import os
import sys
IN_COLAB = 'google.colab' in sys.modules

if IN_COLAB:
  os.environ["LD_PRELOAD"] = "";
  os.environ["APPTAINER_BINDPATH"] = "/content,/tmp,/cvmfs"
  os.environ["MPLCONFIGDIR"] = "/content/matplotlib-mpldir"
  os.environ["LMOD_CMD"] = "/usr/share/lmod/lmod/libexec/lmod"

  !curl -J -O https://raw.githubusercontent.com/NeuroDesk/neurocommand/main/googlecolab_setup.sh
  !chmod +x googlecolab_setup.sh
  !./googlecolab_setup.sh

  os.environ["MODULEPATH"] = ':'.join(map(str, list(map(lambda x: os.path.join(os.path.abspath('/cvmfs/neurodesk.ardc.edu.au/neurodesk-modules/'), x),os.listdir('/cvmfs/neurodesk.ardc.edu.au/neurodesk-modules/')))))

  from google.colab import output
  output.enable_custom_widget_manager()
  !pip install ipyniivue%%bash
# Output CPU information:
cat /proc/cpuinfo | grep 'vendor' | uniq
cat /proc/cpuinfo | grep 'model name' | uniq# we can use lmod to load fsl in a specific version
import lmod
await lmod.load('fsl/6.0.4')
await lmod.list()from nipype.interfaces.fsl.base import Info
print(Info.version())
# if the FSL version is changed using lmod above, the kernel of the notebook needs to be restarted!await lmod.load('afni/22.3.06')
await lmod.load('spm12/r7771')
await lmod.list()%%bash
if [ -f ./sub-01_ses-01_7T_T1w_defaced.nii ]; then
    echo "nii Output file exists, not downloading or unpacking again"
else
    if [ ! -f ./sub-01_ses-01_7T_T1w_defaced.nii.gz  ]; then
        echo "nii.gz does not exist. So, it needs to be downloaded."
        osfURL="osfstorage/TOMCAT_DIB/sub-01/ses-01_7T/anat/sub-01_ses-01_7T_T1w_defaced.nii.gz"
        echo "downloading now ..."
        osf -p bt4ez fetch $osfURL ./sub-01_ses-01_7T_T1w_defaced.nii.gz
    fi

    if [  -f ./sub-01_ses-01_7T_T1w_defaced.nii.gz ]; then
        echo "nii.gz exists. So, it needs to be unpacked and deleted"
        echo "unpacking now ..."
        gunzip ./sub-01_ses-01_7T_T1w_defaced.nii.gz
    fi
fi%ls from nipype.interfaces import fsl
from nipype.interfaces import afni

btr = fsl.BET()
btr.inputs.in_file = './sub-01_ses-01_7T_T1w_defaced.nii'
btr.inputs.frac = 0.4
btr.inputs.out_file = './sub-01_ses-01_7T_T1w_defaced_brain.nii'
res = btr.run() 

edge3 = afni.Edge3()
edge3.inputs.in_file = './sub-01_ses-01_7T_T1w_defaced.nii'
edge3.inputs.out_file = './sub-01_ses-01_7T_T1w_defaced_edges.nii'
edge3.inputs.datum = 'byte'
res = edge3.run()%ls# View 3D data
import matplotlib.pyplot as plt

def view_slices_3d(image_3d, slice_nbr, vmin, vmax, title=''):
#   print('Matrix size: {}'.format(image_3d.shape))
  fig = plt.figure(figsize=(15, 4))
  plt.suptitle(title, fontsize=10)

  plt.subplot(131)
  plt.imshow(np.take(image_3d, slice_nbr, 2), vmin=vmin, vmax=vmax, cmap='gray')
  plt.title('Axial');

  plt.subplot(132)
  image_rot = ndimage.rotate(np.take(image_3d, slice_nbr, 1),90)
  plt.imshow(image_rot, vmin=vmin, vmax=vmax, cmap='gray')
  plt.title('Coronal');

  plt.subplot(133)
  image_rot = ndimage.rotate(np.take(image_3d, slice_nbr, 0),90)
  plt.imshow(image_rot, vmin=vmin, vmax=vmax, cmap='gray')
  plt.title('Sagittal');
  cbar=plt.colorbar()

def get_figure():
    """
    Returns figure and axis objects to plot on. 
    """
    fig, ax = plt.subplots(1)
    plt.tick_params(top=False, right=False, which='both') 
    ax.spines['top'].set_visible(False)
    ax.spines['right'].set_visible(False)
    return fig, aximport nibabel as nib
from matplotlib import transforms
from scipy import ndimage
import numpy as np

# load data
brain_full = nib.load('./sub-01_ses-01_7T_T1w_defaced.nii').get_fdata()
brain = nib.load('./sub-01_ses-01_7T_T1w_defaced_brain.nii.gz').get_fdata()
edges = nib.load('./sub-01_ses-01_7T_T1w_defaced_edges.nii').get_fdata()view_slices_3d(brain_full, slice_nbr=230, vmin=0, vmax=4000, title='Brain and Skull')
view_slices_3d(brain, slice_nbr=230, vmin=0, vmax=4000, title='Brain Extracted')
view_slices_3d(edges, slice_nbr=230, vmin=0, vmax=1000, title='Edges')from ipyniivue import AnyNiivue

nv = AnyNiivue()
nv.load_volumes([{"path": "./sub-01_ses-01_7T_T1w_defaced_brain.nii.gz"}])
nvimport nipype.interfaces.spm as spm

norm12 = spm.Normalize12()
norm12.inputs.image_to_align = './sub-01_ses-01_7T_T1w_defaced.nii'
norm12.run()brain_full = nib.load('./wsub-01_ses-01_7T_T1w_defaced.nii').get_fdata()
view_slices_3d(brain_full, slice_nbr=50, vmin=0, vmax=4000, title='Brain normalized to MNI space')nv.load_volumes([{"path": "./wsub-01_ses-01_7T_T1w_defaced.nii"}])
nv