/usr/share/pyshared/dipy/external/fsl.py is in python-dipy 0.7.1-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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from __future__ import with_statement
import os
from os.path import join as pjoin
from subprocess import Popen, PIPE
import numpy as np
import numpy.linalg as npl
from numpy import newaxis
from scipy.ndimage import map_coordinates as mc
from scipy.ndimage import affine_transform
from dipy.io.dpy import Dpy
import nibabel as nib
from nibabel.tmpdirs import InTemporaryDirectory
_VAL_FMT = ' %e'
class FSLError(Exception):
""" Class signals error in FSL processing """
def have_flirt():
""" Return True if we can call flirt without error
Relies on the fact that flirt produces text on stdout when called with no
arguments
"""
p = Popen('flirt', stdout=PIPE, stderr=PIPE, shell=True)
stdout, stderr = p.communicate()
return stdout != ''
def write_bvals_bvecs(bvals, bvecs, outpath=None, prefix=''):
''' Write FSL FDT bvals and bvecs files
Parameters
-------------
bvals : (N,) sequence
Vector with diffusion gradient strength (one per diffusion
acquisition, N=no of acquisitions)
bvecs : (N, 3) array-like
diffusion gradient directions
outpath : None or str
path to write FDT bvals, bvecs text files
None results in current working directory.
prefix : str
prefix for bvals, bvecs files in directory. Defaults to ''
'''
if outpath is None:
outpath = os.getcwd()
bvals = tuple(bvals)
bvecs = np.asarray(bvecs)
bvecs[np.isnan(bvecs)] = 0
N = len(bvals)
fname = pjoin(outpath, prefix + 'bvals')
fmt = _VAL_FMT * N + '\n'
open(fname, 'wt').write(fmt % bvals)
fname = pjoin(outpath, prefix + 'bvecs')
bvf = open(fname, 'wt')
for dim_vals in bvecs.T:
bvf.write(fmt % tuple(dim_vals))
def flirt2aff(mat, in_img, ref_img):
""" Transform from `in_img` voxels to `ref_img` voxels given `mat`
Parameters
----------
mat : (4,4) array
contents (as array) of output ``-omat`` transformation file from flirt
in_img : img
image passed (as filename) to flirt as ``-in`` image
ref_img : img
image passed (as filename) to flirt as ``-ref`` image
Returns
-------
aff : (4,4) array
Transform from voxel coordinates in ``in_img`` to voxel coordinates in
``ref_img``
Notes
-----
Thanks to Mark Jenkinson and Jesper Andersson for the correct statements
here, apologies for any errors we've added.
``flirt`` registers an ``in`` image to a ``ref`` image. It can produce
(with the ``-omat`` option) - a 4 x 4 affine matrix giving the mapping from
*inspace* to *refspace*.
The rest of this note is to specify what *inspace* and *refspace* are.
In what follows, a *voxtrans* for an image is the 4 by 4 affine
``np.diag([vox_i, vox_j, vox_k, 1])`` where ``vox_i`` etc are the voxel
sizes for the first second and third voxel dimension. ``vox_i`` etc are
always positive.
If the input image has an affine with a negative determinant, then the
mapping from voxel coordinates in the input image to *inspace* is simply
*voxtrans* for the input image. If the reference image has a negative
determinant, the mapping from voxel space in the reference image to
*refspace* is simply *voxtrans* for the reference image.
A negative determinant for the image affine is the common case, of an image
with a x voxel flip. Analyze images don't store affines and flirt assumes a
negative determinant in these cases.
