def TBV_value_extractor(TBVip,voi,ctr,outdir,basename): """ This function extracts the tvalues from data loaded in TBV and save them as binary files. Up to this date there is no possibility to extract the beta values. Parameters ---------- TBVip : string IP index to access the TBV processed data. When TBV is running on the same machine please use 'localhost' voi : integer A value ranging from 0 to infinite. It indicates the index of the ROI used in analysis. ctr : integer A value ranging from 0 to infinite. It indicates the index of the contrast of interest. The contrast can be defined manually using a .ctr file or it can be defined automatically by TBV. Usually the contrast '0' corresponds to the map 'first predictors vs. baseline'. outdir : string The directory for the output files. basename : string Basename for the outputs. Returns ------- None. """ TBV = tbvnetworkinterface.TbvNetworkInterface(TBVip,55555) if TBV.get_current_time_point()[0] == TBV.get_expected_nr_of_time_points()[0]: print('Extracting t-values...') #coordinates of voxels of the roi coord_roi_voxels = np.array(TBV.get_all_coords_of_voxels_of_roi(voi)[0]) tvals = np.array([TBV.get_map_value_of_voxel(voi,coord)[0] for coord in coord_roi_voxels]).reshape(-1,1) output_tval = np.concatenate((coord_roi_voxels,tvals),axis=1) print('Saving t-vals data...') with open(os.path.join(outdir,basename+'_voi'+str(voi)+'.tvals'), 'w') as outfile: np.savetxt(outfile, output_tval) print('Everything have been estimated! Goodbye!')
#load properties in the just created rtRSAObj #the config.json file can be created by using one of the class method #the file si wirtten after the estimation of the RS rtRSAObj.load(sub_json_file) print('rtRSA ready!\n') print('Nr of voxels: ', +len(rtRSAObj.func_coords)) print('Base stimuli name:') print(rtRSAObj.conditions) #%%############################################################################ # TBV interface settings # ############################################################################### #create an instance to access TBV via network plugin TBV = tbvnetworkinterface.TbvNetworkInterface('localhost', 55555) win = visual.Window(fullscr=False, color='gray', screen=0, size=(1024, 768), colorSpace='rgb255') #creation of the cue for the image image = visual.ImageStim(win, image=None, mask=None, units='pix', pos=(0.0, 0.0), size=600, ori=0.0,