ENH: added interface for FSL's dual_regression

nipype/interfaces/fsl/model.py

@@ -1815,6 +1815,72 @@ def _format_arg(self, name, spec, value):
         return super(Cluster, self)._format_arg(name, spec, value)
 
 
+class DualRegressionInputSpec(FSLCommandInputSpec):
+    in_files = InputMultiPath(File(exists=True), argstr="%s", mandatory=True,
+        position=-1, sep=" ",
+        desc="List all subjects' preprocessed, standard-space 4D datasets",)
+    group_IC_maps_4D = File(exists=True, argstr="%s", mandatory=True, position=1,
+        desc="4D image containing spatial IC maps (melodic_IC) from the "
+        "whole-group ICA analysis")
+    des_norm = traits.Bool(True, argstr="%i",  position=2, usedefault=True,
+        desc="Whether to variance-normalise the timecourses used as the "
+        "stage-2 regressors; True is default and recommended")
+    one_sample_group_mean = traits.Bool(argstr="-1", position=3,
+        desc="perform 1-sample group-mean test instead of generic "
+        "permutation test")
+    design_file = File(exists=True, argstr="%s", position=3,
+        desc="Design matrix for final cross-subject modelling with "
+        "randomise")
+    con_file = File(exists=True, argstr="%s", position=4,
+        desc="Design contrasts for final cross-subject modelling with "
+        "randomise")
+    n_perm = traits.Int(argstr="%i", mandatory=True, position=5,
+        desc="Number of permutations for randomise; set to 1 for just raw "
+        "tstat output, set to 0 to not run randomise at all.")
+    out_dir = Directory("output", argstr="%s", usedefault=True, position=6,
+        desc="This directory will be created to hold all output and logfiles",
+        genfile=True)
+
+
+class DualRegressionOutputSpec(TraitedSpec):
+    out_dir = Directory(exists=True)
+
+
+class DualRegression(FSLCommand):
+    """Wrapper Script for Dual Regression Workflow
+
+    Examples
+    --------
+
+    >>> dual_regression = DualRegression()
+    >>> dual_regression.inputs.in_files = ["functional.nii", "functional2.nii", "functional3.nii"]
+    >>> dual_regression.inputs.group_IC_maps_4D = "allFA.nii"
+    >>> dual_regression.inputs.des_norm = False
+    >>> dual_regression.inputs.one_sample_group_mean = True
+    >>> dual_regression.inputs.n_perm = 10
+    >>> dual_regression.inputs.out_dir = "my_output_directory"
+    >>> dual_regression.cmdline # doctest: +ALLOW_UNICODE
+    u'dual_regression allFA.nii 0 -1 10 my_output_directory functional.nii functional2.nii functional3.nii'
+    >>> dual_regression.run() # doctest: +SKIP
+
+    """
+    input_spec = DualRegressionInputSpec
+    output_spec = DualRegressionOutputSpec
+    _cmd = 'dual_regression'
+
+    def _list_outputs(self):
+        outputs = self.output_spec().get()
+        if isdefined(self.inputs.out_dir):
+            outputs['out_dir'] = os.path.abspath(self.inputs.out_dir)
+        else:
+            outputs['out_dir'] = self._gen_filename("out_dir")
+        return outputs
+
+    def _gen_filename(self, name):
+        if name == "out_dir":
+            return os.getcwd()
+
+
 class RandomiseInputSpec(FSLCommandInputSpec):
     in_file = File(exists=True, desc='4D input file', argstr='-i %s',
                    position=0, mandatory=True)

nipype/interfaces/fsl/tests/test_auto_DualRegression.py

@@ -0,0 +1,64 @@
+# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
+from __future__ import unicode_literals
+from ..model import DualRegression
+
+
+def test_DualRegression_inputs():
+    input_map = dict(args=dict(argstr='%s',
+    ),
+    con_file=dict(argstr='%s',
+    position=4,
+    ),
+    des_norm=dict(argstr='%i',
+    position=2,
+    usedefault=True,
+    ),
+    design_file=dict(argstr='%s',
+    position=3,
+    ),
+    environ=dict(nohash=True,
+    usedefault=True,
+    ),
+    group_IC_maps_4D=dict(argstr='%s',
+    mandatory=True,
+    position=1,
+    ),
+    ignore_exception=dict(nohash=True,
+    usedefault=True,
+    ),
+    in_files=dict(argstr='%s',
+    mandatory=True,
+    position=-1,
+    sep=' ',
+    ),
+    n_perm=dict(argstr='%i',
+    mandatory=True,
+    position=5,
+    ),
+    one_sample_group_mean=dict(argstr='-1',
+    position=3,
+    ),
+    out_dir=dict(argstr='%s',
+    genfile=True,
+    position=6,
+    usedefault=True,
+    ),
+    output_type=dict(),
+    terminal_output=dict(nohash=True,
+    ),
+    )
+    inputs = DualRegression.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_DualRegression_outputs():
+    output_map = dict(out_dir=dict(),
+    )
+    outputs = DualRegression.output_spec()
+
+    for key, metadata in list(output_map.items()):
+        for metakey, value in list(metadata.items()):
+            assert getattr(outputs.traits()[key], metakey) == value