Brainhack2023

nipype-auto-conv/specs/a_boverlap.yaml

@@ -7,10 +7,10 @@
 # ----
 # Output (to screen) is a count of various things about how
 #     the automasks of datasets A and B overlap or don't overlap.
-# 
+#
 #     For complete details, see the `3dABoverlap Documentation.
 #     <https://afni.nimh.nih.gov/pub/dist/doc/program_help/3dABoverlap.html>`_
-# 
+#
 #     Examples
 #     --------
 #     >>> from nipype.interfaces import afni
@@ -21,8 +21,8 @@
 #     >>> aboverlap.cmdline
 #     '3dABoverlap functional.nii structural.nii  |& tee out.mask_ae_overlap.txt'
 #     >>> res = aboverlap.run()  # doctest: +SKIP
-# 
-#     
+#
+#
 task_name: ABoverlap
 nipype_name: ABoverlap
 nipype_module: nipype.interfaces.afni.utils
@@ -32,11 +32,11 @@ inputs:
   rename:
   # dict[str, str] - fields to rename in the Pydra interface
   types:
-  # dict[str, type] - override inferred types (use "mime-like" string for file-format types,
-  # e.g. 'medimage/nifti-gz'). For most fields the type will be correctly inferred
-  # 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.
+    # dict[str, type] - override inferred types (use "mime-like" string for file-format types,
+    # e.g. 'medimage/nifti-gz'). For most fields the type will be correctly inferred
+    # 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: medimage/nifti1
     # type=file|default=<undefined>: input file A
     in_file_b: medimage/nifti1
@@ -55,11 +55,11 @@ outputs:
   rename:
   # dict[str, str] - fields to rename in the Pydra interface
   types:
-  # dict[str, type] - override inferred types (use "mime-like" string for file-format types,
-  # e.g. 'medimage/nifti-gz'). For most fields the type will be correctly inferred
-  # 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.
+    # dict[str, type] - override inferred types (use "mime-like" string for file-format types,
+    # e.g. 'medimage/nifti-gz'). For most fields the type will be correctly inferred
+    # 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: text/text-file
     # type=file: output file
     # type=file|default=<undefined>: collect output to a file
@@ -71,86 +71,82 @@ outputs:
   requirements:
   # dict[str, list[str]] - input fields that are required to be provided for the output field to be present
 tests:
-- inputs:
-  # dict[str, str] - values to provide to inputs fields in the task initialisation
-  # (if not specified, will try to choose a sensible value)
-    in_file_a:
-    # type=file|default=<undefined>: input file A
-    in_file_b:
-    # type=file|default=<undefined>: input file B
-    out_file:
-    # type=file: output file
-    # type=file|default=<undefined>: collect output to a file
-    no_automask:
-    # type=bool|default=False: consider input datasets as masks
-    quiet:
-    # type=bool|default=False: be as quiet as possible (without being entirely mute)
-    verb:
-    # type=bool|default=False: print out some progress reports (to stderr)
-    num_threads:
-    # type=int|default=1: set number of threads
-    outputtype:
-    # type=enum|default='AFNI'|allowed['AFNI','NIFTI','NIFTI_GZ']: AFNI output filetype
-    args:
-    # type=str|default='': Additional parameters to the command
-    environ:
-    # type=dict|default={}: Environment variables
-  imports:
-  # list[nipype2pydra.task.base.importstatement] - list import statements required by the test, with each list item
-  # consisting of 'module', 'name', and optionally 'alias' keys
-  expected_outputs:
-  # dict[str, str] - expected values for selected outputs, noting that tests will typically
-  # be terminated before they complete for time-saving reasons, and therefore
-  # these values will be ignored, when running in CI
-  timeout: 10
-  # int - the value to set for the timeout in the generated test, 
-  # after which the test will be considered to have been initialised 
-  # successfully. Set to 0 to disable the timeout (warning, this could
-  # lead to the unittests taking a very long time to complete)
-  xfail: true
-  # bool - whether the unittest is expected to fail or not. Set to false
-  # when you are satisfied with the edits you have made to this file
-- inputs:
-  # dict[str, str] - values to provide to inputs fields in the task initialisation
-  # (if not specified, will try to choose a sensible value)
-    in_file_a:
-    # type=file|default=<undefined>: input file A
-    in_file_b:
-    # type=file|default=<undefined>: input file B
-    out_file: ' "out.mask_ae_overlap.txt"'
-    # type=file: output file
-    # type=file|default=<undefined>: collect output to a file
-  imports:
-  # list[nipype2pydra.task.base.importstatement] - list import statements required by the test, with each list item
-  # consisting of 'module', 'name', and optionally 'alias' keys
-  expected_outputs:
-  # dict[str, str] - expected values for selected outputs, noting that tests will typically
-  # be terminated before they complete for time-saving reasons, and therefore
-  # these values will be ignored, when running in CI
-  timeout: 10
-  # int - the value to set for the timeout in the generated test, 
-  # after which the test will be considered to have been initialised 
-  # successfully. Set to 0 to disable the timeout (warning, this could
