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#!/usr/bin/env python3
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
__doc__ = """
Example of script to parcellate the data from one subject, using various
algorithms.
Note that it can take some time.
author: Bertrand Thirion, 2005-2009
"""
print(__doc__)
from os import getcwd, mkdir, path
# Local import
from get_data_light import DATA_DIR, get_second_level_dataset
from numpy import array
from nipy.labs.spatial_models.parcel_io import fixed_parcellation
# ------------------------------------
# Get the data (mask+functional image)
# take several experimental conditions
# time courses could be used instead
n_beta = [29]
mask_image = path.join(DATA_DIR, 'mask.nii.gz')
betas = [path.join(DATA_DIR, 'spmT_%04d.nii.gz' % n) for n in n_beta]
missing_file = array([not path.exists(m) for m in [mask_image] + betas]).any()
if missing_file:
get_second_level_dataset()
# set the parameters
n_parcels = 500
mu = 10
nn = 6
verbose = 1
# write directory
write_dir = path.join(getcwd(), 'results')
if not path.exists(write_dir):
mkdir(write_dir)
lpa = fixed_parcellation(mask_image, betas, n_parcels, nn, 'gkm',
write_dir, mu, verbose)
lpa = fixed_parcellation(mask_image, betas, n_parcels, nn, 'ward',
write_dir, mu, verbose)
lpa = fixed_parcellation(mask_image, betas, n_parcels, nn, 'ward_and_gkm',
write_dir, mu, verbose)
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