NeptuneProjects / RISProcess

Package to process seismic data recorded on the Ross Ice Shelf, Antarctica from 2014-2017.

RISProcess

RISProcess is a Python package designed to download, process, and save seismic data that were collected on the Ross Ice Shelf (RIS), Antarctica, from 2014- 2017. The package is principally built using Obspy and h5py. The package is used to build the data set required for the deep clustering project, RISCluster. Details on the clustering project are available in Jenkins et al..

Information about the seismic data set can be found at FDSN. The project for which the data were collected is documented in Bromirski et al..

Installation

Pre-requisites: Anaconda or Miniconda

Tested on MacOS 11.1 and Red Hat Enterprise Linux 7.9.

The following steps will set up a Conda environment and install RISProcess.

1. Open a terminal and navigate to the directory you would like to download the RISProcess.yml environment file.
2. Save RISProcess.yml to your computer by running the following:
   a. Mac:
   curl -LJO https://raw.githubusercontent.com/NeptuneProjects/RISProcess/master/RISProcess.yml
   b. Linux:
   wget --no-check-certificate --content-disposition https://raw.githubusercontent.com/NeptuneProjects/RISProcess/master/RISProcess.yml
3. In terminal, run: conda env create -f RISProcess.yml
4. Once the environment is set up and the package is installed, activate your environment by running conda activate RISProcess in terminal.

Usage

The Jupyter notebook, RISProcess.ipynb, provides an outline of general usage and workflow. There are two components to the worfklow: setting up configuration files, and executing scripts. The configuration files can be set up manually (not recommended), or using the provided notebook. Scripts are executed from the terminal, with recommended commands printed within the notebook. Copy and paste the commands from the notebook into terminal, taking care to ensure the working directories and path names are consistent. Due to irregularities that can arise from executing command line functions from within the iPython kernel, I chose to avoid calling commands from within the notebook.

Author

William Jenkins
wjenkins [@] ucsd [dot] edu
Scripps Institution of Oceanography
University of California San Diego
La Jolla, California, USA