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Merge pull request #3516 from DimitriPapadopoulos/doc
DOC: Fix a few more typos
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‎doc/devel/interface_specs.rst

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@@ -148,7 +148,7 @@ base class down to subclasses).:
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``SlicerCommandLineInputSpec``: Defines inputs common to all Slicer classes (``module``)
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Most developers will only need to code at the the interface-level (i.e. implementing custom class inheriting from one of the above classes).
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Most developers will only need to code at the interface-level (i.e. implementing custom class inheriting from one of the above classes).
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Output Specs
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^^^^^^^^^^^^
@@ -519,7 +519,7 @@ SPM
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For SPM-mediated interfaces:
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* ``_jobtype`` and ``_jobname``: special names used used by the SPM job manager. You can find them by saving your batch job as an .m file and looking up the code.
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* ``_jobtype`` and ``_jobname``: special names used by the SPM job manager. You can find them by saving your batch job as an .m file and looking up the code.
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And optionally:
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‎doc/devel/provenance.rst

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@@ -5,7 +5,7 @@ W3C PROV support
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Overview
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--------
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We're using the the `W3C PROV data model <http://www.w3.org/TR/prov-dm/>`_ to
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We're using the `W3C PROV data model <http://www.w3.org/TR/prov-dm/>`_ to
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capture and represent provenance in Nipype.
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For an overview see:

‎nipype/interfaces/afni/utils.py

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@@ -2151,7 +2151,7 @@ class NwarpCatInputSpec(AFNICommandInputSpec):
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usedefault=True,
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)
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expad = traits.Int(
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desc="Pad the nonlinear warps by the given number of voxels voxels in "
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desc="Pad the nonlinear warps by the given number of voxels in "
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"all directions. The warp displacements are extended by linear "
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"extrapolation from the faces of the input grid..",
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argstr="-expad %d",

‎nipype/interfaces/diffusion_toolkit/dti.py

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@@ -208,7 +208,7 @@ class DTITrackerInputSpec(CommandLineInputSpec):
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desc="set angle threshold. default value is 35 degree", argstr="-at %f"
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)
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angle_threshold_weight = traits.Float(
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desc="set angle threshold weighting factor. weighting will be be applied "
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desc="set angle threshold weighting factor. weighting will be applied "
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"on top of the angle_threshold",
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argstr="-atw %f",
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)

‎nipype/interfaces/dtitk/utils.py

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@@ -161,7 +161,7 @@ class TVResampleInputSpec(CommandLineInputSpec):
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desc="how to align output volume to input volume",
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)
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interpolation = traits.Enum(
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"LEI", "EI", argstr="-interp %s", desc="Log Euclidean Euclidean Interpolation"
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"LEI", "EI", argstr="-interp %s", desc="Log Euclidean Interpolation"
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)
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array_size = traits.Tuple(
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(traits.Int(), traits.Int(), traits.Int()),

‎nipype/interfaces/minc/minc.py

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@@ -1285,7 +1285,7 @@ class BeastInputSpec(CommandLineInputSpec):
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-positive: Specify mask of positive segmentation (inside mask) instead of the default mask.
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-output_selection: Specify file to output selected files.
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-count: Specify file to output the patch count.
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-mask: Specify a segmentation mask instead of the the default mask.
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-mask: Specify a segmentation mask instead of the default mask.
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-no_mask: Do not apply a segmentation mask. Perform the segmentation over the entire image.
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-no_positive: Do not apply a positive mask.
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Generic options for all commands:

‎nipype/interfaces/mipav/developer.py

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@@ -1253,7 +1253,7 @@ class MedicAlgorithmSPECTRE2010InputSpec(CommandLineInputSpec):
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traits.Bool,
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File(),
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hash_files=False,
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desc="Tissue classification of of the whole input volume.",
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desc="Tissue classification of the whole input volume.",
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argstr="--outFANTASM %s",
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)
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outd0 = traits.Either(
@@ -1310,7 +1310,7 @@ class MedicAlgorithmSPECTRE2010OutputSpec(TraitedSpec):
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)
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outPrior = File(desc="Probability prior from the atlas registrations", exists=True)
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outFANTASM = File(
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desc="Tissue classification of of the whole input volume.", exists=True
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desc="Tissue classification of the whole input volume.", exists=True
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)
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outd0 = File(desc="Initial Brainmask", exists=True)
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outMidsagittal = File(desc="Plane dividing the brain hemispheres", exists=True)

