ENH: Modify Directory and File traits to get along with pathlib

nipype/algorithms/tests/test_rapidart.py

@@ -79,12 +79,13 @@ def test_sc_init():
 
 def test_sc_populate_inputs():
     sc = ra.StimulusCorrelation()
-    inputs = Bunch(
-        realignment_parameters=None,
-        intensity_values=None,
-        spm_mat_file=None,
-        concatenated_design=None)
-    assert set(sc.inputs.__dict__.keys()) == set(inputs.__dict__.keys())
+    expected = [
+        'concatenated_design',
+        'intensity_values',
+        'realignment_parameters',
+        'spm_mat_file',
+    ]
+    assert sorted(sc.inputs.get().keys()) == expected
 
 
 def test_sc_output_filenames():

nipype/info.py

@@ -135,26 +135,27 @@ def get_nipype_gitversion():
 VERSION = __version__
 PROVIDES = ['nipype']
 REQUIRES = [
-    'nibabel>=%s' % NIBABEL_MIN_VERSION,
-    'networkx>=%s,<=%s ; python_version < "3.0"' % (NETWORKX_MIN_VERSION, NETWORKX_MAX_VERSION_27),
+    'click>=%s' % CLICK_MIN_VERSION,
+    'configparser; python_version <= "3.4"',
+    'funcsigs',
+    'future>=%s' % FUTURE_MIN_VERSION,
+    'futures; python_version == "2.7"',
     'networkx>=%s ; python_version >= "3.0"' % NETWORKX_MIN_VERSION,
-    'numpy>=%s,!=%s ; python_version == "2.7"' % (NUMPY_MIN_VERSION, NUMPY_BAD_VERSION_27),
+    'networkx>=%s,<=%s ; python_version < "3.0"' % (NETWORKX_MIN_VERSION, NETWORKX_MAX_VERSION_27),
+    'neurdflib',
+    'nibabel>=%s' % NIBABEL_MIN_VERSION,
     'numpy>=%s ; python_version > "3.0" and python_version < "3.7"' % NUMPY_MIN_VERSION,
     'numpy>=%s ; python_version >= "3.7"' % NUMPY_MIN_VERSION_37,
+    'numpy>=%s,!=%s ; python_version == "2.7"' % (NUMPY_MIN_VERSION, NUMPY_BAD_VERSION_27),
+    'packaging',
+    'pathlib2; python_version <= "3.4"',
+    'prov>=%s' % PROV_VERSION,
+    'pydot>=%s' % PYDOT_MIN_VERSION,
+    'pydotplus',
     'python-dateutil>=%s' % DATEUTIL_MIN_VERSION,
     'scipy>=%s' % SCIPY_MIN_VERSION,
-    'traits>=%s,!=5.0' % TRAITS_MIN_VERSION,
-    'future>=%s' % FUTURE_MIN_VERSION,
     'simplejson>=%s' % SIMPLEJSON_MIN_VERSION,
-    'prov>=%s' % PROV_VERSION,
-    'neurdflib',
-    'click>=%s' % CLICK_MIN_VERSION,
-    'funcsigs',
-    'pydotplus',
-    'pydot>=%s' % PYDOT_MIN_VERSION,
-    'packaging',
-    'futures; python_version == "2.7"',
-    'configparser; python_version <= "3.4"',
+    'traits>=%s,!=5.0' % TRAITS_MIN_VERSION,
 ]
 
