Metadata-Version: 2.1
Name: falcon_challenge
Version: 0.1.0
Home-page: https://github.com/snel-repo/stability-benchmark
Author: Joel Ye
Author-email: joelye9@gmail.com
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: hydra-core
Requires-Dist: matplotlib
Requires-Dist: tqdm
Requires-Dist: scipy
Requires-Dist: pandas
Requires-Dist: seaborn
Requires-Dist: scikit-learn
Requires-Dist: pynwb

# FALCON Benchmark and Challenge

This package contains core code for submitting decoders to the FALCON challenge. Full github contains additional examples and documentation.

## Installation
Install `falcon_challenge` with:

```bash
pip install falcon-challenge
```

To create Docker containers for submission, you must have Docker installed.
See, e.g. https://docs.docker.com/desktop/install/linux-install/. Try building and locally testing the provided `sklearn_sample.Dockerfile`, to confirm your setup works.

## Submission
To submit to the FALCON benchmark, prepare a decoder and Dockerfile.
- DOCKER instructions todo.

To run local evaluation, first setup a data directory at `./data`.
You can then run:
```bash
python <my_decoder>.py --evaluation local
```
