Provided by: heudiconv_0.5.3-1_all bug

NAME - DICOM converter for organizing brain imaging data into structured directory


       UserWarning:  The  DICOM  readers  are  highly  experimental,  unstable, and only work for
       Siemens time-series at the moment Please use with caution.  We would be grateful for  your
       help in improving them

              from nibabel.nicom import csareader

       usage: heudiconv [-h] [--version]

              [-d DICOM_DIR_TEMPLATE | --files [FILES [FILES ...]]]  [-s [SUBJS [SUBJS ...]]] [-c
              {dcm2niix,none}] [-o OUTDIR] [-l LOCATOR] [-a  CONV_OUTDIR]  [--anon-cmd  ANON_CMD]
              [-f HEURISTIC] [-p] [-ss SESSION] [-b] [--overwrite] [--datalad] [--dbg] [--command
              {heuristics,heuristic-info,ls,populate-templates,sanitize-jsons,treat-jsons}]   [-g
              {studyUID,accession_number}]  [--minmeta]  [--random-seed  RANDOM_SEED]  [-q QUEUE]
              [--sbargs SBATCH_ARGS]

       Example: heudiconv -d rawdata/{subject} -o . -f -s s1 s2 s3

   optional arguments:
       -h, --help
              show this help message and exit

              show program's version number and exit

       -d DICOM_DIR_TEMPLATE, --dicom_dir_template DICOM_DIR_TEMPLATE
              location of dicomdir that can be indexed with  subject  id  {subject}  and  session
              {session}.  Tarballs  (can  be  compressed) are supported in addition to directory.
              All matching tarballs for a subject are extracted and their content processed in  a
              single pass

       --files [FILES [FILES ...]]
              Files  (tarballs,  dicoms)  or  directories  containing files to process. Cannot be
              provided if using --dicom_dir_template or --subjects

       -s [SUBJS [SUBJS ...]], --subjects [SUBJS [SUBJS ...]]
              list of subjects - required for dicom template. If not provided, DICOMS would first
              be "sorted" and subject IDs deduced by the heuristic

       -c {dcm2niix,none}, --converter {dcm2niix,none}
              tool  to use for DICOM conversion. Setting to "none" disables the actual conversion
              step -- usefulfor testing heuristics.

       -o OUTDIR, --outdir OUTDIR
              output directory  for  conversion  setup  (for  further  customization  and  future
              reference. This directory will refer to non-anonymized subject IDs

       -l LOCATOR, --locator LOCATOR
              study  path  under  outdir.  If  provided,  it  overloads the value provided by the
              heuristic. If --datalad is  enabled,  every  directory  within  locator  becomes  a
              super-dataset  thus  establishing  a hierarchy. Setting to "unknown" will skip that

       -a CONV_OUTDIR, --conv-outdir CONV_OUTDIR
              output directory for converted files. By default this  is  identical  to  --outdir.
              This option is most useful in combination with --anon-cmd

       --anon-cmd ANON_CMD
              command  to  run  to  convert  subject  IDs used for DICOMs to anonymized IDs. Such
              command must take a single argument and return a single  anonymized  ID.  Also  see

       -f HEURISTIC, --heuristic HEURISTIC
              Name of a known heuristic or path to the Pythonscript containing heuristic

       -p, --with-prov
              Store additional provenance information. Requires python-rdflib.

       -ss SESSION, --ses SESSION
              session for longitudinal study_sessions, default is none

       -b, --bids
              flag for output into BIDS structure

              flag to allow overwriting existing converted files

              Store  the  entire collection as DataLad dataset(s).  Small files will be committed
              directly to git, while large to annex. New version (6) of annex  repositories  will
              be  used  in  a  "thin"  mode so it would look to mortals as just any other regular
              directory (i.e. no symlinks to under .git/annex). For now just for BIDS mode.

       --dbg  Do not catch exceptions and show exception traceback

       --command {heuristics,heuristic-info,ls,populate-templates,sanitize-jsons,treat-jsons}
              custom actions to be performed on provided files instead of regular operation.

       -g {studyUID,accession_number}, --grouping {studyUID,accession_number}
              How to group dicoms (default: by studyUID)

              Exclude dcmstack meta information in sidecar jsons

       --random-seed RANDOM_SEED
              Random seed to initialize RNG

   Conversion submission options:
       -q QUEUE, --queue QUEUE
              select batch system to submit jobs to instead of running the conversion serially

       --sbargs SBATCH_ARGS
              Additional sbatch arguments if running with queue arg

       Please use with caution.  We would be grateful for your help in improving them

              from nibabel.nicom import csareader

       0.5.3 UserWarning: The DICOM readersJanuaryg2019experimental, unstable, andDICOMS.PY:7:(1)Siemens time-series at the moment