def _run_interface(self, runtime):
transforms = []
invert_transform_flags = []
if isdefined(self.inputs.transform_1):
transforms.append(self.inputs.transform_1)
invert_transform_flags.append(self.inputs.invert_1)
if isdefined(self.inputs.transform_2):
transforms.append(self.inputs.transform_2)
invert_transform_flags.append(self.inputs.invert_2)
if isdefined(self.inputs.transform_3):
transforms.append(self.inputs.transform_3)
invert_transform_flags.append(self.inputs.invert_3)
#output file
split = splitext(os.path.basename(self.inputs.input_image))
self.inputs.output_image = os.getcwd() + os.sep + split[0] + split[1]
if '_space-' in self.inputs.output_image:
self.inputs.output_image = re.sub(
'_space-[A-z]*_', "_space-" + self.inputs.target_space + "_",
self.inputs.output_image)
#combine transformation files and output flags
transforms_zip = zip(transforms, invert_transform_flags)
transform_string = ' '.join([
'-t [ ' + str(t) + ' , ' + str(int(f)) + ' ]'
for t, f in transforms_zip if t != None
])
cmdline = "antsApplyTransforms --float -v 1 -e 3 -d 3 -n " + self.inputs.interpolation + " -i " + self.inputs.input_image + " " + transform_string + " -r " + self.inputs.reference_image + " -o " + self.inputs.output_image
cmd(cmdline)
return runtime
def _run_interface(self, runtime):
#Get extension for input transformation files
ext_1 = splitext(self.inputs.transform_1)[1]
ext_2 = splitext(self.inputs.transform_2)[1]
if ext_1 in ['.mat', '.txt'] and ext_2 in ['.mat', '.txt']:
self.inputs.out_file = os.getcwd(
) + os.sep + 'composite_affine.mat'
elif ext_1 == '.h5' or ext_2 == '.h5':
self.inputs.out_file = os.getcwd() + os.sep + 'composite_warp.h5'
cmd("CompositeTransformUtil --assemble " + ' '.join([
self.inputs.out_file, self.inputs.transform_1,
self.inputs.transform_2
]))
return runtime
def _gen_output(self):
fname = ntpath.basename(self.inputs.pet_file)
fname_list = splitext(fname) # [0]= base filename; [1] =extension
dname = os.getcwd()
kind='vxl'
if self.inputs.roi_based == True :
kind = 'roi'
return dname+ os.sep+fname_list[0] +'_quant-'+kind+'-'+ self.inputs.quant_method +'.nii.gz'
def _create_output_file(self, fn, space):
basefn = os.path.basename(fn)
if not '_space-' in basefn:
basefn_split = splitext(basefn)
return basefn_split[0] + '_space-' + space + basefn_split[1]
else:
return '_'.join([
f if not 'space-' in f else 'space-' + space
for f in basefn.split('_')
])
def mnc2vol(niftifile):
if not os.path.exists(niftifile):
print('Warning: could not find file', niftifile)
exit(1)
datatype = nib.load(niftifile).get_data().dtype
basename = os.getcwd() + os.sep + splitext(os.path.basename(niftifile))[0]
rawfile = basename + '.raw'
headerfile = basename + '.header'
minc2volume.make_raw(niftifile, datatype, rawfile)
minc2volume.make_header(niftifile, datatype, headerfile)
def _gen_output(self, basefile):
fname = ntpath.basename(basefile)
fname_list = splitext(fname) # [0]= base filename; [1] =extension
dname = os.getcwd()
suffix = self._suffix
if suffix[0] != '_':
suffix = '_' + suffix
out_fn = dname + os.sep + fname_list[0] + suffix + fname_list[1]
if '.gz' not in fname_list[1]:
out_fn += '.gz'
return out_fn
def _run_interface(self, runtime):
quantNode = self._quantCommand()
quantNode.inputs = self.inputs
init_command = quantNode.cmdline
modified_command = []
self.inputs.out_file = quantNode.inputs.out_file
for f in init_command.split(' '):
if os.path.exists(f):
f = check_gz(f)
elif f == quantNode.inputs.out_file and splitext(
f)[1] == '.nii.gz':
f = splitext(f)[0] + '.nii'
self.inputs.out_file = f
modified_command.append(f)
print(modified_command)
command = ' '.join(modified_command)
print(command)
cmd(command)
print("Out file", self.inputs.out_file)
return runtime
def _run_interface(self, runtime):
if not isdefined(self.inputs.out_file):
base = os.path.basename(self.inputs.in_file)
split = splitext(base)
self.inputs.out_file = os.getcwd(
) + os.sep + split[0] + self._suffix + split[1]
#Load PET 3D volume
img = nib.load(self.inputs.in_file)
vol = gaussian_filter(img.get_data(), 1)
vol[vol < threshold_otsu(vol[vol > 0])] = 0
vol[vol > 0] = 1
nib.Nifti1Image(vol, img.affine,
img.header).to_filename(self.inputs.out_file)
return runtime
def main(filename, datatype):
if not os.path.isfile(filename):
console_error("File {} does not exist.".format(filename), 1)
check_minc_tools_installed()
basename = splitext(os.path.basename(filename))
dirname = os.path.dirname(filename)
headername = "{}/{}.header".format(dirname, basename)
rawname = "{}/{}.raw".format(dirname, basename)
console_log("Processing file: {}".format(filename))
console_log("Creating header file: {}".format(headername))
make_header(filename, datatype, headername)
console_log("Creating raw data file: {}".format(rawname))
make_raw(filename, datatype, rawname)
def _gen_output(self, basefile):
fname = ntpath.basename(basefile)
fname_list = splitext(fname) # [0]= base filename; [1] =extension
dname = os.getcwd()
return dname + os.sep + fname_list[0] + "_brain_mask" + fname_list[1]
def _gen_output(self, in_file):
ii = splitext(os.path.basename(in_file))[0]
out_file = os.getcwd() + os.sep + ii + "_int.csv"
return out_file
