def __init__(self, sorting_results_uri=None):
if sorting_results_uri is None:
self._sorting_results_uri = _sorting_results_uri
else:
self._sorting_results_uri = sorting_results_uri
x = kc.load_json(self._sorting_results_uri)
self._df = pd.DataFrame(x)
print(f"Found {len(self._df)} sorting outputs")
def load_study_records(study_set_file: str) -> StudySetsDict:
hydrated_sets = kc.load_json(study_set_file)
assert hydrated_sets is not None
study_sets: StudySetsDict = {}
# Make a list of study_set lists, one per StudySet in the source json file.
for study_set in hydrated_sets['StudySets']:
name = study_set['name']
records = make_study_records_from_studyset(study_set)
study_sets[name] = records
return study_sets
def parse_workspace_params(parsed: Namespace) -> Params:
if parsed.dry_run:
workspace_uri = parsed.workspace_uri
else:
workspace_uri = establish_workspace(parsed)
if ((parsed.sortings_file is None
and parsed.sortings_file_kachery_uri is None)
or (parsed.sortings_file is not None
and parsed.sortings_file_kachery_uri is not None)):
raise Exception(
"Exactly one of sortings_file and sortings_file_kachery_uri must be set."
)
if parsed.sortings_file is not None:
with open(parsed.sortings_file) as fp:
sortings = json.load(fp)
else:
sortings = kc.load_json(parsed.sortings_file_kachery_uri)
return Params(workspace_uri, sortings, parsed.dry_run)
def compute_ground_truth_comparison_hi(recording_uri, gt_uri, firings_uri):
print_per_verbose(
1,
f"Computing ground truth comparison for ground truth {gt_uri} and sorting {firings_uri} (recording {recording_uri})"
)
print_per_verbose(3, f'Fetching sample rate from {recording_uri}')
recording = sv.LabboxEphysRecordingExtractor(recording_uri)
sample_rate = recording.get_sampling_frequency()
print_per_verbose(3, f'Got sample rate {sample_rate}')
print_per_verbose(2, f"Building sorting object for ground truth {gt_uri}")
gt_firings = kc.load_json(gt_uri)['firings']
print_per_verbose(2, f"Got ground truth firings {gt_firings}")
gt_sorting_obj = {
'sorting_format': 'mda',
'data': {
'firings': gt_firings,
'samplerate': sample_rate
}
}
gt_sorting = sv.LabboxEphysSortingExtractor(gt_sorting_obj)
print_per_verbose(
2, f"Building sorting object for sorting with firings {firings_uri}")
sorting_obj = {
'sorting_format': 'mda',
'data': {
'firings': firings_uri,
'samplerate': sample_rate
}
}
sorting = sv.LabboxEphysSortingExtractor(sorting_obj)
print_per_verbose(2, f"Executing ground-truth comparison")
try:
gt = compare_with_ground_truth(sorting, gt_sorting)
except Exception as e:
print(f"WARNING: Problem in compute_ground_truth_comparison:\n{e}")
gt = f"Ground truth comparison for gt {gt_uri} and sorting {firings_uri} returned error:\n{e}"
return gt
def load_sortings(sortingsfile: str) -> List[Dict[str, Any]]:
hydrated_sortings = kc.load_json(sortingsfile)
assert hydrated_sortings is not None
return cast(List[Dict[str, Any]], hydrated_sortings)