3 Yd>@s"ddlZddljZddlmZddlmZmZm Z m Z m Z m Z GdddeZ Gdd d e ZGd d d eZGd d d eZGddde ZGdddeZGdddeZGddde ZGdddeZGdddeZGdddeZGdddeZGdddeZGd d!d!eZdS)"N)split_filename)CommandLineInputSpec CommandLinetraits TraitedSpecFile isdefinedc @seZdZedddd)ddZddgZeddd ed Zejej d ddd d d ded Z ddgZ eddde d Z ejej dddd d d de d Z ej ddddZedd*ddgdddZejddd Zejd!d"d Zejd#dd$d%Zejd&dd'd%Zd(S)+FilterTracksInputSpecTz%srzinput tracks to be filtered)existsargstr mandatorypositiondesc include_file include_specz -include %szinclusion file)r r rxorz2inclusion specification in mm and radius (x y z r),mm)rrr minlenmaxlensepunitsr exclude_file exclude_specz -exclude %szexclusion filez2exclusion specification in mm and radius (x y z r)z -minlength %szGSets the minimum length of any track in millimeters (default is 10 mm).)r rrzOutput filtered track filenamein_fileFz%s_filt)r rr name_sourceZ hash_files name_templatez -nomaskinterpz1Turns off trilinear interpolation of mask images.)r rz-invertzsinvert the matching process, so that tracks that wouldotherwise have been included are now excluded and vice-versa.z-quietz7Do not display information messages or progress status.)r rrz-debugzDisplay debugging messages.N)__name__ __module__ __qualname__r r include_xorrrListFloatr exclude_xorrrminimum_tract_lengthout_fileBoolno_mask_interpolationinvertquietdebugr1r1S/var/www/html/virt/lib/python3.6/site-packages/nipype/interfaces/mrtrix/tracking.pyr sj r c@seZdZedddZdS)FilterTracksOutputSpecTzthe output filtered tracks)r rN)r#r$r%r r+r1r1r1r2r3[sr3c@seZdZdZdZeZeZdS) FilterTracksa< Use regions-of-interest to select a subset of tracks from a given MRtrix track file. Example ------- >>> import nipype.interfaces.mrtrix as mrt >>> filt = mrt.FilterTracks() >>> filt.inputs.in_file = 'tracks.tck' >>> filt.run() # doctest: +SKIP Z filter_tracksN) r#r$r%__doc___cmdr input_specr3 output_specr1r1r1r2r4_s r4c@seZdZedddd&ddZeddddd Zejejd d dd d d dZ ej dd ddZ ej dd ddZ ej ddddddddddddd Zejdd d d!d"Zeddd'd#d$Zd%S)(Tracks2ProbInputSpecTz%srz tract file)r r rrrz -template %srzvan image file to be used as a template for the output (the output image wil have the same transform and field of view))r r rrz-vox %srrzBThree comma-separated numbers giving the size of each voxel in mm.)r rrrrrz-colourzHadd colour to the output image according to the direction of the tracks.)r rrz -fractionzproduce an image of the fraction of fibres through each voxel (as a proportion of the total number in the file), rather than the count.ZBitZInt8ZUInt8ZInt16ZUInt16ZInt32ZUInt32Zfloat32Zfloat64z -datatype %szI"i.e. Bfloat". Can be "char", "short", "int", "long", "float" or "double"z -resample %drzresample the tracks at regular intervals using Hermite interpolation. If omitted, the program will select an appropriate interpolation factor automatically.)r rrrzoutput data file)Zgenfiler rrNr!r")r#r$r%r rZ template_filerr'r(Z voxel_dimsr,ZcolourfractionEnumZoutput_datatypeZresample out_filenamer1r1r1r2r9rsTr9c@seZdZedddZdS)Tracks2ProbOutputSpecTz)Output tract count or track density image)r rN)r#r$r%r tract_imager1r1r1r2r=sr=c@s4eZdZdZdZeZeZddZ ddZ ddZ d S) Tracks2Proba Convert a tract file into a map of the