fantine / lfe-detection-ml

Low-frequency earthquake (LFE) detection using machine learning

• Author: Fantine Huot

Getting started

Update the submodules

After cloning the repository, run the following commands to initialize and update the submodules.

git submodule init
git submodule update

Requirements

You can run the project from an interactive bash session within the provided Docker container:

docker run --gpus all -it fantine/ml_framework:latest bash

If you do not have root permissions to run Docker, Singularity might be a good alternative for you. Refer to containers/README.md for more details.

Folder structure

• bin: Scripts to run machine learning jobs.
• catalog: Event catalog files.
• config: Configuration files.
• containers: Details on how to use containers for this project.
• docs: Documentation.
• log: Directory for log files.
• ml_framework: Machine learning framework.
• preprocessing: Data preprocessing steps.
• plot_utils: Utility functions for making figures.
• preprocessing: All the data preprocessing steps.
• processing_utils: Processing utility functions.

Set the datapath for the project

Set the DATAPATH variable inside config/datapath.sh to the data or scratch directory to which you want write data files.

Create and run a machine learning model

This repository provides a parameterized, modular framework for creating and running ML models.

• Prepare the data
• Machine learning training and inference
• Hyperparameter tuning