preprocess - Simple preprocessing analyses

neural.preprocess.create_censor_file(input_dset, out_prefix=None, fraction=0.1, clip_to=0.1, max_exclude=0.3, motion_file=None, motion_exclude=1.0)

create a binary censor file using 3dToutcount

Input_dset:the input dataset Prefix:output 1D file (default: prefix(input_dset) + .1D) Fraction:censor a timepoint if proportional of outliers in this time point is greater than given value Clip_to:keep the number of time points censored under this proportion of total reps. If more time points would be censored, it will only pick the top clip_to*reps points Max_exclude:if more time points than the given proportion of reps are excluded for the entire run, throw an exception – something is probably wrong Motion_file:optional filename of a “motion” file with multiple columns and rows corresponding to reps. It doesn’t really matter what the values are, as long as they are appropriate relative to motion_exclude Motion_exclude:Will exclude any reps that have a value greater than this in any column of motion_file