|
3 | 3 | from setuptools import setup, find_packages
|
4 | 4 |
|
5 | 5 |
|
6 |
| -with open('README.md') as f: |
7 |
| - readme = f.read() |
| 6 | +long_description=""" \ |
| 7 | +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: |
| 8 | +- Serial position curves (probability of recalling items presented at each presentation position) |
| 9 | +- Probability of Nth recall curves (probability of recalling items at each presentation position as the Nth recall in the recall sequence) |
| 10 | +- Lag-Conditional Response Probability curves (probability of transitioning between items in the recall sequence, as a function of their relative presentation positions) |
| 11 | +- 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.) |
| 12 | +- Many nice plotting functions |
| 13 | +- Convenience functions for loading in data |
| 14 | +- Automatically parse speech data (audio files) using wrappers for the Google Cloud Speech to Text API |
| 15 | +
|
| 16 | +For API documentation, examples and tutorials: http://cdl-quail.readthedocs.io/en/latest/ |
| 17 | +For sample Jupyter notebooks using the package: https://github.com/ContextLab/quail-example-notebooks |
| 18 | +""" |
8 | 19 |
|
9 | 20 | with open('LICENSE') as f:
|
10 | 21 | license = f.read()
|
|
13 | 24 | name='quail',
|
14 | 25 | version='0.1.2',
|
15 | 26 | description='A python toolbox for analyzing and plotting free recall data',
|
16 |
| - long_description=readme, |
| 27 | + long_description=long_description, |
17 | 28 | author='Contextual Dynamics Lab',
|
18 | 29 | author_email='contextualdynamics@gmail.com',
|
19 | 30 | url='https://github.com/ContextLab/quail',
|
|
0 commit comments