updated with latest generation of auto-gen yaml files

nipype-auto-conv/specs/accuracy_tester.yaml

@@ -23,10 +23,13 @@ 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.
-    mel_icas: generic/file+list-of
-    # type=inputmultiobject|default=[]: Melodic output directories
     trained_wts_file: generic/file
     # type=file|default=<undefined>: trained-weights file
+    mel_icas: generic/directory+list-of
+    # type=inputmultiobject|default=[]: Melodic output directories
+    output_directory: generic/directory
+    # type=directory: Path to folder in which to store the results of the accuracy test.
+    # type=directory|default=<undefined>: Path to folder in which to store the results of the accuracy test.
   metadata:
   # dict[str, dict[str, any]] - additional metadata to set on any of the input fields (e.g. out_file: position: 1)
 outputs:
@@ -40,6 +43,9 @@ 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.
+    output_directory: generic/directory
+    # type=directory: Path to folder in which to store the results of the accuracy test.
+    # type=directory|default=<undefined>: Path to folder in which to store the results of the accuracy test.
   callables:
   # dict[str, str] - names of methods/callable classes defined in the adjacent `*_callables.py`
   # to set to the `callable` attribute of output fields

nipype-auto-conv/specs/bedpostx5.yaml

@@ -53,6 +53,10 @@ inputs:
     # type=file|default=<undefined>: b values file
     grad_dev: generic/file
     # type=file|default=<undefined>: grad_dev file, if gradnonlin, -g is True
+    logdir: generic/directory
+    # type=directory|default=<undefined>: 
+    out_dir: generic/directory
+    # type=directory|default='bedpostx': output directory
   metadata:
   # dict[str, dict[str, any]] - additional metadata to set on any of the input fields (e.g. out_file: position: 1)
 outputs:

nipype-auto-conv/specs/classifier.yaml

@@ -27,6 +27,8 @@ inputs:
     artifacts_list_file: generic/file
     # type=file: Text file listing which ICs are artifacts; can be the output from classification or can be created manually
     # type=file|default=<undefined>: Text file listing which ICs are artifacts; can be the output from classification or can be created manually
+    mel_ica: generic/directory
+    # type=directory|default=<undefined>: Melodic output directory or directories
   metadata:
   # dict[str, dict[str, any]] - additional metadata to set on any of the input fields (e.g. out_file: position: 1)
 outputs:

nipype-auto-conv/specs/dual_regression.yaml

@@ -57,6 +57,9 @@ 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_dir: generic/directory
+    # type=directory: 
+    # type=directory|default='output': This directory will be created to hold all output and logfiles
   callables:
   # dict[str, str] - names of methods/callable classes defined in the adjacent `*_callables.py`
   # to set to the `callable` attribute of output fields

nipype-auto-conv/specs/feat.yaml

@@ -35,6 +35,8 @@ 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.
+    feat_dir: generic/directory
+    # type=directory: 
   callables:
   # dict[str, str] - names of methods/callable classes defined in the adjacent `*_callables.py`
   # to set to the `callable` attribute of output fields

nipype-auto-conv/specs/feature_extractor.yaml

@@ -22,6 +22,9 @@ 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.
+    mel_ica: generic/directory
+    # type=directory: Melodic output directory or directories
+    # type=directory|default=<undefined>: Melodic output directory or directories
   metadata:
   # dict[str, dict[str, any]] - additional metadata to set on any of the input fields (e.g. out_file: position: 1)
 outputs:
@@ -35,6 +38,9 @@ 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.
+    mel_ica: generic/directory
+    # type=directory: Melodic output directory or directories
+    # type=directory|default=<undefined>: Melodic output directory or directories
   callables:
   # dict[str, str] - names of methods/callable classes defined in the adjacent `*_callables.py`
   # to set to the `callable` attribute of output fields

