updated to fileformats to vendor namespace

Author: tclose

example-specs/interface/nipype/afni/interfaces/afn_ito_nifti.yaml

@@ -36,7 +36,7 @@ inputs:
   # from the nipype interface, but you may want to be more specific, particularly
   # for file types, where specifying the format also specifies the file that will be
   # passed to the field in the automatically generated unittests.
-    in_file: fileformats.medimage_afni.ThreeD
+    in_file: fileformats.vendor.afni.medimage.ThreeD
     # type=file|default=<undefined>: input file to 3dAFNItoNIFTI
   callable_defaults:
   # dict[str, str] - names of methods/callable classes defined in the adjacent `*_callables.py`

example-specs/interface/nipype/afni/interfaces/calc.yaml

@@ -72,7 +72,7 @@ outputs:
   # from the nipype interface, but you may want to be more specific, particularly
   # for file types, where specifying the format also specifies the file that will be
   # passed to the field in the automatically generated unittests.
-    out_file: fileformats.medimage_afni.All1
+    out_file: fileformats.vendor.afni.medimage.All1
     # type=file: output file
     # type=file|default=<undefined>: output image file name
   callables:

example-specs/interface/nipype/afni/interfaces/cat.yaml

@@ -56,7 +56,7 @@ outputs:
   # from the nipype interface, but you may want to be more specific, particularly
   # for file types, where specifying the format also specifies the file that will be
   # passed to the field in the automatically generated unittests.
-    out_file: fileformats.medimage_afni.OneD
+    out_file: fileformats.vendor.afni.medimage.OneD
     # type=file: output file
     # type=file|default='catout.1d': output (concatenated) file name
   callables:

example-specs/interface/nipype/afni/interfaces/convert_dset.yaml

@@ -54,7 +54,7 @@ outputs:
   # from the nipype interface, but you may want to be more specific, particularly
   # for file types, where specifying the format also specifies the file that will be
   # passed to the field in the automatically generated unittests.
-    out_file: fileformats.medimage_afni.Dset
+    out_file: fileformats.vendor.afni.medimage.Dset
     # type=file: output file
     # type=file|default=<undefined>: output file for ConvertDset
   callables:

example-specs/interface/nipype/afni/interfaces/deconvolve.yaml

@@ -75,7 +75,7 @@ outputs:
     # type=file|default=<undefined>: output statistics file
     reml_script: generic/file
     # type=file: automatically generated script to run 3dREMLfit
-    x1D: fileformats.medimage_afni.OneD
+    x1D: fileformats.vendor.afni.medimage.OneD
     # type=file: save out X matrix
     # type=file|default=<undefined>: specify name for saved X matrix
   callables:

example-specs/interface/nipype/afni/interfaces/eval.yaml

@@ -39,7 +39,7 @@ inputs:
   # from the nipype interface, but you may want to be more specific, particularly
   # for file types, where specifying the format also specifies the file that will be
   # passed to the field in the automatically generated unittests.
-    in_file_a: fileformats.medimage_afni.OneD
+    in_file_a: fileformats.vendor.afni.medimage.OneD
     # type=file|default=<undefined>: input file to 1deval
     in_file_b: generic/file
     # type=file|default=<undefined>: operand file to 1deval
@@ -63,7 +63,7 @@ outputs:
   # from the nipype interface, but you may want to be more specific, particularly
   # for file types, where specifying the format also specifies the file that will be
   # passed to the field in the automatically generated unittests.
-    out_file: fileformats.medimage_afni.OneD
+    out_file: fileformats.vendor.afni.medimage.OneD
     # type=file: output file
     # type=file|default=<undefined>: output image file name
   callables:

example-specs/interface/nipype/afni/interfaces/notes.yaml

@@ -36,7 +36,7 @@ inputs:
   # from the nipype interface, but you may want to be more specific, particularly
   # for file types, where specifying the format also specifies the file that will be
   # passed to the field in the automatically generated unittests.
-    in_file: fileformats.medimage_afni.Head
+    in_file: fileformats.vendor.afni.medimage.Head
     # type=file|default=<undefined>: input file to 3dNotes
   callable_defaults:
   # dict[str, str] - names of methods/callable classes defined in the adjacent `*_callables.py`

example-specs/interface/nipype/afni/interfaces/one_d_tool_py.yaml

@@ -31,7 +31,7 @@ inputs:
   # from the nipype interface, but you may want to be more specific, particularly
   # for file types, where specifying the format also specifies the file that will be
   # passed to the field in the automatically generated unittests.
-    in_file: fileformats.medimage_afni.OneD
+    in_file: fileformats.vendor.afni.medimage.OneD
     # type=file|default=<undefined>: input file to OneDTool
     show_cormat_warnings: generic/file
     # type=file|default=<undefined>: Write cormat warnings to a file

example-specs/interface/nipype/afni/interfaces/remlfit.yaml

@@ -51,7 +51,7 @@ inputs:
     # type=file|default=<undefined>: filename of 3D mask dataset; only data time series from within the mask will be analyzed; results for voxels outside the mask will be set to zero.
     matim: generic/file
     # type=file|default=<undefined>: read a standard file as the matrix. You can use only Col as a name in GLTs with these nonstandard matrix input methods, since the other names come from the 'matrix' file. These mutually exclusive options are ignored if 'matrix' is used.
-    matrix: fileformats.medimage_afni.OneD
+    matrix: fileformats.vendor.afni.medimage.OneD
     # type=file|default=<undefined>: the design matrix file, which should have been output from Deconvolve via the 'x1D' option
     slibase: generic/file+list-of
     # type=inputmultiobject|default=[]: similar to 'addbase' in concept, BUT each specified file must have an integer multiple of the number of slices in the input dataset(s); then, separate regression matrices are generated for each slice, with the first column of the file appended to the matrix for the first slice of the dataset, the second column of the file appended to the matrix for the first slice of the dataset, and so on. Intended to help model physiological noise in FMRI, or other effects you want to regress out that might change significantly in the inter-slice time intervals. This will slow the program down, and make it use a lot more memory (to hold all the matrix stuff).

example-specs/interface/nipype/afni/interfaces/retroicor.yaml

@@ -58,7 +58,7 @@ inputs:
     # type=file|default=<undefined>: Filename for 1D cardiac phase output
     in_file: medimage/nifti1
     # type=file|default=<undefined>: input file to 3dretroicor
-    resp: fileformats.medimage_afni.OneD
+    resp: fileformats.vendor.afni.medimage.OneD
     # type=file|default=<undefined>: 1D respiratory waveform data for correction
     respphase: generic/file
     # type=file|default=<undefined>: Filename for 1D resp phase output