fix: do not monkeypatch Tuple and Either

Author: oesteban

nipype/algorithms/confounds.py

@@ -22,7 +22,7 @@
 from ..interfaces.base import (traits, TraitedSpec, BaseInterface,
                                BaseInterfaceInputSpec, File, isdefined,
                                InputMultiPath, OutputMultiPath,
-                               SimpleInterface)
+                               SimpleInterface, Either, Tuple)
 from ..utils import NUMPY_MMAP
 from ..utils.misc import normalize_mc_params
 
@@ -56,7 +56,7 @@ class ComputeDVARSInputSpec(BaseInterfaceInputSpec):
     series_tr = traits.Float(desc='repetition time in sec.')
     save_plot = traits.Bool(False, usedefault=True, desc='write DVARS plot')
     figdpi = traits.Int(100, usedefault=True, desc='output dpi for the plot')
-    figsize = traits.Tuple(
+    figsize = Tuple(
         traits.Float(11.7),
         traits.Float(2.3),
         usedefault=True,
@@ -263,7 +263,7 @@ class FramewiseDisplacementInputSpec(BaseInterfaceInputSpec):
         False, usedefault=True, desc='calculate FD in mm/s')
     figdpi = traits.Int(
         100, usedefault=True, desc='output dpi for the FD plot')
-    figsize = traits.Tuple(
+    figsize = Tuple(
         traits.Float(11.7),
         traits.Float(2.3),
         usedefault=True,
@@ -398,7 +398,7 @@ class CompCorInputSpec(BaseInterfaceInputSpec):
         'components_file.txt',
         usedefault=True,
         desc='Filename to store physiological components')
-    num_components = traits.Either(
+    num_components = Either(
         'all', traits.Range(low=1), xor=['variance_threshold'],
         desc='Number of components to return from the decomposition. If '
              '`num_components` is `all`, then all components will be '
@@ -440,10 +440,10 @@ class CompCorInputSpec(BaseInterfaceInputSpec):
     repetition_time = traits.Float(
         desc='Repetition time (TR) of series - derived from image header if '
         'unspecified')
-    save_pre_filter = traits.Either(
+    save_pre_filter = Either(
         traits.Bool, File, default=False, usedefault=True,
         desc='Save pre-filter basis as text file')
-    save_metadata = traits.Either(
+    save_metadata = Either(
         traits.Bool, File, default=False, usedefault=True,
         desc='Save component metadata as text file')
     ignore_initial_volumes = traits.Range(

nipype/algorithms/mesh.py

@@ -14,7 +14,7 @@
 
 from .. import logging
 from ..interfaces.base import (BaseInterface, traits, TraitedSpec, File,
-                               BaseInterfaceInputSpec)
+                               BaseInterfaceInputSpec, Either, Tuple)
 from ..interfaces.vtkbase import tvtk
 from ..interfaces import vtkbase as VTKInfo
 IFLOGGER = logging.getLogger('nipype.interface')
@@ -281,11 +281,11 @@ class MeshWarpMathsInputSpec(BaseInterfaceInputSpec):
         mandatory=True,
         desc=('Input surface in vtk format, with associated warp '
               'field as point data (ie. from ComputeMeshWarp'))
-    float_trait = traits.Either(
+    float_trait = Either(
         traits.Float(1.0),
-        traits.Tuple(traits.Float(1.0), traits.Float(1.0), traits.Float(1.0)))
+        Tuple(traits.Float(1.0), traits.Float(1.0), traits.Float(1.0)))
 
-    operator = traits.Either(
+    operator = Either(
         float_trait,
         File(exists=True),
         default=1.0,

nipype/algorithms/metrics.py

@@ -19,7 +19,7 @@
 
 from ..interfaces.base import (
     SimpleInterface, BaseInterface, traits, TraitedSpec, File,
-    InputMultiPath, BaseInterfaceInputSpec,
+    Either, InputMultiPath, BaseInterfaceInputSpec,
     isdefined)
 from ..interfaces.nipy.base import NipyBaseInterface
 