fraction of tracks to enter each voxel - also known as a tract density image (TDI) - in MRtrix's image format (.mif). This can be viewed using MRview or converted to Nifti using MRconvert. Example ------- >>> import nipype.interfaces.mrtrix as mrt >>> tdi = mrt.Tracks2Prob() >>> tdi.inputs.in_file = 'dwi_CSD_tracked.tck' >>> tdi.inputs.colour = True >>> tdi.run() # doctest: +SKIP Z tracks2probcCsP|jj}|jj|d<t|ds8tj|j|d<ntj j|d|d<|S)Nr>) r8getinputsr<r opabspath_gen_outfilenameospath)selfoutputsr1r1r2 _list_outputss    zTracks2Prob._list_outputscCs|dkr|jSdSdS)Nr<)rD)rGnamer1r1r2 _gen_filenameszTracks2Prob._gen_filenamecCst|jj\}}}|dS)Nz_TDI.mif)rrAr)rG_rJr1r1r2rDszTracks2Prob._gen_outfilenameN) r#r$r%r5r6r9r7r=r8rIrKrDr1r1r1r2r?s r?c @seZdZeddddKddZddgZeddd ed Zejej d ddd d d ded Z ddgZ eddde d Z ejej dddd d d de d Z ddgZeddded Zejej dddd d d ded ZddgZeddded Zejej dddd d d ded Zejdd d!dd"ddLd$Zejd%d&d'Zejd(d)d'Zejd*d+d'Zejd,d-d'Zej d.dd/d0Zej d1dd2d0Zejd3d4d'Zejd5d6d'Zej d7dd8d0Z ej d9dd:d0Z!ej d;dd>> import nipype.interfaces.mrtrix as mrt >>> strack = mrt.StreamlineTrack() >>> strack.inputs.inputmodel = 'SD_PROB' >>> strack.inputs.in_file = 'data.Bfloat' >>> strack.inputs.seed_file = 'seed_mask.nii' >>> strack.inputs.mask_file = 'mask.nii' >>> strack.cmdline 'streamtrack -mask mask.nii -seed seed_mask.nii SD_PROB data.Bfloat data_tracked.tck' >>> strack.run() # doctest: +SKIP Z streamtrackN) r#r$r%r5r6rMr7rZr8r1r1r1r2r[|sr[c@seZdZeddddddZdS)'DiffusionTensorStreamlineTrackInputSpecTz-grad %srzGradient encoding, supplied as a 4xN text file with each line is in the format [ X Y Z b ], where [ X Y Z ] describe the direction of the applied gradient, and b gives the b-value in units (1000 s/mm^2). See FSL2MRTrix)r r rrrNr!)r#r$r%r Zgradient_encoding_filer1r1r1r2r\s r\cs&eZdZdZeZdfdd ZZS)DiffusionTensorStreamlineTracka Specialized interface to StreamlineTrack. This interface is used for streamline tracking from diffusion tensor data, and calls the MRtrix function 'streamtrack' with the option 'DT_STREAM' Example ------- >>> import nipype.interfaces.mrtrix as mrt >>> dtstrack = mrt.DiffusionTensorStreamlineTrack() >>> dtstrack.inputs.in_file = 'data.Bfloat' >>> dtstrack.inputs.seed_file = 'seed_mask.nii' >>> dtstrack.run() # doctest: +SKIP Nc sd|d<tt|j|f|S)NrRrW)superr]__init__)rGcommandrA) __class__r1r2r_sz'DiffusionTensorStreamlineTrack.__init__)N)r#r$r%r5r\r7r_ __classcell__r1r1)rar2r]sr]c@seZdZejdddZdS)>> import nipype.interfaces.mrtrix as mrt >>> sdprobtrack = mrt.ProbabilisticSphericallyDeconvolutedStreamlineTrack() >>> sdprobtrack.inputs.in_file = 'data.Bfloat' >>> sdprobtrack.inputs.seed_file = 'seed_mask.nii' >>> sdprobtrack.run() # doctest: +SKIP Nc sd|d<tt|j|f|S)NrSrW)r^rdr_)rGr`rA)rar1r2r_sz>> import nipype.interfaces.mrtrix as mrt >>> sdtrack = mrt.SphericallyDeconvolutedStreamlineTrack() >>> sdtrack.inputs.in_file = 'data.Bfloat' >>> sdtrack.inputs.seed_file = 'seed_mask.nii' >>> sdtrack.run() # doctest: +SKIP Nc sd|d<tt|j|f|S)NrTrW)r^rer_)rGr`rA)rar1r2r_s z/SphericallyDeconvolutedStreamlineTrack.__init__)N)r#r$r%r5rMr7r_rbr1r1)rar2resre)rEos.pathrFrBZutils.filemaniprbaserrrrr r r r3r4r9r=r?rMrZr[r\r]rcrdrer1r1r1r2s&   H4)&