VAPOR

The Visualization and Analysis Platform for Ocean, Atmosphere and Solar Researchers.
https://github.com/NCAR/VAPOR

Category: Hydrosphere
Sub Category: Ocean and Hydrology Data Access

Keywords

atmosphere science visualization

Keywords from Contributors

transforms measur archiving compose optimize projection animals observation generic conversion

Last synced: about 18 hours ago
JSON representation

Repository metadata

VAPOR is the Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers

Host: GitHub
URL: https://github.com/NCAR/VAPOR
Owner: NCAR
License: bsd-3-clause
Created: 2017-06-14T19:25:05.000Z (almost 8 years ago)
Default Branch: main
Last Pushed: 2025-04-19T15:17:27.000Z (8 days ago)
Last Synced: 2025-04-20T12:10:33.561Z (7 days ago)
Topics: atmosphere, science, visualization
Language: C++
Homepage: https://www.vapor.ucar.edu/
Size: 77.4 MB
Stars: 186
Watchers: 18
Forks: 50
Open Issues: 375
Releases: 32
Metadata Files:
- Readme: README.md
- Contributing: Contributing.md
- License: LICENSE.txt
- Code of conduct: CODE_OF_CONDUCT.md

Vapor:

VAPOR is the Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers. VAPOR provides an interactive 3D visualization environment that can also produce animations and still frame images. VAPOR runs on most UNIX and Windows systems equipped with modern 3D graphics cards.

The VAPOR Data Collection (VDC) data model allows users progressively access the fidelity of their data, allowing for the visualization of terascale data sets on commodity hardware. VAPOR can also directly import data formats including WRF, MOM, POP, ROMS, and some GRIB and NetCDF files.

Users can perform ad-hoc analysis with VAPOR's interactive Python interpreter; which allows for the creation, modification, and visualization of new variables based on input model data.

VAPOR is a product of the NSF National Center for Atmospheric Research's Computational and Information Systems Lab. Support for VAPOR is provided by the U.S. National Science Foundation (grants # 03-25934 and 09-06379, ACI-14-40412), and by the Korea Institute of Science and Technology Information

Project homepage and binary releases can be found at https://www.vapor.ucar.edu/

Citation

If VAPOR benefits your research, please kindly cite this publication:

@Article{atmos10090488,
AUTHOR = {Li, Shaomeng and Jaroszynski, Stanislaw and Pearse, Scott and Orf, Leigh and Clyne, John},
TITLE = {VAPOR: A Visualization Package Tailored to Analyze Simulation Data in Earth System Science},
JOURNAL = {Atmosphere},
VOLUME = {10},
YEAR = {2019},
NUMBER = {9},
ARTICLE-NUMBER = {488},
URL = {https://www.mdpi.com/2073-4433/10/9/488},
ISSN = {2073-4433},
ABSTRACT = {Visualization is an essential tool for analysis of data and communication of findings in the sciences, and the Earth System Sciences (ESS) are no exception. However, within ESS, specialized visualization requirements and data models, particularly for those data arising from numerical models, often make general purpose visualization packages difficult, if not impossible, to use effectively. This paper presents VAPOR: a domain-specific visualization package that targets the specialized needs of ESS modelers, particularly those working in research settings where highly-interactive exploratory visualization is beneficial. We specifically describe VAPOR&rsquo;s ability to handle ESS simulation data from a wide variety of numerical models, as well as a multi-resolution representation that enables interactive visualization on very large data while using only commodity computing resources. We also describe VAPOR&rsquo;s visualization capabilities, paying particular attention to features for geo-referenced data and advanced rendering algorithms suitable for time-varying, 3D data. Finally, we illustrate VAPOR&rsquo;s utility in the study of a numerically- simulated tornado. Our results demonstrate both ease-of-use and the rich capabilities of VAPOR in such a use case.},
DOI = {10.3390/atmos10090488}
}

Project Members:

Nihanth Cherukuru
John Clyne
Scott Pearse
Samuel Li
Stanislaw Jaroszynski
Kenny Gruchalla
Niklas Roeber
Pamela Gillman

Owner metadata

Name: NSF National Center for Atmospheric Research
Login: NCAR
Email:
Kind: organization
Description: NSF NCAR is sponsored by the U.S. National Science Foundation and managed by the University Corporation for Atmospheric Research.
Website: http://ncar.ucar.edu
Location: Boulder, CO
Twitter:
Company:
Icon url: https://avatars.githubusercontent.com/u/2007542?v=4
Repositories: 934
Last ynced at: 2024-04-16T05:55:57.342Z
Profile URL: https://github.com/NCAR

