ENH: Add three new workbench command interfaces

nipype/interfaces/workbench/__init__.py

@@ -3,4 +3,4 @@
 # vi: set ft=python sts=4 ts=4 sw=4 et:
 """Connectome Workbench is a visualization for neuroimaging data, esp. derived from HCP data."""
 from .metric import MetricResample
-from .cifti import CiftiSmooth
+from .cifti import CiftiSmooth, CiftiCorrelation, CiftiParcellate, CiftiSeparateMetric

nipype/interfaces/workbench/cifti.py

@@ -154,3 +154,278 @@ class CiftiSmooth(WBCommand):
     input_spec = CiftiSmoothInputSpec
     output_spec = CiftiSmoothOutputSpec
     _cmd = "wb_command -cifti-smoothing"
+
+
+class CiftiCorrelationInputSpec(CommandLineInputSpec):
+    in_file = File(
+        exists=True,
+        mandatory=True,
+        argstr="%s ",
+        position=0,
+        desc="The input ptseries or dense series",
+    )
+    out_file = File(
+        name_source=["in_file"],
+        name_template="correlation_matrix_%s.nii",
+        keep_extension=True,
+        argstr=" %s",
+        position=1,
+        desc="The output CIFTI",
+    )
+
+    roi_override = traits.Bool(
+        exists=True,
+        argstr="-roi-override %s ",
+        position=2,
+        desc=" perform correlation from a subset of rows to all rows",
+    )
+
+    left_roi = File(
+        exists=True,
+        position=3,
+        argstr="-left-roi %s",
+        desc="Specify the left roi metric  to use",
+    )
+
+    right_roi = File(
+        exists=True,
+        position=5,
+        argstr="-right-roi %s",
+        desc="Specify the right  roi metric  to use",
+    )
+    cerebellum_roi = File(
+        exists=True,
+        position=6,
+        argstr="-cerebellum-roi %s",
+        desc="specify the cerebellum meytric to use",
+    )
+
+    vol_roi = File(
+        exists=True,
+        position=7,
+        argstr="-vol-roi %s",
+        desc="volume roi to use",
+    )
+
+    cifti_roi = File(
+        exists=True,
+        position=8,
+        argstr="-cifti-roi %s",
+        desc="cifti roi to use",
+    )
+    weights_file = File(
+        exists=True,
+        position=9,
+        argstr="-weights %s",
+        desc="specify the cerebellum surface  metricto use",
+    )
+
+    fisher_ztrans = traits.Bool(
+        position=10,
+        argstr="-fisher-z",
+        desc=" fisherz transfrom",
+    )
+    no_demean = traits.Bool(
+        position=11,
+        argstr="-fisher-z",
+        desc=" fisherz transfrom",
+    )
+    compute_covariance = traits.Bool(
+        position=12,
+        argstr="-covariance ",
+        desc=" compute covariance instead of correlation",
+    )
+
+
+class CiftiCorrelationOutputSpec(TraitedSpec):
+    out_file = File(exists=True, desc="output CIFTI file")
+
+
+class CiftiCorrelation(WBCommand):
+    r"""
+    Compute correlation from CIFTI file
+    The input cifti file must have a brain models mapping on the chosen
+    dimension, columns for .ptseries or .dtseries,  
+    >>> cifticorr = CiftiCorrelation()
+    >>> cifticorr.inputs.in_file = 'sub-01XX_task-rest.ptseries.nii'
+    >>> cifticorr.inputs.out_file = 'sub_01XX_task-rest.pconn.nii'
+    >>> cifticorr.cmdline
+    wb_command  -cifti-correlation sub-01XX_task-rest.ptseries.nii \
+        'sub_01XX_task-rest.pconn.nii'
+    """
+
+    input_spec = CiftiCorrelationInputSpec
+    output_spec = CiftiCorrelationOutputSpec
+    _cmd = "wb_command  -cifti-correlation"
+
+
+class CiftiParcellateInputSpec(CommandLineInputSpec):
+    in_file = File(
+        exists=True,
+        mandatory=True,
+        argstr="%s ",
+        position=0,
+        desc="The input CIFTI file",
+    )
+    atlas_label = traits.File(
+        mandatory=True,
+        argstr="%s ",
+        position=1,
+        desc="atlas label, in mm",
+    )
+    direction = traits.Enum(
+        "ROW",
+        "COLUMN",
+        mandatory=True,
+        argstr="%s ",
+        position=2,
+        desc="which dimension to smooth along, ROW or COLUMN",
+    )
+    out_file = File(
+        name_source=["in_file"],
+        name_template="parcelated_%s.nii",
+        keep_extension=True,
+        argstr=" %s",
+        position=3,
+        desc="The output CIFTI",
+    )
+
+    spatial_weights = traits.Str(
+        argstr="-spatial-weights ",
+        position=4,
+        desc=" spatial weight file",
+    )
+
+    left_area_surf = File(
