[ENH] Mrtrix3 enhancements

doc/devel/matlab_example1.py

@@ -1,13 +1,17 @@
 from nipype.interfaces.matlab import MatlabCommand
-from nipype.interfaces.base import TraitedSpec, \
-    BaseInterface, BaseInterfaceInputSpec, File
+from nipype.interfaces.base import (
+    TraitedSpec,
+    BaseInterface,
+    BaseInterfaceInputSpec,
+    File,
+)
 import os
 from string import Template
 
 
 class ConmapTxt2MatInputSpec(BaseInterfaceInputSpec):
     in_file = File(exists=True, mandatory=True)
-    out_file = File('cmatrix.mat', usedefault=True)
+    out_file = File("cmatrix.mat", usedefault=True)
 
 
 class ConmapTxt2MatOutputSpec(TraitedSpec):
@@ -19,14 +23,15 @@ class ConmapTxt2Mat(BaseInterface):
     output_spec = ConmapTxt2MatOutputSpec
 
     def _run_interface(self, runtime):
-        d = dict(in_file=self.inputs.in_file,
-                 out_file=self.inputs.out_file)
+        d = dict(in_file=self.inputs.in_file, out_file=self.inputs.out_file)
         # This is your MATLAB code template
-        script = Template("""in_file = '$in_file';
+        script = Template(
+            """in_file = '$in_file';
                              out_file = '$out_file';
                              ConmapTxt2Mat(in_file, out_file);
                              exit;
-                          """).substitute(d)
+                          """
+        ).substitute(d)
 
         # mfile = True  will create an .m file with your script and executed.
         # Alternatively
@@ -43,5 +48,5 @@ def _run_interface(self, runtime):
 
     def _list_outputs(self):
         outputs = self._outputs().get()
-        outputs['out_file'] = os.path.abspath(self.inputs.out_file)
+        outputs["out_file"] = os.path.abspath(self.inputs.out_file)
         return outputs

doc/devel/matlab_example2.py

@@ -4,8 +4,7 @@
 
 
 class HelloWorldInputSpec(MatlabInputSpec):
-    name = traits.Str(mandatory=True,
-                      desc='Name of person to say hello to')
+    name = traits.Str(mandatory=True, desc="Name of person to say hello to")
 
 
 class HelloWorldOutputSpec(TraitedSpec):
@@ -29,6 +28,7 @@ class HelloWorld(MatlabCommand):
     >>> out = hello.run()
     >>> print out.outputs.matlab_output
     """
+
     input_spec = HelloWorldInputSpec
     output_spec = HelloWorldOutputSpec
 
@@ -37,7 +37,9 @@ def _my_script(self):
         script = """
         disp('Hello %s Python')
         two = 1 + 1
-        """ % (self.inputs.name)
+        """ % (
+            self.inputs.name
+        )
         return script
 
     def run(self, **inputs):

nipype/interfaces/mrtrix/convert.py

@@ -124,7 +124,9 @@ def track_gen(track_points):
                         "Expecting %s points, found only %s" % (stream_count, n_streams)
                     )
                     iflogger.error(
-                        "Expecting %s points, found only %s", stream_count, n_streams
+                        "Expecting %s points, found only %s",
+                        stream_count,
+                        n_streams,
                     )
                 break
             pts = np.ndarray(shape=(n_pts, pt_cols), dtype=f4dt, buffer=pts_str)
@@ -225,7 +227,8 @@ def _run_interface(self, runtime):
             self.inputs.registration_image_file
         ):
             iflogger.info(
-                "Applying transformation from matrix file %s", self.inputs.matrix_file
+                "Applying transformation from matrix file %s",
+                self.inputs.matrix_file,
             )
             xfm = np.genfromtxt(self.inputs.matrix_file)
             iflogger.info(xfm)

nipype/interfaces/mrtrix/preprocess.py

@@ -595,7 +595,11 @@ class GenerateWhiteMatterMaskInputSpec(CommandLineInputSpec):
         desc="Diffusion-weighted images",
     )
     binary_mask = File(
-        exists=True, argstr="%s", mandatory=True, position=-2, desc="Binary brain mask"
+        exists=True,
+        argstr="%s",
+        mandatory=True,
+        position=-2,
+        desc="Binary brain mask",
     )
     out_WMProb_filename = File(
         genfile=True,
@@ -669,7 +673,9 @@ class ErodeInputSpec(CommandLineInputSpec):
         argstr="-npass %s", desc="the number of passes (default: 1)"
     )
     dilate = traits.Bool(
-        argstr="-dilate", position=1, desc="Perform dilation rather than erosion"
+        argstr="-dilate",
+        position=1,
+        desc="Perform dilation rather than erosion",
     )
     quiet = traits.Bool(
         argstr="-quiet",
@@ -729,7 +735,10 @@ class ThresholdInputSpec(CommandLineInputSpec):
         desc="The input image to be thresholded",
     )
     out_filename = File(
-        genfile=True, argstr="%s", position=-1, desc="The output binary image mask."
+        genfile=True,
+        argstr="%s",
+        position=-1,
+        desc="The output binary image mask.",
     )
     absolute_threshold_value = traits.Float(
         argstr="-abs %s", desc="Specify threshold value as absolute intensity."

