tedana.selection.selection_nodes

Functions that will be used as steps in a decision tree.

Functions

calc_extend_factor(selector[, ...])	Calculate the scalar used to set a threshold for d_table_score.
calc_kappa_elbow(selector, decide_comps[, ...])	Calculate elbow for kappa across components.
calc_max_good_meanmetricrank(selector, ...)	Calculate the metric "max_good_meanmetricrank".
calc_median(selector, decide_comps, ...[, ...])	Calculate the median across components for the metric defined by metric_name.
calc_revised_meanmetricrank_guesses(...[, ...])	Calculate a new d_table_score (meanmetricrank).
calc_rho_elbow(selector, decide_comps[, ...])	Calculate elbow for rho across components.
calc_varex_kappa_ratio(selector, decide_comps)	Calculate the cross-component metric "kappa_rate".
calc_varex_thresh(selector, decide_comps, ...)	Calculate the variance explained threshold to use in the kundu decision tree.
dec_classification_doesnt_exist(selector, ...)	Change the classification of all components in decide_comps.
dec_left_op_right(selector, if_true, ...[, ...])	Perform a relational comparison.
dec_reclassify_high_var_comps(selector, ...)	Identify and reclassify a couple components with the largest gaps in variance.
dec_variance_lessthan_thresholds(selector, ...)	Change classifications for components with variance<single_comp_threshold.
manual_classify(selector, decide_comps, ...)	Assign a classification defined in new_classification to the components in decide_comps.