fix:test & fix bug using aux functions in connect

nipype/interfaces/petpvc.py

@@ -6,81 +6,8 @@
    >>> filepath = os.path.dirname( os.path.realpath( __file__ ) )
    >>> datadir = os.path.realpath(os.path.join(filepath, '../testing/data'))
    >>> os.chdir(datadir)
-
-Nipype interface for PETPVC.
-
-PETPVC is a software from the Nuclear Medicine Department
-of the UCL University Hospital, London, UK.
-
-Its source code is here: https://github.com/UCL/PETPVC
-
-The methods that it implement are explained here:
-K. Erlandsson, I. Buvat, P. H. Pretorius, B. A. Thomas, and B. F. Hutton,
-"A review of partial volume correction techniques for emission tomography
-and their applications in neurology, cardiology and oncology," Phys. Med.
-Biol., vol. 57, no. 21, p. R119, 2012.
-
-There is a publication waiting to be accepted for this software tool.
-
-
-Its command line help shows this:
-
-   -i --input < filename >
-      = PET image file
-   -o --output < filename >
-      = Output file
-   [ -m --mask < filename > ]
-      = Mask image file
-   -p --pvc < keyword >
-      = Desired PVC method
-   -x < X >
-      = The full-width at half maximum in mm along x-axis
-   -y < Y >
-      = The full-width at half maximum in mm along y-axis
-   -z < Z >
-      = The full-width at half maximum in mm along z-axis
-   [ -d --debug ]
-      = Prints debug information
-   [ -n --iter [ Val ] ]
-      = Number of iterations
-        With: Val (Default = 10)
-   [ -k [ Val ] ]
-      = Number of deconvolution iterations
-        With: Val (Default = 10)
-   [ -a --alpha [ aval ] ]
-      = Alpha value
-        With: aval (Default = 1.5)
-   [ -s --stop [ stopval ] ]
-      = Stopping criterion
-        With: stopval (Default = 0.01)
-
-----------------------------------------------
-Technique - keyword
-
-Geometric transfer matrix - "GTM"
-Labbe approach - "LABBE"
-Richardson-Lucy - "RL"
-Van-Cittert - "VC"
-Region-based voxel-wise correction - "RBV"
-RBV with Labbe - "LABBE+RBV"
-RBV with Van-Cittert - "RBV+VC"
-RBV with Richardson-Lucy - "RBV+RL"
-RBV with Labbe and Van-Cittert - "LABBE+RBV+VC"
-RBV with Labbe and Richardson-Lucy- "LABBE+RBV+RL"
-Multi-target correction - "MTC"
-MTC with Labbe - "LABBE+MTC"
-MTC with Van-Cittert - "MTC+VC"
-MTC with Richardson-Lucy - "MTC+RL"
-MTC with Labbe and Van-Cittert - "LABBE+MTC+VC"
-MTC with Labbe and Richardson-Lucy- "LABBE+MTC+RL"
-Iterative Yang - "IY"
-Iterative Yang with Van-Cittert - "IY+VC"
-Iterative Yang with Richardson-Lucy - "IY+RL"
-Muller Gartner - "MG"
-Muller Gartner with Van-Cittert - "MG+VC"
-Muller Gartner with Richardson-Lucy - "MG+RL"
-
 """
+
 from __future__ import print_function
 from __future__ import division
 
@@ -144,6 +71,76 @@ class PETPVCOutputSpec(TraitedSpec):
 class PETPVC(CommandLine):
     """ Use PETPVC for partial volume correction of PET images.
 