@@ -631,7 +631,7 @@ class SimilarityInputSpec(BaseInterfaceInputSpec):
     volume2 = File(exists=True, desc="3D/4D volume", mandatory=True)
     mask1 = File(exists=True, desc="3D volume")
     mask2 = File(exists=True, desc="3D volume")
-    metric = traits.Either(
+    metric = Either(
         traits.Enum('cc', 'cr', 'crl1', 'mi', 'nmi', 'slr'),
         traits.Callable(),
         desc="""str or callable

nipype/algorithms/misc.py

@@ -22,7 +22,7 @@
 from . import metrics as nam
 from ..interfaces.base import (
     BaseInterface, traits, TraitedSpec, File, InputMultiPath, OutputMultiPath,
-    BaseInterfaceInputSpec, isdefined, DynamicTraitedSpec, Undefined)
+    BaseInterfaceInputSpec, isdefined, DynamicTraitedSpec, Undefined, Either, Tuple)
 from ..utils.filemanip import fname_presuffix, split_filename, ensure_list
 from ..utils import NUMPY_MMAP
 
@@ -36,7 +36,7 @@ class PickAtlasInputSpec(BaseInterfaceInputSpec):
         exists=True,
         desc="Location of the atlas that will be used.",
         mandatory=True)
-    labels = traits.Either(
+    labels = Either(
         traits.Int,
         traits.List(traits.Int),
         desc=("Labels of regions that will be included in the mask. Must be\
@@ -1099,7 +1099,7 @@ def _list_outputs(self):
 class SplitROIsInputSpec(TraitedSpec):
     in_file = File(exists=True, mandatory=True, desc='file to be splitted')
     in_mask = File(exists=True, desc='only process files inside mask')
-    roi_size = traits.Tuple(
+    roi_size = Tuple(
         traits.Int, traits.Int, traits.Int, desc='desired ROI size')
 
 

nipype/algorithms/modelgen.py

@@ -25,7 +25,7 @@
 
 from ..utils import NUMPY_MMAP
 from ..interfaces.base import (BaseInterface, TraitedSpec, InputMultiPath,
-                               traits, File, Bunch, BaseInterfaceInputSpec,
+                               traits, File, Bunch, Either, BaseInterfaceInputSpec,
                                isdefined)
 from ..utils.filemanip import ensure_list
 from ..utils.misc import normalize_mc_params
@@ -284,7 +284,7 @@ class SpecifyModelInputSpec(BaseInterfaceInputSpec):
         'that should be tossed',
         copyfile=False)
     functional_runs = InputMultiPath(
-        traits.Either(traits.List(File(exists=True)), File(exists=True)),
+        Either(traits.List(File(exists=True)), File(exists=True)),
         mandatory=True,
         desc='Data files for model. List of 4D '
         'files or list of list of 3D '

nipype/interfaces/afni/base.py

@@ -13,7 +13,7 @@
 from ... import logging, LooseVersion
 from ...utils.filemanip import split_filename
 from ..base import (CommandLine, traits, CommandLineInputSpec, isdefined, File,
-                    TraitedSpec, PackageInfo)
+                    TraitedSpec, PackageInfo, Either)
 from ...external.due import BibTeX
 
 # Use nipype's logging system
@@ -248,7 +248,7 @@ def no_afni():
 class AFNIPythonCommandInputSpec(CommandLineInputSpec):
     outputtype = traits.Enum(
         'AFNI', list(Info.ftypes.keys()), desc='AFNI output filetype')
-    py27_path = traits.Either(
+    py27_path = Either(
         'python2', File(exists=True), usedefault=True, default='python2')
 
