Platform for running and training AI models for Seismology

TODO add short description of the purpose of the platform

Running AI models

On Episodes Platform

On user local machines or HPC clusters

The AI tools are available as an ordinary Python packages. We recommend for installation to use Anaconda or Mambaforge, but it should be possible to use any other Python installations or distributions.

Mambaforge installation

Mambaforge is a Python distribution based on Conda. This is a preferred way to run scripts and notebooks distributed on our Platform. It is possible to install and run on other python distributions, but we provide support only for Mambaforge/Anaconda.

The installation starts with downloading the Mambaforge binary from the official project site for your platform. Then follow the instructions in the official guide.

We prepared a Conda environment with all the AI tools installed. To create the environment please:

Download the epos-ai-tools.yml from our repository.
If necessary activate the Mambaforge environment.
Run the installation
```
mamba env create -f epos-ai-tools.yml
```

Then to activate the environment it is necessary to run for each new shell session:

conda activate epos-ai-tools

To check if you have enabled the environment correctly you should see the name of the environment in the shell prompt.

Available Tools

The installation comes with the following applications:

gpd_tool - an application for automatic detection of the first arrival time of the P and S waves based on Generalized Seismic Phase Detection with Deep Learning by Ross, Z. E., Meier, M.-A., Hauksson, E., and T. H. Heaton (2018)
phasenet_tool - an application for automatic detection of the first arrival time of the P and S waves based on PhaseNet: a deep-neural-network-based seismic arrival-time picking method by Zhu, W., & Beroza, G. C. (2019)

and official packages such as:

Seisbench - an open-source python toolbox for machine learning in seismology,
ObsPy - an open-source project dedicated to provide a Python framework for processing seismological data,
Jupyter Notebook and JupyterLab - a web services for interactive computing,
IPython - a powerful interactive shell,
PyTorch - an optimized tensor library for deep learning using GPUs and CPUs

Training AI models

Acknowledgements

The development of the EPOS AI platform and its integration with the EPISODES Platform was partially funded by the EPOS-PL+ project (No POIR.04.02.00-00-C005/19-00), co-financed by the European Union from the funds of the European Regional Development Fund (ERDF).

<TODO: Można tu dodać też jakieś credits, jeśli potrzebujemy odnośniki do W&B albo innych rzeczy>