compute_consecutive_censor_stats

bidsaid.qc.compute_consecutive_censor_stats(censor_mask, n_dummy_scans=0)[source]

Compute the mean and standard deviation of the consecutive censored volumes.

Parameters

censor_mask: NDArray

A numpy array where 1 = keep, 0 = censor.

n_dummy_scansint, default=0

Number of non-steady-state scans to censor.

Return

dict[str, float]

A dictionary with the following keys:

  • “consecutive_censored_volumes_mean”: Mean number of consecutively censored volumes. Returns 0.0 if no volumes were censored.

  • “consecutive_censored_volumes_std”: Standard deviation of consecutively censored volumes. Returns NaN if no volumes were censored.