def write_sorting(sorting: SortingExtractor, save_path: PathType):
# if multiple groups, use the NeuroscopeMultiSortingExtactor write function
if 'group' in sorting.get_shared_unit_property_names():
NeuroscopeMultiSortingExtractor.write_sorting(sorting, save_path)
else:
save_path.mkdir(parents=True, exist_ok=True)
if save_path.suffix == '':
sorting_name = save_path.name
else:
sorting_name = save_path.stem
xml_name = sorting_name
save_xml_filepath = save_path / (str(xml_name) + '.xml')
# create parameters file if none exists
if save_xml_filepath.is_file():
raise FileExistsError(f'{save_xml_filepath} already exists!')
xml_root = et.Element('xml')
et.SubElement(xml_root, 'acquisitionSystem')
et.SubElement(xml_root.find('acquisitionSystem'), 'samplingRate')
xml_root.find('acquisitionSystem').find('samplingRate').text = str(
sorting.get_sampling_frequency())
et.ElementTree(xml_root).write(str(save_xml_filepath.absolute()),
pretty_print=True)
# Create and save .res and .clu files from the current sorting object
save_res = save_path / f'{sorting_name}.res'
save_clu = save_path / f'{sorting_name}.clu'
res, clu = _extract_res_clu_arrays(sorting)
np.savetxt(save_res, res, fmt='%i')
np.savetxt(save_clu, clu, fmt='%i')
def write_sorting(sorting: SortingExtractor, save_path: PathType):
assert save_path.suffixes == [
".spikes",
".cellinfo",
".mat",
], "The save_path must correspond to the CellExplorer format of sorting_id.spikes.cellinfo.mat!"
base_path = save_path.parent
sorting_id = save_path.name.split(".")[0]
session_info_save_path = base_path / f"{sorting_id}.sessionInfo.mat"
spikes_save_path = save_path
base_path.mkdir(parents=True, exist_ok=True)
sampling_frequency = sorting.get_sampling_frequency()
session_info_mat_dict = dict(sessionInfo=dict(rates=dict(
wideband=sampling_frequency)))
scipy.io.savemat(file_name=session_info_save_path,
mdict=session_info_mat_dict)
spikes_mat_dict = dict(spikes=dict(
UID=sorting.get_unit_ids(),
times=[[[y / sampling_frequency] for y in x]
for x in sorting.get_units_spike_train()],
))
# If, in the future, it is ever desired to allow this to write unit properties, they must conform
# to the format here: https://cellexplorer.org/datastructure/data-structure-and-format/
scipy.io.savemat(file_name=spikes_save_path, mdict=spikes_mat_dict)
def from_memory(sorting: se.SortingExtractor, serialize=False):
if serialize:
with hi.TemporaryDirectory() as tmpdir:
fname = tmpdir + '/' + _random_string(10) + '_firings.mda'
MdaSortingExtractor.write_sorting(sorting=sorting, save_path=fname)
with ka.config(use_hard_links=True):
uri = ka.store_file(fname, basename='firings.mda')
sorting = LabboxEphysSortingExtractor({
'sorting_format': 'mda',
'data': {
'firings': uri,
'samplerate': sorting.get_sampling_frequency()
}
})
return sorting
obj = {
'sorting_format': 'in_memory',
'data': register_in_memory_object(sorting)
}
return LabboxEphysSortingExtractor(obj)
def write_sorting(sorting: SortingExtractor, save_path: PathType):
# if multiple groups, use the NeuroscopeMultiSortingExtactor write function
if 'group' in sorting.get_shared_unit_property_names():
NeuroscopeMultiSortingExtractor.write_sorting(sorting, save_path)
else:
if not save_path.is_dir():
os.makedirs(save_path)
if save_path.suffix == '':
sorting_name = save_path.name
else:
sorting_name = save_path.stem
xml_name = sorting_name
save_xml_filepath = save_path / (str(xml_name) + '.xml')
# create parameters file if none exists
if save_xml_filepath.is_file():
raise FileExistsError(f'{save_xml_filepath} already exists!')
soup = BeautifulSoup("", 'xml')
new_tag = soup.new_tag('samplingrate')
new_tag.string = str(sorting.get_sampling_frequency())
soup.append(new_tag)
# write parameters file
with save_xml_filepath.open("w") as f:
f.write(str(soup))
# Create and save .res and .clu files from the current sorting object
save_res = save_path / f'{sorting_name}.res'
save_clu = save_path / f'{sorting_name}.clu'
res, clu = _extract_res_clu_arrays(sorting)
np.savetxt(save_res, res, fmt='%i')
np.savetxt(save_clu, clu, fmt='%i')
