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())
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)
