def test_loadnib_dict():
    # create test img
    t_data = np.array([1,2,3])
    t_dict = {'testnib': t_data}
    img = nib.Nifti1Image(t_data, np.eye(4))
    nib.save(img,'testnib.nii.gz')
    # my function
    my_dict = loadnib_dict('testnib.nii.gz', 'testnib')
    assert (list(t_dict.keys())[0] == list(my_dict.keys())[0])
    assert_array_equal(list(t_dict.values())[0], list(my_dict.values())[0])
        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)

for i in range(10,17):
    for j in range(1,4):
        # set general path for reaching dvars and fd files
        # also path for saving files
        txtpath=pathtodata+'ds005/sub0'+`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'