Nipype already places child workflows in subdirectories.

qipipe/pipeline/modeling.py

@@ -455,8 +455,7 @@ def _create_airc_workflow(self, **opts):
         :param opts: the PK modeling parameters
         :return: the Nipype Workflow
         """
-        base_dir = "%s/%s" % (self.base_dir, 'airc')
-        workflow = pe.Workflow(name='airc', base_dir=base_dir)
+        workflow = pe.Workflow(name='airc', base_dir=self.base_dir)
 
         # The modeling profile configuration sections.
         self.profile_sections = OHSU_CONF_SECTIONS
@@ -635,8 +634,7 @@ def _create_mock_workflow(self, **opts):
         :param opts: the PK modeling parameters
         :return: the Nipype Workflow
         """
-        base_dir = "%s/%s" % (self.base_dir, 'mock')
-        workflow = pe.Workflow(name='mock', base_dir=base_dir)
+        workflow = pe.Workflow(name='mock', base_dir=self.base_dir)
 
         # The modeling profile configuration sections.
         self.profile_sections = []

qipipe/pipeline/qipipeline.py

@@ -638,7 +638,7 @@ def _create_workflow(self, subject, session, scan, actions, **opts):
                                output_names=['results'],
                                function=model)
             mdl_node = pe.Node(mdl_xfc, name='model')
-            mdl_opts = self._child_options(name='model')
+            mdl_opts = self._child_options()
             mdl_opts['technique'] = self.modeling_technique
             mdl_node.inputs.opts = mdl_opts
             self.logger.info("Enabled modeling with options %s." % mdl_opts)
@@ -659,7 +659,7 @@ def _create_workflow(self, subject, session, scan, actions, **opts):
             # than delegating to this qipipeline workflow as the
             # parent, since Nipype Function arguments must be
             # primitive.
-            reg_opts = self._child_options(name='registration')
+            reg_opts = self._child_options()
             reg_opts['resource'] = self.registration_resource
             reg_opts['technique'] = self.registration_technique
             if 'recursive_registration' in opts:
@@ -693,7 +693,7 @@ def _create_workflow(self, subject, session, scan, actions, **opts):
                                output_names=['volume'],
                                function=roi)
             roi_node = pe.Node(roi_xfc, name='roi')
-            roi_opts = self._child_options(name='roi')
+            roi_opts = self._child_options()
             roi_node.inputs.opts = roi_opts
             self.logger.info("Enabled ROI conversion with options %s." %
                              roi_opts)
@@ -716,7 +716,7 @@ def _create_workflow(self, subject, session, scan, actions, **opts):
             #     TypeError: cannot deepcopy this pattern object
             # The work-around is to break out the separate simple options
             # that the WorkflowBase constructor extracts from the parent.
-            stg_opts = self._child_options(name='stage')
+            stg_opts = self._child_options()
             if 'dest' in opts:
                 stg_opts['dest'] = opts['dest']
             if not self.collection:
@@ -757,7 +757,7 @@ def _create_workflow(self, subject, session, scan, actions, **opts):
                     raise PipelineError("The mask workflow requires the"
                                         " collection option")
                 crop_posterior = self.collection.crop_posterior
-                mask_opts = self._child_options(name='mask')
+                mask_opts = self._child_options()
                 mask_opts['crop_posterior'] = crop_posterior
                 mask_inputs = ['subject', 'session', 'scan', 'time_series',
                                'opts']

qipipe/pipeline/registration.py

@@ -393,8 +393,7 @@ def _create_realignment_workflow(self, **opts):
         self.logger.debug('Creating the registration realignment workflow...')
 
         # The workflow.
-        base_dir = "%s/%s" % (self.base_dir, self.technique)
-        realign_wf = pe.Workflow(name=self.technique, base_dir=base_dir)
+        realign_wf = pe.Workflow(name=self.technique, base_dir=self.base_dir)
 
         # The workflow input.
         in_fields = ['subject', 'session', 'scan', 'in_file',

qipipe/pipeline/staging.py

@@ -384,8 +384,7 @@ def _create_workflow(self):
         self.logger.debug('Creating the DICOM processing workflow...')
 