nipype/interfaces/mrtrix3/__init__.py

@@ -2,29 +2,32 @@
 # vi: set ft=python sts=4 ts=4 sw=4 et:
 # -*- coding: utf-8 -*-
 """MRTrix3 provides software tools to perform various types of diffusion MRI analyses."""
+from .connectivity import BuildConnectome, LabelConfig, LabelConvert
+from .preprocess import (
+    ACTPrepareFSL,
+    DWIBiasCorrect,
+    DWIDenoise,
+    DWIPreproc,
+    MRDeGibbs,
+    ReplaceFSwithFIRST,
+    ResponseSD,
+)
+from .reconst import ConstrainedSphericalDeconvolution, EstimateFOD, FitTensor
+from .tracking import Tractography
 from .utils import (
-    Mesh2PVE,
-    Generate5tt,
+    TCK2VTK,
     BrainMask,
-    TensorMetrics,
     ComputeTDI,
-    TCK2VTK,
-    MRMath,
+    DWIExtract,
+    Generate5tt,
+    Mesh2PVE,
+    MRCat,
     MRConvert,
+    MRMath,
     MRResize,
-    DWIExtract,
-    SHConv,
+    MRTransform,
     SH2Amp,
+    SHConv,
+    TensorMetrics,
+    TransformFSLConvert,
 )
-from .preprocess import (
-    ResponseSD,
-    ACTPrepareFSL,
-    ReplaceFSwithFIRST,
-    DWIPreproc,
-    DWIDenoise,
-    MRDeGibbs,
-    DWIBiasCorrect,
-)
-from .tracking import Tractography
-from .reconst import FitTensor, EstimateFOD, ConstrainedSphericalDeconvolution
-from .connectivity import LabelConfig, LabelConvert, BuildConnectome

nipype/interfaces/mrtrix3/base.py

@@ -2,15 +2,15 @@
 # vi: set ft=python sts=4 ts=4 sw=4 et:
 # -*- coding: utf-8 -*-
 
-from ... import logging, LooseVersion
+from ... import LooseVersion, logging
 from ...utils.filemanip import which
 from ..base import (
-    CommandLineInputSpec,
     CommandLine,
-    traits,
+    CommandLineInputSpec,
     File,
-    isdefined,
     PackageInfo,
+    isdefined,
+    traits,
 )
 
 iflogger = logging.getLogger("nipype.interface")
@@ -79,6 +79,15 @@ class MRTrix3BaseInputSpec(CommandLineInputSpec):
         exists=True, argstr="-fslgrad %s %s", desc="bvecs file in FSL format"
     )
     in_bval = File(exists=True, desc="bvals file in FSL format")
+    out_bvec = File(
+        exists=False,
+        argstr="-export_grad_fsl %s %s",
+        desc="export bvec file in FSL format",
+    )
+    out_bval = File(
+        exists=False,
+        desc="export bval file in FSL format",
+    )
 
 
 class MRTrix3Base(CommandLine):
@@ -96,6 +105,8 @@ def _format_arg(self, name, trait_spec, value):
 
         if name == "in_bvec":
             return trait_spec.argstr % (value, self.inputs.in_bval)
+        if name == "out_bvec":
+            return trait_spec.argstr % (value, self.inputs.out_bval)
 
         return super(MRTrix3Base, self)._format_arg(name, trait_spec, value)
 

nipype/interfaces/mrtrix3/preprocess.py

@@ -19,7 +19,11 @@
 
 class DWIDenoiseInputSpec(MRTrix3BaseInputSpec):
     in_file = File(
-        exists=True, argstr="%s", position=-2, mandatory=True, desc="input DWI image"
+        exists=True,
+        argstr="%s",
+        position=-2,
+        mandatory=True,
+        desc="input DWI image",
     )
     mask = File(exists=True, argstr="-mask %s", position=1, desc="mask image")
     extent = traits.Tuple(
@@ -88,7 +92,11 @@ class DWIDenoise(MRTrix3Base):
 
 class MRDeGibbsInputSpec(MRTrix3BaseInputSpec):
     in_file = File(
-        exists=True, argstr="%s", position=-2, mandatory=True, desc="input DWI image"
+        exists=True,
+        argstr="%s",
+        position=-2,
+        mandatory=True,
+        desc="input DWI image",
     )
     axes = traits.ListInt(
         default_value=[0, 1],
@@ -177,7 +185,11 @@ class MRDeGibbs(MRTrix3Base):
 
