tedana.selection.selection_utils.log_decision_tree_step

log_decision_tree_step(function_name_idx, comps2use, decide_comps=None, n_true=None, n_false=None, if_true=None, if_false=None, calc_outputs=None)[source]

Log text to add after every decision tree calculation.

Parameters:

  • function_name_idx (str) – The name of the function that should be logged. By convention, this be “Step current_node_idx_: function_name”

  • comps2use (list[int] or -1) – A list of component indices that should be used by a function. Only used to report no components found if empty and report the number of components found if not empty. Note: calc_ functions that don’t use component metrics do not need to use the component_table and may not require selecting components. For those functions, set comps2use==-1 to avoid logging a warning that no components were found. Currently, this is only used by calc_extend_factor

  • decide_comps (str or list[str] or list[int]) – This is string or a list of strings describing what classifications of components to operate on. Only used in this function to report its contents if no components with these classifications were found

  • n_true, n_false (int) – The number of components classified as True or False

  • if_true, if_false (str) – If a component is true or false, the classification to assign that component

  • calc_outputs (dict) – A dictionary with output information from the function. If it contains a key “calc_cross_comp_metrics” then the value for that key is a list of cross component metrics (i.e. kappa or rho elbows) that were calculated within the function. Each of those metrics will also be a key in calc_outputs and those keys and values will be logged by this function

Returns:

  • Information is added to the LGR.info logger. This either logs that

  • nothing was changed, the number of components classified as true or

  • false and what they changed to, or the cross component metrics that were

  • calculated