Installation Guide
System requirements
python = 2.7 or python >= 3.4
tensorflow >= 1.13.1
For notebook demos, jupyter
For notebook demos, ipython
For plotting features, matplotlib
PsychRNN was developed to work with both Python 2.7 and 3.4+ using TensorFlow 1.13.1+. It is currently being tested on Python 2.7 and 3.4-3.8 with TensorFlow 1.13.1-2.2.
Note
TensorFlow 2.2 does not support Python < 3.5. Only TensorFlow 1.13.1-1.14 are compatible with Python 3.4. Python 3.8 is only supported by TensorFlow 2.2.
Installation
Normally, you can install with:
pip install psychrnn=1.0.0
Alternatively, you can download and extract the source files from the GitHub release. Within the downloaded PsychRNN-v1.0.0 folder, run:
python setup.py install
If you’re concerned about clashing dependencies, PsychRNN can be installed
in a new conda
environment:
conda create -n psychrnn python=3.6
conda activate psychrnn
pip install psychrnn=1.0.0
[THIS OPTION IS NOT RECOMMENDED FOR MOST USERS] To get the most recent (not necessarily stable) version from the github repo, clone the repository and install:
git clone https://github.com/murraylab/PsychRNN.git
cd PsychRNN
python setup.py install
Contributing
Please report bugs to https://github.com/murraylab/psychrnn/issues. This includes any problems with the documentation. Fixes (in the form of pull requests) for bugs are greatly appreciated.
Feature requests are welcome but may or may not be accepted due to limited resources. If you implement the feature yourself we are open to accepting it in PsychRNN. If you implement a new feature in PsychRNN, please do the following before submitting a pull request on GitHub:
Make sure your code is clean and well commented
If appropriate, update the official documentation in the
docs/
directoryWrite unit tests and optionally integration tests for your new feature in the
tests/
folder.Ensure all existing tests pass (
pytest
returns without error)
For all other questions or comments, contact psychrnn@gmail.com.