Merge branch 'master' into enh/slurmgraph

Author: chrisgorgo

CHANGES

@@ -13,6 +13,7 @@ Next release
 * FIX: FUGUE is now properly listing outputs. (https://github.com/nipy/nipype/pull/978)
 * ENH: Improved FieldMap-Based (FMB) workflow for correction of susceptibility distortions in EPI seqs.
        (https://github.com/nipy/nipype/pull/1019)
+* FIX: In the FSLXcommand _list_outputs function fixed for loop range (https://github.com/nipy/nipype/pull/1071)
 * ENH: Dropped support for now 7 years old Python 2.6 (https://github.com/nipy/nipype/pull/1069)
 * FIX: terminal_output is not mandatory anymore (https://github.com/nipy/nipype/pull/1070)
 * ENH: Added "nipype_cmd" tool for running interfaces from the command line (https://github.com/nipy/nipype/pull/795)
@@ -59,6 +60,8 @@ Next release
 * ENH: Added -newgrid input to Warp in AFNI (3dWarp wrapper) (https://github.com/nipy/nipype/pull/1128)
 * FIX: Fixed AFNI Copy interface to use positional inputs as required (https://github.com/nipy/nipype/pull/1131)
 * ENH: Added a check in Dcm2nii to check if nipype created the config.ini file and remove if true (https://github.com/nipy/nipype/pull/1132)
+* ENH: Use a while loop to wait for Xvfb (up to a max wait time "xvfb_max_wait" in config file, default 10)
+       (https://github.com/nipy/nipype/pull/1142)
 
 Release 0.10.0 (October 10, 2014)
 ============

README.rst

@@ -77,10 +77,10 @@ to `NeuroStars.org <http://neurostars.org>`_ with a *nipype* tag. `NeuroStars.or
        http://neurostars.org/t/nipype/
 	   
 
-To participate in the Nipype development related discussion please use the following mailing list::
+To participate in the Nipype development related discussions please use the following mailing list::
        
-       http://projects.scipy.org/mailman/listinfo/nipy-devel
-	   
+       http://mail.python.org/mailman/listinfo/neuroimaging
+
 Please add *[nipype]* to the subject line when posting on the mailing list.
 
 
@@ -124,5 +124,5 @@ There are interfaces to some GNU code but these are entirely optional.
 All trademarks referenced herein are property of their respective
 holders.
 
-Copyright (c) 2009-2014, NIPY Developers
+Copyright (c) 2009-2015, NIPY Developers
 All rights reserved.

doc/users/config_file.rst

@@ -125,6 +125,9 @@ Execution
     all pending jobs and checking for job completion. To be nice to cluster
     schedulers the default is set to 60 seconds.
 
