def test_converter_more_files(_sdds_file, _test_file):
rep = 2
converter_entrypoint(files=[_sdds_file],
outputdir=_test_file.parent,
realizations=rep)
origin = tbt.read_tbt(_sdds_file)
for i in range(rep):
new = tbt.read_tbt(f"{_test_file}_r{i}.sdds")
_compare_tbt(origin, new, False)
def test_converter_one_file_with_noise(_sdds_file, _test_file):
np.random.seed(2019)
noiselevel = 0.0005
converter_entrypoint(files=[_sdds_file],
outputdir=_test_file.parent,
noise_levels=[noiselevel])
origin = tbt.read_tbt(_sdds_file)
new = tbt.read_tbt(f"{_test_file}_n{noiselevel}.sdds")
_compare_tbt(origin, new, True, noiselevel * 10)
def test_converter_more_files_with_noise(_sdds_file, _test_file):
np.random.seed(2019)
rep = 2
noiselevel = 0.0005
converter_entrypoint(files=[_sdds_file],
outputdir=_test_file.parent,
realizations=rep,
noise_levels=[noiselevel])
origin = tbt.read_tbt(_sdds_file)
for i in range(rep):
new = tbt.read_tbt(f"{_test_file}_n{noiselevel}_r{i}.sdds")
_compare_tbt(origin, new, True, noiselevel * 10)
def test_converter_drop_elements(_sdds_file, _test_file, dropped_elements):
converter_entrypoint(
files=[_sdds_file],
outputdir=_test_file.parent,
drop_elements=dropped_elements,
)
new = tbt.read_tbt(f"{_test_file}.sdds")
for transverse_data in new.matrices:
for dataframe in (transverse_data.X, transverse_data.Y):
for element in dropped_elements:
assert element not in dataframe.index
def _run_harpy(harpy_options):
iotools.create_dirs(harpy_options.outputdir)
with timeit(
lambda spanned: LOGGER.info(f"Total time for Harpy: {spanned}")):
lins = []
all_options = _replicate_harpy_options_per_file(harpy_options)
tbt_datas = [(tbt.read_tbt(option.files,
datatype=option.tbt_datatype), option)
for option in all_options]
for tbt_data, option in tbt_datas:
lins.extend([
handler.run_per_bunch(bunch_data, bunch_options)
for bunch_data, bunch_options in _multibunch(tbt_data, option)
])
return lins
def _read_and_write_files(opt):
for input_file in opt.files:
tbt_data = tbt.read_tbt(input_file, datatype=opt.tbt_datatype)
if opt.drop_elements:
tbt_data = _drop_elements(tbt_data, opt.drop_elements)
if opt.use_average:
tbt_data = tbt.utils.generate_average_tbtdata(tbt_data)
for i in range(opt.realizations):
suffix = f"_r{i}" if opt.realizations > 1 else ""
if opt.noise_levels is None:
tbt.write(
Path(opt.outputdir) /
f"{_file_name_without_sdds(input_file)}{suffix}",
tbt_data=tbt_data,
)
else:
for noise_level in opt.noise_levels:
tbt.write(
Path(opt.outputdir) /
f"{_file_name_without_sdds(input_file)}_n{noise_level}{suffix}",
tbt_data=tbt_data,
noise=float(noise_level),
)
def test_converter_one_file(_sdds_file, _test_file):
converter_entrypoint(files=[_sdds_file], outputdir=_test_file.parent)
origin = tbt.read_tbt(_sdds_file)
new = tbt.read_tbt(f"{_test_file}.sdds")
_compare_tbt(origin, new, False)