SCOPED Container for ML catalog construction

This notebook is part of the SCOPED container for machine learning based earthquake catalog construction. The SCOPED ML catalog tutorial page is at https://github.com/kaiwenwang233/scoped_ML_tutorial

Follow the instructions to pull and run the tutorial container:

To run it on your local machine:

Install docker from https://docs.docker.com/get-docker/

For Mac: https://docs.docker.com/desktop/install/mac-install/

For Linux: https://docs.docker.com/desktop/install/linux-install/

For Windows: https://docs.docker.com/desktop/install/windows-install/

To run it on AWS cloud (SCOPED workshop users):

Follow instructions on https://seisscoped.org/HPS-book/chapters/cloud/AWS_101.html to log in to AWS and launching your instance.

When launching your instance (at Step 2), in the Application and OS Images (Amazon Machine Image) block, choose *Architecture as 64-bit (Arm).

Use 'option 1' to install docker on your instance. And then pull container image with the command lines below.

Pulling container image

Use the following commands to pull the container from the GitHub Container Registry (GHCR):

docker pull ghcr.io/seisscoped/ml_catalog:latest

docker run -p 8888:8888 ghcr.io/seisscoped/ml_catalog:latest

For SCOPED workshop users, use:

sudo docker pull ghcr.io/seisscoped/ml_catalog:latest

sudo docker run -p 8888:8888 ghcr.io/seisscoped/ml_catalog:latest

Run tutorial Jupyter Notebook

The container will start JupyterLab with a link to open it in a web browser, something like:

To access the notebook, open this file in a browser:
        file:///root/.local/share/jupyter/runtime/nbserver-1-open.html
Or copy and paste one of these URLs:
        http://35e1877ea874:8888/?token=1cfd3a35f9d58cfd52807494ab36dd7166140bb856dbfbb7
or http://127.0.0.1:8888/?token=1cfd3a35f9d58cfd52807494ab36dd7166140bb856dbfbb7

Copy and paste one of the URLs to open it in a browser. Then run the tutorial notebook MLworkflow.ipynb

For SCOPED workshop users,

Find the Public IPv4 DNS of your AWS instance, replace the IP address in the link with this Public IPv4 DNS and open it in your web browser.

This will open a JupyterLab of the tutorial. Then run the notebook "MLworkflow.ipynb" for machine learning catalog construction workflow.