‎nipype/interfaces/semtools/diffusion/gtract.py

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@@ -1119,7 +1119,7 @@ class gtractCoRegAnatomyInputSpec(CommandLineInputSpec):
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argstr="--inputVolume %s",
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)
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inputAnatomicalVolume = File(
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desc="Required: input anatomical image file name. It is recommended that that the input anatomical image has been skull stripped and has the same orientation as the DWI scan.",
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desc="Required: input anatomical image file name. It is recommended that the input anatomical image has been skull stripped and has the same orientation as the DWI scan.",
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exists=True,
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argstr="--inputAnatomicalVolume %s",
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)

‎nipype/interfaces/slicer/generate_classes.py

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@@ -196,7 +196,7 @@ def generate_class(
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if longFlagNode:
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# Prefer to use longFlag as name if it is given, rather than the parameter name
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longFlagName = longFlagNode[0].firstChild.nodeValue
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# SEM automatically strips prefixed "--" or "-" from from xml before processing
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# SEM automatically strips prefixed "--" or "-" from xml before processing
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# we need to replicate that behavior here The following
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# two nodes in xml have the same behavior in the program
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# <longflag>--test</longflag>

‎nipype/interfaces/slicer/registration/brainsfit.py

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@@ -279,7 +279,7 @@ class BRAINSFitInputSpec(CommandLineInputSpec):
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argstr="--numberOfThreads %d",
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)
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forceMINumberOfThreads = traits.Int(
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desc="Force the the maximum number of threads to use for non thread safe MI metric. CAUTION: Inconsistent results my arise!",
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desc="Force the maximum number of threads to use for non thread safe MI metric. CAUTION: Inconsistent results my arise!",
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argstr="--forceMINumberOfThreads %d",
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)
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debugLevel = traits.Int(

‎nipype/interfaces/slicer/registration/brainsresample.py

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@@ -94,7 +94,7 @@ class BRAINSResample(SEMLikeCommandLine):
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category: Registration
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description:
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This program resamples an image image using a deformation field or a transform (BSpline, Affine, Rigid, etc.).
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This program resamples an image using a deformation field or a transform (BSpline, Affine, Rigid, etc.).
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version: 3.0.0

‎nipype/interfaces/spm/model.py

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@@ -616,7 +616,7 @@ class ThresholdInputSpec(SPMCommandInputSpec):
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desc=(
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"In case no clusters survive the "
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"topological inference step this "
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"will pick a culster with the highes "
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"will pick a culster with the highest "
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"sum of t-values. Use with care."
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),
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)

‎nipype/pipeline/engine/utils.py

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@@ -1030,7 +1030,7 @@ def generate_expanded_graph(graph_in):
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iterables = {}
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# the source node iterables values
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src_values = [getattr(iter_src.inputs, field) for field in src_fields]
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# if there is one source field, then the key is the the source value,
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# if there is one source field, then the key is the source value,
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# otherwise the key is the tuple of source values
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if len(src_values) == 1:
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key = src_values[0]

‎nipype/utils/spm_flat_config.m

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@@ -1,7 +1,7 @@
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function cfgstruct = spm_flat_config(print_names)
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% Get a flat spm_config structure, with option to print out names
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%
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% This calls spm_config() to get the the nested configuration
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% This calls spm_config() to get the nested configuration
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% structure from spm. We use this to fetch documentation, the
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% flattened structure is much easier to search through. If
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% print_names is true (value of 1) it will print out the configuration

‎nipype/utils/tests/test_filemanip.py

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@@ -631,7 +631,7 @@ def test_path_strict_resolve(tmpdir):
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"""Check the monkeypatch to test strict resolution of Path."""
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tmpdir.chdir()
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# Default strict=False should work out out of the box
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# Default strict=False should work out of the box
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testfile = Path("somefile.txt")
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resolved = "%s/somefile.txt" % tmpdir
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assert str(path_resolve(testfile)) == resolved

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