Transitions

Counting transitions

count_lags(list_length, pool_items, recall_items)	Count actual and possible serial position lags.
count_category(pool_items, recall_items, …)	Count within-category transitions.
count_distance(distances, edges, pool_items, …)	Count transitions within distance bins.

Ranking transitions

percentile_rank(actual, possible)	Get percentile rank of a score compared to possible scores.
rank_lags(pool_items, recall_items[, …])	Calculate rank of absolute lag for free recall lists.
rank_distance(distances, pool_items, …[, …])	Calculate percentile rank of transition distances.

Iterating over recalls

outputs_masker(pool_items, recall_items, …)	Iterate over valid outputs.
transitions_masker(pool_items, recall_items, …)	Iterate over transitions with masking.

Transition measure base class

TransitionMeasure(items_key, label_key[, …])
TransitionMeasure.split_lists(data, phase)	Get relevant fields and split by list.
TransitionMeasure.analyze(data)
TransitionMeasure.analyze_subject(subject, …)

Transition measures

TransitionOutputs(list_length[, item_query, …])
TransitionLag(list_length[, item_query, …])
TransitionLagRank([item_query, test_key, test])
TransitionCategory(category_key[, …])
TransitionDistance(index_key, distances, edges)
TransitionDistanceRank(index_key, distances)

psifr.fr.plot_swarm_error psifr.transitions.count_lags