# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
"""
Example of activation image vizualization
with nipy.neurospin vizualization tools
"""
print __doc__
import os.path
import pylab as pl
from nipy.io.imageformats import load
from nipy.neurospin import viz
import get_data_light
# get the data
data_dir = get_data_light.get_it()
img = load(os.path.join(data_dir, 'spmT_0029.nii.gz'))
data = img.get_data()
affine = img.get_affine()
viz.plot_map(data, affine, cut_coords=(-52, 10, 22),
threshold=2.0, cmap=viz.cm.cold_hot)
pl.show()
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]
data_dir = op.expanduser(op.join('~', '.nipy', 'tests', 'data'))
mask_image = op.join(data_dir, 'mask.nii.gz')
betas = [op.join(data_dir, 'spmT_%04d.nii.gz' % n) for n in n_beta]
missing_file = array(
[op.exists(m) == False for m in [mask_image] + betas]).any()
if missing_file:
import get_data_light
get_data_light.get_it()
# set the parameters
n_parcels = 500
mu = 10
nn = 6
write_dir = tempfile.mkdtemp()
verbose = 1
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)