nipype-auto-conv/specs/filmgls.yaml

@@ -55,6 +55,9 @@ inputs:
     # type=file|default=<undefined>: input data file
     design_file: generic/file
     # type=file|default=<undefined>: design matrix file
+    results_dir: generic/directory
+    # type=directory: directory storing model estimation output
+    # type=directory|default='results': directory to store results in
   metadata:
   # dict[str, dict[str, any]] - additional metadata to set on any of the input fields (e.g. out_file: position: 1)
 outputs:
@@ -78,6 +81,9 @@ outputs:
     # type=file: The FILM autocorrelation parameters
     logfile: generic/file
     # type=file: FILM run logfile
+    results_dir: generic/directory
+    # type=directory: directory storing model estimation output
+    # type=directory|default='results': directory to store results in
   callables:
   # dict[str, str] - names of methods/callable classes defined in the adjacent `*_callables.py`
   # to set to the `callable` attribute of output fields

nipype-auto-conv/specs/flameo.yaml

@@ -55,6 +55,8 @@ inputs:
     # type=file|default=<undefined>: ascii matrix specifying f-contrasts
     cov_split_file: datascience/text-matrix
     # type=file|default=<undefined>: ascii matrix specifying the groups the covariance is split into
+    log_dir: generic/directory
+    # type=directory|default='stats': 
   metadata:
   # dict[str, dict[str, any]] - additional metadata to set on any of the input fields (e.g. out_file: position: 1)
 outputs:
@@ -68,6 +70,8 @@ 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.
+    stats_dir: generic/directory
+    # type=directory: directory storing model estimation output
   callables:
   # dict[str, str] - names of methods/callable classes defined in the adjacent `*_callables.py`
   # to set to the `callable` attribute of output fields

nipype-auto-conv/specs/fnirt.yaml

@@ -227,8 +227,9 @@ tests:
     in_fwhm: '[8, 4, 2, 2]'
     # type=list|default=[]: FWHM (in mm) of gaussian smoothing kernel for input volume, default [6, 4, 2, 2]
     subsampling_scheme: '[4, 2, 1, 1]'
-    warp_resolution: '(6, 6, 6)'
     # type=list|default=[]: sub-sampling scheme, list, default [4, 2, 1, 1]
+    warp_resolution: (6, 6, 6)
+    # type=tuple|default=(0, 0, 0): (approximate) resolution (in mm) of warp basis in x-, y- and z-direction, default 10, 10, 10
   imports: &id001
   # list[nipype2pydra.task.importstatement] - list import statements required by the test, with each list item
   # consisting of 'module', 'name', and optionally 'alias' keys
@@ -256,8 +257,10 @@ doctests:
   # '.mock()' method of the corresponding class is used instead.
     in_fwhm: '[8, 4, 2, 2]'
     # type=list|default=[]: FWHM (in mm) of gaussian smoothing kernel for input volume, default [6, 4, 2, 2]
-    subsampling_scheme: '[4, 2, 1, 1]    Specify the resolution of the warps    >>> fnirt_mprage.inputs.warp_resolution = (6, 6, 6)'
+    subsampling_scheme: '[4, 2, 1, 1]'
     # type=list|default=[]: sub-sampling scheme, list, default [4, 2, 1, 1]
+    warp_resolution: (6, 6, 6)
+    # type=tuple|default=(0, 0, 0): (approximate) resolution (in mm) of warp basis in x-, y- and z-direction, default 10, 10, 10
   imports: *id001
   # list[nipype2pydra.task.importstatement] - list import statements required by the test, with each list item
   # consisting of 'module', 'name', and optionally 'alias' keys

nipype-auto-conv/specs/fslx_command.yaml

@@ -30,6 +30,8 @@ inputs:
     # type=file|default=<undefined>: b vectors file
     bvals: generic/file
     # type=file|default=<undefined>: b values file
+    logdir: generic/directory
+    # type=directory|default='.': 
   metadata:
   # dict[str, dict[str, any]] - additional metadata to set on any of the input fields (e.g. out_file: position: 1)
 outputs:

nipype-auto-conv/specs/ica__aroma.yaml

@@ -56,6 +56,13 @@ inputs:
     # type=file|default=<undefined>: File name of the warp-file describing the non-linear registration (e.g. FSL FNIRT) of the structural data to MNI152 space (.nii.gz)
     motion_parameters: text/text-file
     # type=file|default=<undefined>: motion parameters file
+    feat_dir: generic/directory
+    # type=directory|default=<undefined>: If a feat directory exists and temporal filtering has not been run yet, ICA_AROMA can use the files in this directory.
+    out_dir: generic/directory
+    # type=directory: directory contains (in addition to the denoised files): melodic.ica + classified_motion_components + classification_overview + feature_scores + melodic_ic_mni)
+    # type=directory|default='out': output directory
+    melodic_dir: generic/directory
+    # type=directory|default=<undefined>: path to MELODIC directory if MELODIC has already been run
   metadata:
   # dict[str, dict[str, any]] - additional metadata to set on any of the input fields (e.g. out_file: position: 1)
 outputs:
@@ -73,6 +80,9 @@ outputs:
     # type=file: if generated: aggressively denoised volume
     nonaggr_denoised_file: generic/file
     # type=file: if generated: non aggressively denoised volume
+    out_dir: generic/directory
+    # type=directory: directory contains (in addition to the denoised files): melodic.ica + classified_motion_components + classification_overview + feature_scores + melodic_ic_mni)
+    # type=directory|default='out': output directory
   callables:
   # dict[str, str] - names of methods/callable classes defined in the adjacent `*_callables.py`
   # to set to the `callable` attribute of output fields

nipype-auto-conv/specs/melodic.yaml

@@ -77,6 +77,11 @@ 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_dir: generic/directory
+    # type=directory: 
+    # type=directory|default=<undefined>: output directory name
+    report_dir: generic/directory
+    # type=directory: 
   callables:
   # dict[str, str] - names of methods/callable classes defined in the adjacent `*_callables.py`
   # to set to the `callable` attribute of output fields

nipype-auto-conv/specs/topup.yaml

@@ -45,8 +45,6 @@ inputs:
     # type=file|default=<undefined>: name of 4D file with images
     encoding_file: text/text-file
     # type=file|default=<undefined>: name of text file with PE directions/times
-    readout_times: generic/file+list-of
-    # type=inputmultiobject|default=[]: readout times (dwell times by # phase-encode steps minus 1)
     out_base: generic/file
     # type=file|default=<undefined>: base-name of output files (spline coefficients (Hz) and movement parameters)
     out_field: generic/file

nipype-auto-conv/specs/training.yaml

@@ -22,7 +22,7 @@ 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.
-    mel_icas: generic/file+list-of
+    mel_icas: generic/directory+list-of
     # type=inputmultiobject|default=[]: Melodic output directories
   metadata:
   # dict[str, dict[str, any]] - additional metadata to set on any of the input fields (e.g. out_file: position: 1)

nipype-auto-conv/specs/training_set_creator.yaml

@@ -27,7 +27,7 @@ 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.
-    mel_icas_in: generic/file+list-of
+    mel_icas_in: generic/directory+list-of
     # type=inputmultiobject|default=[]: Melodic output directories
   metadata:
   # dict[str, dict[str, any]] - additional metadata to set on any of the input fields (e.g. out_file: position: 1)

nipype-auto-conv/specs/x_fibres_5.yaml

@@ -33,6 +33,8 @@ inputs:
     # type=file|default=<undefined>: b vectors file
     bvals: generic/file
     # type=file|default=<undefined>: b values file
+    logdir: generic/directory
+    # type=directory|default='.': 
   metadata:
   # dict[str, dict[str, any]] - additional metadata to set on any of the input fields (e.g. out_file: position: 1)
 outputs: