Merge remote-tracking branch 'upstream/master' into fix/bunchmapnode

* upstream/master:
  better test
  Revert "my own nipype version"
  fix
  test
  Update __init__.py in fsl interfaces to have new ApplyXFM
  my own nipype version
  fix outputs
  test
  Revert "fix fast??"
  fix fast??
  fix README after neurostars is down
  m
  m
  ApplyXfm -> ApplyXFM
  fix: hierarchy typo
  add: itername to track hierarchy + iterables
  fix: missing import
  tst: added test case
  test: use fullname

Author: satra

README.rst

@@ -77,18 +77,21 @@ Information specific to Nipype is located here::
 Support and Communication
 -------------------------
 
-If you have a problem or would like to ask a question about how to do something in Nipype please submit a question
-to `NeuroStars.org <http://neurostars.org>`_ with a *nipype* tag. `NeuroStars.org <http://neurostars.org>`_  is a platform similar to StackOverflow but dedicated to neuroinformatics. All previous Nipype questions are available here::
-
-       http://neurostars.org/t/nipype/
-
+If you have a problem or would like to ask a question about how to do something in Nipype please open an issue
+in this GitHub repository.
 
 To participate in the Nipype development related discussions please use the following mailing list::
 
        http://mail.python.org/mailman/listinfo/neuroimaging
 
 Please add *[nipype]* to the subject line when posting on the mailing list.
 
+  .. warning ::
+
+    As of `Nov 23, 2016 <https://twitter.com/neuroquestion/status/801453442132754432>`_,
+    `NeuroStars <http://neurostars.org>`_ is down. We used to have all previous Nipype
+    questions available under the `nipype <http://neurostars.org/t/nipype/>`_ label.
+
 
 Nipype structure
 ----------------

nipype/interfaces/fsl/__init__.py

@@ -8,8 +8,8 @@
 """
 
 from .base import (FSLCommand, Info, check_fsl, no_fsl, no_fsl_course_data)
-from .preprocess import (FAST, FLIRT, ApplyXfm, BET, MCFLIRT, FNIRT, ApplyWarp,
-                         SliceTimer, SUSAN, PRELUDE, FUGUE, FIRST)
+from .preprocess import (FAST, FLIRT, ApplyXfm, ApplyXFM, BET, MCFLIRT, FNIRT,
+                         ApplyWarp, SliceTimer, SUSAN, PRELUDE, FUGUE, FIRST)
 from .model import (Level1Design, FEAT, FEATModel, FILMGLS, FEATRegister,
                     FLAMEO, ContrastMgr, MultipleRegressDesign, L2Model, SMM,
                     MELODIC, SmoothEstimate, Cluster, Randomise, GLM)

nipype/interfaces/fsl/preprocess.py

@@ -323,17 +323,20 @@ def _list_outputs(self):
             nclasses = self.inputs.number_classes
         # when using multichannel, results basename is based on last
         # input filename
+        _gen_fname_opts = {}
         if isdefined(self.inputs.out_basename):
-            basefile = self.inputs.out_basename
+            _gen_fname_opts['basename'] = self.inputs.out_basename
+            _gen_fname_opts['cwd'] = os.getcwd()
         else:
-            basefile = self.inputs.in_files[-1]
+            _gen_fname_opts['basename'] = self.inputs.in_files[-1]
+            _gen_fname_opts['cwd'], _, _ = split_filename(_gen_fname_opts['basename'])
 
-        outputs['tissue_class_map'] = self._gen_fname(basefile, suffix='_seg')
+        outputs['tissue_class_map'] = self._gen_fname(suffix='_seg', **_gen_fname_opts)
         if self.inputs.segments:
             outputs['tissue_class_files'] = []
             for i in range(nclasses):
                 outputs['tissue_class_files'].append(
-                    self._gen_fname(basefile, suffix='_seg_%d' % i))
+                    self._gen_fname(suffix='_seg_%d' % i, **_gen_fname_opts))
         if isdefined(self.inputs.output_biascorrected):
             outputs['restored_image'] = []
             if len(self.inputs.in_files) > 1:
@@ -342,22 +345,21 @@ def _list_outputs(self):
                 for val, f in enumerate(self.inputs.in_files):
                     # image numbering is 1-based
                     outputs['restored_image'].append(
-                        self._gen_fname(basefile,
-                                        suffix='_restore_%d' % (val + 1)))
+                        self._gen_fname(suffix='_restore_%d' % (val + 1), **_gen_fname_opts))
             else:
                 # single image segmentation has unnumbered output image
                 outputs['restored_image'].append(
-                    self._gen_fname(basefile, suffix='_restore'))
+                    self._gen_fname(suffix='_restore', **_gen_fname_opts))
 
