|
3 | 3 | from setuptools import setup, find_packages
|
4 | 4 |
|
5 | 5 |
|
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 |
| -""" |
| 6 | +with open('README.md') as f: |
| 7 | + readme = f.read() |
19 | 8 |
|
20 | 9 | with open('LICENSE') as f:
|
21 | 10 | license = f.read()
|
|
24 | 13 | name='quail',
|
25 | 14 | version='0.1.2',
|
26 | 15 | description='A python toolbox for analyzing and plotting free recall data',
|
27 |
| - long_description=long_description, |
| 16 | + long_description=readme, |
28 | 17 | author='Contextual Dynamics Lab',
|
29 | 18 | author_email='contextualdynamics@gmail.com',
|
30 | 19 | url='https://github.com/ContextLab/quail',
|
|
0 commit comments