EQCCT

EQCCT, or the EarthQuake Compact Convolutional Transformer, is a highly effective, accurate, generalizable, and production-ready machine-learning algorithm designed to autonomously detect seismic phases for earthquake detection. EQCCT was developed by Saad, O.M., Chen, Y.F., Siervo, D., Zhang, F., Savvaidis, A., Huang, G., Igonin, N., Fomel, S., and Chen, Y., (2023). More information regarding the purpose, design, functionality, results, and real-world implementation and application of EQCCT can be read about in their research paper here.

Installation Guide

If you desire to use and pull only EQCCT (EQCCTOne) as originally developed in the 2023 research paper, use the following commands:

[skevofilaxc] mkdir my_work_directory
[skevofilaxc] cd my_work_directory
[skevofilaxc] git clone --depth 1 --filter=tree:0 https://github.com/ut-beg-texnet/eqcct.git --sparse
[skevofilaxc] cd eqcct
[skevofilaxc] git sparse-checkout set eqcctone

This should pull only the eqcctone folder, which contains all the source and demo code as designed by Yangkang Chen.

Further documentation can be found in the eqcctone subfolder.

EQCCTPro

EQCCTPro builds on EQCCT's accurate seismic event detection, creating a highly efficient framework for real-time waveform processing across large seismic networks. By leveraging parallelization frameworks like Ray and optimizing hardware configurations, EQCCTPro enables fast, accurate, and efficient seismic data processing with continuous real-time monitoring capabilities.

EQCCTPro was created by Skevofilax, C., Salles, V., Munoz, C., Siervo, D., Saad, O.M., Chen, Y., and Savvaidis, A., (2025), and can be read about here.

Installation Guide

There are two installation methods for EQCCTPro:

1. Method 1: Install EQCCTPro out of the box (for experienced users)
2. Method 2: Install EQCCTPro with sample waveform data (recommended for first-time users)

It is highly recommended that first-time users pull the EQCCTPro folder, which includes sample waveform data and code to help get acquainted with EQCCTPro.

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Method 1: Install EQCCTPro (No Sample Data)

This method installs only the EQCCTPro package without the sample waveform data.

Step 1: Create a Clean Conda Environment for the Install

EQCCTPro requires Python 3.10.14 or higher as well as minimum Tensorflow packages. If you have a clean working environment, you can simply run pip install eqcctpro. However, if you have a nonclean environment, its highly recommended to create a new conda environment so that you can install the necessary packages safely with no issues. You can create a new conda environment with the correct Python version by using the following commands:

[skevofilaxc] conda create --name yourenvironemntname python=3.10.14 -y
[skevofilaxc] conda activate yourenvironemntname 
[skevofilaxc] python3 --version

Expected output:

Python 3.10.14

After activating your new conda environment, run the following command:

[skevofilaxc] pip install eqcctpro

You will have access to EQCCTPro and its functionality. However you will not have immediate access to the provided sample waveform data to use for testing. Youcan pull the waveform data either by downloading the .zip file from the repository or by following step 3.

Step 3 (Optional): Pull the EQCCTPro Folder

Although not required, it is highly recommended to pull the EQCCTPro folder to gain access to sample waveform data for testing.

[skevofilaxc] mkdir my_work_directory
[skevofilaxc] cd my_work_directory
[skevofilaxc] git clone --depth 1 --filter=tree:0 https://github.com/ut-beg-texnet/eqcct.git --sparse
[skevofilaxc] cd eqcct
[skevofilaxc] git sparse-checkout set eqcctpro

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Method 2: Install EQCCTPro with Sample Data (Recommended for First-Time Users)

This method sets up EQCCTPro with a pre-created conda environment and sample waveform data.

Step 1: Clone the EQCCTPro Repository

[skevofilaxc] mkdir my_work_directory
[skevofilaxc] cd my_work_directory
[skevofilaxc] git clone --depth 1 --filter=tree:0 https://github.com/ut-beg-texnet/eqcct.git --sparse
[skevofilaxc] cd eqcct
[skevofilaxc] git sparse-checkout set eqcctpro

Step 2: Create and Activate the Conda Environment

A pre-configured conda environment is included in the repository to handle all dependencies.

[skevofilaxc] conda env create -f environment.yml
[skevofilaxc] conda activate eqcctpro

Step 3: Install EQCCTPro

After activating the environment, install the EQCCTPro package:

[skevofilaxc] pip install eqcctpro

This will install any remaining dependencies needed for EQCCTPro.

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More Information

For additional details and package updates, visit the EQCCTPro PyPI page:
🔗 EQCCTPro on PyPI

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Further documentation and source-code can be found in the eqcctpro subfolder.

Downloading and using EQCCTOne/Pro

If you would like to use specific versions/implementations of EQCCT, read the above instructions on how to pull the specific folder containing the version you want to pull.

If you want to pull the whole repository, run the following command:

git clone https://github.com/ut-beg-texnet/eqcct.git

Contact Information

If you wish to contact the developers of EQCCTOne, please email [email protected].

If you wish to contact the developers of EQCCTPro, please email [email protected] or [email protected].