项目作者: NeptuneProjects

项目描述 :
Package to process seismic data recorded on the Ross Ice Shelf, Antarctica from 2014-2017.
高级语言: Python
项目地址: git://github.com/NeptuneProjects/RISProcess.git
创建时间: 2021-01-23T00:48:40Z
项目社区:https://github.com/NeptuneProjects/RISProcess

开源协议:MIT License

下载


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-

  1. 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