For positive determinant affines, flirt starts *inspace* and / or *refspace*
with an x voxel flip. The mapping implied for an x voxel flip for image
with shape (N_i, N_j, N_k) is:
[[-1, 0, 0, N_i - 1],
[ 0, 1, 0, 0],
[ 0, 0, 1, 0],
[ 0, 0, 0, 1]]
If the input image has an affine with a positive determinant, then mapping
from input image voxel coordinates to *inspace* is ``np.dot(input_voxtrans,
input_x_flip)`` - where ``input_x_flip`` is the matrix above with ``N_i``
given by the input image first axis length. Similarly the mapping from
reference voxel coordinates to *refspace*, if the reference image has a
positive determinant, is ``np.dot(ref_voxtrans, ref_x_flip)`` - where
``ref_x_flip`` is the matrix above with ``N_i`` given by the reference image
first axis length.
"""
in_hdr = in_img.get_header()
ref_hdr = ref_img.get_header()
# get_zooms gets the positive voxel sizes as returned in the header
inspace = np.diag(in_hdr.get_zooms() + (1,))
refspace = np.diag(ref_hdr.get_zooms() + (1,))
if npl.det(in_img.get_affine()) >= 0:
inspace = np.dot(inspace, _x_flipper(in_hdr.get_data_shape()[0]))
if npl.det(ref_img.get_affine()) >= 0:
refspace = np.dot(refspace, _x_flipper(ref_hdr.get_data_shape()[0]))
# Return voxel to voxel mapping
return np.dot(npl.inv(refspace), np.dot(mat, inspace))
def _x_flipper(N_i):
flipr = np.diag([-1, 1, 1, 1])
flipr[0, 3] = N_i - 1
return flipr
def flirt2aff_files(matfile, in_fname, ref_fname):
""" Map from `in_fname` image voxels to `ref_fname` voxels given `matfile`
See :func:`flirt2aff` docstring for details.
Parameters
------------
matfile : str
filename of output ``-omat`` transformation file from flirt
in_fname : str
filename for image passed to flirt as ``-in`` image
ref_fname : str
filename for image passed to flirt as ``-ref`` image
Returns
-------
aff : (4,4) array
Transform from voxel coordinates in image for ``in_fname`` to voxel
coordinates in image for ``ref_fname``
"""
mat = np.loadtxt(matfile)
in_img = nib.load(in_fname)
ref_img = nib.load(ref_fname)
return flirt2aff(mat, in_img, ref_img)
def warp_displacements(ffa, flaff, fdis, fref, ffaw, order=1):
''' Warp an image using fsl displacements
Parameters
------------
ffa : filename of nifti to be warped
flaff : filename of .mat (flirt)
fdis : filename of displacements (fnirtfileutils)
fref : filename of reference volume e.g. (FMRIB58_FA_1mm.nii.gz)
ffaw : filename for the output warped image
'''
refaff = nib.load(fref).get_affine()
disdata = nib.load(fdis).get_data()
imgfa = nib.load(ffa)
fadata = imgfa.get_data()
fazooms = imgfa.get_header().get_zooms()
# from fa index to ref index
res = flirt2aff_files(flaff, ffa, fref)
# from ref index to fa index
ires = np.linalg.inv(res)
# create the 4d volume which has the indices for the reference image
reftmp = np.zeros(disdata.shape)
'''
#create the grid indices for the reference
#refinds = np.ndindex(disdata.shape[:3])
for ijk_t in refinds:
i,j,k = ijk_t
reftmp[i,j,k,0]=i
reftmp[i,j,k,1]=j
reftmp[i,j,k,2]=k
'''
# same as commented above but much faster
reftmp[..., 0] = np.arange(disdata.shape[0])[:, newaxis, newaxis]
reftmp[..., 1] = np.arange(disdata.shape[1])[newaxis, :, newaxis]
reftmp[..., 2] = np.arange(disdata.shape[2])[newaxis, newaxis, :]
# affine transform from reference index to the fa index
A = np.dot(reftmp, ires[:3, :3].T) + ires[:3, 3]
# add the displacements but first devide them by the voxel sizes
A2 = A + disdata / fazooms
# hold the displacements' shape reshaping
di, dj, dk, dl = disdata.shape
# do the interpolation using map coordinates
# the list of points where the interpolation is done given by the reshaped in 2D A2 (list of 3d points in fa index)
W = mc(fadata, A2.reshape(di * dj * dk, dl).T, order=order).reshape(di, dj, dk)
# save the warped image
Wimg = nib.Nifti1Image(W, refaff)
nib.save(Wimg, ffaw)
def warp_displacements_tracks(fdpy, ffa, fmat, finv, fdis, fdisa, fref, fdpyw):
""" Warp tracks from native space to the FMRIB58/MNI space
We use here the fsl displacements. Have a look at create_displacements to
see an example of how to use these displacements.
