Merge branch 'master' into remove_users_docs

Author: miykael

docker/generate_dockerfiles.sh

@@ -109,7 +109,7 @@ function generate_main_dockerfile() {
   --miniconda env_name=neuro \
               pip_install="grabbit==0.1.2" \
   --run-bash "mkdir -p /src/pybids
-         && curl -sSL --retry 5 https://github.com/INCF/pybids/tarball/0.6.5
+         && curl -sSL --retry 5 https://github.com/INCF/pybids/tarball/0.5.1
          | tar -xz -C /src/pybids --strip-components 1
          && source activate neuro
          && pip install --no-cache-dir -e /src/pybids" \

nipype/info.py

@@ -154,7 +154,7 @@ def get_nipype_gitversion():
 if sys.version_info <= (3, 4):
     REQUIRES.append('configparser')
 
-TESTS_REQUIRES = ['pytest-cov', 'codecov', 'pytest-env']
+TESTS_REQUIRES = ['pytest-cov', 'codecov', 'pytest-env', 'coverage<5']
 
 EXTRA_REQUIRES = {
     'doc': ['Sphinx>=1.4', 'numpydoc', 'matplotlib', 'pydotplus', 'pydot>=1.2.3'],

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/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()

nipype/interfaces/mrtrix3/reconst.py

@@ -39,8 +39,8 @@ class FitTensorInputSpec(MRTrix3BaseInputSpec):
         argstr='-method %s',
         desc=('select method used to perform the fitting'))
     reg_term = traits.Float(
-        5.e3, usedefault=True,
         argstr='-regularisation %f',
+        max_ver='0.3.13',
         desc=('specify the strength of the regularisation term on the '
               'magnitude of the tensor elements (default = 5000). This '
               'only applies to the non-linear methods'))
@@ -64,8 +64,7 @@ class FitTensor(MRTrix3Base):
     >>> tsr.inputs.in_mask = 'mask.nii.gz'
     >>> tsr.inputs.grad_fsl = ('bvecs', 'bvals')
     >>> tsr.cmdline                               # doctest: +ELLIPSIS
-    'dwi2tensor -fslgrad bvecs bvals -mask mask.nii.gz \
--regularisation 5000.000000 dwi.mif dti.mif'
+    'dwi2tensor -fslgrad bvecs bvals -mask mask.nii.gz dwi.mif dti.mif'
     >>> tsr.run()                                 # doctest: +SKIP
     """
 

nipype/interfaces/mrtrix3/tests/test_auto_FitTensor.py

@@ -34,7 +34,7 @@ def test_FitTensor_inputs():
         ),
         reg_term=dict(
             argstr='-regularisation %f',
-            usedefault=True,
+            max_ver='0.3.13',
         ),
     )
     inputs = FitTensor.input_spec()

nipype/pipeline/engine/tests/test_engine.py

@@ -484,9 +484,12 @@ def test_deep_nested_write_graph_runs(tmpdir):
             except OSError:
                 pass
 
+import networkx
+# Format of the graph has slightly changed
+graph_str = '""' if int(networkx.__version__.split('.')[0]) == 1 else ''
 
 # examples of dot files used in the following test
-dotfile_orig = ['strict digraph  {\n',
+dotfile_orig = ['strict digraph ' + graph_str + ' {\n',
                 '"mod1 (engine)";\n',
                 '"mod2 (engine)";\n',
                 '"mod1 (engine)" -> "mod2 (engine)";\n',

nipype/pipeline/engine/utils.py

@@ -1473,7 +1473,8 @@ def clean_working_directory(outputs,
         needed_files += [path for path, type in input_files if type == 'f']
     for extra in [
             '_0x*.json', 'provenance.*', 'pyscript*.m', 'pyjobs*.mat',
-            'command.txt', 'result*.pklz', '_inputs.pklz', '_node.pklz'
+            'command.txt', 'result*.pklz', '_inputs.pklz', '_node.pklz',
+            '.proc-*',
     ]:
         needed_files.extend(glob(os.path.join(cwd, extra)))
     if files2keep:

nipype/utils/config.py

@@ -291,6 +291,10 @@ def enable_resource_monitor(self):
         """Sets the resource monitor on"""
         self.resource_monitor = True
 
+    def disable_resource_monitor(self):
+        """Sets the resource monitor off"""
+        self.resource_monitor = False
+
     def get_display(self):
         """Returns the first display available"""