 

nipype/interfaces/afni/model.py

@@ -15,7 +15,8 @@
 import os
 
 from ..base import (CommandLineInputSpec, CommandLine, Directory, TraitedSpec,
-                    traits, isdefined, File, InputMultiPath, Undefined, Str)
+                    traits, isdefined, File, InputMultiPath, Undefined, Str,
+                    Either, Tuple)
 from ...external.due import BibTeX
 
 from .base import (AFNICommandBase, AFNICommand, AFNICommandInputSpec,
@@ -101,7 +102,7 @@ class DeconvolveInputSpec(AFNICommandInputSpec):
         desc='don\'t consider all zero matrix columns to be the type of error '
         'that \'gotforit\' is needed to ignore.',
         argstr='-allzero_OK')
-    dname = traits.Tuple(
+    dname = Tuple(
         Str,
         Str,
         desc='set environmental variable to provided value',
@@ -133,7 +134,7 @@ class DeconvolveInputSpec(AFNICommandInputSpec):
         desc='degree of polynomial corresponding to the null hypothesis '
         '[default: 1]',
         argstr='-polort %d')
-    ortvec = traits.Tuple(
+    ortvec = Tuple(
         File(desc='filename', exists=True),
         Str(desc='label'),
         desc='this option lets you input a rectangular array of 1 or more '
@@ -180,7 +181,7 @@ class DeconvolveInputSpec(AFNICommandInputSpec):
         argstr='-num_stimts %d',
         position=-6)
     stim_times = traits.List(
-        traits.Tuple(
+        Tuple(
             traits.Int(desc='k-th response model'),
             File(desc='stimulus timing file', exists=True),
             Str(desc='model')),
@@ -189,7 +190,7 @@ class DeconvolveInputSpec(AFNICommandInputSpec):
         argstr='-stim_times %d %s \'%s\'...',
         position=-5)
     stim_label = traits.List(
-        traits.Tuple(
+        Tuple(
             traits.Int(desc='k-th input stimulus'),
             Str(desc='stimulus label')),
         desc='label for kth input stimulus (e.g., Label1)',
@@ -213,7 +214,7 @@ class DeconvolveInputSpec(AFNICommandInputSpec):
         argstr='-gltsym \'SYM: %s\'...',
         position=-2)
     glt_label = traits.List(
-        traits.Tuple(
+        Tuple(
             traits.Int(desc='k-th general linear test'),
             Str(desc='GLT label')),
         desc='general linear test (i.e., contrast) labels',
@@ -492,8 +493,8 @@ class RemlfitInputSpec(AFNICommandInputSpec):
         'to the \'rbeta_file\' and/or \'obeta_file\' output datasets.',
         argstr='-nobout')
     gltsym = traits.List(
-        traits.Either(
-            traits.Tuple(File(exists=True), Str()), traits.Tuple(Str(),
+        Either(
+            Tuple(File(exists=True), Str()), Tuple(Str(),
                                                                  Str())),
         desc='read a symbolic GLT from input file and associate it with a '
         'label. As in Deconvolve, you can also use the \'SYM:\' method '

nipype/interfaces/afni/preprocess.py

@@ -13,7 +13,7 @@
                                 fname_presuffix)
 from ..base import (CommandLineInputSpec, CommandLine, TraitedSpec, traits,
                     isdefined, File, InputMultiPath, Undefined, Str,
-                    InputMultiObject)
+                    InputMultiObject, Either, Tuple)
 