Parameters
------------
fdpy : filename of the .dpy file with the tractography
ffa : filename of nifti to be warped
fmat : filename of .mat (flirt)
fdis : filename of displacements (fnirtfileutils)
fdisa : filename of displacements (fnirtfileutils + affine)
finv : filename of invwarp displacements (invwarp)
fref : filename of reference volume e.g. (FMRIB58_FA_1mm.nii.gz)
fdpyw : filename of the warped tractography
See also
-----------
dipy.external.fsl.create_displacements
"""
# read the tracks from the image space
dpr = Dpy(fdpy, 'r')
T = dpr.read_tracks()
dpr.close()
# copy them in a new file
dpw = Dpy(fdpyw, 'w', compression=1)
dpw.write_tracks(T)
dpw.close()
# from fa index to ref index
res = flirt2aff_files(fmat, ffa, fref)
# load the reference img
imgref = nib.load(fref)
refaff = imgref.get_affine()
# load the invwarp displacements
imginvw = nib.load(finv)
invwdata = imginvw.get_data()
invwaff = imginvw.get_affine()
# load the forward displacements
imgdis = nib.load(fdis)
disdata = imgdis.get_data()
# load the forward displacements + affine
imgdis2 = nib.load(fdisa)
disdata2 = imgdis2.get_data()
# from their difference create the affine
disaff = disdata2 - disdata
del disdata
del disdata2
shape = nib.load(ffa).get_data().shape
# transform the displacements affine back to image space
disaff0 = affine_transform(disaff[..., 0], res[:3, :3], res[:3, 3], shape, order=1)
disaff1 = affine_transform(disaff[..., 1], res[:3, :3], res[:3, 3], shape, order=1)
disaff2 = affine_transform(disaff[..., 2], res[:3, :3], res[:3, 3], shape, order=1)
# remove the transformed affine from the invwarp displacements
di = invwdata[:, :, :, 0] + disaff0
dj = invwdata[:, :, :, 1] + disaff1
dk = invwdata[:, :, :, 2] + disaff2
dprw = Dpy(fdpyw, 'r+')
rows = len(dprw.f.root.streamlines.tracks)
blocks = np.round(np.linspace(0, rows, 10)).astype(int) # lets work in blocks
# print rows
for i in range(len(blocks) - 1):
# print blocks[i],blocks[i+1]
# copy a lot of tracks together
caboodle = dprw.f.root.streamlines.tracks[blocks[i]:blocks[i + 1]]
mci = mc(di, caboodle.T, order=1) # interpolations for i displacement
mcj = mc(dj, caboodle.T, order=1) # interpolations for j displacement
mck = mc(dk, caboodle.T, order=1) # interpolations for k displacement
D = np.vstack((mci, mcj, mck)).T
# go back to mni image space
WI2 = np.dot(caboodle, res[:3, :3].T) + res[:3, 3] + D
# and then to mni world space
caboodlew = np.dot(WI2, refaff[:3, :3].T) + refaff[:3, 3]
# write back
dprw.f.root.streamlines.tracks[blocks[i]:blocks[i + 1]] = caboodlew.astype('f4')
dprw.close()
def pipe(cmd):
""" A tine pipeline system to run external tools.
