fix: udpated indexing to ensure edge cases are considered

CHANGES

@@ -1,6 +1,7 @@
 Next release
 ============
 
+* FIX: Edge case with sparsemodels and PEP8 cleanup (https://github.com/nipy/nipype/pull/1046)
 * ENH: New io interfaces for JSON files reading/writing (https://github.com/nipy/nipype/pull/1020)
 * ENH: Enhanced openfmri script to support freesurfer linkage (https://github.com/nipy/nipype/pull/1037)
 * BUG: matplotlib is supposed to be optional (https://github.com/nipy/nipype/pull/1003)

examples/fmri_ants_openfmri.py

@@ -218,7 +218,7 @@ 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': '-pe orte 4', 
+    reg.plugin_args = {'qsub_args': '-pe orte 4',
                        'sbatch_args': '--mem=6G -c 4'}
     register.connect(stripper, 'out_file', reg, 'moving_image')
     register.connect(inputnode,'target_image_brain', reg,'fixed_image')
@@ -428,7 +428,7 @@ def create_fs_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': '-pe orte 4', 
+    reg.plugin_args = {'qsub_args': '-pe orte 4',
                        'sbatch_args': '--mem=6G -c 4'}
     register.connect(stripper, 'out_file', reg, 'moving_image')
     register.connect(inputnode,'target_image', reg,'fixed_image')
@@ -562,17 +562,17 @@ def get_subjectinfo(subject_id, base_dir, task_id, model_id):
                                          'task%03d_run*' % (idx + 1))))
         runs = [int(val[-3:]) for val in files]
         run_ids.insert(idx, runs)
-    json_info = os.path.join(base_dir, subject_id, 'BOLD', 
-                                 'task%03d_run%03d' % (task_id, run_ids[task_id - 1][0]), 
+    json_info = os.path.join(base_dir, subject_id, 'BOLD',
+                                 'task%03d_run%03d' % (task_id, run_ids[task_id - 1][0]),
                                  'bold_scaninfo.json')
     if os.path.exists(json_info):
         import json
         with open(json_info, 'rt') as fp:
             data = json.load(fp)
             TR = data['global']['const']['RepetitionTime']/1000.
     else:
-        task_scan_key = os.path.join(base_dir, subject_id, 'BOLD', 
-                                 'task%03d_run%03d' % (task_id, run_ids[task_id - 1][0]), 
+        task_scan_key = os.path.join(base_dir, subject_id, 'BOLD',
+                                 'task%03d_run%03d' % (task_id, run_ids[task_id - 1][0]),
                                  'scan_key.txt')
         if os.path.exists(task_scan_key):
             TR = np.genfromtxt(task_scan_key)[1]
@@ -667,7 +667,7 @@ def analyze_openfmri_dataset(data_dir, subject=None, model_id=None,
                          name='datasource')
     datasource.inputs.base_directory = data_dir
     datasource.inputs.template = '*'
-    
+
     if has_contrast:
         datasource.inputs.field_template = {'anat': '%s/anatomy/T1_001.nii.gz',
                                             'bold': '%s/BOLD/task%03d_r*/bold.nii.gz',
@@ -909,18 +909,18 @@ def split_files(in_files, splits):
                splitfunc, 'in_files')
 
     if subjects_dir:
-        get_roi_mean = pe.MapNode(fs.SegStats(default_color_table=True), 
+        get_roi_mean = pe.MapNode(fs.SegStats(default_color_table=True),
                                   iterfield=['in_file'], name='get_aparc_means')
         get_roi_mean.inputs.avgwf_txt_file = True
         wf.connect(fixed_fx.get_node('outputspec'), 'copes', get_roi_mean, 'in_file')
         wf.connect(registration, 'outputspec.aparc', get_roi_mean, 'segmentation_file')
-        
-        get_roi_tsnr = pe.MapNode(fs.SegStats(default_color_table=True), 
+
+        get_roi_tsnr = pe.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')
-        
+
     """
     Connect to a datasink
     """

nipype/pipeline/plugins/tests/test_callback.py

@@ -72,7 +72,8 @@ def test_callback_multiproc_normal():
                                   output_names=[]),
                      name='f_node')
     wf.add_nodes([f_node])
-    wf.config['execution'] = {'crashdump_dir': wf.base_dir}
+    wf.config['execution']['crashdump_dir'] = wf.base_dir
+    wf.config['execution']['poll_sleep_duration'] = 2
     wf.run(plugin='MultiProc', plugin_args={'status_callback': so.callback})
     assert_equal(len(so.statuses), 2)
     for (n, s) in so.statuses:
@@ -89,7 +90,8 @@ def test_callback_multiproc_exception():
                                   output_names=[]),
                      name='f_node')
     wf.add_nodes([f_node])
-    wf.config['execution'] = {'crashdump_dir': wf.base_dir}
+    wf.config['execution']['crashdump_dir'] = wf.base_dir
+    wf.config['execution']['poll_sleep_duration'] = 2
     try:
         wf.run(plugin='MultiProc',
                plugin_args={'status_callback': so.callback})

nipype/pipeline/plugins/tests/test_multiproc.py

@@ -39,6 +39,7 @@ def test_run_multiproc():
     pipe.connect([(mod1,mod2,[('output1','input1')])])
     pipe.base_dir = os.getcwd()
     mod1.inputs.input1 = 1
+    pipe.config['execution']['poll_sleep_duration'] = 2
     execgraph = pipe.run(plugin="MultiProc")
     names = ['.'.join((node._hierarchy,node.name)) for node in execgraph.nodes()]
     node = execgraph.nodes()[names.index('pipe.mod1')]

nipype/pipeline/plugins/tests/test_multiproc_nondaemon.py

@@ -106,7 +106,9 @@ def run_multiproc_nondaemon_with_flag(nondaemon_flag):
     pipe.base_dir = os.getcwd()
     f1.inputs.insum = 0
 
-    pipe.config = {'execution': {'stop_on_first_crash': True}}
+    pipe.config['execution']['stop_on_first_crash'] = True
+    pipe.config['execution']['poll_sleep_duration'] = 2
+
     # execute the pipe using the MultiProc plugin with 2 processes and the non_daemon flag
     # to enable child processes which start other multiprocessing jobs
     execgraph = pipe.run(plugin="MultiProc",

nipype/pipeline/tests/test_engine.py

@@ -660,7 +660,8 @@ def func1(in1):
     # set local check
     w1.config['execution'] = {'stop_on_first_crash': 'true',
                               'local_hash_check': 'true',
-                              'crashdump_dir': wd}
+                              'crashdump_dir': wd,
+                              'poll_sleep_duration': 2}
 
     # test output of num_subnodes method when serial is default (False)
     yield assert_equal, n1.num_subnodes(), len(n1.inputs.in1)