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satrasatra
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Merge pull request #1956 from imalone/fslmaths-dimension-reducing
[ENH] FSL maths interface, add the remaining dimension reduction operations…
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‎nipype/interfaces/fsl/__init__.py‎

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@@ -29,6 +29,8 @@
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TractSkeleton, MakeDyadicVectors, BEDPOSTX5, XFibres5)
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from .maths import (ChangeDataType, Threshold, MeanImage, ApplyMask,
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IsotropicSmooth, TemporalFilter, DilateImage, ErodeImage,
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SpatialFilter, UnaryMaths, BinaryMaths, MultiImageMaths)
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SpatialFilter, UnaryMaths, BinaryMaths, MultiImageMaths,
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MaxnImage, MinImage, MedianImage, PercentileImage,
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AR1Image)
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from .possum import B0Calc

‎nipype/interfaces/fsl/maths.py‎

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@@ -174,6 +174,98 @@ class MaxImage(MathsCommand):
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_suffix = "_max"
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class PercentileImageInput(MathsInput):
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dimension = traits.Enum("T", "X", "Y", "Z", usedefault=True,
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argstr="-%sperc", position=4,
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desc="dimension to percentile across")
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perc = traits.Range(low=0, high=100, usedefault=False,
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argstr="%f", position=5,
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desc=("nth percentile (0-100) of FULL RANGE "
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"across dimension"))
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class PercentileImage(MathsCommand):
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"""Use fslmaths to generate a percentile image across a given dimension.
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Examples
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--------
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>>> from nipype.interfaces.fsl.maths import MaxImage
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>>> percer = PercentileImage()
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>>> percer.inputs.in_file = "functional.nii" # doctest: +SKIP
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>>> percer.dimension = "T"
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>>> percer.perc = 90
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>>> percer.cmdline # doctest: +SKIP
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'fslmaths functional.nii -Tperc 90 functional_perc.nii'
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"""
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input_spec = PercentileImageInput
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_suffix = "_perc"
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class MaxnImageInput(MathsInput):
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dimension = traits.Enum("T", "X", "Y", "Z", usedefault=True,
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argstr="-%smaxn", position=4,
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desc="dimension to index max across")
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class MaxnImage(MathsCommand):
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"""Use fslmaths to generate an image of index of max across
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a given dimension.
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"""
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input_spec = MaxnImageInput
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_suffix = "_maxn"
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class MinImageInput(MathsInput):
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dimension = traits.Enum("T", "X", "Y", "Z", usedefault=True,
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argstr="-%smin", position=4,
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desc="dimension to min across")
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class MinImage(MathsCommand):
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"""Use fslmaths to generate a minimum image across a given dimension.
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"""
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input_spec = MinImageInput
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_suffix = "_min"
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class MedianImageInput(MathsInput):
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dimension = traits.Enum("T", "X", "Y", "Z", usedefault=True,
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argstr="-%smedian", position=4,
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desc="dimension to median across")
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class MedianImage(MathsCommand):
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"""Use fslmaths to generate a median image across a given dimension.
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"""
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input_spec = MedianImageInput
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_suffix = "_median"
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class AR1ImageInput(MathsInput):
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dimension = traits.Enum("T", "X", "Y", "Z", usedefault=True,
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argstr="-%sar1", position=4,
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desc=("dimension to find AR(1) coefficient"
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"across"))
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class AR1Image(MathsCommand):
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"""Use fslmaths to generate an AR1 coefficient image across a
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given dimension. (Should use -odt float and probably demean first)
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"""
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input_spec = AR1ImageInput
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_suffix = "_ar1"
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class IsotropicSmoothInput(MathsInput):
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fwhm = traits.Float(mandatory=True, xor=["sigma"],

‎nipype/interfaces/fsl/tests/test_auto_AR1Image.py‎

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# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
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from __future__ import unicode_literals
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from ..maths import AR1Image
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def test_AR1Image_inputs():
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input_map = dict(args=dict(argstr='%s',
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),
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dimension=dict(argstr='-%sar1',
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position=4,
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usedefault=True,
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),
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environ=dict(nohash=True,
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usedefault=True,
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),
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ignore_exception=dict(nohash=True,
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usedefault=True,
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),
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in_file=dict(argstr='%s',
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mandatory=True,
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position=2,
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),
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internal_datatype=dict(argstr='-dt %s',
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position=1,
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),
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nan2zeros=dict(argstr='-nan',
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position=3,
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),
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out_file=dict(argstr='%s',
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genfile=True,
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hash_files=False,
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position=-2,
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),
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output_datatype=dict(argstr='-odt %s',
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position=-1,
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),
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output_type=dict(),
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terminal_output=dict(nohash=True,
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),
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)
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inputs = AR1Image.input_spec()
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for key, metadata in list(input_map.items()):
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for metakey, value in list(metadata.items()):
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assert getattr(inputs.traits()[key], metakey) == value
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def test_AR1Image_outputs():
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output_map = dict(out_file=dict(),
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)
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outputs = AR1Image.output_spec()
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for key, metadata in list(output_map.items()):
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for metakey, value in list(metadata.items()):
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assert getattr(outputs.traits()[key], metakey) == value