 class DWIBiasCorrectInputSpec(MRTrix3BaseInputSpec):
     in_file = File(
-        exists=True, argstr="%s", position=-2, mandatory=True, desc="input DWI image"
+        exists=True,
+        argstr="%s",
+        position=-2,
+        mandatory=True,
+        desc="input DWI image",
     )
     in_mask = File(argstr="-mask %s", desc="input mask image for bias field estimation")
     use_ants = traits.Bool(
@@ -245,7 +257,11 @@ def _format_arg(self, name, trait_spec, value):
 
 class DWIPreprocInputSpec(MRTrix3BaseInputSpec):
     in_file = File(
-        exists=True, argstr="%s", position=0, mandatory=True, desc="input DWI image"
+        exists=True,
+        argstr="%s",
+        position=0,
+        mandatory=True,
+        desc="input DWI image",
     )
     out_file = File(
         "preproc.mif",
@@ -292,7 +308,8 @@ class DWIPreprocInputSpec(MRTrix3BaseInputSpec):
         desc="Manually provide additional command-line options to the topup command",
     )
     export_grad_mrtrix = traits.Bool(
-        argstr="-export_grad_mrtrix", desc="export new gradient files in mrtrix format"
+        argstr="-export_grad_mrtrix",
+        desc="export new gradient files in mrtrix format",
     )
     export_grad_fsl = traits.Bool(
         argstr="-export_grad_fsl", desc="export gradient files in FSL format"
@@ -387,7 +404,11 @@ class ResponseSDInputSpec(MRTrix3BaseInputSpec):
         desc="response estimation algorithm (multi-tissue)",
     )
     in_file = File(
-        exists=True, argstr="%s", position=-5, mandatory=True, desc="input DWI image"
+        exists=True,
+        argstr="%s",
+        position=-5,
+        mandatory=True,
+        desc="input DWI image",
     )
     mtt_file = File(argstr="%s", position=-4, desc="input 5tt image")
     wm_file = File(
@@ -511,10 +532,17 @@ class ReplaceFSwithFIRSTInputSpec(CommandLineInputSpec):
         desc="input anatomical image",
     )
     in_t1w = File(
-        exists=True, argstr="%s", mandatory=True, position=-3, desc="input T1 image"
+        exists=True,
+        argstr="%s",
+        mandatory=True,
+        position=-3,
+        desc="input T1 image",
     )
     in_config = File(
-        exists=True, argstr="%s", position=-2, desc="connectome configuration file"
+        exists=True,
+        argstr="%s",
+        position=-2,
+        desc="connectome configuration file",
     )
 
     out_file = File(

nipype/interfaces/mrtrix3/tests/test_auto_MRCat.py

@@ -0,0 +1,73 @@
+# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
+from ..utils import MRCat
+
+
+def test_MRCat_inputs():
+    input_map = dict(
+        args=dict(
+            argstr="%s",
+        ),
+        axis=dict(
+            argstr="-axis %s",
+        ),
+        bval_scale=dict(
+            argstr="-bvalue_scaling %s",
+        ),
+        datatype=dict(
+            argstr="-datatype %s",
+        ),
+        environ=dict(
+            nohash=True,
+            usedefault=True,
+        ),
+        grad_file=dict(
+            argstr="-grad %s",
+            extensions=None,
+            xor=["grad_fsl"],
+        ),
+        grad_fsl=dict(
+            argstr="-fslgrad %s %s",
+            xor=["grad_file"],
+        ),
+        in_bval=dict(
+            extensions=None,
+        ),
+        in_bvec=dict(
+            argstr="-fslgrad %s %s",
+            extensions=None,
+        ),
+        in_files=dict(
+            argstr="%s",
+            mandatory=True,
+            position=-2,
+        ),
+        nthreads=dict(
+            argstr="-nthreads %d",
+            nohash=True,
+        ),
+        out_file=dict(
+            argstr="%s",
+            extensions=None,
+            mandatory=True,
+            position=-1,
+            usedefault=True,
+        ),
+    )
+    inputs = MRCat.input_spec()
+
+    for key, metadata in list(input_map.items()):
+        for metakey, value in list(metadata.items()):
+            assert getattr(inputs.traits()[key], metakey) == value
+
+
+def test_MRCat_outputs():
+    output_map = dict(
+        out_file=dict(
+            extensions=None,
+        ),
+    )
+    outputs = MRCat.output_spec()
+
+    for key, metadata in list(output_map.items()):
+        for metakey, value in list(metadata.items()):
+            assert getattr(outputs.traits()[key], metakey) == value