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_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])