+*xvfb_max_wait*
+    Maximum time (in seconds) to wait for Xvfb to start, if the _redirect_x parameter of an Interface is True.
+
 Example
 ~~~~~~~
 

examples/fmri_ants_openfmri.py

@@ -124,6 +124,7 @@ def create_reg_workflow(name='registration'):
                                                                  'transformed_files',
                                                                  'transformed_mean',
                                                                  'anat2target',
+                                                                 'mean2anat_mask'
                                                                  ]),
                          name='outputspec')
 
@@ -171,6 +172,13 @@ def create_reg_workflow(name='registration'):
     register.connect(mean2anat, 'out_matrix_file',
                      mean2anatbbr, 'in_matrix_file')
 
+    """
+    Create a mask of the median image coregistered to the anatomical image
+    """
+
+    mean2anat_mask = Node(fsl.BET(mask=True), name='mean2anat_mask')
+    register.connect(mean2anatbbr, 'out_file', mean2anat_mask, 'in_file')
+
     """
     Convert the BBRegister transformation to ANTS ITK format
     """
@@ -276,6 +284,8 @@ def create_reg_workflow(name='registration'):
     register.connect(warpall, 'output_image', outputnode, 'transformed_files')
     register.connect(mean2anatbbr, 'out_matrix_file',
                      outputnode, 'func2anat_transform')
+    register.connect(mean2anat_mask, 'mask_file',
+                     outputnode, 'mean2anat_mask')
     register.connect(reg, 'composite_transform',
                      outputnode, 'anat2target_transform')
 
@@ -333,7 +343,8 @@ def create_fs_reg_workflow(name='registration'):
                                                           'transformed_files',
                                                           'min_cost_file',
                                                           'anat2target',
-                                                          'aparc'
+                                                          'aparc',
+                                                          'mean2anat_mask'
                                                           ]),
                       name='outputspec')
 
@@ -349,7 +360,7 @@ def create_fs_reg_workflow(name='registration'):
     register.connect(fssource, 'T1', convert, 'in_file')
 
     # Coregister the median to the surface
-    bbregister = Node(freesurfer.BBRegister(),
+    bbregister = Node(freesurfer.BBRegister(registered_file=True),
                     name='bbregister')
     bbregister.inputs.init = 'fsl'
     bbregister.inputs.contrast_type = 't2'
@@ -359,6 +370,10 @@ def create_fs_reg_workflow(name='registration'):
     register.connect(inputnode, 'mean_image', bbregister, 'source_file')
     register.connect(inputnode, 'subjects_dir', bbregister, 'subjects_dir')
 
+    # Create a mask of the median coregistered to the anatomical image
+    mean2anat_mask = Node(fsl.BET(mask=True), name='mean2anat_mask')
+    register.connect(bbregister, 'registered_file', mean2anat_mask, 'in_file')
+
     """
     use aparc+aseg's brain mask
     """
@@ -500,6 +515,8 @@ def create_fs_reg_workflow(name='registration'):
                      outputnode, 'out_reg_file')
     register.connect(bbregister, 'min_cost_file',
                      outputnode, 'min_cost_file')
+    register.connect(mean2anat_mask, 'mask_file',
+                     outputnode, 'mean2anat_mask')
     register.connect(reg, 'composite_transform',
                      outputnode, 'anat2target_transform')
     register.connect(merge, 'out', outputnode, 'transforms')
@@ -964,6 +981,8 @@ def get_subs(subject_id, conds, run_id, model_id, task_id):
         subs.append(('/model%03d/task%03d_' % (model_id, task_id), '/'))
         subs.append(('_bold_dtype_mcf_bet_thresh_dil', '_mask'))
         subs.append(('_output_warped_image', '_anat2target'))
+        subs.append(('median_flirt_brain_mask', 'median_brain_mask'))
+        subs.append(('median_bbreg_brain_mask', 'median_brain_mask'))
         return subs
 
     subsgen = pe.Node(niu.Function(input_names=['subject_id', 'conds', 'run_id',
@@ -998,6 +1017,7 @@ def get_subs(subject_id, conds, run_id, model_id, task_id):
                                      ('outputspec.motion_plots',
                                       'qa.motion.plots'),
                                      ('outputspec.mask', 'qa.mask')])])
+    wf.connect(registration, 'outputspec.mean2anat_mask', datasink, 'qa.mask.mean2anat')
     wf.connect(art, 'norm_files', datasink, 'qa.art.@norm')
     wf.connect(art, 'intensity_files', datasink, 'qa.art.@intensity')
     wf.connect(art, 'outlier_files', datasink, 'qa.art.@outlier_files')

matlabscripts/README.txt

@@ -994,9 +994,13 @@ def run(self, **inputs):
                     xvfb_proc = subprocess.Popen(xvfb_cmd,
                                                  stdout=open(os.devnull),
                                                  stderr=open(os.devnull))
-                    time.sleep(0.2)  # give Xvfb time to start
-                    if xvfb_proc.poll() is not None:
-                        raise Exception('Error: Xvfb did not start')
+                    wait_step = 0.2
+                    wait_time = 0
+                    while xvfb_proc.poll() is not None:
+                        if wait_time > config.get('execution', 'xvfb_max_wait'):
+                            raise Exception('Error: Xvfb did not start')
+                        time.sleep(wait_step)  # give Xvfb time to start
+                        wait_time += wait_step
 
                     runtime.environ['DISPLAY'] = ':%s' % vdisplay_num
 

matlabscripts/parse_spm_config.m

@@ -32,7 +32,7 @@
 def tensor_fitting(data, bvals, bvecs, mask_file=None):
     """
     Use dipy to fit DTI
-    
+
     Parameters
     ----------
     in_file : str
@@ -58,7 +58,7 @@ def tensor_fitting(data, bvals, bvecs, mask_file=None):
 
     # Load information about the gradients:
     gtab = grad.gradient_table(self.inputs.bvals, self.inputs.bvecs)
-        
+
     # Fit it
     tenmodel = dti.TensorModel(gtab)
     return tenmodel.fit(data, mask), affine
@@ -84,7 +84,7 @@ class DTIOutputSpec(TraitedSpec):
 class DTI(BaseInterface):
     """
     Calculates the diffusion tensor model parameters
-    
+
     Example
     -------
 
@@ -99,7 +99,7 @@ class DTI(BaseInterface):
     output_spec = DTIOutputSpec
 
     def _run_interface(self, runtime):
-        ten_fit, affine = tensor_fitting(self.inputs.in_file, 
+        ten_fit, affine = tensor_fitting(self.inputs.in_file,
                                          self.inputs.bvals,
                                          self.inputs.bvecs,
                                          self.inputs.mask_file)
@@ -124,7 +124,7 @@ def _gen_filename(self, name):
     def _gen_outfilename(self):
         _, name, _ = split_filename(self.inputs.in_file)
         return name + '_dti.nii'
-    
+
 
 class TensorModeInputSpec(TraitedSpec):
     in_file = File(exists=True, mandatory=True,

matlabscripts/parse_spm_config2.m

@@ -7,6 +7,10 @@ def test_SimulateMultiTensor_inputs():
     ),
     bvalues=dict(usedefault=True,
     ),
+    diff_iso=dict(usedefault=True,
+    ),
+    diff_sf=dict(usedefault=True,
+    ),
     gradients=dict(),
     ignore_exception=dict(nohash=True,
     usedefault=True,