 from .base import (AFNICommandBase, AFNICommand, AFNICommandInputSpec,
                    AFNICommandOutputSpec, AFNIPythonCommandInputSpec,
@@ -54,7 +54,7 @@ class AlignEpiAnatPyInputSpec(AFNIPythonCommandInputSpec):
         mandatory=True,
         exists=True,
         copyfile=False)
-    epi_base = traits.Either(
+    epi_base = Either(
         traits.Range(low=0),
         traits.Enum('mean', 'median', 'max'),
         desc='the epi base used in alignment'
@@ -361,7 +361,7 @@ class AllineateInputSpec(AFNICommandInputSpec):
         desc='Set the weighting for each voxel in the base dataset; '
         'larger weights mean that voxel count more in the cost function. '
         'Must be defined on the same grid as the base dataset')
-    weight = traits.Either(
+    weight = Either(
         File(exists=True),
         traits.Float(),
         argstr='-weight %s',
@@ -2047,7 +2047,7 @@ class SegInputSpec(CommandLineInputSpec):
         mandatory=True,
         exists=True,
         copyfile=True)
-    mask = traits.Either(
+    mask = Either(
         traits.Enum('AUTO'),
         File(exists=True),
         desc='only non-zero voxels in mask are analyzed. mask can either be a '
@@ -2258,7 +2258,7 @@ class TCorrMapInputSpec(AFNICommandInputSpec):
     mask = File(exists=True, argstr='-mask %s')
     automask = traits.Bool(argstr='-automask')
     polort = traits.Int(argstr='-polort %d')
-    bandpass = traits.Tuple(
+    bandpass = Tuple(
         (traits.Float(), traits.Float()), argstr='-bpass %f %f')
     regress_out_timeseries = File(exists=True, argstr='-ort %s')
     blur_fwhm = traits.Float(argstr='-Gblur %f')
@@ -2591,11 +2591,11 @@ class TProjectInputSpec(AFNICommandInputSpec):
                 ++ That is, 'fset' contains a different nuisance time
                    series for each voxel (e.g., from AnatICOR).
                 ++ Multiple -dsort options are allowed.""")
-    bandpass = traits.Tuple(
+    bandpass = Tuple(
         traits.Float, traits.Float,
         desc="""Remove all frequencies EXCEPT those in the range""",
         argstr='-bandpass %g %g')
-    stopband = traits.Tuple(
+    stopband = Tuple(
         traits.Float, traits.Float,
         desc="""Remove all frequencies in the range""",
         argstr='-stopband %g %g')
@@ -2693,7 +2693,7 @@ class TShiftInputSpec(AFNICommandInputSpec):
         desc='different interpolation methods (see 3dTshift for details) '
         'default = Fourier',
         argstr='-%s')
-    tpattern = traits.Either(
+    tpattern = Either(
         traits.Enum('alt+z', 'altplus',    # Synonyms
                     'alt+z2',
                     'alt-z', 'altminus',   # Synonyms
@@ -2704,7 +2704,7 @@ class TShiftInputSpec(AFNICommandInputSpec):
         desc='use specified slice time pattern rather than one in header',
         argstr='-tpattern %s',
         xor=['slice_timing'])
-    slice_timing = traits.Either(
+    slice_timing = Either(
         File(exists=True),
         traits.List(traits.Float),
         desc='time offsets from the volume acquisition onset for each slice',
@@ -2861,8 +2861,8 @@ class VolregInputSpec(AFNICommandInputSpec):
         mandatory=True,
         exists=True,
         copyfile=False)
-    in_weight_volume = traits.Either(
-        traits.Tuple(File(exists=True), traits.Int),
+    in_weight_volume = Either(
+        Tuple(File(exists=True), traits.Int),
         File(exists=True),
         desc='weights for each voxel specified by a file with an '
              'optional volume number (defaults to 0)',
@@ -3234,8 +3234,8 @@ class QwarpInputSpec(AFNICommandInputSpec):
         argstr='-wball %s',
         minlen=5,
         maxlen=5)
-    traits.Tuple((traits.Float(), traits.Float()), argstr='-bpass %f %f')
-    wmask = traits.Tuple(
+    Tuple((traits.Float(), traits.Float()), argstr='-bpass %f %f')
+    wmask = Tuple(
         (File(exists=True), traits.Float()),
         desc='-wmask ws f'
         'Similar to \'-wball\', but here, you provide a dataset \'ws\''