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)

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