-        outputs['mixeltype'] = self._gen_fname(basefile, suffix='_mixeltype')
+        outputs['mixeltype'] = self._gen_fname(suffix='_mixeltype', **_gen_fname_opts)
         if not self.inputs.no_pve:
             outputs['partial_volume_map'] = self._gen_fname(
-                basefile, suffix='_pveseg')
+                suffix='_pveseg', **_gen_fname_opts)
             outputs['partial_volume_files'] = []
             for i in range(nclasses):
                 outputs[
                     'partial_volume_files'].append(
-                        self._gen_fname(basefile, suffix='_pve_%d' % i))
+                        self._gen_fname(suffix='_pve_%d' % i, **_gen_fname_opts))
         if self.inputs.output_biasfield:
             outputs['bias_field'] = []
             if len(self.inputs.in_files) > 1:
@@ -366,18 +368,17 @@ def _list_outputs(self):
                 for val, f in enumerate(self.inputs.in_files):
                     # image numbering is 1-based
                     outputs['bias_field'].append(
-                        self._gen_fname(basefile,
-                                        suffix='_bias_%d' % (val + 1)))
+                        self._gen_fname(suffix='_bias_%d' % (val + 1), **_gen_fname_opts))
             else:
                 # single image segmentation has unnumbered output image
                 outputs['bias_field'].append(
-                    self._gen_fname(basefile, suffix='_bias'))
+                    self._gen_fname(suffix='_bias', **_gen_fname_opts))
 
         if self.inputs.probability_maps:
             outputs['probability_maps'] = []
             for i in range(nclasses):
                 outputs['probability_maps'].append(
-                    self._gen_fname(basefile, suffix='_prob_%d' % i))
+                    self._gen_fname(suffix='_prob_%d' % i, **_gen_fname_opts))
         return outputs
 
 
@@ -563,27 +564,26 @@ def _parse_inputs(self, skip=None):
         skip.append('save_log')
         return super(FLIRT, self)._parse_inputs(skip=skip)
 
-
-class ApplyXfmInputSpec(FLIRTInputSpec):
+class ApplyXFMInputSpec(FLIRTInputSpec):
     apply_xfm = traits.Bool(
         True, argstr='-applyxfm', requires=['in_matrix_file'],
         desc='apply transformation supplied by in_matrix_file',
         usedefault=True)
 
 
-class ApplyXfm(FLIRT):
+class ApplyXFM(FLIRT):
     """Currently just a light wrapper around FLIRT,
     with no modifications
 
-    ApplyXfm is used to apply an existing tranform to an image
+    ApplyXFM is used to apply an existing tranform to an image
 
 
     Examples
     --------
 
     >>> import nipype.interfaces.fsl as fsl
     >>> from nipype.testing import example_data
-    >>> applyxfm = fsl.ApplyXfm()
+    >>> applyxfm = fsl.preprocess.ApplyXFM()
     >>> applyxfm.inputs.in_file = example_data('structural.nii')
     >>> applyxfm.inputs.in_matrix_file = example_data('trans.mat')
     >>> applyxfm.inputs.out_file = 'newfile.nii'
@@ -592,8 +592,18 @@ class ApplyXfm(FLIRT):
     >>> result = applyxfm.run() # doctest: +SKIP
 
     """
-    input_spec = ApplyXfmInputSpec
+    input_spec = ApplyXFMInputSpec
 
+class ApplyXfm(ApplyXFM):
+    """
+    .. deprecated:: 0.12.1
+       Use :py:class:`nipype.interfaces.fsl.ApplyXFM` instead
+    """
+    def __init__(self, **inputs):
+        super(ApplyXfm, self).__init__(**inputs)
+        warn(('This interface has been renamed since 0.12.1, please use '
+              'nipype.interfaces.fsl.ApplyXFM'),
+             UserWarning)
 
 class MCFLIRTInputSpec(FSLCommandInputSpec):
     in_file = File(exists=True, position=0, argstr="-in %s", mandatory=True,

nipype/interfaces/fsl/tests/test_preprocess.py

@@ -10,9 +10,9 @@
 import shutil
 
 from nipype.testing import (assert_equal, assert_not_equal, assert_raises,
-                            skipif)
+                            skipif, assert_true)
 
-from nipype.utils.filemanip import split_filename
+from nipype.utils.filemanip import split_filename, filename_to_list
 from .. import preprocess as fsl
 from nipype.interfaces.fsl import Info
 from nipype.interfaces.base import File, TraitError, Undefined, isdefined
@@ -167,6 +167,33 @@ def test_fast():
                                                       "-S 1 %s" % tmp_infile])
     teardown_infile(tmp_dir)
 
