def test_process(self):
try:
plugin = pu.load_plugin(self.plugin_name)
if self.plugin_name == base_class_name:
self.assertRaises(NotImplementedError, plugin.process, "test",
"test", 1, 1)
return
# load appropriate data
data = tu.get_appropriate_input_data(plugin)
self.assertGreater(len(data), 0,
"Cannot find appropriate test data")
# generate somewhere for the data to go
output = tu.get_appropriate_output_data(plugin, data)
self.assertGreater(len(output), 0,
"Cannot create appropriate output data")
plugin.set_parameters(None)
for i in range(len(data)):
plugin.run_process(data[i], output[i], ["CPU0"], 0)
print("Output from plugin under test ( %s ) is in %s" %
(plugin.name, output[i].backing_file.filename))
data[i].complete()
output[i].complete()
except ImportError as e:
print(
"Failed to run plugin test as libraries not available (%s), passing test"
% (e))
pass
def test_process(self):
try:
plugin = pu.load_plugin(self.plugin_name)
if self.plugin_name == base_class_name:
self.assertRaises(NotImplementedError, plugin.process,
"test", "test", 1, 1)
return
# load appropriate data
data = tu.get_appropriate_input_data(plugin)
self.assertGreater(len(data), 0, "Cannot find appropriate test data")
# generate somewhere for the data to go
output = tu.get_appropriate_output_data(plugin, data)
self.assertGreater(len(output), 0,
"Cannot create appropriate output data")
plugin.set_parameters(None)
for i in range(len(data)):
plugin.run_plugin(data[i], output[i], ["CPU0"], 0)
print("Output from plugin under test ( %s ) is in %s" %
(plugin.name, output[i].backing_file.filename))
data[i].complete()
output[i].complete()
except ImportError as e:
print("Failed to run plugin test as libraries not available (%s), passing test" % (e))
pass
def test_create_smaller_data_block(self):
data = tu.get_nx_tomo_test_data()
plugin = pu.load_plugin("savu.plugins.downsample_filter")
output = tu.get_appropriate_output_data(plugin, data)[0]
self.assertEqual(output.get_data_shape(), (111, 68, 80))
logging.debug("Loading plugin %s", options.plugin)
plugin = pu.load_plugin(None, options.plugin)
logging.debug("Loaded plugin %s", options.plugin)
# load appropriate data
logging.debug("Loading test data")
data = tu.get_appropriate_input_data(plugin)
if data is None:
logging.error("Cannot create appropriate input data")
raise Exception("Cannot create appropriate input data")
# generate somewhere for the data to go
logging.debug("Sorting out output data")
output = \
tu.get_appropriate_output_data(plugin, data, mpi=True,
file_name=global_data['file_name'])
if output is None:
logging.error("Cannot create appropriate output data")
raise Exception("Cannot create appropriate output data")
plugin.set_parameters(None)
for i in range(len(data)):
logging.debug("processing")
plugin.run_process(data[i], output[i], ALL_PROCESSES, RANK)
logging.debug("Processed to file : %s",
output[i].backing_file.filename)
data[i].complete()
output[i].complete()
logging.debug("Loading plugin %s", options.plugin)
plugin = pu.load_plugin(None, options.plugin)
logging.debug("Loaded plugin %s", options.plugin)
# load appropriate data
logging.debug("Loading test data")
data = tu.get_appropriate_input_data(plugin)
if data is None:
logging.error("Cannot create appropriate input data")
raise Exception("Cannot create appropriate input data")
# generate somewhere for the data to go
logging.debug("Sorting out output data")
output = \
tu.get_appropriate_output_data(plugin, data, mpi=True,
file_name=global_data['file_name'])
if output is None:
logging.error("Cannot create appropriate output data")
raise Exception("Cannot create appropriate output data")
plugin.set_parameters(None)
for i in range(len(data)):
logging.debug("processing")
plugin.run_process(data[i], output[i], ALL_PROCESSES, RANK)
logging.debug("Processed to file : %s",
output[i].backing_file.filename)
data[i].complete()
output[i].complete()
def test_create_smaller_data_block(self):
data = tu.get_nx_tomo_test_data()
plugin = pu.load_plugin("savu.plugins.downsample_filter")
output = tu.get_appropriate_output_data(plugin, data)[0]
self.assertEqual(output.get_data_shape(), (111, 68, 80))
