v0.2.0 (February 2018)

Enhancements:

• accuracy, spc, pfr/pnr and lag-crp all extended to support high-dimensional stimuli (like movies):

• 2 new matching functions (+ classic approach) to create a recall matrix / run analyses:

  • exact - the presented and recalled stimulus matching exactly is chosen (this is the classic approach)
  • best - the presented stimulus that most closely matches a the recalled stimulus is chosen
  • smooth - a weighted average of the stimuli are chosen, where the weights are derived by the similarity between the recalled item and each presented item.
  • support for a variety of distance functions (to compare presented/recalled stimuli) with a new argument, distance (anything supported by scipy.spatial.distance.cdist).

• eggs have been revamped! Changes:

  • item and features are now combined in a dataframe of dictionaries replacing egg.pres (previously just the items with a separate 'features' field)
  • features for recall items now supported. egg.rec is now a dataframe of dictionaries (previously egg.rec was a dataframe of items`
  • added egg.get_pres_items which returns a dataframe of presented items
  • added egg.get_pres_features which returns a dataframe of features of the presented items
  • added egg.get_rec_items which returns a dataframe of recalled items
  • added egg.get_rec_features which returns a dataframe of features of the recalled items
  • added support to pass a recall matrix (recmat) instead of pres and rec when constructing an Egg
  • save format has been changed from pickles to hdf5 for better cross-version compatibility
  • Analysis can be performed by calling egg.analyze() (does the same thing as quail.analyze(egg)

• a new class FriedEgg containing the result of an analysis of an egg. Includes plot and save methods.

• a new function load for loading Eggs, FriedEggs and example data (old load function renamed loadEL)