‎nipype/interfaces/fsl/tests/test_auto_MaxnImage.py‎

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# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
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from __future__ import unicode_literals
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from ..maths import MaxnImage
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def test_MaxnImage_inputs():
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input_map = dict(args=dict(argstr='%s',
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),
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dimension=dict(argstr='-%smaxn',
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position=4,
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usedefault=True,
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),
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environ=dict(nohash=True,
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usedefault=True,
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),
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ignore_exception=dict(nohash=True,
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usedefault=True,
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),
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in_file=dict(argstr='%s',
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mandatory=True,
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position=2,
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),
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internal_datatype=dict(argstr='-dt %s',
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position=1,
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),
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nan2zeros=dict(argstr='-nan',
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position=3,
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),
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out_file=dict(argstr='%s',
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genfile=True,
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hash_files=False,
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position=-2,
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),
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output_datatype=dict(argstr='-odt %s',
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position=-1,
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),
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output_type=dict(),
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terminal_output=dict(nohash=True,
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),
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)
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inputs = MaxnImage.input_spec()
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for key, metadata in list(input_map.items()):
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for metakey, value in list(metadata.items()):
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assert getattr(inputs.traits()[key], metakey) == value
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def test_MaxnImage_outputs():
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output_map = dict(out_file=dict(),
50+
)
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outputs = MaxnImage.output_spec()
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for key, metadata in list(output_map.items()):
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for metakey, value in list(metadata.items()):
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assert getattr(outputs.traits()[key], metakey) == value

‎nipype/interfaces/fsl/tests/test_auto_MedianImage.py‎

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# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
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from __future__ import unicode_literals
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from ..maths import MedianImage
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def test_MedianImage_inputs():
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input_map = dict(args=dict(argstr='%s',
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),
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dimension=dict(argstr='-%smedian',
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position=4,
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usedefault=True,
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),
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environ=dict(nohash=True,
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usedefault=True,
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),
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ignore_exception=dict(nohash=True,
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usedefault=True,
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),
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in_file=dict(argstr='%s',
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mandatory=True,
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position=2,
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),
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internal_datatype=dict(argstr='-dt %s',
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position=1,
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),
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nan2zeros=dict(argstr='-nan',
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position=3,
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),
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out_file=dict(argstr='%s',
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genfile=True,
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hash_files=False,
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position=-2,
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),
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output_datatype=dict(argstr='-odt %s',
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position=-1,
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),
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output_type=dict(),
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terminal_output=dict(nohash=True,
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),
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)
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inputs = MedianImage.input_spec()
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for key, metadata in list(input_map.items()):
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for metakey, value in list(metadata.items()):
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assert getattr(inputs.traits()[key], metakey) == value
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def test_MedianImage_outputs():
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output_map = dict(out_file=dict(),
50+
)
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outputs = MedianImage.output_spec()
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for key, metadata in list(output_map.items()):
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for metakey, value in list(metadata.items()):
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assert getattr(outputs.traits()[key], metakey) == value

‎nipype/interfaces/fsl/tests/test_auto_MinImage.py‎

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# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
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from __future__ import unicode_literals
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from ..maths import MinImage
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def test_MinImage_inputs():
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input_map = dict(args=dict(argstr='%s',
8+
),
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dimension=dict(argstr='-%smin',
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position=4,
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usedefault=True,
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),
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environ=dict(nohash=True,
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usedefault=True,
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),
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ignore_exception=dict(nohash=True,
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usedefault=True,
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),
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in_file=dict(argstr='%s',
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mandatory=True,
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position=2,
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),
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internal_datatype=dict(argstr='-dt %s',
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position=1,
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),
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nan2zeros=dict(argstr='-nan',
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position=3,
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),
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out_file=dict(argstr='%s',
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genfile=True,
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hash_files=False,
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position=-2,
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),
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output_datatype=dict(argstr='-odt %s',
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position=-1,
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),
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output_type=dict(),
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terminal_output=dict(nohash=True,
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),
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)
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inputs = MinImage.input_spec()
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for key, metadata in list(input_map.items()):
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for metakey, value in list(metadata.items()):
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assert getattr(inputs.traits()[key], metakey) == value
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def test_MinImage_outputs():
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output_map = dict(out_file=dict(),
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)
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outputs = MinImage.output_spec()
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for key, metadata in list(output_map.items()):
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for metakey, value in list(metadata.items()):
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assert getattr(outputs.traits()[key], metakey) == value

‎nipype/interfaces/fsl/tests/test_auto_PercentileImage.py‎

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# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
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from __future__ import unicode_literals
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from ..maths import PercentileImage
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def test_PercentileImage_inputs():
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input_map = dict(args=dict(argstr='%s',
8+
),
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dimension=dict(argstr='-%sperc',
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position=4,
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usedefault=True,
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),
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environ=dict(nohash=True,
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usedefault=True,
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),
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ignore_exception=dict(nohash=True,
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usedefault=True,
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),
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in_file=dict(argstr='%s',
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mandatory=True,
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position=2,
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),
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internal_datatype=dict(argstr='-dt %s',
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position=1,
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),
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nan2zeros=dict(argstr='-nan',
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position=3,
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),
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out_file=dict(argstr='%s',
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genfile=True,
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hash_files=False,
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position=-2,
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),
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output_datatype=dict(argstr='-odt %s',
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position=-1,
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),
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output_type=dict(),
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perc=dict(argstr='%f',
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position=5,
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usedefault=False,
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),
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terminal_output=dict(nohash=True,
43+
),
44+
)
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inputs = PercentileImage.input_spec()
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for key, metadata in list(input_map.items()):
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for metakey, value in list(metadata.items()):
49+
assert getattr(inputs.traits()[key], metakey) == value
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52+
def test_PercentileImage_outputs():
53+
output_map = dict(out_file=dict(),
54+
)
55+
outputs = PercentileImage.output_spec()
56+
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for key, metadata in list(output_map.items()):
58+
for metakey, value in list(metadata.items()):
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assert getattr(outputs.traits()[key], metakey) == value

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