+@skipif(no_fsl)
+def test_fast_list_outputs():
+    ''' By default (no -o), FSL's fast command outputs files into the same
+    directory as the input files. If the flag -o is set, it outputs files into
+    the cwd '''
+    def _run_and_test(opts, output_base):
+        outputs = fsl.FAST(**opts)._list_outputs()
+        for output in outputs.values():
+            filenames = filename_to_list(output)
+            if filenames is not None:
+                for filename in filenames:
+                    assert_equal(filename[:len(output_base)], output_base)
+
+    # set up
+    infile, indir = setup_infile()
+    cwd = tempfile.mkdtemp()
+    os.chdir(cwd)
+    yield assert_not_equal, indir, cwd
+    out_basename = 'a_basename'
+
+    # run and test
+    opts = {'in_files': tmp_infile}
+    input_path, input_filename, input_ext = split_filename(tmp_infile)
+    _run_and_test(opts, os.path.join(input_path, input_filename))
+
+    opts['out_basename'] = out_basename
+    _run_and_test(opts, os.path.join(cwd, out_basename))
 
 @skipif(no_fsl)
 def setup_flirt():
@@ -587,3 +614,8 @@ def test_first_genfname():
     value = first._gen_fname(name='original_segmentations')
     expected_value = os.path.abspath('segment_all_none_origsegs.nii.gz')
     yield assert_equal, value, expected_value
+
+@skipif(no_fsl)
+def test_deprecation():
+    interface = fsl.ApplyXfm()
+    yield assert_true, isinstance(interface, fsl.ApplyXFM)

nipype/pipeline/engine/base.py

@@ -69,6 +69,13 @@ def fullname(self):
             fullname = self._hierarchy + '.' + self.name
         return fullname
 
+    @property
+    def itername(self):
+        itername = self._id
+        if self._hierarchy:
+            itername = self._hierarchy + '.' + self._id
+        return itername
+
     def clone(self, name):
         """Clone an EngineBase object
 

nipype/pipeline/engine/tests/test_join.py

@@ -602,6 +602,46 @@ def test_set_join_node_file_input():
     os.chdir(cwd)
     rmtree(wd)
 
+def test_nested_workflow_join():
+    """Test collecting join inputs within a nested workflow"""
+    cwd = os.getcwd()
+    wd = mkdtemp()
+    os.chdir(wd)
+
+    # Make the nested workflow
+    def nested_wf(i, name='smallwf'):
+        #iterables with list of nums
+        inputspec = pe.Node(IdentityInterface(fields=['n']), name='inputspec')
+        inputspec.iterables = [('n', i)]
+        # increment each iterable before joining
+        pre_join = pe.Node(IncrementInterface(),
+                           name='pre_join')
+        # rejoin nums into list
+        join = pe.JoinNode(IdentityInterface(fields=['n']),
+                          joinsource='inputspec',
+                          joinfield='n',
+                          name='join')
+        #define and connect nested workflow
+        wf = pe.Workflow(name='wf_%d'%i[0])
+        wf.connect(inputspec, 'n', pre_join, 'input1')
+        wf.connect(pre_join, 'output1', join, 'n')
+        return wf
+    # master wf
+    meta_wf = pe.Workflow(name='meta', base_dir='.')
+    # add each mini-workflow to master
+    for i in [[1,3],[2,4]]:
+        mini_wf = nested_wf(i)
+        meta_wf.add_nodes([mini_wf])
+
+    result = meta_wf.run()
+    
+    # there should be six nodes in total
+    assert_equal(len(result.nodes()), 6,
+             "The number of expanded nodes is incorrect.")
+    
+    os.chdir(cwd)
+    rmtree(wd)
+
 
 if __name__ == "__main__":
     import nose

nipype/pipeline/engine/utils.py

@@ -711,7 +711,7 @@ def generate_expanded_graph(graph_in):
             in_edges = jedge_dict[jnode] = {}
             edges2remove = []
             for src, dest, data in graph_in.in_edges_iter(jnode, True):
-                in_edges[src._id] = data
+                in_edges[src.itername] = data
                 edges2remove.append((src, dest))
 
             for src, dest in edges2remove:
@@ -796,7 +796,7 @@ def make_field_func(*pair):
             expansions = defaultdict(list)
             for node in graph_in.nodes_iter():
                 for src_id, edge_data in list(old_edge_dict.items()):
-                    if node._id.startswith(src_id):
+                    if node.itername.startswith(src_id):
                         expansions[src_id].append(node)
             for in_id, in_nodes in list(expansions.items()):
                 logger.debug("The join node %s input %s was expanded"