cmind_build_feat_dir(output_dir, ...[, ...]) Build a first-level feat directory from separate first level .tar.gz files
cmind.pipeline.cmind_build_feat_dir.cmind_build_feat_dir(output_dir, preproc_tarfile, stats_tarfile, reg_tarfile, reg_standard_tarfile, reduce_file_level=1, poststats_tarfile=None, output_tar=None, verbose=False, ForceUpdate=False, logger=None)[source]

Build a first-level feat directory from separate first level .tar.gz files


output_dir : str

desired output location for the first-level feat directory structure. The feat folder will be: output_dir/Feat_Level1

preproc_tarfile : str

tar file of preprocessing results

stats_tarfile : str

tar file of stats results

reg_tarfile : str

tar file of registration to anatomical/structural space

reg_standard_tarfile : str

tar file of registration to standard space

reduce_file_level : int

if 0 include all files from the source .tar.gz. If 1, minimize the resulting .tar.gz size be removing some files unnecessary for 2nd level analysis. If >1, remove unneccessary files more aggressively.

poststats_tarfile : str, optional

tar file of first level poststats results (not required for 2nd level analysis)

output_tar : str, optional

output name for .tar.gz (will remove output_dir after compression). If output_tar is a filename rather than a full path, it will be placed within output_dir. If output_tar==’auto’, the default filename will be os.path.join(output_dir,’feat_level1.tar.gz’).

ForceUpdate : bool, optional

if True, rerun and overwrite any previously existing results

verbose : bool, optional

print additional output (to terminal and log)

logger : logging.Logger or str, optional

logging.Logger object (or string of a filename to log to)


output_name : str or None, optional

will be the name of the generated directory or tar file