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vapor-python-cookbook

Getting started with vapor python

https://github.com/projectpythia/vapor-python-cookbook

Science Score: 54.0%

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Last synced: 6 months ago · JSON representation ·

Repository

Getting started with vapor python

Basic Info
Statistics
  • Stars: 6
  • Watchers: 3
  • Forks: 6
  • Open Issues: 3
  • Releases: 4
Created over 2 years ago · Last pushed 6 months ago
Metadata Files
Readme License Citation

README.md

vapor logo in front of a wildfire data visualization

VAPOR Python Cookbook

nightly-build DOI

This Project Pythia Cookbook provides an overview of the VAPOR Python API with example workflows.

Motivation

The Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers (VAPOR) provides an interactive 3D visualization environment for exploratory visual analysis and the production of captivating animations and high-quality images. VAPOR runs on most UNIX and Windows systems equipped with modern 3D graphics cards.

Authors

Nihanth W. Cherukuru, Stanislaw 'Stas' Jarosynski, Philip Austin, Ian Franda

Contributors

Structure

This cookbook is divided into three main sections. The "Quickstart" section is a good starting point for a general overview of VAPOR's features and capabilities. The "Foundations" section gives more detailed examples for specific features in VAPOR. The "Example Workflows" section provides practical examples to see VAPOR in action and to gain an understanding of various workflows. Feel free to visit the sections that best fit your needs -- it's not necessary to follow them sequentially!

VAPOR Foundations

The foundation section gives a quick overview of the major components of VAPOR python. These include the funcationality to load/read data, set camera parameters, annotations, save animations and images, implementing renderes for data visualization.

Additionally, the links below can serve as a helpful reference.

::::{grid} :gutter: 3

:::{grid-item-card} Discussion Forum Discussion forum for VAPOR. :::

:::{grid-item-card} Python API Reference Use this to delve deeper into the python classes :::

:::{grid-item-card} VAPOR GUI GUI version provides a graphical interface for VAPOR :::

::::

Example Workflows

The example workflows section provides examples showing and end-end pipeline for analysis and visualization using VAPOR python.

Running the Notebooks

These notebooks cannot be run on Binder at the moment and need to be run on your machine.

Running on Your 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/vapor-python-cookbook repository:

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

  1. Move into the vapor-python-cookbook directory bash cd vapor-python-cookbook
  2. Create and activate your conda environment from the environment.yml file bash conda env create -f vapor_environment.yml conda activate vapor-cookbook-dev
  3. Move into the notebooks directory and start up Jupyterlab bash cd notebooks/ jupyter lab At this point, you can interact with the notebooks! Make sure to check out the “Getting Started with Jupyter” content from the Pythia Foundations material if you are new to Jupyter or need a refresher.

Owner

  • Name: Project Pythia
  • Login: ProjectPythia
  • Kind: organization
  • Email: projectpythia@ucar.edu
  • Location: United States of America

Community learning resource for Python-based computing in the geosciences

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this cookbook, please cite it as below."
authors:
  # add additional entries for each author -- see https://github.com/citation-file-format/citation-file-format/blob/main/schema-guide.md
  - family-names: Cherukuru
    given-names: Nihanth
    website: https://github.com/NihanthCW # optional
    affiliation: National Center for Atmospheric Research # optional
  - family-names: Jarosynski
    given-names: Stanislaw 'Stas'
    website: https://github.com/StasJ # optional
    affiliation: National Center for Atmospheric Research # optional
  - family-names: Austin
    given-names: Philip
    website: https://github.com/phaustin # optional
    affiliation: University of British Columbia # optional
  - name: "VAPOR python cookbook contributors" # use the 'name' field to acknowledge organizations
    website: "https://github.com/ProjectPythia/vapor-python-cookbook/graphs/contributors"
title: "Vapor Python Cookbook"
abstract: "The Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers (VAPOR) provides an interactive 3D visualization environment for exploratory visual analysis and the production of captivating animations and high-quality images. VAPOR runs on most UNIX and Windows systems equipped with modern 3D graphics cards. "

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Last Year
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Last synced: 6 months ago

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  • Average time to close issues: N/A
  • Average time to close pull requests: about 19 hours
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  • Total pull request authors: 3
  • Average comments per issue: 0
  • Average comments per pull request: 0.71
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 7
  • Average time to close issues: N/A
  • Average time to close pull requests: about 19 hours
  • Issue authors: 0
  • Pull request authors: 3
  • Average comments per issue: 0
  • Average comments per pull request: 0.71
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 0
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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
environment.yml pypi
  • sphinx-pythia-theme *