def packing(dataset, radius=4, nifti=False, randoffset=False):
"""return a hexagonal close sphere packing grid for a PyMVPA fMRI dataset
Keyword arguments:
radius-- radius in voxels of the spheres to pack (default 4)
nifti-- write out a seed voxel mask as a nifti
randomoffset-- random jitter of the seed voxel grid
"""
from pylab import find, random
from numpy import ones, zeros, arange, sqrt, remainder
from mvpa2.suite import fmri_dataset, Dataset
import os
if randoffset:
ro = random(3)
else:
ro = zeros(3)
minco = dataset.fa.voxel_indices.min(0)
maxco = dataset.fa.voxel_indices.max(0)
rect = ones(dataset.a.voxel_dim)
fac = sqrt(6)*2*radius/3
for iz,z in enumerate(arange(minco[2], maxco[2], fac)):
for iy,y in enumerate(arange(minco[1], maxco[1], fac)):
for x in arange(minco[0], maxco[0], 2*radius):
hx = x + remainder(iy, 2)*radius + ro[0]*radius
hy = y + remainder(iz, 2)*fac + ro[1]*radius
hz = z + ro[2]*radius
if hz <= maxco[2]:
rect [hx, hy, hz] += 1
maskedrect = dataset.mapper.forward1(rect)
roiIndex = find((maskedrect == 2))
print 'number of seed voxel: '+str(len(roiIndex))
maskedrectds = Dataset([maskedrect])
maskedrectds.a = dataset.a.copy()
maskedrectds.fa = dataset.fa.copy()
if nifti:
from nibabel import Nifti1Image
Nifti1Image(maskedrectds.O.squeeze(),
dataset.a.imghdr.get_best_affine()
).to_filename(os.path.join('sparse'+str(int(radius))+'.nii.gz'))
return roiIndex, maskedrectds
