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from nisnap import snap
from nisnap.utils import aseg
import sys
aparc_fp, bg, snap_fp = sys.argv[1:]

filepaths = aseg.__preproc_aseg__(aparc_fp, bg)

axes = 'x'
figsize = {'x': (23, 15)}
rowsize = {'x': 8}

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#! /usr/bin/env python
# Usage: python qc_reg.py path_to_T1 path_to_T2 path_to_GIF

import sys
t1_fp, t2_fp, gif_fp = sys.argv[1:]


def ants_snapshot(t1w_fp, coreg_fp):
    """ Create 2 sets of snapshots, one with the background (T1) image,
    one with the overlay. Both along the 3 axes (axial, coronal and sagittal).

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import pyxnat 
from nisnap import xnat, snap 
from glob import glob 
import os.path as op 
methods = ['T1', 'T1_FLAIR', 'T1_T2', 'T1_maskT1T2'] 
 
x = pyxnat.Interface(config='/home/grg/.xnat_goperto_ci.cfg') 
dd = '/mnt/projects/Segmentation_ALFA_PLUS_IRENE'  
subjects2 = sorted([int(e.split('/')[-1]) for e in glob(op.join(dd, 'segmentacions_T1', '*'))]) 
subjects = sorted([int(e['subject_label']) for e in x.array.experiments(project_id='ALFA_PLUS', 

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import json
import pandas as pd
import pyxnat

c = pyxnat.Interface(config='/home/grg/.xnat_bsc.cfg')

# Collect experiments
experiments = json.load(open('/home/grg/Downloads/mri_list.json'))
    
# Querying FreeSurfer resource -if any- from each experiment