Merge remote-tracking branch 'upstream/master' into enh/neurodocker

Author: Jakub Kaczmarzyk

.zenodo.json

@@ -320,7 +320,9 @@
       "name": "Ghayoor, Ali"
     },
     {
-      "name": "Liem, Franz"
+      "affiliation": "University of Zurich",
+      "name": "Liem, Franz",
+      "orcid": "0000-0003-0646-4810"
     },
     {
       "name": "Millman, Jarrod"

doc/conf.py

@@ -50,7 +50,7 @@
               'sphinx.ext.autosummary',
               'numpydoc',
               'matplotlib.sphinxext.plot_directive',
-              'matplotlib.sphinxext.only_directives',
+              #'matplotlib.sphinxext.only_directives',
               'nipype.sphinxext.plot_workflow',
               #'IPython.sphinxext.ipython_directive',
               #'IPython.sphinxext.ipython_console_highlighting'

nipype/info.py

@@ -108,7 +108,7 @@ def get_nipype_gitversion():
 PYTEST_MIN_VERSION = '3.0'
 FUTURE_MIN_VERSION = '0.16.0'
 SIMPLEJSON_MIN_VERSION = '3.8.0'
-PROV_VERSION = '1.5.0'
+PROV_VERSION = '1.5.2'
 CLICK_MIN_VERSION = '6.6.0'
 PYDOT_MIN_VERSION = '1.2.3'
 
@@ -139,7 +139,8 @@ def get_nipype_gitversion():
     'traits>=%s' % TRAITS_MIN_VERSION,
     'future>=%s' % FUTURE_MIN_VERSION,
     'simplejson>=%s' % SIMPLEJSON_MIN_VERSION,
-    'prov==%s' % PROV_VERSION,
+    'prov>=%s' % PROV_VERSION,
+    'neurdflib',
     'click>=%s' % CLICK_MIN_VERSION,
     'funcsigs',
     'pytest>=%s' % PYTEST_MIN_VERSION,

nipype/interfaces/afni/preprocess.py

@@ -2618,6 +2618,14 @@ class TShiftInputSpec(AFNICommandInputSpec):
         desc='time offsets from the volume acquisition onset for each slice',
         argstr='-tpattern @%s',
         xor=['tpattern'])
+    slice_encoding_direction = traits.Enum(
+        'k', 'k-',
+        usedefault=True,
+        desc='Direction in which slice_timing is specified (default: k). If negative,'
+             'slice_timing is defined in reverse order, that is, the first entry '
+             'corresponds to the slice with the largest index, and the final entry '
+             'corresponds to slice index zero. Only in effect when slice_timing is '
+             'passed as list, not when it is passed as file.',)
     rlt = traits.Bool(
         desc='Before shifting, remove the mean and linear trend',
         argstr='-rlt')
@@ -2660,6 +2668,17 @@ class TShift(AFNICommand):
     >>> tshift._list_outputs()['timing_file']  # doctest: +ELLIPSIS
     '.../slice_timing.1D'
 
+    >>> np.loadtxt(tshift._list_outputs()['timing_file']).tolist()[:5]
+    [0.0, 0.4, 0.8, 1.2, 1.6]
+
+    If ``slice_encoding_direction`` is set to ``'k-'``, the slice timing is reversed:
+
+    >>> tshift.inputs.slice_encoding_direction = 'k-'
+    >>> tshift.cmdline
+    '3dTshift -prefix functional_tshift -tpattern @slice_timing.1D -TR 2.5s -tzero 0.0 functional.nii'
+    >>> np.loadtxt(tshift._list_outputs()['timing_file']).tolist()[:5]
+    [15.6, 15.2, 14.8, 14.4, 14.0]
+
     This method creates a ``slice_timing.1D`` file to be passed to ``3dTshift``.
     A pre-existing slice-timing file may be used in the same way:
 
