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'