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Community Data Analysis Tools

License: Other

Shell 0.41% C++ 0.03% Python 39.07% C 6.30% Fortran 44.18% CSS 0.22% Makefile 0.32% HTML 0.13% CMake 8.64% M4 0.61% Dockerfile 0.02% sed 0.01% SWIG 0.05% Jinja 0.01%

cdat's Introduction

cdat

โš ๏ธ 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 and xCDAT - Xarray Extended With Climate Data Analysis Tools projects.

build status stable version platforms DOI

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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 to see how to get your changes merged in.

cdat's People

Contributors

doutriaux1 avatar thomasmaxwell avatar aashish24 avatar durack1 avatar sankhesh avatar linamuryanto avatar chaosphere2112 avatar danlipsa avatar cjh1 avatar remram44 avatar charlesdoutriaux avatar mcenerney1 avatar jbeezley avatar harinarayankrishnan avatar painter1 avatar bradking avatar muryanto1 avatar dnadeau4 avatar leung25 avatar dakoop avatar williams13 avatar hvo avatar zachmullen avatar boonth avatar tomvothecoder avatar arulalant avatar jasonb5 avatar jccosta avatar mattben avatar stefraynaud avatar

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