def setUp(self):
self.h5py = import_or_skip('h5py')
self.dac = Context(targets=[0, 1])
self.output_path = temp_filepath('.hdf5')
self.expected = np.arange(20).reshape(2, 10)
with self.h5py.File(self.output_path, 'w') as fp:
fp["test"] = self.expected
def setUpClass(cls):
# raise a skipTest if plotting import fails
# (because matplotlib isn't installed, probably)
cls.plt = import_or_skip("distarray.plotting")
super(TestPlotting, cls).setUpClass()
cls.da = Distribution(cls.context, (64, 64))
cls.arr = cls.context.ones(cls.da)
def test_writing_two_datasets(self):
h5py = import_or_skip('h5py')
datalen = 33
dac = Context(self.client)
da = dac.empty((datalen,), dist={0: 'b'})
for i in range(datalen):
da[i] = i
output_path = temp_filepath('.hdf5')
try:
# make a file, and write to dataset 'foo'
with h5py.File(output_path, 'w') as fp:
fp['foo'] = np.arange(10)
# try saving to a different dataset
dac.save_hdf5(output_path, da, key='bar', mode='a')
with h5py.File(output_path, 'r') as fp:
self.assertTrue("foo" in fp)
self.assertTrue("bar" in fp)
finally:
if os.path.exists(output_path):
os.remove(output_path)
def test_write_3d(self):
h5py = import_or_skip('h5py')
shape = (4, 5, 3)
source = np.random.random(shape)
dac = Context(self.client)
dist = {0: 'b', 1: 'c', 2: 'n'}
da = dac.empty(shape, dist=dist)
for i in range(shape[0]):
for j in range(shape[1]):
for k in range(shape[2]):
da[i, j, k] = source[i, j, k]
output_path = temp_filepath('.hdf5')
try:
dac.save_hdf5(output_path, da, mode='w')
self.assertTrue(os.path.exists(output_path))
with h5py.File(output_path, 'r') as fp:
self.assertTrue("buffer" in fp)
assert_allclose(source, fp["buffer"])
finally:
if os.path.exists(output_path):
os.remove(output_path)
def setUpClass(cls):
# raise a skipTest if plotting import fails
# (because matplotlib isn't installed, probably)
cls.plt = import_or_skip("distarray.plotting")
super(TestPlotting, cls).setUpClass()
cls.da = Distribution(cls.context, (64, 64))
cls.arr = cls.context.ones(cls.da)
def setUp(self):
self.rank = self.comm.Get_rank()
self.h5py = import_or_skip('h5py')
self.key = "data"
# set up a common file to work with
if self.rank == 0:
self.output_path = temp_filepath(extension='.hdf5')
else:
self.output_path = None
self.output_path = self.comm.bcast(self.output_path, root=0)
def setUp(self):
self.rank = self.comm.Get_rank()
self.h5py = import_or_skip('h5py')
self.key = "data"
# set up a common file to work with
if self.rank == 0:
self.output_path = temp_filepath(extension='.hdf5')
else:
self.output_path = None
self.output_path = self.comm.bcast(self.output_path, root=0)
def setUpClass(cls):
cls.h5py = import_or_skip('h5py')
super(TestHdf5FileLoad, cls).setUpClass()
cls.output_path = cls.context.apply(engine_temp_path, ('.hdf5',),
targets=[cls.context.targets[0]])[0]
cls.expected = np.arange(20).reshape(2, 10)
def make_test_file(output_path, arr):
import h5py
with h5py.File(output_path, 'w') as fp:
fp["test"] = arr
cls.context.apply(make_test_file, (cls.output_path, cls.expected),
targets=[cls.context.targets[0]])
def setUp(self):
self.rank = self.comm.Get_rank()
self.h5py = import_or_skip('h5py')
self.key = "data"
self.expected = numpy.arange(20).reshape(2, 10)
# set up a common file to work with
if self.rank == 0:
self.output_path = temp_filepath(extension='.hdf5')
with self.h5py.File(self.output_path, 'w') as fp:
fp[self.key] = self.expected
else:
self.output_path = None
self.comm.Barrier() # wait until file exists
self.output_path = self.comm.bcast(self.output_path, root=0)
def setUp(self):
self.rank = self.comm.Get_rank()
self.h5py = import_or_skip('h5py')
self.key = "data"
self.expected = numpy.arange(20).reshape(2, 10)
# set up a common file to work with
if self.rank == 0:
self.output_path = temp_filepath(extension='.hdf5')
with self.h5py.File(self.output_path, 'w') as fp:
fp[self.key] = self.expected
else:
self.output_path = None
self.comm.Barrier() # wait until file exists
self.output_path = self.comm.bcast(self.output_path, root=0)
def test_hdf5_file_write(self):
h5py = import_or_skip('h5py')
key = "data"
larr0 = LocalArray((51,), comm=self.comm)
output_dir = tempfile.gettempdir()
filename = 'localarray_hdf5test.hdf5'
output_path = os.path.join(output_dir, filename)
try:
save_hdf5(output_path, larr0, key=key, mode='w')
if self.comm.Get_rank() == 0:
with h5py.File(output_path, 'r') as fp:
self.assertTrue("data" in fp)
finally:
if self.comm.Get_rank() == 0:
if os.path.exists(output_path):
os.remove(output_path)
def test_write_block(self):
h5py = import_or_skip('h5py')
datalen = 33
dac = Context(self.client)
da = dac.empty((datalen,), dist={0: 'b'})
for i in range(datalen):
da[i] = i
output_path = temp_filepath('.hdf5')
try:
dac.save_hdf5(output_path, da, mode='w')
self.assertTrue(os.path.exists(output_path))
with h5py.File(output_path, 'r') as fp:
self.assertTrue("buffer" in fp)
expected = np.arange(datalen)
assert_equal(expected, fp["buffer"])
finally:
if os.path.exists(output_path):
os.remove(output_path)
def setUp(self):
super(TestHdf5FileSave, self).setUp()
self.h5py = import_or_skip('h5py')
self.output_path = self.context.apply(engine_temp_path, ('.hdf5',),
targets=[self.context.targets[0]])[0]
def setUp(self):
self.h5py = import_or_skip('h5py')
self.output_path = temp_filepath('.hdf5')
self.dac = Context()
