add documentation & doc tests to fsl preprocess

Author: neuroumbrage

.cache/v/cache/lastfailed

@@ -0,0 +1,4 @@
+{
+  "nipype/pipeline/engine/tests/test_engine.py::test_deep_nested_write_graph_runs": true, 
+  "nipype/pipeline/engine/tests/test_engine.py::test_write_graph_runs": true
+}

README.rst

@@ -78,8 +78,8 @@ Support and Communication
 -------------------------
 
 If you have a problem or would like to ask a question about how to do something in Nipype please open an issue to
-`NeuroStars.org <http://neurostars.org>`_ with a *nipype* tag. `NeuroStars.org <http://neurostars.org>`_  is a 
-platform similar to StackOverflow but dedicated to neuroinformatics. 
+`NeuroStars.org <http://neurostars.org>`_ with a *nipype* tag. `NeuroStars.org <http://neurostars.org>`_  is a
+platform similar to StackOverflow but dedicated to neuroinformatics.
 
 To participate in the Nipype development related discussions please use the following mailing list::
 

nipype/algorithms/tests/test_auto_CompCor.py

@@ -17,6 +17,8 @@ def test_ComputeDVARS_inputs():
     ),
     in_mask=dict(mandatory=True,
     ),
+    intensity_normalization=dict(usedefault=True,
+    ),
     remove_zerovariance=dict(usedefault=True,
     ),
     save_all=dict(usedefault=True,

nipype/algorithms/tests/test_auto_ComputeDVARS.py

@@ -19,6 +19,8 @@ def test_FramewiseDisplacement_inputs():
     ),
     out_file=dict(usedefault=True,
     ),
+    parameter_source=dict(mandatory=True,
+    ),
     radius=dict(usedefault=True,
     ),
     save_plot=dict(usedefault=True,

nipype/algorithms/tests/test_auto_ErrorMap.py

@@ -18,6 +18,7 @@ def test_BBRegister_inputs():
     usedefault=True,
     ),
     init=dict(argstr='--init-%s',
+    mandatory=True,
     xor=['init_reg_file'],
     ),
     init_reg_file=dict(argstr='--init-reg %s',

nipype/algorithms/tests/test_auto_FramewiseDisplacement.py

@@ -118,15 +118,17 @@ class BET(FSLCommand):
     """Use FSL BET command for skull stripping.
 
     For complete details, see the `BET Documentation.
-    <http://www.fmrib.ox.ac.uk/fsl/bet2/index.html>`_
+    <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/BET/UserGuide>`_
 
     Examples
     --------
     >>> from nipype.interfaces import fsl
-    >>> from nipype.testing import  example_data
     >>> btr = fsl.BET()
-    >>> btr.inputs.in_file = example_data('structural.nii')
+    >>> btr.inputs.in_file = 'structural.nii'
     >>> btr.inputs.frac = 0.7
+    >>> btr.inputs.out_file = 'brain_anat.nii'
+    >>> btr.cmdline  # doctest: +ALLOW_UNICODE
+    'bet structural.nii brain_anat.nii -f 0.70'
     >>> res = btr.run() # doctest: +SKIP
 
     """
@@ -275,7 +277,7 @@ class FASTOutputSpec(TraitedSpec):
 
     mixeltype = File(desc="path/name of mixeltype volume file _mixeltype")
 
-    partial_volume_map = File(desc="path/name of partial volume file _pveseg")
+    partial_volume_map = File(desc='path/name of partial volume file _pveseg')
     partial_volume_files = OutputMultiPath(File(
         desc='path/name of partial volumes files one for each class, _pve_x'))
 
@@ -288,18 +290,17 @@ class FAST(FSLCommand):
     """ Use FSL FAST for segmenting and bias correction.
 
     For complete details, see the `FAST Documentation.
-    <http://www.fmrib.ox.ac.uk/fsl/fast4/index.html>`_
+    <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FAST>`_
 
     Examples
     --------
     >>> from nipype.interfaces import fsl
-    >>> from nipype.testing import example_data
-
-    Assign options through the ``inputs`` attribute:
-
     >>> fastr = fsl.FAST()
-    >>> fastr.inputs.in_files = example_data('structural.nii')
-    >>> out = fastr.run() #doctest: +SKIP
+    >>> fastr.inputs.in_files = 'structural.nii'
+    >>> fastr.inputs.out_basename = 'fast_'
+    >>> fastr.cmdline  # doctest: +ALLOW_UNICODE
+    'fast -o fast_ -S 1 structural.nii'
+    >>> out = fastr.run()  # doctest: +SKIP
 
     """
     _cmd = 'fast'
@@ -308,12 +309,12 @@ class FAST(FSLCommand):
 
     def _format_arg(self, name, spec, value):
         # first do what should be done in general
-        formated = super(FAST, self)._format_arg(name, spec, value)
+        formatted = super(FAST, self)._format_arg(name, spec, value)
         if name == 'in_files':
             # FAST needs the -S parameter value to correspond to the number
             # of input images, otherwise it will ignore all but the first
-            formated = "-S %d %s" % (len(value), formated)
-        return formated
+            formatted = "-S %d %s" % (len(value), formatted)
+        return formatted
 
     def _list_outputs(self):
         outputs = self.output_spec().get()
@@ -526,7 +527,7 @@ class FLIRT(FSLCommand):
     """Use FSL FLIRT for coregistration.
 
     For complete details, see the `FLIRT Documentation.
-    <http://www.fmrib.ox.ac.uk/fsl/flirt/index.html>`_
+    <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FLIRT>`_
 
     To print out the command line help, use:
         fsl.FLIRT().inputs_help()
@@ -665,14 +666,18 @@ class MCFLIRT(FSLCommand):
     """Use FSL MCFLIRT to do within-modality motion correction.
 
     For complete details, see the `MCFLIRT Documentation.
-    <http://www.fmrib.ox.ac.uk/fsl/mcflirt/index.html>`_
+    <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/MCFLIRT>`_
 
     Examples
     --------
     >>> from nipype.interfaces import fsl
-    >>> from nipype.testing import example_data
-    >>> mcflt = fsl.MCFLIRT(in_file=example_data('functional.nii'), cost='mutualinfo')
-    >>> res = mcflt.run() # doctest: +SKIP
+    >>> mcflt = fsl.MCFLIRT()
+    >>> mcflt.inputs.in_file = 'functional.nii'
+    >>> mcflt.inputs.cost = 'mutualinfo'
+    >>> mcflt.inputs.out_file = 'moco.nii'
+    >>> mcflt.cmdline # doctest: +ALLOW_UNICODE
+    'mcflirt -in functional.nii -cost mutualinfo -out moco.nii'
+    >>> res = mcflt.run()  # doctest: +SKIP
 
     """
     _cmd = 'mcflirt'
@@ -918,6 +923,9 @@ class FNIRTOutputSpec(TraitedSpec):
 class FNIRT(FSLCommand):
     """Use FSL FNIRT for non-linear registration.
 
+    For complete details, see the `MCFLIRT Documentation.
+    <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FNIRT>`_
+
     Examples
     --------
     >>> from nipype.interfaces import fsl
@@ -1218,6 +1226,9 @@ class SUSANOutputSpec(TraitedSpec):
 class SUSAN(FSLCommand):
     """ use FSL SUSAN to perform smoothing
 
+    For complete details, see the `MCFLIRT Documentation.
+    <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/SUSAN>`_
+
     Examples
     --------