GitHub Events

Total

Create event: 62
Release event: 23
Issues event: 109
Watch event: 11
Delete event: 40
Issue comment event: 55
Push event: 200
Pull request review comment event: 48
Pull request event: 67
Pull request review event: 70
Fork event: 1

Last Year

Create event: 62
Release event: 23
Issues event: 109
Watch event: 11
Delete event: 40
Issue comment event: 55
Push event: 200
Pull request review comment event: 48
Pull request event: 67
Pull request review event: 70
Fork event: 1

Committers metadata

Last synced: 6 days ago

Total Commits: 3,677
Total Committers: 25
Avg Commits per committer: 147.08
Development Distribution Score (DDS): 0.696

Commits in past year: 76
Committers in past year: 5
Avg Commits per committer in past year: 15.2
Development Distribution Score (DDS) in past year: 0.566

Name	Email	Commits
Scott Pearse	p**e@u**u	1119
Stanislaw Jaroszynski	s**j@u**u	1049
Samuel Li	s**g@u**u	1018
John Clyne	c**e@u**u	446
Ian Franda	1****a	10
Stanislaw Jaroszynski	S****i	7
U-CISL-MADISON\stasj-admin	C**n@C**u	5
Nihanth Wagmi Cherukuru	n**u@u**u	3
dependabot[bot]	4****]	2
Stas	s**s@c**u	2
Samuel Li	s**g@c**u	2
Rémi Lacroix	r**x@i**r	1
John Clyne	c**e@c**u	1
Legacy Code	v**r@u**u	1
Samuel Li	S**m@N**a	1
Samuel Li	s**g@c**r	1
Stas	s**s@S**n	1
U-CIT\pearse	p**e@c**u	1
pavolklacansky	k**y@s**u	1
Orion Poplawski	o**n@n**m	1
Orhan Eroglu	3****n	1
Kevin Hallock	k****k	1
Joel Daves	j**s@u**u	1
Giovanni Rosa	g**3@y**m	1
CoreCode	c****e	1

Committer domains:

Issue and Pull Request metadata

Last synced: 2 days ago

Total issues: 2,415
Total pull requests: 1,381
Average time to close issues: 8 months
Average time to close pull requests: 6 days
Total issue authors: 55
Total pull request authors: 16
Average comments per issue: 1.25
Average comments per pull request: 1.06
Merged pull request: 1,252
Bot issues: 0
Bot pull requests: 4

Past year issues: 115
Past year pull requests: 72
Past year average time to close issues: about 2 months
Past year average time to close pull requests: 8 days
Past year issue authors: 7
Past year pull request authors: 5
Past year average comments per issue: 0.76
Past year average comments per pull request: 0.92
Past year merged pull request: 58
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/NCAR/VAPOR

Top Issue Authors

sgpearse (654)
StasJ (586)
shaomeng (547)
clyne (457)
NihanthCW (40)
jvalan (36)
leighorf (12)
hawbecker (9)
winash12 (6)
Padanian (6)
ifranda (6)
ogressel (3)
opoplawski (2)
vema1818 (2)
AvijeetPrasad (2)

Top Pull Request Authors

sgpearse (464)
StasJ (421)
clyne (253)
shaomeng (212)
ifranda (12)
dependabot[bot] (4)
ghost (4)
NihanthCW (2)
ayenpure (2)
core-code (1)
khallock (1)
erogluorhan (1)
RemiLacroix-IDRIS (1)
klacansky (1)
opoplawski (1)

Top Issue Labels

Bug (1,596)
High (1,163)
Fixed (877)
Medium (433)
Enhancement (318)
Usability (163)
Low (162)
Rejected (162)
Documentation (125)
Duplicate (81)
✓ still exists (80)
Works For Me (69)
Refactor Needed (67)
Performance (48)
DevOps (44)
Will Not Fix (37)
No Longer Applicable (34)
Developer Feature (33)
Question (29)
Postponed (29)
Feedback (17)
Regression (13)
testing (5)
conda/mamba related (3)
Unprioritized (2)
Crash (2)
Work in progress (2)
Not-In-Master (1)

Top Pull Request Labels

Postponed (6)
dependencies (4)
Rejected (1)
Work in progress (1)
Fixed (1)

Dependencies

share/docker/centos7/Dockerfile docker

centos 7.4.1708 build

share/docker/ubuntu18/Dockerfile docker

ubuntu 18.04 build

apps/pythonapi/setup.py pypi

cppyy *
ipython *
jupyter *
matplotlib *
scipy *
xarray *

Score: 9.548596730390896

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