Make project a Workflow attribute.

qipipe/__init__.py

@@ -6,5 +6,3 @@
 `Fast and Loose Versioning <https://gist.github.com/FredLoney/6d946112e0b0f2fc4b57>`_
 scheme. Minor and patch version numbers begin at 1.
 """
-
-from helpers.project import project

qipipe/pipeline/mask.py

@@ -3,7 +3,6 @@
 from nipype.pipeline import engine as pe
 from nipype.interfaces.utility import (IdentityInterface, Function)
 from nipype.interfaces import fsl
-from .. import project
 from ..interfaces import (XNATUpload, MriVolCluster)
 from .workflow_base import WorkflowBase
 from qiutil.logging import logger
@@ -15,19 +14,22 @@
 """The XNAT scan time series resource name."""
 
 
-def run(subject, session, scan, time_series, **opts):
+def run(project, subject, session, scan, time_series, **opts):
     """
     Creates a :class:`qipipe.pipeline.mask.MaskWorkflow` and runs it
     on the given inputs.
     
+    :param project: the project name
     :param subject: the input subject
     :param session: the input session
     :param scan: the input scan number
     :param time_series: the input 4D NiFTI time series to mask
     :param opts: additional :class:`MaskWorkflow` initialization parameters
     :return: the XNAT mask resource name
     """
-    return MaskWorkflow(**opts).run(subject, session, scan, time_series)
+    wf_gen = MaskWorkflow(project, **opts)
+
+    return wf_gen.run(subject, session, scan, time_series)
 
 
 class MaskWorkflow(WorkflowBase):
@@ -62,17 +64,20 @@ class MaskWorkflow(WorkflowBase):
         interface options
     """
 
-    def __init__(self, cfg_file=None, base_dir=None):
+    def __init__(self, project, **opts):
         """
         If the optional configuration file is specified, then the workflow
         settings in that file override the default settings.
         
+        :param project: the XNAT project name
+        :param opts: the :class:`qipipe.pipeline.workflow_base.WorkflowBase`
+            initializer options, as well as the following options:
         :keyword base_dir: the workflow execution directory
             (default is a new temp directory)
-        :keyword cfg_file: the optional workflow inputs configuration file
         """
-        super(MaskWorkflow, self).__init__(logger(__name__), cfg_file)
+        super(MaskWorkflow, self).__init__(project, logger(__name__), **opts)
 
+        base_dir = opts.get('base_dir')
         self.workflow = self._create_workflow(base_dir)
         """The mask creation workflow."""
 
@@ -167,7 +172,7 @@ def _create_workflow(self, base_dir=None):
         workflow.connect(mask_name, 'out_file', inv_mask, 'out_file')
 
         # Upload the mask to XNAT.
-        upload_mask_xfc = XNATUpload(project=project(), resource=RESOURCE,
+        upload_mask_xfc = XNATUpload(project=self.project, resource=RESOURCE,
                                      modality='MR')
         upload_mask = pe.Node(upload_mask_xfc, name='upload_mask')
         workflow.connect(input_spec, 'subject', upload_mask, 'subject')

qipipe/pipeline/modeling.py

@@ -6,7 +6,6 @@
 from nipype.interfaces.utility import (IdentityInterface, Function, Merge)
 import qiutil
 from qiutil.logging import logger
-from .. import project
 from ..interfaces import XNATUpload
 from ..helpers.bolus_arrival import bolus_arrival_index, BolusArrivalError
 from .workflow_base import WorkflowBase
@@ -16,11 +15,12 @@
 """The XNAT modeling resource object label prefix."""
 
 
-def run(subject, session, scan, time_series, **opts):
+def run(project, subject, session, scan, time_series, **opts):
     """
     Creates a :class:`qipipe.pipeline.modeling.ModelingWorkflow` and
     runs it on the given inputs.
 
+    :param project: the project name
     :param subject: the input subject
     :param session: the input session
     :param scan: input scan
@@ -31,7 +31,7 @@ def run(subject, session, scan, time_series, **opts):
         result
     """
     mask = opts.pop('mask', None)
-    wf = ModelingWorkflow(**opts)
+    wf = ModelingWorkflow(project, **opts)
 
     return wf.run(subject, session, scan, time_series, mask=mask)
 
@@ -124,7 +124,7 @@ class ModelingWorkflow(WorkflowBase):
     .. _AIRC DCE: https://everett.ohsu.edu/hg/qin_dce
     """
 
-    def __init__(self, **opts):
+    def __init__(self, project, **opts):
         """
         The modeling parameters can be defined in either the options or the
         configuration as follows:
@@ -147,8 +147,9 @@ def __init__(self, **opts):
         - The *baseline_end_idx* defaults to 1 if it is not set in
           either the input options or the configuration.
 
-        :param opts: the following initialization options:
-        :keyword cfg_file: the optional workflow inputs configuration file
+        :param project: the XNAT project name
+        :param opts: the :class:`qipipe.pipeline.workflow_base.WorkflowBase`
+            initializer options, as well as the following options:
         :keyword base_dir: the workflow execution directory
             (default a new temp directory)
         :keyword r1_0_val: the optional fixed |R10| value
@@ -159,8 +160,7 @@ def __init__(self, **opts):
         :keyword baseline_end_idx: the number of volumes to merge into a R1
             series baseline image (default is 1)
         """
-        cfg_file = opts.pop('cfg_file', None)
-        super(ModelingWorkflow, self).__init__(logger(__name__), cfg_file)
+        super(ModelingWorkflow, self).__init__(project, logger(__name__), **opts)
 
         resource = opts.pop('modeling', None)
         if not resource:
@@ -237,7 +237,7 @@ def _generate_resource_name(self):
         """
         return '_'.join((PK_PREFIX, qiutil.file.generate_file_name()))
 
-    def _create_workflow(self, base_dir=None, **opts):
+    def _create_workflow(self, **opts):
         """
         Builds the modeling workflow.
 
@@ -249,12 +249,11 @@ def _create_workflow(self, base_dir=None, **opts):
         self._logger.debug("Building the modeling workflow...")
 
         # The base workflow.
-        if not base_dir:
-            base_dir = tempfile.mkdtemp()
+        base_dir = opts.pop('base_dir', tempfile.mkdtemp())
         mdl_wf = pe.Workflow(name='modeling', base_dir=base_dir)
 
         # Start with a base workflow.
-        base_wf = self._create_base_workflow(base_dir=base_dir, **opts)
+        base_wf = self._create_base_workflow(base_dir, **opts)
 
         # The workflow input fields.
         in_fields = ['subject', 'session', 'scan', 'time_series', 'mask',
@@ -280,7 +279,7 @@ def _create_workflow(self, base_dir=None, **opts):
         for i, field in enumerate(out_fields):
             base_field = 'output_spec.' + field
             mdl_wf.connect(base_wf, base_field, merge_outputs, "in%d" % (i + 1))
-        upload_xfc = XNATUpload(project=project(), resource=self.resource)
+        upload_xfc = XNATUpload(project=self.project, resource=self.resource)
         upload_node = pe.Node(upload_xfc, name='upload_outputs')
         mdl_wf.connect(input_spec, 'subject', upload_node, 'subject')
         mdl_wf.connect(input_spec, 'session', upload_node, 'session')
@@ -307,7 +306,7 @@ def _create_workflow(self, base_dir=None, **opts):
 
         return mdl_wf
 
-    def _create_base_workflow(self, base_dir=None, **opts):
+    def _create_base_workflow(self, base_dir, **opts):
         """
         Creates the modeling base workflow. This workflow performs the steps
         described in :class:`qipipe.pipeline.modeling.ModelingWorkflow` with