# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
import numpy as np

import nipy.neurospin.statistical_mapping as sm
from nipy.io.imageformats import Nifti1Image as Image
from nipy.utils import example_data

def remake_images(): 
    # Get group data
    group_data = example_data.get_filename('neurospin','language_babies','offset_002.npz')
    f = np.load(group_data)
    data, vardata, xyz = f['mat'], f['var'], f['xyz']
    dX = xyz[0,:].max() + 1
    dY = xyz[1,:].max() + 1
    dZ = xyz[2,:].max() + 1
    aux = np.zeros([dX,dY,dZ])
    data_images = []
    vardata_images = []
    mask_images = []
    for i in range(data.shape[0]):
        aux[list(xyz)] = data[i,:]
        data_images.append(Image(aux.copy(), np.eye(4)))
        aux[list(xyz)] = vardata[i,:]
        vardata_images.append(Image(aux.copy(), np.eye(4)))
        aux[list(xyz)] = 1
        mask_images.append(Image(aux.copy(), np.eye(4)))

    return data_images, vardata_images, mask_images

data_images, vardata_images, mask_images = remake_images()

#zimg, mask = sm.onesample_test(data_images, None, mask_images, 'student')
zimg, mask, nulls = sm.onesample_test(data_images, None, mask_images, 'wilcoxon', 
                                      permutations=1024, cluster_forming_th=0.01)
clusters, info = sm.cluster_stats(zimg, mask, 0.01, nulls=nulls)

"""
# Save results
np.savez('group_result.npz', clusters=clusters, info=info)
"""
"""
# Load results 
f = np.load('group_result.npz')
clusters = f['clusters']
info = f['info']
"""