Merge pull request #50 from CoBrALab/updates

Added memory specification for running in multiproc.

Author: Gab-D-G

rabies/preprocess_bold_pkg/hmc.py

@@ -38,7 +38,7 @@ def init_bold_hmc_wf(name='bold_hmc_wf'):
         name='outputnode')
 
     # Head motion correction (hmc)
-    motion_estimation = pe.Node(EstimateMotion(), name='ants_MC')
+    motion_estimation = pe.Node(EstimateMotion(), name='ants_MC', mem_gb=3)
     motion_estimation.plugin_args = {'qsub_args': '-pe smp 4', 'overwrite': True}
 
 

rabies/preprocess_bold_pkg/registration.py

@@ -57,7 +57,7 @@ def init_bold_reg_wf(coreg_script='SyN', name='bold_reg_wf'):
     run_reg = pe.Node(Function(input_names=["reg_script", "moving_image", "fixed_image",
                                             "anat_mask"],
                    output_names=['affine_bold2anat', 'warp_bold2anat', 'inverse_warp_bold2anat', 'output_warped_bold'],
-                   function=run_antsRegistration), name='EPI_Coregistration')
+                   function=run_antsRegistration), name='EPI_Coregistration', mem_gb=3)
     run_reg.inputs.reg_script=coreg_script
     run_reg.plugin_args = {'qsub_args': '-pe smp 4', 'overwrite': True}
 

rabies/preprocess_bold_pkg/resampling.py

@@ -21,12 +21,12 @@ def init_bold_preproc_trans_wf(resampling_dim, name='bold_preproc_trans_wf'):
         name='outputnode')
 
 
-    bold_transform = pe.Node(slice_applyTransforms(), name='bold_transform')
+    bold_transform = pe.Node(slice_applyTransforms(), name='bold_transform', mem_gb=3)
     bold_transform.inputs.apply_motcorr = True
     bold_transform.inputs.resampling_dim = resampling_dim
     bold_transform.inputs.data_type = os.environ["rabies_data_type"]
 
-    merge = pe.Node(Merge(), name='merge')
+    merge = pe.Node(Merge(), name='merge', mem_gb=3)
     merge.inputs.data_type = os.environ["rabies_data_type"]
     #merge.plugin_args = {'qsub_args': '-pe smp 2 -l h_vmem=1G ', 'overwrite': True}
 
@@ -66,13 +66,13 @@ def init_bold_commonspace_trans_wf(resampling_dim, name='bold_commonspace_trans_
         niu.IdentityInterface(fields=['bold', 'bold_ref', 'brain_mask', 'WM_mask', 'CSF_mask', 'labels']),
         name='outputnode')
 
-    bold_transform = pe.Node(slice_applyTransforms(), name='bold_transform')
+    bold_transform = pe.Node(slice_applyTransforms(), name='bold_transform', mem_gb=3)
     bold_transform.inputs.apply_motcorr = True
     bold_transform.inputs.ref_file = os.environ["template_anat"]
     bold_transform.inputs.resampling_dim = resampling_dim
     bold_transform.inputs.data_type = os.environ["rabies_data_type"]
 
-    merge = pe.Node(Merge(), name='merge')
+    merge = pe.Node(Merge(), name='merge', mem_gb=3)
     merge.inputs.data_type = os.environ["rabies_data_type"]
 
     # Generate a new BOLD reference