ONEQC(eid, one=None, bpod_ntrials=None, lazy=False)¶
17. Proportion of datasetTypes extracted Variable name: nDatasetTypes Metric: len(one.load(eid, offline=True, download_only=True)) / nExpetedDatasetTypes (hardcoded per task?)
load_dstype_qc_metrics(dstype_name: str) → dict¶
Returns dict to update to metrics or criteria frame Metrics:
_length = number of trials in ONE dstype _count = number of nans in dstype
length / bpod number of trials count / length of dstype
NB: Makes sense for dstypes that should have one value per trial and where nans are informative of failures Other dstypes will have nans because of the contingency of the trial, e.g. if contrastLeft has a nan it means the contrast was on the right.