def decimate(self, dec):
'''nim is the mri data in python format
dec is the decimation factor'''
#nim = self.nifti
header = self.nifti.get_header()
self.filename = self.nifti.get_filename()
xend = self.nifti.get_shape()[0]
yend = self.nifti.get_shape()[1]
zend = self.nifti.get_shape()[2]
if type(dec) != float and type(dec) != int:
print 'nonuniform decimation'
xstartval=ceil(dec[0]/2);
print xstartval,
ystartval=ceil(dec[1]/2);
zstartval=ceil(dec[2]/2);
decimg=array(self.data[xstartval::dec[0],:,:][:,ystartval::dec[1],:][:,:,zstartval::dec[2]])
nonz = where(decimg > 0)
x = ((nonz[0])*dec[0])+(dec[0])
y = ((nonz[1])*dec[1])+(dec[1])
z = ((nonz[2])*dec[2])+(dec[2])
else:
print 'uniform decimation'
startval=ceil(dec/2);
decimg=array(self.data[startval::dec,:,:][:,startval::dec,:][:,:,startval::dec])
nonz = where(decimg > 0)
x = ((nonz[0]+1)*dec)#-(dec)
y = ((nonz[1]+1)*dec)#-(dec)
z = ((nonz[2]+1)*dec)#-(dec)
#--20090702--danc--not sure about reordering
#mrixyz = array([x,y,z])
#--20090702--danc--adding voxel scaling. this had to be a huge bug, so why i haven't noticed it so far???
# The effect would be non existant on isotropic volumes, so thats probably why.
voxdim = header['pixdim'][1:4]#.voxdim[::-1] #flipped voxel dims
print voxdim
#print 'WARNING: assuming voxdim reverse of img.voxdim. Could be wrong'
mrixyz = (array([x,y,z]).T*voxdim).T
self.mrixyz = mrixyz
self.img = decimg
self.factor = dec
self.ind = array(nonz)
try:
[t,r] = transform.meg2mri(self.lpa,self.rpa,self.nas)
self.megxyz = transform.mri2meg(t,r,self.mrixyz)
except AttributeError:
print 'Transform Error, skipping'