Merge branch 'master' of https://github.com/nipy/nipype into raise_from

Author: Shoshana Berleant

CHANGES

@@ -1,6 +1,7 @@
 Release 0.12.0-rc1 (April 20, 2016)
 ============
 
+* ENH: Added grad_dev input to fsl.dti.bedpostx5 interface(https://github.com/nipy/nipype/pull/1493)
 * ENH: ResourceMultiProc plugin to support resource allocation (https://github.com/nipy/nipype/pull/1372)
 * ENH: Added dcm2niix interface (https://github.com/nipy/nipype/pull/1435)
 * ENH: Add nipype_crash_search command (https://github.com/nipy/nipype/pull/1422)

nipype/__init__.py

@@ -55,26 +55,10 @@ def test(self, label='fast', verbose=1, extra_argv=['--exe'],
     test = _NoseTester().test
 del nosetester
 
-
-def _test_local_install():
-    """ Warn the user that running with nipy being
-        imported locally is a bad idea.
-    """
-    if os.getcwd() == os.sep.join(
-            os.path.abspath(__file__).split(os.sep)[:-2]):
-        import warnings
-        warnings.warn('Running the tests from the install directory may '
-                      'trigger some failures')
-
-_test_local_install()
-
 # Set up package information function
 from .pkg_info import get_pkg_info as _get_pkg_info
 get_info = lambda: _get_pkg_info(os.path.dirname(__file__))
 
-# Cleanup namespace
-del _test_local_install
-
 # If this file is exec after being imported, the following lines will
 # fail
 try:

nipype/interfaces/fsl/dti.py

@@ -265,6 +265,7 @@ class BEDPOSTX5InputSpec(FSLXCommandInputSpec):
                         usedefault=True, position=1, argstr='%s')
     gradnonlin = traits.Bool(False, argstr='-g', desc=('consider gradient '
                                                        'nonlinearities, default off'))
+    grad_dev = File(exists=True, desc='grad_dev file, if gradnonlin, -g is True')
     use_gpu = traits.Bool(False, desc='Use the GPU version of bedpostx')
 
 
@@ -348,6 +349,10 @@ def _run_interface(self, runtime):
                  os.path.join(subjectdir, 'bvals'))
         copyfile(self.inputs.bvecs,
                  os.path.join(subjectdir, 'bvecs'))
+        if isdefined(self.inputs.grad_dev):
+            _, _, ext = split_filename(self.inputs.grad_dev)
+            copyfile(self.inputs.grad_dev,
+                     os.path.join(subjectdir, 'grad_dev' + ext))
 
         retval = super(BEDPOSTX5, self)._run_interface(runtime)
 

nipype/interfaces/fsl/epi.py

@@ -314,11 +314,9 @@ class ApplyTOPUPInputSpec(FSLCommandInputSpec):
     encoding_file = File(exists=True, mandatory=True,
                          desc='name of text file with PE directions/times',
                          argstr='--datain=%s')
-    in_index = traits.List(traits.Int, argstr='--inindex=%s', sep=',',
-                           mandatory=True,
-                           desc=('comma separated list of indicies into '
-                                 '--datain of the input image (to be '
-                                 'corrected)'))
+    in_index = traits.List(
+        traits.Int, argstr='--inindex=%s', sep=',',
+        desc='comma separated list of indices corresponding to --datain')
     in_topup_fieldcoef = File(exists=True, argstr="--topup=%s", copyfile=False,
                               requires=['in_topup_movpar'],
                               desc=('topup file containing the field '
@@ -360,7 +358,6 @@ class ApplyTOPUP(FSLCommand):
     >>> applytopup = ApplyTOPUP()
     >>> applytopup.inputs.in_files = ["epi.nii", "epi_rev.nii"]
     >>> applytopup.inputs.encoding_file = "topup_encoding.txt"
-    >>> applytopup.inputs.in_index = [1,2]
     >>> applytopup.inputs.in_topup_fieldcoef = "topup_fieldcoef.nii.gz"
     >>> applytopup.inputs.in_topup_movpar = "topup_movpar.txt"
     >>> applytopup.inputs.output_type = "NIFTI_GZ"
@@ -374,6 +371,17 @@ class ApplyTOPUP(FSLCommand):
     input_spec = ApplyTOPUPInputSpec
     output_spec = ApplyTOPUPOutputSpec
 
+    def _parse_inputs(self, skip=None):
+        if skip is None:
+            skip = []
+
+        # If not defined, assume index are the first N entries in the
+        # parameters file, for N input images.
+        if not isdefined(self.inputs.in_index):
+            self.inputs.in_index = list(range(1, len(self.inputs.in_files) + 1))
+
+        return super(ApplyTOPUP, self)._parse_inputs(skip=skip)
+
     def _format_arg(self, name, spec, value):
         if name == 'in_topup_fieldcoef':
             return spec.argstr % value.split('_fieldcoef')[0]

nipype/interfaces/fsl/tests/test_auto_ApplyTOPUP.py

@@ -22,7 +22,6 @@ def test_ApplyTOPUP_inputs():
     sep=',',
     ),
     in_index=dict(argstr='--inindex=%s',
-    mandatory=True,
     sep=',',
     ),
     in_topup_fieldcoef=dict(argstr='--topup=%s',

nipype/interfaces/fsl/tests/test_auto_BEDPOSTX5.py

@@ -36,6 +36,7 @@ def test_BEDPOSTX5_inputs():
     ),
     fudge=dict(argstr='-w %d',
     ),
+    grad_dev=dict(),
     gradnonlin=dict(argstr='-g',
     ),
     ignore_exception=dict(nohash=True,

nipype/interfaces/io.py

@@ -2458,8 +2458,8 @@ class JSONFileGrabber(IOBase):
     {'param1': 'overrideMe', 'param3': 1.0}
     >>> jsonSource.inputs.in_file = 'jsongrabber.txt'
     >>> res = jsonSource.run()
-    >>> pprint.pprint(res.outputs.get())  # doctest: +NORMALIZE_WHITESPACE
-    {'param1': 'exampleStr', 'param2': 4, 'param3': 1.0}
+    >>> pprint.pprint(res.outputs.get())  # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
+    {'param1': ...'exampleStr', 'param2': 4, 'param3': 1.0}
 
 
     """