 TESTS_REQUIRES = [
@@ -170,7 +171,7 @@ def get_nipype_gitversion():
     'doc': ['Sphinx>=1.4', 'numpydoc', 'matplotlib', 'pydotplus', 'pydot>=1.2.3'],
     'tests': TESTS_REQUIRES,
     'specs': ['yapf'],
-    'nipy': ['nitime', 'nilearn<0.5.0', 'dipy', 'nipy', 'matplotlib'],
+    'nipy': ['nitime', 'nilearn<0.5.0', 'dipy!=0.15,>=0.14', 'nipy', 'matplotlib'],
     'profiler': ['psutil>=5.0'],
     'duecredit': ['duecredit'],
     'xvfbwrapper': ['xvfbwrapper'],

nipype/interfaces/afni/base.py

@@ -115,12 +115,6 @@ class AFNICommandInputSpec(CommandLineInputSpec):
         1, usedefault=True, nohash=True, desc='set number of threads')
     outputtype = traits.Enum(
         'AFNI', list(Info.ftypes.keys()), desc='AFNI output filetype')
-    out_file = File(
-        name_template="%s_afni",
-        desc='output image file name',
-        argstr='-prefix %s',
-        name_source=["in_file"])
-
 
 class AFNICommandOutputSpec(TraitedSpec):
     out_file = File(desc='output file', exists=True)

nipype/interfaces/afni/preprocess.py

@@ -13,7 +13,7 @@
 from ...utils.filemanip import (load_json, save_json, split_filename,
                                 fname_presuffix)
 from ..base import (CommandLineInputSpec, CommandLine, TraitedSpec, traits,
-                    isdefined, File, InputMultiPath, Undefined, Str,
+                    isdefined, File, Directory, InputMultiPath, Undefined, Str,
                     InputMultiObject)
 
 from .base import (AFNICommandBase, AFNICommand, AFNICommandInputSpec,
@@ -757,8 +757,7 @@ class BandpassInputSpec(AFNICommandInputSpec):
         desc='output file from 3dBandpass',
         argstr='-prefix %s',
         position=1,
-        name_source='in_file',
-        genfile=True)
+        name_source='in_file')
     lowpass = traits.Float(
         desc='lowpass', argstr='%f', position=-2, mandatory=True)
     highpass = traits.Float(
@@ -909,6 +908,11 @@ class BlurToFWHMInputSpec(AFNICommandInputSpec):
         argstr='-input %s',
         mandatory=True,
         exists=True)
+    out_file = File(
+        name_template='%s_afni',
+        desc='output image file name',
+        argstr='-prefix %s',
+        name_source='in_file')
     automask = traits.Bool(
         desc='Create an automask from the input dataset.', argstr='-automask')
     fwhm = traits.Float(
@@ -1042,6 +1046,11 @@ class DegreeCentralityInputSpec(CentralityInputSpec):
         mandatory=True,
         exists=True,
         copyfile=False)
+    out_file = File(
+        name_template='%s_afni',
+        desc='output image file name',
+        argstr='-prefix %s',
+        name_source='in_file')
     sparsity = traits.Float(
         desc='only take the top percent of connections', argstr='-sparsity %f')
     oned_file = Str(
@@ -1188,6 +1197,11 @@ class ECMInputSpec(CentralityInputSpec):
         mandatory=True,
         exists=True,
         copyfile=False)
+    out_file = File(
+        name_template='%s_afni',
+        desc='output image file name',
+        argstr='-prefix %s',
+        name_source='in_file')
     sparsity = traits.Float(
         desc='only take the top percent of connections', argstr='-sparsity %f')
     full = traits.Bool(
@@ -1453,6 +1467,11 @@ class LFCDInputSpec(CentralityInputSpec):
         mandatory=True,
         exists=True,
         copyfile=False)
+    out_file = File(
+        name_template='%s_afni',
+        desc='output image file name',
+        argstr='-prefix %s',
+        name_source='in_file')
 
 
 class LFCD(AFNICommand):
@@ -3072,58 +3091,56 @@ def _list_outputs(self):
 