@@ -2723,9 +2742,13 @@ def _format_arg(self, name, trait_spec, value):
         return super(TShift, self)._format_arg(name, trait_spec, value)
 
     def _write_slice_timing(self):
+        slice_timing = list(self.inputs.slice_timing)
+        if self.inputs.slice_encoding_direction.endswith("-"):
+            slice_timing.reverse()
+
         fname = 'slice_timing.1D'
         with open(fname, 'w') as fobj:
-            fobj.write('\t'.join(map(str, self.inputs.slice_timing)))
+            fobj.write('\t'.join(map(str, slice_timing)))
         return fname
 
     def _list_outputs(self):

nipype/interfaces/ants/segmentation.py

@@ -203,7 +203,9 @@ class LaplacianThicknessInputSpec(ANTSCommandInputSpec):
         desc='name of output file',
         argstr='%s',
         position=3,
-        genfile=True,
+        name_source=['input_wm'],
+        name_template='%s_thickness',
+        keep_extension=True,
         hash_files=False)
     smooth_param = traits.Float(argstr='smoothparam=%d', desc='', position=4)
     prior_thickness = traits.Float(
@@ -228,6 +230,9 @@ class LaplacianThickness(ANTSCommand):
     >>> cort_thick = LaplacianThickness()
     >>> cort_thick.inputs.input_wm = 'white_matter.nii.gz'
     >>> cort_thick.inputs.input_gm = 'gray_matter.nii.gz'
+    >>> cort_thick.cmdline
+    'LaplacianThickness white_matter.nii.gz gray_matter.nii.gz white_matter_thickness.nii.gz'
+
     >>> cort_thick.inputs.output_image = 'output_thickness.nii.gz'
     >>> cort_thick.cmdline
     'LaplacianThickness white_matter.nii.gz gray_matter.nii.gz output_thickness.nii.gz'
@@ -238,22 +243,6 @@ class LaplacianThickness(ANTSCommand):
     input_spec = LaplacianThicknessInputSpec
     output_spec = LaplacianThicknessOutputSpec
 
-    def _gen_filename(self, name):
-        if name == 'output_image':
-            output = self.inputs.output_image
-            if not isdefined(output):
-                _, name, ext = split_filename(self.inputs.input_wm)
-                output = name + '_thickness' + ext
-            return output
-        return None
-
-    def _list_outputs(self):
-        outputs = self._outputs().get()
-        _, name, ext = split_filename(os.path.abspath(self.inputs.input_wm))
-        outputs['output_image'] = os.path.join(os.getcwd(), ''.join(
-            (name, self.inputs.output_image, ext)))
-        return outputs
-
 
 class N4BiasFieldCorrectionInputSpec(ANTSCommandInputSpec):
     dimension = traits.Enum(

nipype/interfaces/ants/tests/test_auto_LaplacianThickness.py

@@ -36,8 +36,10 @@ def test_LaplacianThickness_inputs():
         ),
         output_image=dict(
             argstr='%s',
-            genfile=True,
             hash_files=False,
+            keep_extension=True,
+            name_source=['input_wm'],
+            name_template='%s_thickness',
             position=3,
         ),
         prior_thickness=dict(

nipype/interfaces/base/specs.py

@@ -234,7 +234,6 @@ def get_hashval(self, hash_method=None):
             The md5 hash value of the traited spec
 
         """
-
         list_withhash = []
         list_nofilename = []
         for name, val in sorted(self.trait_get().items()):
@@ -309,6 +308,10 @@ def _get_sorteddict(self,
                     out = objekt
         return out
 
+    @property
+    def __all__(self):
+        return self.copyable_trait_names()
+
 
 class TraitedSpec(BaseTraitedSpec):
     """ Create a subclass with strict traits.

nipype/interfaces/base/tests/test_resource_monitor.py

@@ -18,10 +18,16 @@
 from ... import utility as niu
 
 # Try to enable the resource monitor
-config.enable_resource_monitor()
 run_profile = config.resource_monitor
 
 
+@pytest.fixture(scope="module")
+def use_resource_monitor():
+    config.enable_resource_monitor()
+    yield
+    config.disable_resource_monitor()
+
+
 class UseResourcesInputSpec(CommandLineInputSpec):
     mem_gb = traits.Float(
         desc='Number of GB of RAM to use', argstr='-g %f', mandatory=True)
@@ -51,7 +57,7 @@ class UseResources(CommandLine):
     os.getenv('CI_SKIP_TEST', False), reason='disabled in CI tests')
 @pytest.mark.parametrize("mem_gb,n_procs", [(0.5, 3), (2.2, 8), (0.8, 4),
                                             (1.5, 1)])
-def test_cmdline_profiling(tmpdir, mem_gb, n_procs):
+def test_cmdline_profiling(tmpdir, mem_gb, n_procs, use_resource_monitor):
     """
     Test runtime profiler correctly records workflow RAM/CPUs consumption
     of a CommandLine-derived interface
@@ -73,7 +79,7 @@ def test_cmdline_profiling(tmpdir, mem_gb, n_procs):
     True, reason='test disabled temporarily, until funcion profiling works')
 @pytest.mark.parametrize("mem_gb,n_procs", [(0.5, 3), (2.2, 8), (0.8, 4),
                                             (1.5, 1)])
-def test_function_profiling(tmpdir, mem_gb, n_procs):
+def test_function_profiling(tmpdir, mem_gb, n_procs, use_resource_monitor):
     """
     Test runtime profiler correctly records workflow RAM/CPUs consumption
     of a Function interface

