SeisMonitoring Example

A minimal working example with a Jupyter notebook of the seismic noise processing using SeisMonitoring.jl.

View the notebook, click the badge:

or read the QR code:

How to run the notebook

We have two options to run this notebook.

1. Run using the docker container

We first recommend using the docker container, which does not contaminate your environment in the local machine.

To run this notebook using docker,

1. Install the docker engine on your machine.

   See the official documentation for the installation. The Docker Desktop is useful in general machines like Windows, Linux, and Mac OS. We developed this notebook using MacOS with both M1 (Monterey 12.6.7) and Intel (Ventura 13.4.1) chips. We have also tested this notebook with Windows 10 using Docker Desktop. You need to set up the WSL2 to run the docker engine.

   You can configure them in the settings of the Docker Desktop. The required docker resources are the following:

   Resources	Allocation
   CPUs	>=2
   Memory	> 8GB
   Swap	> 1GB
   Disk image size	> 8GB

2. Launch the docker engine.

   Type docker ps in the terminal to check if the docker command works. if you get the error like Cannot connect to the Docker daemon at unix:///var/run/docker.sock. Is the docker daemon running?, the docker engine is not likely to be ready. Check the status of Docker desktop.

3. Download the example repository, and build the docker container.

   Type the commands below to build the docker container in your machine.

   git clone https://github.com/kura-okubo/SeisMonitoring_Example
   cd SeisMonitoring_Example
   docker compose up -d

   NOTE: For Windows users, git clone may fail as some of the file name contains a colon. Type cd SeisMonitoring_Example; git restore --source=HEAD :/ to restore the docker files.

   The JupyterLab server automatically starts in the container when you start it following the description written in docker-compose.yml. Type

   docker compose ps
   

   and if the container is successfully started, it returns as follows:

   NAME                SERVICE             STATUS              PORTS
   seismonitoring      seismonitoring      running             0.0.0.0:8888->8888/tcp
   

   We use the docker image of Julia v1.9.2, which is the latest version as of August 2023.

4. Launch the JupyterLab in your web browser.

   Go to http://localhost:8888 with your browser (e.g. Google Chrome) or type open http://127.0.0.1:8888 in your terminal to open the JupyterLab. If succeeded, you will find the Launcher of the kernels.

   

   Go to the code directory, and open run_seismonitoring.ipynb.

2. Run in the local environment

You can run this notebook by installing Julia in your local environment instead of using the docker container.

NOTE: This may modify your Julia environment, so please use the docker if you want to keep your packages.

Try the following steps:

1. Download the example repository

   Download the example repository from GitHub as follows:

   git clone https://github.com/kura-okubo/SeisMonitoring_Example
   cd SeisMonitoring_Example

2. Download Julia in your machine.

   We developed and conducted the SeisMonitoring.jl using the Julia v1.7.3, while we also tested this notebook in Julia v1.9.2.

   You can download either version of Julia from the official website (https://julialang.org/downloads/oldreleases/).

   After installing the Julia, launch the Julia REPL by executing e.g. /Applications/Julia-1.9.app/Contents/Resources/julia/bin/julia. You will find the logo in the terminal as follows:

                   _
       _       _ _(_)_     |  Documentation: https://docs.julialang.org
      (_)     | (_) (_)    |
       _ _   _| |_  __ _   |  Type "?" for help, "]?" for Pkg help.
      | | | | | | |/ _` |  |
      | | |_| | | | (_| |  |  Version 1.9.2 (2023-07-05)
     _/ |\__'_|_|_|\__'_|  |  Official https://julialang.org/ release
    |__/                   |
   
    julia>
   

3. Install IJulia.jl

   To launch the JupyterLab with the Julia kernel, you need to install the IJulia.

   Type

   import Pkg; Pkg.add("IJulia")
   

   to download and install the package. Note that the package is located in ~/.julia/packages. Then, type

   import IJulia
   IJulia.jupyterlab(dir=pwd())
   

   You are asked to install Jupyter such as install Jupyter via Conda, y/n? [y]:, so type y to install it.

   After installing Jupyter, it opens JupyterLab Launcher in your browser.
   Tips: You can launch the JupyterLab by the bash command such as

   julia -e 'import Pkg; Pkg.add("Conda")'
   `julia -e "import Conda; print(Conda.PREFIX)"`/bin/jupyter lab --NotebookApp.token=''
   

   This calls the jupyter located in e.g. /root/.julia/conda/3/x86_64/bin. We use this metric in the docker-compose to launch the JupyterLab.

This repository does not support the binder to simplify the building of container with the docker file.

After open the notebook, you can Run All Cells to run the noise processings.

Reference

Okubo, K., Delbridge, B. G., & Denolle, M. A. (2024). Monitoring velocity change over 20 years at Parkfield. Journal of Geophysical Research: Solid Earth, 129, e2023JB028084. https://doi.org/10.1029/2023JB028084