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# nilearn version 0.9.2

import time
import warnings

warnings.filterwarnings(action='ignore')

from pathlib import Path
import numpy as np

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import string
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm

n = 7
mat = np.random.rand(n, n)
labels = list(string.ascii_lowercase)[:n]

ind_array = np.arange(0, n, 1)

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#!/bin/bash
# NOTE: make sure freesurfer licence is under ${HOME}/.freesurfer.txt before running the script
SING_IMG="/data/cisl/containers/fmriprep-20.2.1lts.sif"
DATASET="ds000228"
DATASET_DIR="/data/cisl/datasets/${DATASET}"

# run BIDS validator
singularity exec -B ${DATASET_DIR}/${DATASET}_openfmri:/DATA \
    ${SING_IMG} bids-validator \
    /DATA

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from pathlib import Path
from templateflow import api as tflow
from templateflow import conf as tf_conf


TEMPLATEFLOW_HOME = "./data/raw/mytemplateflow"
tf_conf.TF_HOME = Path(TEMPLATEFLOW_HOME)
tf_conf.update()  # disable if you don't need access to actual templateflow data
tf_conf.init_layout()
tflow.get("myspace", resolution="02", atlas="myatlas",

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from pathlib import Path
import json

import numpy as np
from numpy.core.fromnumeric import compress
import pandas as pd

import sonpy

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import nibabel as nb
import numpy as np

original = nb.load("sub-A00018030_ses-FLU1_task-rest_acq-645_space-fsLR_den-91k_bold.dtseries.nii")

meta = {k: i for k, i in original.header.matrix.metadata.data.items()}

data = np.random.rand(30, 100)
vertices = nb.cifti2.Cifti2VertexIndices(np.arange(data.shape[-1]))
bm = nb.cifti2.Cifti2BrainModel(

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name: scca
channels:
  - defaults
dependencies:
  - _libgcc_mutex=0.1=main
  - _r-mutex=1.0.0=anacondar_1
  - binutils_impl_linux-64=2.31.1=h6176602_1
  - binutils_linux-64=2.31.1=h6176602_8
  - blas=1.0=mkl
  - bwidget=1.9.11=1

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name: neuro
channels:
  - conda-forge
  - defaults
dependencies:
  - ca-certificates=2019.9.11=hecc5488_0
  - certifi=2019.9.11=py37_0
  - dbus=1.13.6=he372182_0
  - dcm2niix=1.0.20190902=hc9558a2_0
  - fontconfig=2.13.1=h86ecdb6_1001