nipype/interfaces/base/tests/test_specs.py

@@ -11,6 +11,10 @@
 from ....utils.filemanip import split_filename
 from ... import base as nib
 from ...base import traits, Undefined
+from ....interfaces import fsl
+from ...utility.wrappers import Function
+from ....pipeline import Node
+
 
 standard_library.install_aliases()
 
@@ -47,6 +51,20 @@ class spec(nib.TraitedSpec):
     assert infields.__repr__() == '\nfoo = 1\ngoo = 0.0\n'
 
 
+def test_TraitedSpec_tab_completion():
+    bet_nd = Node(fsl.BET(), name='bet')
+    bet_interface = fsl.BET()
+    bet_inputs = bet_nd.inputs.class_editable_traits()
+    bet_outputs = bet_nd.outputs.class_editable_traits() 
+    
+    # Check __all__ for bet node and interface inputs
+    assert set(bet_nd.inputs.__all__) == set(bet_inputs)
+    assert set(bet_interface.inputs.__all__) == set(bet_inputs)
+
+    # Check __all__ for bet node outputs
+    assert set(bet_nd.outputs.__all__) == set(bet_outputs)
+
+
 @pytest.mark.skip
 def test_TraitedSpec_dynamic():
     from pickle import dumps, loads
@@ -63,6 +81,36 @@ def test_TraitedSpec_dynamic():
         assign_a_again
 
 
+def test_DynamicTraitedSpec_tab_completion():
+    def extract_func(list_out):
+        return list_out[0]
+
+    # Define interface
+    func_interface = Function(input_names=["list_out"],
+                              output_names=["out_file", "another_file"],
+                              function=extract_func)
+    # Define node
+    list_extract = Node(Function(
+        input_names=["list_out"], output_names=["out_file"],
+        function=extract_func), name="list_extract")
+
+    # Check __all__ for interface inputs
+    expected_input = set(list_extract.inputs.editable_traits())
+    assert(set(func_interface.inputs.__all__) == expected_input)
+
+    # Check __all__ for node inputs
+    assert(set(list_extract.inputs.__all__) == expected_input)
+
+    # Check __all__ for node outputs
+    expected_output = set(list_extract.outputs.editable_traits())
+    assert(set(list_extract.outputs.__all__) == expected_output)
+
+    # Add trait and retest
+    list_extract._interface._output_names.append('added_out_trait')
+    expected_output.add('added_out_trait')
+    assert(set(list_extract.outputs.__all__) == expected_output)
+
+
 def test_TraitedSpec_logic():
     class spec3(nib.TraitedSpec):
         _xor_inputs = ('foo', 'bar')

nipype/interfaces/fsl/dti.py

@@ -85,6 +85,8 @@ class DTIFitOutputSpec(TraitedSpec):
               'diffusion weighting'))
     tensor = File(
         exists=True, desc='path/name of file with the 4D tensor volume')
+    sse = File(
+        exists=True, desc='path/name of file with the summed squared error')
 
 
 class DTIFit(FSLCommand):
@@ -111,13 +113,21 @@ class DTIFit(FSLCommand):
     output_spec = DTIFitOutputSpec
 
     def _list_outputs(self):
+        keys_to_ignore = {'outputtype', 'environ', 'args'}
+        # Optional output: Map output name to input flag
+        opt_output = {'tensor': self.inputs.save_tensor,
+                      'sse': self.inputs.sse}
+        # Ignore optional output, whose corresponding input-flag is not defined
+        # or set to False
+        for output, input_flag in opt_output.items():
+            if isdefined(input_flag) and input_flag:
+                # this is wanted output, do not ignore
+                continue
+            keys_to_ignore.add(output)
+
         outputs = self.output_spec().get()
-        for k in list(outputs.keys()):
-            if k not in ('outputtype', 'environ', 'args'):
-                if k != 'tensor' or (isdefined(self.inputs.save_tensor)
-                                     and self.inputs.save_tensor):
-                    outputs[k] = self._gen_fname(
-                        self.inputs.base_name, suffix='_' + k)
+        for k in set(outputs.keys()) - keys_to_ignore:
+            outputs[k] = self._gen_fname(self.inputs.base_name, suffix='_' + k)
         return outputs
 
