = {"dist_type": 'n',
"size": 16}
new_distribution = Distribution(self.comm, [dd00, dd01])
rvals = a.global_index.get_slice((slice(5, None), slice(None)),
new_distribution=new_distribution)
assert_array_equal(rvals, np.ones((3, 16)))
elif self.comm.Get_rank() == 1:
dd10 = {"dist_type": 'b',
"size": 5,
"start": 3,
"stop": 5,
"proc_grid_size": 2,
"proc_grid_rank": 1}
dd11 = {"dist_type": 'n',
"size": 16}
new_distribution = Distribution(self.comm, [dd10, dd11])
rvals = a.global_index.get_slice((slice(None, 10), slice(None)),
new_distribution=new_distribution)
assert_array_equal(rvals, np.ones((2, 16)))
def check_op(self, op):
"""Check unary operation for success.
Check the one- and two-arg ufunc versions as well as the method
version attached to a LocalArray.
"""
d = Distribution.from_shape(comm=self.comm,
shape=(16, 16),
dist=('b', 'n'))
x = localarray.ones(d)
y = localarray.ones(d)
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=RuntimeWarning)
result0 = op(x, casting='unsafe') # standard form
op(x, y=y, casting='unsafe') # two-arg form
assert_array_equal(result0.ndarray, y.ndarray)
def test_slicing(self):
distribution = Distribution.from_shape(self.comm, (16, 16),
dist=('b', 'n'))
a = ones(distribution)
if self.comm.Get_rank() == 0:
dd00 = {
"dist_type": 'b',
"size": 5,
"start": 0,
"stop": 3,
"proc_grid_size": 2,
"proc_grid_rank": 0
}
dd01 = {"dist_type": 'n', "size": 16}
new_distribution = Distribution(self.comm, [dd00, dd01])
rvals = a.global_index.get_slice((slice(5, None), slice(None)),
new_distribution=new_distribution)
assert_array_equal(rvals, np.ones((3, 16)))
elif self.comm.Get_rank() == 1:
dd10 = {
"dist_type": 'b',
"size": 5,
"start": 3,
"stop": 5,
"proc_grid_size": 2,
"proc_grid_rank": 1
}
dd11 = {"dist_type": 'n', "size": 16}
new_distribution = Distribution(self.comm, [dd10, dd11])
rvals = a.global_index.get_slice((slice(None, 10), slice(None)),
new_distribution=new_distribution)
assert_array_equal(rvals, np.ones((2, 16)))