 class QwarpInputSpec(AFNICommandInputSpec):
     in_file = File(
-        desc=
-        'Source image (opposite phase encoding direction than base image).',
+        desc='Source image (opposite phase encoding direction than base image).',
         argstr='-source %s',
         mandatory=True,
         exists=True,
         copyfile=False)
     base_file = File(
-        desc=
-        'Base image (opposite phase encoding direction than source image).',
+        desc='Base image (opposite phase encoding direction than source image).',
         argstr='-base %s',
         mandatory=True,
         exists=True,
         copyfile=False)
     out_file = File(
         argstr='-prefix %s',
         name_template='%s_QW',
-        name_source=['in_file'],
-        genfile=True,
-        desc='out_file ppp'
-        'Sets the prefix for the output datasets.'
-        '* The source dataset is warped to match the base'
-        'and gets prefix \'ppp\'. (Except if \'-plusminus\' is used.)'
-        '* The final interpolation to this output dataset is'
-        'done using the \'wsinc5\' method.  See the output of'
-        ' 3dAllineate -HELP'
-        '(in the "Modifying \'-final wsinc5\'" section) for'
-        'the lengthy technical details.'
-        '* The 3D warp used is saved in a dataset with'
-        'prefix \'ppp_WARP\' -- this dataset can be used'
-        'with 3dNwarpApply and 3dNwarpCat, for example.'
-        '* To be clear, this is the warp from source dataset'
-        ' coordinates to base dataset coordinates, where the'
-        ' values at each base grid point are the xyz displacments'
-        ' needed to move that grid point\'s xyz values to the'
-        ' corresponding xyz values in the source dataset:'
-        '   base( (x,y,z) + WARP(x,y,z) ) matches source(x,y,z)'
-        ' Another way to think of this warp is that it \'pulls\''
-        ' values back from source space to base space.'
-        '* 3dNwarpApply would use \'ppp_WARP\' to transform datasets'
-        'aligned with the source dataset to be aligned with the'
-        'base dataset.'
-        '** If you do NOT want this warp saved, use the option \'-nowarp\'.'
-        '-->> (However, this warp is usually the most valuable possible output!)'
-        '* If you want to calculate and save the inverse 3D warp,'
-        'use the option \'-iwarp\'.  This inverse warp will then be'
-        'saved in a dataset with prefix \'ppp_WARPINV\'.'
-        '* This inverse warp could be used to transform data from base'
-        'space to source space, if you need to do such an operation.'
-        '* You can easily compute the inverse later, say by a command like'
-        ' 3dNwarpCat -prefix Z_WARPINV \'INV(Z_WARP+tlrc)\''
-        'or the inverse can be computed as needed in 3dNwarpApply, like'
-        ' 3dNwarpApply -nwarp \'INV(Z_WARP+tlrc)\' -source Dataset.nii ...')
+        name_source='in_file',
+        desc="""\
+out_file ppp\
+Sets the prefix for the output datasets.\
+* The source dataset is warped to match the base\
+and gets prefix \'ppp\'. (Except if \'-plusminus\' is used.)\
+* The final interpolation to this output dataset is\
+done using the \'wsinc5\' method.  See the output of\
+ 3dAllineate -HELP\
+(in the "Modifying \'-final wsinc5\'" section) for\
+the lengthy technical details.\
+* The 3D warp used is saved in a dataset with\
+prefix \'ppp_WARP\' -- this dataset can be used\
+with 3dNwarpApply and 3dNwarpCat, for example.\
+* To be clear, this is the warp from source dataset\
+ coordinates to base dataset coordinates, where the\
+ values at each base grid point are the xyz displacments\
+ needed to move that grid point\'s xyz values to the\
+ corresponding xyz values in the source dataset:\
+   base( (x,y,z) + WARP(x,y,z) ) matches source(x,y,z)\
+ Another way to think of this warp is that it \'pulls\'\
+ values back from source space to base space.\
+* 3dNwarpApply would use \'ppp_WARP\' to transform datasets\
+aligned with the source dataset to be aligned with the\
+base dataset.\
+** If you do NOT want this warp saved, use the option \'-nowarp\'.\
+-->> (However, this warp is usually the most valuable possible output!)\
+* If you want to calculate and save the inverse 3D warp,\
+use the option \'-iwarp\'.  This inverse warp will then be\
+saved in a dataset with prefix \'ppp_WARPINV\'.\
+* This inverse warp could be used to transform data from base\
+space to source space, if you need to do such an operation.\
+* You can easily compute the inverse later, say by a command like\
+ 3dNwarpCat -prefix Z_WARPINV \'INV(Z_WARP+tlrc)\'\
+or the inverse can be computed as needed in 3dNwarpApply, like\
+ 3dNwarpApply -nwarp \'INV(Z_WARP+tlrc)\' -source Dataset.nii ...""")
     resample = traits.Bool(
         desc='This option simply resamples the source dataset to match the'
         'base dataset grid.  You can use this if the two datasets'

