3 d @shddlZddlmZmZmZmZmZmZddlm Z GdddeZ Gdd d eZ Gd d d eZ dS) N)traits TraitedSpecFile CommandLineCommandLineInputSpecInputMultiPath)split_filenamec @sneZdZeedddddddZejddd d d d d ddddd Zejdddddddddd Z eddddZ dS) ImageStatsInputSpecT)existsz -images %szWList of images to process. They must be in the same space and have the same dimensions.)argstr mandatorypositiondescminmaxZmeanZmediansumZstdvarz-stat %sZNAzThe statistic to compute.)rZunitsrrfloatcharshortintlongdoublez-outputdatatype %szCA Camino data type string, default is "float". Type must be signed.)rZ usedefaultrz-outputroot %szmFilename root prepended onto the names of the output files. The extension will be determined from the input.)rrrN) __name__ __module__ __qualname__rrin_filesrEnumstatZout_type output_rootr$r$@/tmp/pip-build-7vycvbft/nipype/nipype/interfaces/camino/utils.pyr s@r c@seZdZedddZdS)ImageStatsOutputSpecTz3Path of the file computed with the statistic chosen)r rN)rrrrout_filer$r$r$r%r&>sr&c@s,eZdZdZdZeZeZddZ ddZ dS) ImageStatsa This program computes voxelwise statistics on a series of 3D images. The images must be in the same space; the operation is performed voxelwise and one output is produced per voxel. Examples -------- >>> import nipype.interfaces.camino as cam >>> imstats = cam.ImageStats() >>> imstats.inputs.in_files = ['im1.nii','im2.nii','im3.nii'] >>> imstats.inputs.stat = 'max' >>> imstats.run() # doctest: +SKIP Z imagestatscCs$|jj}tjj|j|d<|S)Nr') output_specgetospathabspath_gen_outfilename)selfoutputsr$r$r% _list_outputsXs zImageStats._list_outputscCs*|jj}|jjd}t|\}}}||S)Nr)inputsr#r r )r/r#Z first_file_extr$r$r%r.]s zImageStats._gen_outfilenameN) rrr__doc__Z_cmdr Z input_specr&r)r1r.r$r$r$r%r(Ds r() r+baserrrrrrZutils.filemanipr r r&r(r$r$r$r%s   /