For more advanced pipelining use nipype http://www.nipy.org/nipype
"""
p = Popen(cmd, shell=True, stdout=PIPE, stderr=PIPE)
sto = p.stdout.readlines()
ste = p.stderr.readlines()
print(sto)
print(ste)
def dcm2nii(dname, outdir, filt='*.dcm', options='-d n -g n -i n -o'):
cmd = 'dcm2nii ' + options + ' ' + outdir + ' ' + dname + '/' + filt
print(cmd)
pipe(cmd)
def eddy_correct(in_nii, out_nii, ref=0):
cmd = 'eddy_correct ' + in_nii + ' ' + out_nii + ' ' + str(ref)
print(cmd)
pipe(cmd)
def bet(in_nii, out_nii, options=' -F -f .2 -g 0'):
cmd = 'bet ' + in_nii + ' ' + out_nii + options
print(cmd)
pipe(cmd)
def run_flirt_imgs(in_img, ref_img, dof=6, flags=''):
""" Run flirt on nibabel images, returning affine
Parameters
----------
in_img : `SpatialImage`
image to register
ref_img : `SpatialImage`
image to register to
dof : int, optional
degrees of freedom for registration (default 6)
flags : str, optional
other flags to pass to flirt command string
Returns
-------
in_vox2out_vox : (4,4) ndarray
affine such that, if ``[i, j, k]`` is a coordinate in voxels in the
`in_img`, and ``[p, q, r]`` are the equivalent voxel coordinates in the
reference image, then
``[p, q, r] = np.dot(in_vox2out_vox[:3,:3]), [i, j, k] + in_vox2out_vox[:3,3])``
"""
omat = 'reg.mat'
with InTemporaryDirectory():
nib.save(in_img, 'in.nii')
nib.save(ref_img, 'ref.nii')
cmd = 'flirt %s -dof %d -in in.nii -ref ref.nii -omat %s' % (
flags, dof, omat)
proc = Popen(cmd, shell=True, stdout=PIPE, stderr=PIPE)
stdout, stderr = proc.communicate()
if not os.path.isfile(omat):
raise FSLError('Command "%s" failed somehow - stdout: %s\n'
'and stderr: %s\n' % (cmd, stdout, stderr))
res = np.loadtxt(omat)
return flirt2aff(res, in_img, ref_img)
def apply_warp(in_nii, affine_mat, nonlin_nii, out_nii):
cmd = 'applywarp --ref=${FSLDIR}/data/standard/FMRIB58_FA_1mm --in=' + in_nii + ' --warp=' + nonlin_nii + \
' --out=' + out_nii
print(cmd)
pipe(cmd)
def create_displacements(fin, fmat, fnonlin, finvw, fdisp, fdispa, fref):
""" Create displacements using FSL's FLIRT and FNIRT tools
Parameters
----------
fin : filename of initial source image
fmat : filename of .mat (flirt)
fnonlin : filename of fnirt output
finvw : filename of invwarp displacements (invwarp)
fdis : filename of fnirtfileutils
fdisa : filename of fnirtfileutils (with other parameters)
fref : filename of reference image e.g. (FMRIB58_FA_1mm.nii.gz)
"""
commands = []
commands.append('flirt -ref ' + fref + ' -in ' + fin + ' -omat ' + fmat)
commands.append('fnirt --in=' + fin + ' --aff=' + fmat + ' --cout=' + fnonlin + ' --config=FA_2_FMRIB58_1mm')
commands.append('invwarp --ref=' + fin + ' --warp=' + fnonlin + ' --out=' + finvw)
commands.append('fnirtfileutils --in=' + fnonlin + ' --ref=${FSLDIR}/data/standard/FMRIB58_FA_1mm --out=' + fdisp)
commands.append('fnirtfileutils --in=' + fnonlin + ' --ref=${FSLDIR}/data/standard/FMRIB58_FA_1mm --out=' +
fdispa + ' --withaff')
for c in commands:
print(c)
pipe(c)
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