AFNI program: gtkyd_check.py
Output of -help
This program is for Getting To Know Your Data (GTKYD). Provide a list
of datasets, and this program will check their header (and possibly a
few data) properties. Properties are checked with 3dinfo, nifti_tool
and 3dBrickStat.
This program creates the following useful outputs:
+ A compiled spreadsheet-like table file, for reference, with 1 row
per input dataset and one column per measured property. This is
actually made using gen_ss_review_table.py.
(name: OUT.xls)
+ For each item checked, there will also be a detailed report file (N
lines of data for N input datasets)
(name: OUT/rep_gtkyd_detail_*.dat)
+ For each item checked, there will be a "uniqueness" report file,
which will have 1 line of data for each unique value present across
all input datasets. So, if there is only 1 line of data, then that
property is consistent across all dsets; otherwise, there is some
variability in it.
(name: OUT/rep_gtkyd_unique_*.dat)
+ For each input dataset, a colon-separated dictionary of basic
properties. These can be further queried with gen_ss_review_table.py.
(name: OUT/dset_*.txt)
ver = ${version}
auth = PA Taylor (SSCC, NIMH, NIH, USA), but no doubt also including
the valuable insights of RC Reynolds and DR Glen
------------------------------------------------------------------------
Overview ~1~
------------------------------------------------------------------------
Usage ~1~
-infiles FILE1 [FILE2 FILE3 ...]
:(req) name of one or more file to input
-outdir ODIR :(req) name of output "report directory", for more the
reports of details and uniqueness of each property.
-do_minmax :include dataset min and max value info, which can be
slow (uses '3dBrickStat -slow ...' to calculate it
afresh)
-id_keeps_dirs N :keep N directories (counting backward from the
input filename) as part of the 'subject ID' field;
default is to only keep the prefix_noext of the input
filename (i.e., N=0). This can be useful if the paths
encode useful information to identify subject infiles.
-overwrite :overwrite any preexisting outdir and corresponding XLS
file
-help, -h :display program help file
-echo :run very verbosely, by echoing each part of script
before executing it
-hist :display program history
-ver :display program version number
-verb VVV :control verbosity (def: 1)
-show_valid_opts :show valid options for this program
------------------------------------------------------------------------
Examples ~1~
1) Basic example, running on a set of EPI:
gtkyd_check.py \
-infiles group_study/sub*/func*/*task*.nii.gz \
-outdir group_summary
2) Include (possibly slow) min/max info, and check anatomical dsets:
gtkyd_check.py \
-infiles group_study2/sub*/*T1w*.nii.gz \
group_study2/sub*/*T1w*HEAD \
-do_minmax \
-outdir group_summary2
... and any of these might be usefully followed up with
gen_ss_review_table.py (querying the dset*.txt files in the outdir),
to find subject datasets that have certain properties. For example:
gen_ss_review_table.py \
-infiles group_summary/dset*txt \
-report_outliers 'nv' VARY \
-report_outliers 'orient' VARY \
-report_outliers 'ad3' LT 3.0
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Thu Oct 31 09:44:22 PM EDT 2024