         # The Nipype workflow object.
-        base_dir = "%s/%s" % (self.base_dir, 'stage_volume')
-        workflow = pe.Workflow(name='stage_volume', base_dir=base_dir)
+        workflow = pe.Workflow(name='stage_volume', base_dir=self.base_dir)
 
         # The workflow input.
         in_fields = ['collection', 'subject', 'session', 'scan',

qipipe/pipeline/workflow_base.py

@@ -178,18 +178,20 @@ def depict_workflow(self, workflow):
         self.logger.debug("The %s workflow graph is depicted at %s.png." %
                          (workflow.name, base_name))
 
-    def _child_options(self, name=None):
+    def _child_options(self):
         """
         Collects the following options for creating a child workflow:
         * project
         * config_dir
+        * base_dir
         * dry_run
         * distributable
 
         :return: the options sufficient to create a child workflow
         """
         return dict(
             project=self.project,
+            base_dir=self.base_dir,
             config_dir=self.config_dir,
             dry_run=self.dry_run,
             distributable=self.is_distributable

test/unit/pipeline/test_qipipeline.py

@@ -20,22 +20,22 @@
 class TestQIPipeline(object):
     """
     Pipeline unit tests.
-    
+
     Note:: a precondition for running this test is that the environment
         variable ``QIPIPE_DATA`` is set to the DICOM source directory.
         If ``QIPIPE_DATA`` is not set, then no test cases are run and a
         log message is issued.
-    
+
     Note:: this test takes app. four hours to run serially without
     modeling.
     """
-    
+
     def setUp(self):
         shutil.rmtree(RESULTS, True)
-    
+
     def tearDown(self):
         shutil.rmtree(RESULTS, True)
-    
+
     def test_breast(self):
         data = os.getenv('QIPIPE_DATA')
         if data:
@@ -57,7 +57,7 @@ def test_breast(self):
             logger(__name__).info('Skipping the pipeline unit Breast'
                                   ' test, since the QIPIPE_DATA environment'
                                   ' variable is not set.')
-    
+
     def test_sarcoma(self):
         data = os.getenv('QIPIPE_DATA')
         if data:
@@ -78,24 +78,23 @@ def test_sarcoma(self):
             logger(__name__).info('Skipping the pipeline unit Sarcoma'
                                   ' test, since the QIPIPE_DATA environment'
                                   ' variable is not set.')
-    
+
     def _test_collection(self, collection, fixture):
         """
         Run the pipeline on the given collection and verify that scans are
         created in XNAT.
-        
+
         :param collection: the image collection name
         :param fixture: the test input directory holding a link to the
             first visit data
         """
         logger(__name__).debug("Testing the pipeline on %s..." % fixture)
-        
+
         # The staging destination and work area.
         dest = os.path.join(RESULTS, 'data')
-        base_dir = os.path.join(RESULTS, 'work')
-
+
         # The pipeline options.
-        opts = dict(base_dir=base_dir, config_dir=CONF_DIR, dest=dest,
+        opts = dict(base_dir=RESULTS, config_dir=CONF_DIR, dest=dest,
                     project=PROJECT, collection=collection,
                     registration_technique='mock',
                     modeling_technique='mock')
@@ -106,7 +105,7 @@ def _test_collection(self, collection, fixture):
         subjects = sbj_dir_dict.keys()
         # The test subject input directories.
         sources = sbj_dir_dict.values()
-        
+
         with qixnat.connect() as xnat:
             # Delete any existing test subjects.
             for sbj in subjects:
@@ -142,13 +141,13 @@ def _test_collection(self, collection, fixture):
                         assert_true(mdl_obj.exists(),
                                     "The %s %s modeling resource %s was not"
                                     " created in XNAT" % (sbj, sess, rsc))
-            
+
             # Delete the test subjects.
             for sbj in subjects:
                 xnat.delete(PROJECT, sbj)
 
 
 if __name__ == "__main__":
     import nose
-    
+
     nose.main(defaultTest=__name__)