 

nipype/interfaces/fsl/tests/test_auto_DTIFit.py

@@ -66,6 +66,7 @@ def test_DTIFit_outputs():
         V2=dict(),
         V3=dict(),
         tensor=dict(),
+        sse=dict(),
     )
     outputs = DTIFit.output_spec()
 

nipype/interfaces/fsl/utils.py

@@ -551,9 +551,9 @@ def _list_outputs(self):
         """
         outputs = self._outputs().get()
         ext = Info.output_type_to_ext(self.inputs.output_type)
-        outbase = 'vol*'
+        outbase = 'vol[0-9]*'
         if isdefined(self.inputs.out_base_name):
-            outbase = '%s*' % self.inputs.out_base_name
+            outbase = '%s[0-9]*' % self.inputs.out_base_name
         outputs['out_files'] = sorted(
             glob(os.path.join(os.getcwd(), outbase + ext)))
         return outputs

nipype/interfaces/meshfix.py

@@ -38,10 +38,10 @@ class MeshFixInputSpec(CommandLineInputSpec):
     dont_clean = traits.Bool(argstr='--no-clean', desc="Don't Clean")
 
     save_as_stl = traits.Bool(
-        xor=['save_as_vmrl', 'save_as_freesurfer_mesh'],
+        xor=['save_as_vrml', 'save_as_freesurfer_mesh'],
         argstr='--stl',
         desc="Result is saved in stereolithographic format (.stl)")
-    save_as_vmrl = traits.Bool(
+    save_as_vrml = traits.Bool(
         argstr='--wrl',
         xor=['save_as_stl', 'save_as_freesurfer_mesh'],
         desc="Result is saved in VRML1.0 format (.wrl)")
@@ -210,7 +210,7 @@ def _gen_outfilename(self):
         if self.inputs.save_as_stl or self.inputs.output_type == 'stl':
             self.inputs.output_type = 'stl'
             self.inputs.save_as_stl = True
-        if self.inputs.save_as_vmrl or self.inputs.output_type == 'vmrl':
-            self.inputs.output_type = 'vmrl'
-            self.inputs.save_as_vmrl = True
+        if self.inputs.save_as_vrml or self.inputs.output_type == 'vrml':
+            self.inputs.output_type = 'vrml'
+            self.inputs.save_as_vrml = True
         return name + '_fixed.' + self.inputs.output_type

nipype/interfaces/mrtrix3/base.py

@@ -4,11 +4,39 @@
 from __future__ import (print_function, division, unicode_literals,
                         absolute_import)
 
-from ... import logging
-from ..base import (CommandLineInputSpec, CommandLine, traits, File, isdefined)
+from ... import logging, LooseVersion
+from ...utils.filemanip import which
+from ..base import (CommandLineInputSpec, CommandLine, traits, File, isdefined, PackageInfo)
 iflogger = logging.getLogger('nipype.interface')
 
 
+class Info(PackageInfo):
+    version_cmd = 'mrconvert --version'
+
+    @staticmethod
+    def parse_version(raw_info):
+        # info is like: "== mrconvert 0.3.15-githash"
+        for line in raw_info.splitlines():
+            if line.startswith('== mrconvert '):
+                v_string = line.split()[2]
+                break
+        else:
+            return None
+
+        # -githash may or may not be appended
+        v_string = v_string.split('-')[0]
+
+        return '.'.join(v_string.split('.')[:3])
+
+    @classmethod
+    def looseversion(cls):
+        """ Return a comparable version object
+
+        If no version found, use LooseVersion('0.0.0')
+        """
+        return LooseVersion(cls.version() or '0.0.0')
+
+
 class MRTrix3BaseInputSpec(CommandLineInputSpec):
     nthreads = traits.Int(
         argstr='-nthreads %d',
@@ -78,3 +106,7 @@ def _parse_inputs(self, skip=None):
             pass
 
         return super(MRTrix3Base, self)._parse_inputs(skip=skip)
+
+    @property
+    def version(self):
+        return Info.version()