nipype/interfaces/afni/tests/test_auto_AFNICommand.py

@@ -14,11 +14,6 @@ def test_AFNICommand_inputs():
             nohash=True,
             usedefault=True,
         ),
-        out_file=dict(
-            argstr='-prefix %s',
-            name_source=['in_file'],
-            name_template='%s_afni',
-        ),
         outputtype=dict(),
     )
     inputs = AFNICommand.input_spec()

nipype/interfaces/afni/tests/test_auto_AFNIPythonCommand.py

@@ -14,11 +14,6 @@ def test_AFNIPythonCommand_inputs():
             nohash=True,
             usedefault=True,
         ),
-        out_file=dict(
-            argstr='-prefix %s',
-            name_source=['in_file'],
-            name_template='%s_afni',
-        ),
         outputtype=dict(),
     )
     inputs = AFNIPythonCommand.input_spec()

nipype/interfaces/afni/tests/test_auto_Bandpass.py

@@ -46,7 +46,6 @@ def test_Bandpass_inputs():
         orthogonalize_file=dict(argstr='-ort %s', ),
         out_file=dict(
             argstr='-prefix %s',
-            genfile=True,
             name_source='in_file',
             name_template='%s_bp',
             position=1,

nipype/interfaces/afni/tests/test_auto_BlurToFWHM.py

@@ -25,7 +25,7 @@ def test_BlurToFWHM_inputs():
         ),
         out_file=dict(
             argstr='-prefix %s',
-            name_source=['in_file'],
+            name_source='in_file',
             name_template='%s_afni',
         ),
         outputtype=dict(),

nipype/interfaces/afni/tests/test_auto_DegreeCentrality.py

@@ -26,7 +26,7 @@ def test_DegreeCentrality_inputs():
         oned_file=dict(argstr='-out1D %s', ),
         out_file=dict(
             argstr='-prefix %s',
-            name_source=['in_file'],
+            name_source='in_file',
             name_template='%s_afni',
         ),
         outputtype=dict(),

nipype/interfaces/afni/tests/test_auto_ECM.py

@@ -30,7 +30,7 @@ def test_ECM_inputs():
         ),
         out_file=dict(
             argstr='-prefix %s',
-            name_source=['in_file'],
+            name_source='in_file',
             name_template='%s_afni',
         ),
         outputtype=dict(),

nipype/interfaces/afni/tests/test_auto_LFCD.py

@@ -25,7 +25,7 @@ def test_LFCD_inputs():
         ),
         out_file=dict(
             argstr='-prefix %s',
-            name_source=['in_file'],
+            name_source='in_file',
             name_template='%s_afni',
         ),
         outputtype=dict(),

nipype/interfaces/afni/tests/test_auto_Qwarp.py

@@ -117,8 +117,7 @@ def test_Qwarp_inputs():
         ),
         out_file=dict(
             argstr='-prefix %s',
-            genfile=True,
-            name_source=['in_file'],
+            name_source='in_file',
             name_template='%s_QW',
         ),
         out_weight_file=dict(argstr='-wtprefix %s', ),

nipype/interfaces/afni/tests/test_auto_TCorrMap.py

@@ -62,11 +62,6 @@ def test_TCorrMap_inputs():
             nohash=True,
             usedefault=True,
         ),
-        out_file=dict(
-            argstr='-prefix %s',
-            name_source=['in_file'],
-            name_template='%s_afni',
-        ),
         outputtype=dict(),
         pmean=dict(
             argstr='-Pmean %s',