fix: remove pe, clean doc and add sbatch args

Author: satra

examples/rsfmri_vol_surface_preprocessing_nipy.py

@@ -506,7 +506,7 @@ def create_reg_workflow(name='registration'):
     reg.inputs.args = '--float'
     reg.inputs.output_warped_image = 'output_warped_image.nii.gz'
     reg.inputs.num_threads = 4
-    reg.plugin_args = {'qsub_args': '-l nodes=1:ppn=4'}
+    reg.plugin_args = {'sbatch_args': '-c%d' % 4}
     register.connect(stripper, 'out_file', reg, 'moving_image')
     register.connect(inputnode,'target_image', reg,'fixed_image')
 
@@ -532,6 +532,7 @@ def create_reg_workflow(name='registration'):
     warpmean.inputs.terminal_output = 'file'
     warpmean.inputs.args = '--float'
     warpmean.inputs.num_threads = 4
+    warpmean.plugin_args = {'sbatch_args': '-c%d' % 4}
 
     register.connect(inputnode,'target_image', warpmean,'reference_image')
     register.connect(inputnode, 'mean_image', warpmean, 'input_image')
@@ -596,6 +597,7 @@ def create_workflow(files,
     realign.inputs.slice_times = slice_times
     realign.inputs.tr = TR
     realign.inputs.slice_info = 2
+    realign.plugin_args = {'sbatch_args': '-c%d' % 4}
 
 
     # Comute TSNR on realigned data regressing polynomials upto order 2
@@ -620,8 +622,8 @@ def create_workflow(files,
 
     """Quantify TSNR in each freesurfer ROI
     """
-    get_roi_tsnr = pe.MapNode(fs.SegStats(default_color_table=True),
-                              iterfield=['in_file'], name='get_aparc_tsnr')
+    get_roi_tsnr = MapNode(fs.SegStats(default_color_table=True),
+                           iterfield=['in_file'], name='get_aparc_tsnr')
     get_roi_tsnr.inputs.avgwf_txt_file = True
     wf.connect(tsnr, 'tsnr_file', get_roi_tsnr, 'in_file')
     wf.connect(registration, 'outputspec.aparc', get_roi_tsnr, 'segmentation_file')
@@ -764,7 +766,8 @@ def merge_files(in1, in2):
     warpall.inputs.terminal_output = 'file'
     warpall.inputs.reference_image = target_file
     warpall.inputs.args = '--float'
-    warpall.inputs.num_threads = 1
+    warpall.inputs.num_threads = 2
+    warpall.plugin_args = {'sbatch_args': '-c%d' % 2}
 
     # transform to target
     wf.connect(collector, 'out', warpall, 'input_image')
@@ -884,13 +887,14 @@ def get_names(files, suffix):
     substitutions += [("_filtermotion%d" % i,"") for i in range(11)[::-1]]
     substitutions += [("_filter_noise_nosmooth%d" % i,"") for i in range(11)[::-1]]
     substitutions += [("_makecompcorfilter%d" % i,"") for i in range(11)[::-1]]
+    substitutions += [("_get_aparc_tsnr%d/" % i, "run%d_" % (i + 1)) for i in range(11)[::-1]]
 
-    substitutions += [("T1_out_brain_pve_0_maths_warped","compcor_csf"),
-                      ("T1_out_brain_pve_1_maths_warped","compcor_gm"),
+    substitutions += [("T1_out_brain_pve_0_maths_warped", "compcor_csf"),
+                      ("T1_out_brain_pve_1_maths_warped", "compcor_gm"),
                       ("T1_out_brain_pve_2_maths_warped", "compcor_wm"),
-                      ("output_warped_image_maths","target_brain_mask"),
-                      ("median_brain_mask","native_brain_mask"),
-                      ("corr_","")]
+                      ("output_warped_image_maths", "target_brain_mask"),
+                      ("median_brain_mask", "native_brain_mask"),
+                      ("corr_", "")]
 
     regex_subs = [('_combiner.*/sar', '/smooth/'),
                   ('_combiner.*/ar', '/unsmooth/'),
@@ -921,6 +925,7 @@ def get_names(files, suffix):
     wf.connect(filter2, 'out_f', datasink, 'resting.qa.compmaps')
     wf.connect(filter2, 'out_pf', datasink, 'resting.qa.compmaps.@p')
     wf.connect(registration, 'outputspec.min_cost_file', datasink, 'resting.qa.mincost')
+    wf.connect(tsnr, 'tsnr_file', datasink, 'resting.qa.tsnr.@map')
     wf.connect([(get_roi_tsnr, datasink, [('avgwf_txt_file', 'resting.qa.tsnr'),
                                           ('summary_file', 'resting.qa.tsnr.@summary')])])