Metadata-Version: 2.1
Name: quail
Version: 0.2.2
Summary: A python toolbox for analyzing and plotting free recall data
Home-page: https://github.com/ContextLab/quail
Author: Contextual Dynamics Lab
Author-email: contextualdynamics@gmail.com
License: MIT
Description-Content-Type: text/x-rst
License-File: LICENSE
Requires-Dist: numpy >=1.10.4
Requires-Dist: scipy >=0.17.1
Requires-Dist: matplotlib >=1.5.1
Requires-Dist: seaborn >=0.9.0
Requires-Dist: pandas >=0.24.0
Requires-Dist: future
Requires-Dist: six
Requires-Dist: deepdish
Requires-Dist: joblib
Provides-Extra: efficient-learning
Requires-Dist: sqlalchemy ; extra == 'efficient-learning'
Provides-Extra: speech-decoding
Requires-Dist: pydub ; extra == 'speech-decoding'
Requires-Dist: google-cloud-speech <0.31dev,>=0.30.0 ; extra == 'speech-decoding'
Requires-Dist: google-cloud <0.34.0,>=0.32.0 ; extra == 'speech-decoding'

Quail is a Python package that facilitates analyses of behavioral data from memory experiments. (The current focus is on free recall experiments.) Key features include:

- Serial position curves (probability of recalling items presented at each presentation position)
- Probability of Nth recall curves (probability of recalling items at each presentation position as the Nth recall in the recall sequence)
- Lag-Conditional Response Probability curves (probability of transitioning between items in the recall sequence, as a function of their relative presentation positions)
- Clustering metrics (e.g. single-number summaries of how often participants transition from recalling a word to another related word, where "related" can be user-defined.)
- Many nice plotting functions
- Convenience functions for loading in data
- Automatically parse speech data (audio files) using wrappers for the Google Cloud Speech to Text API

The intended user of this toolbox is a memory researcher who seeks an easy way to analyze and visualize data from free recall psychology experiments.
