xcp_d.interfaces.workbench.FixCiftiIntent

class xcp_d.interfaces.workbench.FixCiftiIntent(from_file=None, resource_monitor=None, **inputs)

This is not technically a Connectome Workbench interface, but it is related.

CiftiSmooth (-cifti-smooth) overwrites the output file’s intent to match a dtseries extension, even when it is a dscalar file. This interface sets the appropriate intent based on the extension.

We initially tried using a _post_run_hook in a modified version of the CiftiSmooth interface, but felt that the errors being raised were too opaque.

If in_file has the correct intent code, it will be returned without modification.

Mandatory Inputs:

in_file (a pathlike object or string representing an existing file) – CIFTI file to check.

Outputs:

out_file (a pathlike object or string representing an existing file) – Fixed CIFTI file.

__init__(from_file=None, resource_monitor=None, **inputs)

Subclasses must implement __init__

Methods

__init__([from_file, resource_monitor])	Subclasses must implement __init__
aggregate_outputs([runtime, needed_outputs])	Collate expected outputs and apply output traits validation.
help([returnhelp])	Prints class help
load_inputs_from_json(json_file[, overwrite])	A convenient way to load pre-set inputs from a JSON file.
run([cwd, ignore_exception])	Execute this interface.
save_inputs_to_json(json_file)	A convenient way to save current inputs to a JSON file.

Attributes

always_run	Should the interface be always run even if the inputs were not changed? Only applies to interfaces being run within a workflow context.
can_resume	Defines if the interface can reuse partial results after interruption.
resource_monitor
version	interfaces should implement a version property