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)