+    PETPVC is a software from the Nuclear Medicine Department
+    of the UCL University Hospital, London, UK.
+
+    Its source code is here: https://github.com/UCL/PETPVC
+
+    The methods that it implement are explained here:
+    K. Erlandsson, I. Buvat, P. H. Pretorius, B. A. Thomas, and B. F. Hutton,
+    "A review of partial volume correction techniques for emission tomography
+    and their applications in neurology, cardiology and oncology," Phys. Med.
+    Biol., vol. 57, no. 21, p. R119, 2012.
+
+    There is a publication waiting to be accepted for this software tool.
+
+    Its command line help shows this:
+
+       -i --input < filename >
+          = PET image file
+       -o --output < filename >
+          = Output file
+       [ -m --mask < filename > ]
+          = Mask image file
+       -p --pvc < keyword >
+          = Desired PVC method
+       -x < X >
+          = The full-width at half maximum in mm along x-axis
+       -y < Y >
+          = The full-width at half maximum in mm along y-axis
+       -z < Z >
+          = The full-width at half maximum in mm along z-axis
+       [ -d --debug ]
+          = Prints debug information
+       [ -n --iter [ Val ] ]
+          = Number of iterations
+            With: Val (Default = 10)
+       [ -k [ Val ] ]
+          = Number of deconvolution iterations
+            With: Val (Default = 10)
+       [ -a --alpha [ aval ] ]
+          = Alpha value
+            With: aval (Default = 1.5)
+       [ -s --stop [ stopval ] ]
+          = Stopping criterion
+            With: stopval (Default = 0.01)
+
+    ----------------------------------------------
+    Technique - keyword
+
+    Geometric transfer matrix - "GTM"
+    Labbe approach - "LABBE"
+    Richardson-Lucy - "RL"
+    Van-Cittert - "VC"
+    Region-based voxel-wise correction - "RBV"
+    RBV with Labbe - "LABBE+RBV"
+    RBV with Van-Cittert - "RBV+VC"
+    RBV with Richardson-Lucy - "RBV+RL"
+    RBV with Labbe and Van-Cittert - "LABBE+RBV+VC"
+    RBV with Labbe and Richardson-Lucy- "LABBE+RBV+RL"
+    Multi-target correction - "MTC"
+    MTC with Labbe - "LABBE+MTC"
+    MTC with Van-Cittert - "MTC+VC"
+    MTC with Richardson-Lucy - "MTC+RL"
+    MTC with Labbe and Van-Cittert - "LABBE+MTC+VC"
+    MTC with Labbe and Richardson-Lucy- "LABBE+MTC+RL"
+    Iterative Yang - "IY"
+    Iterative Yang with Van-Cittert - "IY+VC"
+    Iterative Yang with Richardson-Lucy - "IY+RL"
+    Muller Gartner - "MG"
+    Muller Gartner with Van-Cittert - "MG+VC"
+    Muller Gartner with Richardson-Lucy - "MG+RL"
+
     Examples
     --------
     >>> from ..testing import example_data

nipype/interfaces/tests/test_utility.py

@@ -63,7 +63,6 @@ def increment_array(in_array):
     f2 = pe.MapNode(utility.Function(input_names=['in_array'], output_names=['out_array'], function=increment_array), name='increment_array', iterfield=['in_array'])
 
     wf.connect(f1, 'random_array', f2, 'in_array')
-
     wf.run()
 
     # Clean up
@@ -167,3 +166,57 @@ def test_csvReader():
                 yield assert_equal, out.outputs.column_1, ['hello', 'world', 'goodbye']
                 yield assert_equal, out.outputs.column_2, ['300.1', '5', '0.3']
         os.unlink(name)
+
+
+def test_aux_connect_function():
+    """ This tests excution nodes with multiple inputs and auxiliary
+    function inside the Workflow connect function.
+    """
+    tempdir = os.path.realpath(mkdtemp())
+    origdir = os.getcwd()
+    os.chdir(tempdir)
+
+    wf = pe.Workflow(name="test_workflow")
+
+    def _gen_tuple(size):
+        return [1, ] * size
+
+    def _sum_and_sub_mul(a, b, c):
+        return (a+b)*c, (a-b)*c
+
+    def _inc(x):
+        return x + 1
+
+    params = pe.Node(utility.IdentityInterface(fields=['size', 'num']), name='params')
+    params.inputs.num  = 42
+    params.inputs.size = 1
+
+    gen_tuple = pe.Node(utility.Function(input_names=['size'],
+                                         output_names=['tuple'],
+                                         function=_gen_tuple),
+                                         name='gen_tuple')
+
+    ssm = pe.Node(utility.Function(input_names=['a', 'b', 'c'],
+                                   output_names=['sum', 'sub'],
+                                   function=_sum_and_sub_mul),
+                                   name='sum_and_sub_mul')
+
+    split = pe.Node(utility.Split(splits=[1, 1],
+                                  squeeze=True),
+                    name='split')
+
+
+    wf.connect([
+                (params,    gen_tuple,  [(("size", _inc),   "size")]),
+                (params,    ssm,        [(("num", _inc),    "c")]),
+                (gen_tuple, split,      [("tuple",          "inlist")]),
+                (split,     ssm,        [(("out1", _inc),   "a"),
+                                         ("out2",           "b"),
+                                        ]),
+                ])
+
+    wf.run()
+
+    # Clean up
+    os.chdir(origdir)
+    shutil.rmtree(tempdir)

nipype/pipeline/engine/workflows.py

@@ -690,7 +690,7 @@ def _configure_exec_nodes(self, graph):
             node.input_source = {}
             for edge in graph.in_edges_iter(node):
                 data = graph.get_edge_data(*edge)
-                for sourceinfo, field in sorted(data['connect']):
+                for sourceinfo, field in data['connect']:
                     node.input_source[field] = \
                         (op.join(edge[0].output_dir(),
                                  'result_%s.pklz' % edge[0].name),