+        exists=True,
+        position=5,
+        argstr="-left-area-surface %s",
+        desc="Specify the left surface to use",
+    )
+
+    right_area_surf = File(
+        exists=True,
+        position=6,
+        argstr="-right-area-surface %s",
+        desc="Specify the right surface to use",
+    )
+    cerebellum_area_surf = File(
+        exists=True,
+        position=7,
+        argstr="-cerebellum-area-surf %s",
+        desc="specify the cerebellum surface to use",
+    )
+
+    left_area_metric = File(
+        exists=True,
+        position=8,
+        argstr="-left-area-metric %s",
+        desc="Specify the left surface metric to use",
+    )
+
+    right_area_metric = File(
+        exists=True,
+        position=9,
+        argstr="-right-area-metric %s",
+        desc="Specify the right surface  metric to use",
+    )
+    cerebellum_area_metric = File(
+        exists=True,
+        position=10,
+        argstr="-cerebellum-area-metric %s",
+        desc="specify the cerebellum surface  metricto use",
+    )
+
+    cifti_weights = File(
+        exists=True,
+        position=11,
+        argstr="-cifti-weights %s",
+        desc="cifti file containing weights",
+    )
+    cor_method = traits.Str(
+        position=12,
+        default="MEAN ",
+        argstr="-method %s",
+        desc=" correlation method, option inlcude MODE",
+    )
+
+
+class CiftiParcellateOutputSpec(TraitedSpec):
+    out_file = File(exists=True, desc="output CIFTI file")
+
+
+class CiftiParcellate(WBCommand):
+    r"""
+    Extract timeseries from CIFTI file
+    The input cifti file must have a brain models mapping on the chosen
+    dimension, columns for .dtseries,  
+    >>> ciftiparcel = CiftiParcellate()
+    >>> ciftiparcel.inputs.in_file = 'sub-01XX_task-rest.dtseries.nii'
+    >>> ciftiparcel.inputs.out_file = 'sub_01XX_task-rest.ptseries.nii'
+    >>>  ciftiparcel.inputs.atlas_label = 'schaefer_space-fsLR_den-32k_desc-400_atlas.dlabel.nii' 
+    >>> ciftiparcel.inputs.direction = 'COLUMN'
+    >>> ciftiparcel.cmdline
+    wb_command -cifti-parcellate sub-01XX_task-rest.dtseries.nii \
+    schaefer_space-fsLR_den-32k_desc-400_atlas.dlabel.nii   COLUMN \  
+    sub_01XX_task-rest.ptseries.nii
+    """
+    input_spec = CiftiParcellateInputSpec
+    output_spec = CiftiParcellateOutputSpec
+    _cmd = "wb_command -cifti-parcellate"
+
+
+class CiftiSeparateMetricInputSpec(CommandLineInputSpec):
+    in_file = File(
+        exists=True,
+        mandatory=True,
+        argstr="%s ",
+        position=0,
+        desc="The input dense series",
+    )
+    direction = traits.Enum(
+        "ROW",
+        "COLUMN",
+        mandatory=True,
+        argstr="%s ",
+        position=1,
+        desc="which dimension to smooth along, ROW or COLUMN",
+    )
+    metric = traits.Str(
+        mandatory=True,
+        argstr=" -metric %s ",
+        position=2,
+        desc="which of the structure eg CORTEX_LEFT CORTEX_RIGHT"
+        "check https://www.humanconnectome.org/software/workbench-command/-cifti-separate ",
+    )
+    out_file = File(
+        name_source=["in_file"],
+        name_template="correlation_matrix_%s.func.gii",
+        keep_extension=True,
+        argstr=" %s",
+        position=3,
+        desc="The gifti output, iether left and right",
+    )
+
+
+class CiftiSeparateMetricOutputSpec(TraitedSpec):
+    out_file = File(exists=True, desc="output CIFTI file")
+
+
+class CiftiSeparateMetric(WBCommand):
+    r"""
+    Extract left or right hemisphere surface from CIFTI file (.dtseries)
+    other structure can also be extracted
+    The input cifti file must have a brain models mapping on the chosen
+    dimension, columns for .dtseries,  
+    >>> ciftiseparate = CiftiSeparateMetric()
+    >>> ciftiseparate.inputs.in_file = 'sub-01XX_task-rest.dtseries.nii'
+    >>> ciftiseparate.inputs.metric = "CORTEX_LEFT" # extract left hemisphere
+    >>> ciftiseparate.inputs.out_file = 'sub_01XX_task-rest_hemi-L.func.gii'
+    >>> ciftiseparate.inputs.direction = 'COLUMN'
+    >>> ciftiseparate.cmdline
+    wb_command  -cifti-separate 'sub-01XX_task-rest.dtseries.nii'  COLUMN \
+      -metric CORTEX_LEFT 'sub_01XX_task-rest_hemi-L.func.gii'
+    """
+    input_spec = CiftiSeparateMetricInputSpec
+    output_spec = CiftiSeparateMetricOutputSpec
+    _cmd = "wb_command  -cifti-separate "

