xcp_d.interfaces.censoring.Censor

class xcp_d.interfaces.censoring.Censor(from_file=None, resource_monitor=None, **inputs)[source]

Apply temporal mask to data.

Mandatory Inputs:

in_file (a pathlike object or string representing an existing file) – BOLD file after denoising, interpolation, and filtering.
temporal_mask (a pathlike object or string representing an existing file) – Temporal mask; all motion outlier volumes set to 1. This is a TSV file with one column: ‘framewise_displacement’.

Outputs:

censored_denoised_bold (a pathlike object or string representing an existing file) – Censored BOLD file.

__init__(from_file=None, resource_monitor=None, **inputs)[source]: 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