-  # lead to the unittests taking a very long time to complete)
-  xfail: true
-  # bool - whether the unittest is expected to fail or not. Set to false
-  # when you are satisfied with the edits you have made to this file
+  - inputs:
+      # dict[str, str] - values to provide to inputs fields in the task initialisation
+      # (if not specified, will try to choose a sensible value)
+      in_file_a:
+      # type=file|default=<undefined>: input file A
+      in_file_b:
+      # type=file|default=<undefined>: input file B
+      # out_file:
+      # type=file: output file
+      # type=file|default=<undefined>: collect output to a file
+      no_automask: "False"
+      # type=bool|default=False: consider input datasets as masks
+      quiet: "False"
+      # type=bool|default=False: be as quiet as possible (without being entirely mute)
+      verb: "False"
+      # type=bool|default=False: print out some progress reports (to stderr)
+      num_threads: 1
+      # type=int|default=1: set number of threads
+      outputtype:
+      # type=enum|default='AFNI'|allowed['AFNI','NIFTI','NIFTI_GZ']: AFNI output filetype
+    imports:
+    # list[nipype2pydra.task.base.importstatement] - list import statements required by the test, with each list item
+    # consisting of 'module', 'name', and optionally 'alias' keys
+    expected_outputs:
+    # dict[str, str] - expected values for selected outputs, noting that tests will typically
+    # be terminated before they complete for time-saving reasons, and therefore
+    # these values will be ignored, when running in CI
+    timeout: 10
+    # int - the value to set for the timeout in the generated test,
+    # after which the test will be considered to have been initialised
+    # successfully. Set to 0 to disable the timeout (warning, this could
+    # lead to the unittests taking a very long time to complete)
+    xfail: true
+    # bool - whether the unittest is expected to fail or not. Set to false
+    # when you are satisfied with the edits you have made to this file
+  - inputs:
+      # dict[str, str] - values to provide to inputs fields in the task initialisation
+      # (if not specified, will try to choose a sensible value)
+      in_file_a:
+      # type=file|default=<undefined>: input file A
+      in_file_b:
+      # type=file|default=<undefined>: input file B
+      # out_file:
+      # type=file: output file
+      # type=file|default=<undefined>: collect output to a file
+    imports:
+    # list[nipype2pydra.task.base.importstatement] - list import statements required by the test, with each list item
+    # consisting of 'module', 'name', and optionally 'alias' keys
+    expected_outputs:
+    # dict[str, str] - expected values for selected outputs, noting that tests will typically
+    # be terminated before they complete for time-saving reasons, and therefore
+    # these values will be ignored, when running in CI
+    timeout: 10
+    # int - the value to set for the timeout in the generated test,
+    # after which the test will be considered to have been initialised
+    # successfully. Set to 0 to disable the timeout (warning, this could
+    # lead to the unittests taking a very long time to complete)
+    xfail: true
+    # bool - whether the unittest is expected to fail or not. Set to false
+    # when you are satisfied with the edits you have made to this file
 doctests:
-- cmdline: 3dABoverlap functional.nii structural.nii |& tee out.mask_ae_overlap.txt
-  # str - the expected cmdline output
-  inputs:
-  # dict[str, str] - name-value pairs for inputs to be provided to the doctest.
-  # If the field is of file-format type and the value is None, then the
-  # '.mock()' method of the corresponding class is used instead.
-    in_file_a:
-    # type=file|default=<undefined>: input file A
-    in_file_b:
-    # type=file|default=<undefined>: input file B
-    out_file: ' "out.mask_ae_overlap.txt"'
-    # type=file: output file
-    # type=file|default=<undefined>: collect output to a file
-  imports:
-  # list[nipype2pydra.task.base.importstatement] - list import statements required by the test, with each list item
-  # consisting of 'module', 'name', and optionally 'alias' keys
-  directive:
-  # str - any doctest directive to place on the cmdline call, e.g. # doctest: +ELLIPSIS
+  - cmdline: 3dABoverlap functional.nii structural.nii |& tee out.mask_ae_overlap.txt
+    # str - the expected cmdline output
+    inputs:
+      # dict[str, str] - name-value pairs for inputs to be provided to the doctest.
+      # If the field is of file-format type and the value is None, then the
+      # '.mock()' method of the corresponding class is used instead.
+      in_file_a:
+      # type=file|default=<undefined>: input file A
+      in_file_b:
+      # type=file|default=<undefined>: input file B
+      out_file: ' "out.mask_ae_overlap.txt"'
+      # type=file: output file
+      # type=file|default=<undefined>: collect output to a file
+    imports:
+    # list[nipype2pydra.task.base.importstatement] - list import statements required by the test, with each list item
+    # consisting of 'module', 'name', and optionally 'alias' keys
+    directive:
+    # str - any doctest directive to place on the cmdline call, e.g. # doctest: +ELLIPSIS

nipype-auto-conv/specs/afn_ito_nifti.yaml

@@ -73,27 +73,23 @@ tests:
       # (if not specified, will try to choose a sensible value)
       in_file:
       # type=file|default=<undefined>: input file to 3dAFNItoNIFTI
-      out_file:
+      #out_file:
       # type=file: output file
       # type=file|default=<undefined>: output image file name
-      pure:
+      pure: "False"
       # type=bool|default=False: Do NOT write an AFNI extension field into the output file. Only use this option if needed. You can also use the 'nifti_tool' program to strip extensions from a file.
-      denote:
+      denote: "False"
       # type=bool|default=False: When writing the AFNI extension field, remove text notes that might contain subject identifying information.
-      oldid:
+      oldid: "False"
       # type=bool|default=False: Give the new dataset the input datasets AFNI ID code.
-      newid:
+      newid: "False"
       # type=bool|default=False: Give the new dataset a new AFNI ID code, to distinguish it from the input dataset.
-      num_threads:
+      num_threads: 1
       # type=int|default=1: set number of threads
-      outputtype:
+      outputtype: "'NIFTI'"
       # type=enum|default='AFNI'|allowed['AFNI','NIFTI','NIFTI_GZ']: AFNI output filetype
-      args:
-      # type=str|default='': Additional parameters to the command
-      environ:
-      # type=dict|default={}: Environment variables
     imports:
-    # list[nipype2pydra.task.base.importstatement] - list import statements required by the test, with each list item
+    # list[nipype2pydra.task.importstatement] - list import statements required by the test, with each list item
     # consisting of 'module', 'name', and optionally 'alias' keys
     expected_outputs:
     # dict[str, str] - expected values for selected outputs, noting that tests will typically
@@ -112,11 +108,11 @@ tests:
       # (if not specified, will try to choose a sensible value)
       in_file:
       # type=file|default=<undefined>: input file to 3dAFNItoNIFTI
-      out_file: ' "afni_output.nii"'
+      #out_file:
       # type=file: output file
       # type=file|default=<undefined>: output image file name
     imports:
-    # list[nipype2pydra.task.base.importstatement] - list import statements required by the test, with each list item
+    # list[nipype2pydra.task.importstatement] - list import statements required by the test, with each list item
     # consisting of 'module', 'name', and optionally 'alias' keys
     expected_outputs:
     # dict[str, str] - expected values for selected outputs, noting that tests will typically

nipype-auto-conv/specs/align_epi_anat_py.yaml

@@ -125,29 +125,31 @@ tests:
     # type=file|default=<undefined>: EPI dataset to align
     anat:
     # type=file|default=<undefined>: name of structural dataset
-    epi_base:
+    epi_base: 
+    #Blank is mapped to None
     # type=traitcompound|default=None: the epi base used in alignmentshould be one of (0/mean/median/max/subbrick#)
-    anat2epi:
+    anat2epi: "False"
     # type=bool|default=False: align anatomical to EPI dataset (default)
-    epi2anat:
+    epi2anat: "False"
     # type=bool|default=False: align EPI to anatomical dataset
     save_skullstrip:
     # type=bool|default=False: save skull-stripped (not aligned)
-    suffix:
+    suffix: "'_al'"
     # type=str|default='_al': append suffix to the original anat/epi dataset to usein the resulting dataset names (default is "_al")
-    epi_strip:
+    epi_strip: "'3dSkullStrip'"
     # type=enum|default='3dSkullStrip'|allowed['3dAutomask','3dSkullStrip','None']: method to mask brain in EPI datashould be one of[3dSkullStrip]/3dAutomask/None)
-    volreg:
+    volreg: "'on'"
     # type=enum|default='on'|allowed['off','on']: do volume registration on EPI dataset before alignmentshould be 'on' or 'off', defaults to 'on'
-    tshift:
+    tshift: "'on'"
     # type=enum|default='on'|allowed['off','on']: do time shifting of EPI dataset before alignmentshould be 'on' or 'off', defaults to 'on'
-    outputtype:
+    outputtype: "'AFNI'"
     # type=enum|default='AFNI'|allowed['AFNI','NIFTI','NIFTI_GZ']: AFNI output filetype
-    py27_path:
+    ###delete the following 3:###
+    #py27_path:
     # type=traitcompound|default='python2': 
-    args:
+    #args:
     # type=str|default='': Additional parameters to the command
-    environ:
+    #environ:
     # type=dict|default={}: Environment variables
   imports:
   # list[nipype2pydra.task.base.importstatement] - list import statements required by the test, with each list item