https://github.com/CDAT/cdat

Community Data Analysis Tools
https://github.com/CDAT/cdat

Last synced: 2 months ago
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Community Data Analysis Tools

• Host: GitHub
• URL: https://github.com/CDAT/cdat
• Owner: CDAT
• License: other
• Created: 2012-11-12T20:58:18.000Z (about 12 years ago)
• Default Branch: master
• Last Pushed: 2022-05-18T22:31:18.000Z (over 2 years ago)
• Last Synced: 2024-11-10T20:06:47.332Z (2 months ago)
• Language: Fortran
• Homepage:
• Size: 299 MB
• Stars: 175
• Watchers: 31
• Forks: 68
• Open Issues: 279
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-atmos - cdat

README

        
cdat

======

| :warning: WARNING: Maintenance-only mode until around the end of 2023.          |

| :------------------------------------------------------------------------------ |

The CDAT library is now in maintenance-only mode, with plans for deprecation and cease of support around the end of calendar year 2023. Until this time, the dependencies for specific CDAT packages (`cdms2`, `cdat_info`, `cdutil`, `cdtime`, `genutil`, `libcdms`) will be monitored to ensure they build and install in Conda environments. We currently support Python versions 3.7, 3.8, 3.9, and 3.10. Unfortunately, feature requests and bug fixes will no longer be addressed.|

If you are interested in an alternative solution, please check out the [xarray](https://docs.xarray.dev/en/stable/index.html) and [xCDAT - Xarray Extended With Climate Data Analysis Tools](https://github.com/xCDAT/xcdat) projects.|

[![build status](https://travis-ci.org/CDAT/cdat.svg?branch=master)](https://travis-ci.org/CDAT/cdat/builds)

[![stable version](http://img.shields.io/badge/stable%20version-8.1-brightgreen.svg)](https://github.com/CDAT/cdat/releases/tag/v8.1)

![platforms](http://img.shields.io/badge/platforms-linux%20|%20osx-lightgrey.svg)

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2586088.svg)](https://doi.org/10.5281/zenodo.2586088)

[![Anaconda-Server Badge](https://anaconda.org/cdat/cdat/badges/installer/conda.svg)](https://conda.anaconda.org/cdat)

[![Anaconda-Server Badge](https://anaconda.org/cdat/cdat/badges/downloads.svg)](https://anaconda.org/cdat/cdat)

CDAT builds on the following key technologies:

  1. Python and its ecosystem (e.g. NumPy, Matplotlib);

  2. Jupyter Notebooks and iPython;

  3. A toolset developed at LLNL for the analysis, visualization, and management of large-scale distributed climate data;

  4. VTK, the Visualization Toolkit, which is open source software for manipulating and displaying scientific data.

These combined tools, along with others such as the R open-source statistical

analysis and plotting software and custom packages (e.g. DV3D), form CDAT

and provide a synergistic approach to climate modeling, allowing researchers to

advance scientific visualization of large-scale climate data sets. The CDAT

framework couples powerful software infrastructures through two primary means:

  1. Tightly coupled integration of the CDAT Core with the VTK infrastructure to provide high-performance, parallel-streaming data analysis and visualization of massive climate-data sets (other tighly coupled tools include

  VCS, DV3D, and ESMF/ESMP);

  2. Loosely coupled integration to provide the flexibility of using tools quickly

  in the infrastructure such as ViSUS or R for data analysis and

  visualization as well as to apply customized data analysis applications within

  an integrated environment.

Within both paradigms, CDAT will provide data-provenance capture and

mechanisms to support data analysis.

CDAT is licensed under the [BSD-3][bds3] license.

------

We'd love to get contributions from you! Please take a look at the

[Contribution Documents](CONTRIBUTING.md) to see how to get your changes merged

in.