nipype/interfaces/workbench/tests/test_auto_CiftiCorrelation.py

@@ -0,0 +1,93 @@
+# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
+from ..cifti import CiftiCorrelation
+
+
+def test_CiftiCorrelation_inputs():
+    input_map = dict(
+        args=dict(
+            argstr="%s",
+        ),
+        cerebellum_roi=dict(
+            argstr="-cerebellum-roi %s",
+            extensions=None,
+            position=6,
+        ),
+        cifti_roi=dict(
+            argstr="-cifti-roi %s",
+            extensions=None,
+            position=8,
+        ),
+        compute_covariance=dict(
+            argstr="-covariance ",
+            position=12,
+        ),
+        environ=dict(
+            nohash=True,
+            usedefault=True,
+        ),
+        fisher_ztrans=dict(
+            argstr="-fisher-z",
+            position=10,
+        ),
+        in_file=dict(
+            argstr="%s ",
+            extensions=None,
+            mandatory=True,
+            position=0,
+        ),
+        left_roi=dict(
+            argstr="-left-roi %s",
+            extensions=None,
+            position=3,
+        ),
+        no_demean=dict(
+            argstr="-fisher-z",
+            position=11,
+        ),
+        out_file=dict(
+            argstr=" %s",
+            extensions=None,
+            keep_extension=True,
+            name_source=["in_file"],
+            name_template="correlation_matrix_%s.nii",
+            position=1,
+        ),
+        right_roi=dict(
+            argstr="-right-roi %s",
+            extensions=None,
+            position=5,
+        ),
+        roi_override=dict(
+            argstr="-roi-override %s ",
+            exists=True,
+            position=2,
+        ),
+        vol_roi=dict(
+            argstr="-vol-roi %s",
+            extensions=None,
+            position=7,
+        ),
+        weights_file=dict(
+            argstr="-weights %s",
+            extensions=None,
+            position=9,
+        ),
+    )
+    inputs = CiftiCorrelation.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_CiftiCorrelation_outputs():
+    output_map = dict(
+        out_file=dict(
+            extensions=None,
+        ),
+    )
+    outputs = CiftiCorrelation.output_spec()
+
+    for key, metadata in list(output_map.items()):
+        for metakey, value in list(metadata.items()):
+            assert getattr(outputs.traits()[key], metakey) == value