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snow-cookbook

cookbook for accessing snow datasets

https://github.com/snowex/snow-cookbook

Science Score: 49.0%

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Last synced: 6 months ago · JSON representation

Repository

cookbook for accessing snow datasets

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Created 8 months ago · Last pushed 6 months ago
Metadata Files
Readme License Citation

README.md

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Snow Cookbook

nightly-build Binder DOI

This Project Pythia Cookbook is a compilation of tutorials and training materials in support of the NASA snow reserach community. Some tutorials come from the 2020 to 2024 SnowEx Hackweek program hosted at the UW eScience Institute. Other materials are drawn from the NASA Goddard "SnowPit" Science Task Group or STG. The purpose of the tutorials is to help people with data access and to demonstrate a variety of disciplinary use cases.

Motivation

There are numerous data products and methods for accessing and analyzing snow observations. These include field, airborne, and satellite missions. The goal of these tutorials is to streamline data access, reduce duplication of effort and build an open science community around snow research datasets, algorithms and software.

Authors

Zach Fair Anthony Arendt, Mark Welden-Smith

more to be added

Contributors

Structure

This cookbook is broken up into two main sections - "Foundations" and "Example Workflows."

Section 1: Foundations

  • TBD

Section 2: Example Workflows for Specific Disciplines

  • TBD

Running the Notebooks

You can either run the notebook using Binder or on your local machine.

Running on Binder

The simplest way to interact with a Jupyter Notebook is through Binder, which enables the execution of a Jupyter Book in the cloud. The details of how this works are not important for now. All you need to know is how to launch a Pythia Cookbooks chapter via Binder. Simply navigate your mouse to the top right corner of the book chapter you are viewing and click on the rocket ship icon, (see figure below), and be sure to select launch Binder. After a moment you should be presented with a notebook that you can interact with. I.e. youll be able to execute and even change the example programs. Youll see that the code cells have no output at first, until you execute them by pressing {kbd}Shift+{kbd}Enter. Complete details on how to interact with a live Jupyter notebook are described in Getting Started with Jupyter.

Note, not all Cookbook chapters are executable. If you do not see the rocket ship icon, such as on this page, you are not viewing an executable book chapter.

Running on Your Own Machine

If you are interested in running this material locally on your computer, you will need to follow this workflow:

  1. Clone the https://github.com/ProjectPythia/snow-cookbook repository:

bash git clone https://github.com/ProjectPythia/snow-cookbook.git

  1. Move into the snow-cookbook directory bash cd snow-cookbook
  2. Create and activate your conda environment from the environment.yml file bash conda env create -f environment.yml conda activate snow-cookbook
  3. Move into the notebooks directory and start up Jupyterlab bash cd notebooks/ jupyter lab

Owner

  • Name: SnowEx
  • Login: SnowEx
  • Kind: organization

GitHub Events

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Top Authors
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  • zachghiaccio (5)
  • aaarendt (3)
  • Alex-Lewandowski (3)
  • dependabot[bot] (1)
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dependencies (1) github_actions (1)

Dependencies

.github/workflows/nightly-build.yaml actions
.github/workflows/publish-book.yaml actions
.github/workflows/trigger-book-build.yaml actions
.github/workflows/trigger-delete-preview.yaml actions
.github/workflows/trigger-link-check.yaml actions
.github/workflows/trigger-preview.yaml actions
.github/workflows/trigger-replace-links.yaml actions
  • actions/checkout v4 composite
  • jacobtomlinson/gha-find-replace v3 composite
  • stefanzweifel/git-auto-commit-action v6 composite
environment.yml pypi