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NetworkX pickle.z5Computed k-shell network stored as a NetworkX pickle.z5Computed k-crust network stored as a NetworkX pickle.zLNetwork measures for the group that return dictionaries, stored as a Pickle.zSNetwork measures for the group that return dictionaries, stored as matlab matrices.N)rrrr r gpickled_network_filesmatlab_matrix_filesglobal_measures_matlabnode_measures_matlabedge_measures_matlabnode_measure_networksedge_measure_networks k_networksr{r}r~pickled_extra_measuresmatlab_dict_measuresrrrrrs*          rc@s0eZdZdZeZeZddZddZ ddZ dS) NetworkXMetricsa( Calculates and outputs NetworkX-based measures for an input network Example ------- >>> import nipype.interfaces.cmtk as cmtk >>> nxmetrics = cmtk.NetworkXMetrics() >>> nxmetrics.inputs.in_file = 'subj1.pck' >>> nxmetrics.run() # doctest: +SKIP c Csddlj}tatatatatatj |j j }|j j }|j j }t|||}t|j jrntj|j j}ntj|jdd}|j||ddtj|t||}xJt|jD]:} t|| |} tj|j| d} tj| | tj| qWt|j jrtj|j j} ntj|jdd} |j| |ddtj| tjtt|} xLt| jD]<} t| | |} tj|j| d} tj| | tj| qZWt|j jrtj|j j}ntj|jdd}|j|| ddtj|tjtt|}xt|jD]} | d kr(tj|j|j j d} | d krHtj|j|j j!d} | d krhtj|j|j j"d} tj|| | tj| qWtjttj|j|j j#d}t$|}t%j&d tj|t'|d }t(j)||WdQRXt%j&dtta*xt+|jD]\}} xvt+|| jD]b\}}|dkrNt,j-|}t,j-|| |}n0t,j|t,j-|}t,j-|| |}t,j||}qWt,j.||f}tj|j| d} i}||| <|j| |ddt*j| qW|S)Nr globalmetricsmatcolumn)Zoned_aspck nodemetrics edgemetricsr{r}r~z0Saving extra measure file to %s in Pickle formatwzSaving MATLAB measures as %s)/r4r5rgpickled nodentwks edgentwkskntwksZmatlabrrinputsrrrrkr rrHrB_gen_outfilenamerCrArbr@rorDrextendrcrvrrlrrrrrdr6r7openpickledumpdictsr<r9r^Zvstack)selfruntimerIrr`rjZglobal_measuresZglobal_out_fileZ node_measuresrPZnewntwkout_fileZ node_out_fileZ edge_measuresZ edge_out_fileZ ntwk_measuresrZ dict_measuresfornZidxdZkeydZ nparraykeysZ nparrayvaluesr_ZnparrayZnpdictrrr_run_interfaces                    zNetworkXMetrics._run_interfacecCs|jj}tj|j|jjd|d<tj|j|jjd|d<tj|j|jjd|d<t |d<t |d<t |d<t |d<t |d <tj|jd d |d <tj|jd d |d<tj|jdd |d<|d 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Example ------- >>> import nipype.interfaces.cmtk as cmtk >>> avg = cmtk.AverageNetworks() >>> avg.inputs.in_files = ['subj1.pck', 'subj2.pck'] >>> avg.run() # doctest: +SKIP cCs>t|jjr|jj}n |jjd}t|jj||jj\}a|S)Nr)r rrrErRrGrJ)rrrFrQrrrrs    zAverageNetworks._run_interfacecCs|jj}t|jjs8tj|j|jjdd|d<ntj|jj|d<t|jj svtj|j|jjdd|d<ntj|jj |d<t |d<|S)NZ_averagerrZgexfrr) rrr rrrHrBrrGrrJ)rrrrrrs   zAverageNetworks._list_outputscCs |d|S)Nrr)rrrrrrrsz AverageNetworks._gen_outfilenameN) rrrrrrrrrrrrrrrrps  r)F)TF)rr)*r2r3rHrnumpyr9r$rrZutils.filemaniprbaserrrr r r r r r getLoggerr6rr!r-r0rRrbrcrdrkrlrorvrwrrrrrrrrrs6   (   & u / (  + %