tedana.selection.selection_nodes.calc_extend_factor

calc_extend_factor(selector, log_extra_info='', custom_node_label='', only_used_metrics=False, extend_factor=None)[source]

Calculate the scalar used to set a threshold for d_table_score.

2 if fewer than 90 fMRI volumes, 3 if more than 110 and linear in-between The explanation for the calculation is in tedana.selection.selection_utils.get_extend_factor

Parameters:

  • selector (ComponentSelector) – If only_used_metrics is False, the updated selector is returned.

  • decide_comps (str or list[str]) – What classification(s) to operate on. using default or intermediate_classification labels. For example: decide_comps=’unclassified’ means to operate only on unclassified components. Use ‘all’ to include all components.

  • log_extra_info (str) – Additional text to the information log. Default=””.

  • custom_node_label (str) – A short label to describe what happens in this step. If “” then a label is automatically generated. Default=””.

  • only_used_metrics (bool) – If True, only return the component_table metrics that would be used. Default=False.

  • extend_factor (float) – If a number, then use rather than calculating anything. If None than calculate. default=None

Returns:

  • selector (ComponentSelector) – If only_used_metrics is False, the updated selector is returned.

  • used_metrics (set(str)) – If only_used_metrics is True, the names of the metrics used in the function are returned.