def sort_pes(pes):
from nipype import config, logging
from nipype.interfaces.fsl import Merge
from os.path import abspath
config.enable_debug_mode()
logging.update_logging(config)
print(pes)
pe1s = []
pe0s = []
for file in pes:
if 'pe0' in file:
pe0s.append(file)
elif 'pe1' in file:
pe1s.append(file)
pe1s = sorted(pe1s)
pe0s = sorted(pe0s)
me = Merge()
merged_pes = []
for i in range(0,len(pe1s)):
num=pe1s[i][-12:-11]
me.inputs.in_files = [pe1s[i],pe0s[i]]
me.inputs.dimension='t'
me.inputs.merged_file = 'merged_pes%s.nii.gz' % num
me.run()
file = abspath('merged_pes%s.nii.gz' % num)
merged_pes.append(file)
return(merged_pes)
def rs_grouplevel(copes, varcopes, dofs, output_dir, work_dir):
from nipype.interfaces.fsl.model import MultipleRegressDesign
from nipype.interfaces.utility import Function
from nipype.interfaces.fsl.model import FLAMEO
from nipype.interfaces.fsl.model import SmoothEstimate
from connectivity.interfaces import Cluster
from nipype.interfaces.fsl.utils import Merge
from nipype.interfaces.fsl import Info
from connectivity.interfaces import PtoZ
grplevelworkflow = pe.Workflow(name="grplevelworkflow")
grplevelworkflow.base_dir = work_dir
merger = Merge()
merger.inputs.dimension = 't'
merger.inputs.in_files = copes
merger.inputs.merged_file = op.join(work_dir, 'cope.nii.gz')
merger.run()
merger.inputs.in_files = varcopes
merger.inputs.merged_file = op.join(work_dir, 'varcope.nii.gz')
merger.run()
merger.inputs.in_files = dofs
merger.inputs.merged_file = op.join(work_dir, 'dof.nii.gz')
merger.run()
model = pe.Node(interface=MultipleRegressDesign(), name='model')
model.inputs.contrasts = [['mean', 'T', ['roi'], [1]]]
model.inputs.regressors = dict(roi=np.ones(len(copes)).tolist())
flameo = pe.Node(interface=FLAMEO(), name='flameo')
flameo.inputs.cope_file = op.join(work_dir, 'cope.nii.gz')
flameo.inputs.var_cope_file = op.join(work_dir, 'varcope.nii.gz')
flameo.inputs.dof_var_cope_file = op.join(work_dir, 'dof.nii.gz')
flameo.inputs.run_mode = 'flame1'
flameo.inputs.mask_file = Info.standard_image(
'MNI152_T1_2mm_brain_mask.nii.gz')
grplevelworkflow.connect(model, 'design_con', flameo, 't_con_file')
grplevelworkflow.connect(model, 'design_grp', flameo, 'cov_split_file')
grplevelworkflow.connect(model, 'design_mat', flameo, 'design_file')
smoothest = pe.Node(SmoothEstimate(), name='smooth_estimate')
grplevelworkflow.connect(flameo, 'zstats', smoothest, 'residual_fit_file')
smoothest.inputs.mask_file = Info.standard_image(
'MNI152_T1_2mm_brain_mask.nii.gz')
smoothest.inputs.dof = len(dofs) - 1
cluster = pe.Node(Cluster(), name='cluster')
ptoz = pe.Node(PtoZ(), name='ptoz')
ptoz.inputs.pvalue = 0.001
calculate_resels = pe.Node(Function(input_names=["volume", "resels"],
output_names=["resels"],
function=calcres),
name="calcres")
grplevelworkflow.connect(smoothest, 'resels', cluster, 'resels')
grplevelworkflow.connect(smoothest, 'resels', calculate_resels, 'resels')
grplevelworkflow.connect(smoothest, 'volume', calculate_resels, 'volume')
grplevelworkflow.connect(calculate_resels, 'resels', ptoz, 'resels')
grplevelworkflow.connect(ptoz, 'zstat', cluster, 'threshold')
cluster.inputs.connectivity = 26
cluster.inputs.out_threshold_file = True
cluster.inputs.out_index_file = True
cluster.inputs.out_localmax_txt_file = True
cluster.inputs.voxthresh = True
grplevelworkflow.connect(flameo, 'zstats', cluster, 'in_file')
datasink = pe.Node(nio.DataSink(), name='sinker')
datasink.inputs.base_directory = work_dir
grplevelworkflow.connect(flameo, 'zstats', datasink, 'z')
grplevelworkflow.connect(cluster, 'threshold_file', datasink, 'z_thresh')
grplevelworkflow.run()
shutil.rmtree(op.join(work_dir, 'grplevelworkflow'))
#copy data to directory
shutil.copyfile(op.join(work_dir, 'z', 'zstat1.nii.gz'),
op.join(output_dir, 'z.nii.gz'))
shutil.copyfile(op.join(work_dir, 'z_thresh', 'zstat1_threshold.nii.gz'),
op.join(output_dir, 'z_level-voxel_corr-FWE.nii.gz'))
shutil.rmtree(work_dir)
from nipype.interfaces.fsl.model import SmoothEstimate
from interfaces import Cluster
from nipype.interfaces.fsl.utils import Merge
from nipype.interfaces.fsl.Info import standard_image
from interfaces import PtoZ
def calcres(smoothest_input)
resels = int(smoothest_input[0]/smoothest_input[1])
grplevelworkflow = pe.Workflow(name="grplevelworkflow")
merger = Merge()
merger.inputs.dimensions = 't'
merger.inputs.in_files = copes
merger.inputs.merged_file = op.join(work_dir, 'cope.nii.gz')
merger.run()
merger.inputs.in_files = varcopes
merger.inputs.merged_file = op.join(work_dir, 'varcope.nii.gz')
merger.run()
model = MultipleRegressDesign()
model.inputs.contrasts = [['mean', 'T', ['roi'], [1]]]
model.intputs.regressors = dict(roi=np.ones(len(copes)))
flameo = pe.Node(interface=FLAMEO(), name='flameo')
flameo.inputs.cope_file = op.join(work_dir, 'cope.nii.gz')
flameo.inputs.var_cope_file = op.join(work_dir, 'varcope.nii.gz')
flameo.inputs.run_mode = 'flame1'
flameo.inputs.mask = standard_image('MNI152_T1_2mm_brain_mask.nii.gz')
