def _local_load_hdf5(filename, ddpr, comm, key):
from distarray.localapi import load_hdf5
if len(ddpr):
dim_data = ddpr[comm.Get_rank()]
else:
dim_data = ()
return proxyize(load_hdf5(comm, filename, dim_data, key))
def test_load_bn(self):
dim_data_per_rank = bn_test_data
la = load_hdf5(comm=self.comm, filename=self.output_path,
dim_data=dim_data_per_rank[self.rank],
key=self.key)
with self.h5py.File(self.output_path, 'r', driver='mpio',
comm=self.comm) as fp:
assert_equal(la, self.expected[numpy.newaxis, self.rank])
def test_load_nu(self):
dim_data_per_rank = nu_test_data
expected_indices = [dd[1]['indices'] for dd in dim_data_per_rank]
la = load_hdf5(comm=self.comm, filename=self.output_path,
dim_data=dim_data_per_rank[self.rank],
key=self.key)
with self.h5py.File(self.output_path, 'r', driver='mpio',
comm=self.comm) as fp:
assert_equal(la, self.expected[:, expected_indices[self.rank]])
def test_load_bn(self):
dim_data_per_rank = bn_test_data
la = load_hdf5(comm=self.comm,
filename=self.output_path,
dim_data=dim_data_per_rank[self.rank],
key=self.key)
with self.h5py.File(self.output_path,
'r',
driver='mpio',
comm=self.comm) as fp:
assert_equal(la, self.expected[numpy.newaxis, self.rank])
def test_load_nc(self):
dim_data_per_rank = nc_test_data
expected_slices = [(slice(None), slice(0, None, 2)),
(slice(None), slice(1, None, 2))]
la = load_hdf5(comm=self.comm, filename=self.output_path,
dim_data=dim_data_per_rank[self.rank],
key=self.key)
with self.h5py.File(self.output_path, 'r', driver='mpio',
comm=self.comm) as fp:
expected_slice = expected_slices[self.rank]
assert_equal(la, self.expected[expected_slice])
def test_load_nu(self):
dim_data_per_rank = nu_test_data
expected_indices = [dd[1]['indices'] for dd in dim_data_per_rank]
la = load_hdf5(comm=self.comm,
filename=self.output_path,
dim_data=dim_data_per_rank[self.rank],
key=self.key)
with self.h5py.File(self.output_path,
'r',
driver='mpio',
comm=self.comm) as fp:
assert_equal(la, self.expected[:, expected_indices[self.rank]])
def test_load_nc(self):
dim_data_per_rank = nc_test_data
expected_slices = [(slice(None), slice(0, None, 2)),
(slice(None), slice(1, None, 2))]
la = load_hdf5(comm=self.comm,
filename=self.output_path,
dim_data=dim_data_per_rank[self.rank],
key=self.key)
with self.h5py.File(self.output_path,
'r',
driver='mpio',
comm=self.comm) as fp:
expected_slice = expected_slices[self.rank]
assert_equal(la, self.expected[expected_slice])
