ENH: Auto-derive input_names in Function

nipype/interfaces/utility/tests/test_wrappers.py

@@ -8,6 +8,12 @@
 from nipype.interfaces import utility
 import nipype.pipeline.engine as pe
 
+concat_sort = """\
+def concat_sort(in_arrays):
+    import numpy as np
+    all_vals = np.concatenate([arr.flatten() for arr in in_arrays])
+    return np.sort(all_vals)
+"""
 
 def test_function(tmpdir):
     os.chdir(str(tmpdir))
@@ -24,9 +30,15 @@ def gen_random_array(size):
     def increment_array(in_array):
         return in_array + 1
 
-    f2 = pe.MapNode(utility.Function(input_names=['in_array'], output_names=['out_array'], function=increment_array), name='increment_array', iterfield=['in_array'])
+    f2 = pe.MapNode(utility.Function(function=increment_array), name='increment_array', iterfield=['in_array'])
 
     wf.connect(f1, 'random_array', f2, 'in_array')
+
+    f3 = pe.Node(
+        utility.Function(function=concat_sort),
+        name="concat_sort")
+
+    wf.connect(f2, 'out', f3, 'in_arrays')
     wf.run()
 
 

nipype/interfaces/utility/wrappers.py

@@ -58,18 +58,19 @@ class Function(IOBase):
     input_spec = FunctionInputSpec
     output_spec = DynamicTraitedSpec
 
-    def __init__(self, input_names, output_names, function=None, imports=None,
-                 **inputs):
+    def __init__(self, input_names=None, output_names='out', function=None,
+                 imports=None, **inputs):
         """
 
         Parameters
         ----------
 
-        input_names: single str or list
+        input_names: single str or list or None
             names corresponding to function inputs
+            if ``None``, derive input names from function argument names
         output_names: single str or list
-            names corresponding to function outputs.
-            has to match the number of outputs
+            names corresponding to function outputs (default: 'out').
+            if list of length > 1, has to match the number of outputs
         function : callable
             callable python object. must be able to execute in an
             isolated namespace (possibly in concert with the ``imports``
@@ -88,10 +89,18 @@ def __init__(self, input_names, output_names, function=None, imports=None,
                     raise Exception('Interface Function does not accept '
                                     'function objects defined interactively '
                                     'in a python session')
+                else:
+                    if input_names is None:
+                        fninfo = function.__code__
             elif isinstance(function, (str, bytes)):
                 self.inputs.function_str = function
+                if input_names is None:
+                    fninfo = create_function_from_source(
+                        function, imports).__code__
             else:
                 raise Exception('Unknown type of function')
+            if input_names is None:
+                input_names = fninfo.co_varnames[:fninfo.co_argcount]
         self.inputs.on_trait_change(self._set_function_string,
                                     'function_str')
         self._input_names = filename_to_list(input_names)
@@ -106,10 +115,18 @@ def _set_function_string(self, obj, name, old, new):
         if name == 'function_str':
             if hasattr(new, '__call__'):
                 function_source = getsource(new)
+                fninfo = new.__code__
             elif isinstance(new, (str, bytes)):
                 function_source = new
+                fninfo = create_function_from_source(
+                    new, self.imports).__code__
             self.inputs.trait_set(trait_change_notify=False,
                                   **{'%s' % name: function_source})
+            # Update input traits
+            input_names = fninfo.co_varnames[:fninfo.co_argcount]
+            new_names = set(input_names) - set(self._input_names)
+            add_traits(self.inputs, list(new_names))
+            self._input_names.extend(new_names)
 
     def _add_output_traits(self, base):
         undefined_traits = {}