def test_loadtxt_dict(): # Using loadtxt_dict mydict = loadtxt_dict('temp.txt', 'mytxt') # True dictionary truedict = {'mytxt': np.arange(30.)} assert_array_equal(list(mydict.values()), list(truedict.values())) assert_array_equal(mydict.keys(), truedict.keys())
# load outlier files dvars_out = json.load(open(pathtodata+"ds005/dvarsOutliers.txt")) fd_out = json.load(open(pathtodata+"ds005/fdOutliers.txt")) # need to create two loops, one for 1-9 and one for 10-16 # because of folder naming difference. for i in range(1,10): for j in range(1,4): # set general path for reaching dvars and fd files # also path for saving files txtpath= pathtodata+'ds005/sub00'+`i`+'/BOLD/task001_run00'+`j`+'/QA/' # dvars path and name, call function dvarsfile=txtpath+'dvars.txt' dvarsfigname=pathtofig+'dvars_sub'+`i`+'run'+`j`+'.png' dvars_dict = loadtxt_dict(dvarsfile, dvarsfigname) dvars_outliers = dvars_out['sub'+`i`+'run'+`j`] plot_dvars(dvars_dict, dvars_outliers, saveit=True) # fd path and name, call function fdfile=txtpath+'fd.txt' fdfigname=pathtofig+'fd_sub'+`i`+'run'+`j`+'.png' fd_dict = loadtxt_dict(fdfile, fdfigname) fd_outliers = fd_out['sub'+`i`+'run'+`j`] plot_fd(fd_dict, fd_outliers, saveit=True) # mean path and name, call function niipath=pathtodata+'ds005/sub00'+`i`+'/BOLD/task001_run00'+`j` meandata=niipath+'/bold.nii.gz' meanfigname=pathtofig+'mean_sub'+`i`+'run'+`j`+'.png' data_dict = loadnib_dict(meandata, meanfigname) plot_meanSig(data_dict, saveit=True)