def main():
try:
print("""
Benchmarking various operations on the IndexDataContainerTable.
""")
with closing(tables.open_file(filename, mode='w')) as handle:
root = handle.root
table = IndexedDataContainerTable(root, 'my_data_table')
print(
"Append {}:".format(n),
bench(lambda: append(handle, 1000, data_container)))
with closing(tables.open_file(filename, mode='w')) as handle:
root = handle.root
table = IndexedDataContainerTable(
root, 'my_data_table', expected_number=n)
print(
"Append {} masked:".format(n),
bench(lambda: append(handle, 1000, data_container_half)))
uids = create_table(filename)
sample = random.sample(uids, 300)
with closing(tables.open_file(filename, mode='r')) as handle:
root = handle.root
table = IndexedDataContainerTable(
root, 'my_data_table', expected_number=n)
print("Iterate {}:".format(n), bench(lambda: iteration(table)))
print(
'Getitem sample of 300:',
bench(lambda: getitem_access(table, sample)))
with closing(tables.open_file(filename, mode='a')) as handle:
root = handle.root
table = IndexedDataContainerTable(
root, 'my_data_table', expected_number=n)
print(
"Update item of 300 sample:",
bench(lambda: setitem(table, data_container_half, sample)))
finally:
shutil.rmtree(temp_dir)
def main():
print("""
Benchmarking various operations between different data containers
.. note:
Only the relative time taken for each type of container within a
section is comparable.
""")
print('Initialization:')
print("dict:", bench(lambda: dict(dict_data)))
print("DataContainer:", bench(lambda: DataContainer(dict_data)))
print("dict == DataContainer", dict(dict_data) == DataContainer(dict_data))
print()
print('Iterations:')
print("dict:", bench(lambda: iteration(dict_data)))
print("DataContainer:", bench(lambda: iteration(data_container)))
print()
print('getitem access:')
print("dict:", bench(lambda: getitem_access(dict_data, indices)))
print(
"DataContainer:",
bench(lambda: getitem_access(data_container, indices)))
print(
"dict == DataContainer",
getitem_access(dict_data, indices) == getitem_access(data_container, indices)) # noqa
print()
print('setitem with CUBA keys:')
print("dict:", bench(lambda: setitem_with_CUBA_keys(dict_data)))
print(
"DataContainer:",
bench(lambda: setitem_with_CUBA_keys(data_container)))
print(
"dict == DataContainer",
setitem_with_CUBA_keys(dict_data) == setitem_with_CUBA_keys(data_container)) # noqa
def main():
try:
print("""
Benchmarking various operations on the DataContainerTable.
""")
with closing(tables.open_file(filename, mode='w')) as handle:
root = handle.root
table = DataContainerTable(root, 'my_data_table')
print(
"Append {}:".format(n),
bench(lambda: append(handle, 1000, data_container)))
with closing(tables.open_file(filename, mode='w')) as handle:
root = handle.root
table = DataContainerTable(root, 'my_data_table')
print(
"Append {} masked:".format(n),
bench(lambda: append(handle, 1000, data_container_half)))
uids = [uuid.uuid4() for _ in range(n)]
with closing(tables.open_file(filename, mode='w')) as handle:
print(
"Set item {}:".format(n),
bench(
lambda: set_item(handle, uids, data_container),
repeat=1, adjust_runs=False))
with closing(tables.open_file(filename, mode='w')) as handle:
root = handle.root
table = DataContainerTable(root, 'my_data_table')
print(
"Set item {} masked:".format(n),
bench(
lambda: set_item(handle, uids, data_container),
repeat=1, adjust_runs=False))
uids = create_table(filename)
sample = random.sample(uids, 300)
with closing(tables.open_file(filename, mode='r')) as handle:
root = handle.root
table = DataContainerTable(root, 'my_data_table')
print("Iterate {}:".format(n), bench(lambda: iteration(table)))
print(
"IterSequence of 300:",
bench(lambda: iteration_with_sequence(table, sample)))
print(
'Getitem sample of 300:',
bench(lambda: getitem_access(table, sample)))
with closing(tables.open_file(filename, mode='a')) as handle:
root = handle.root
table = DataContainerTable(root, 'my_data_table')
print(
"Update item of 300 sample:",
bench(lambda: setitem(table, data_container_half, sample)))
print(
"Delitem of 300 sample:", bench(
lambda: delitem(table, sample),
repeat=1, adjust_runs=False))
finally:
shutil.rmtree(temp_dir)
particles, state_data = get_particles(y_range)
number_particles = sum(p.count_of(
CUBA.PARTICLE) for p in particles)
number_time_steps = 10
SD = "DUMMY - TODO"
for test in run_wrapper_tests:
lammps_wrapper = lammps.LammpsWrapper(
use_internal_interface=is_internal)
configure_wrapper(lammps_wrapper,
state_data,
particles,
number_time_steps=number_time_steps)
results = bench(lambda: run_test(test.method, lammps_wrapper),
repeat=1,
adjust_runs=False)
print(describe(test.name,
number_particles,
number_time_steps,
is_internal), results)
# test configuration
lammps_wrapper = lammps.LammpsWrapper(
use_internal_interface=is_internal)
results = bench(lambda: configure_wrapper(lammps_wrapper,
state_data,
particles,
number_time_steps),
def __enter__(self):
self._file = H5CUDS.open(self._filename)
self._file.add_dataset(Particles("test"))
return self._file.get_dataset("test")
def __exit__(self, type, value, tb):
if os.path.exists(self._filename):
self._file.close()
shutil.rmtree(self.temp_dir)
if __name__ == '__main__':
print(
"create_file_with_particles:",
bench(lambda: create_file_with_particles(), repeat=3))
print(
"create_file_with_id_particles:",
bench(lambda: create_file_with_id_particles(), repeat=3))
with Container() as pc:
add_particles_to_container(pc)
print(
"iter_particles_in_container",
bench(lambda: iter_particles_in_container(pc)))
with Container() as pc:
add_particles_to_container(pc)
print(
"update_coordinates_of_particles_in_container_using_iter",