Skip to main content

Tide Model Driver to read OTIS, GOT and FES formatted tidal solutions and make tidal predictions

Project description

pyTMD

Language License PyPI Version Documentation Status codecov Binder Binder

Python-based tidal prediction software that reads OTIS, GOT and FES formatted tidal solutions for calculating ocean and load tides

Pole tide prediction software for calculating radial pole tide displacements

Dependencies

Reference

T. C. Sutterley, T. Markus, T. A. Neumann, M. R. van den Broeke, J. M. van Wessem, and S. R. M. Ligtenberg, "Antarctic ice shelf thickness change from multimission lidar mapping", The Cryosphere, 13, 1801-1817, (2019). doi:tc-13-1801-2019

L. Padman, M. R. Siegfried, H. A. Fricker, "Ocean Tide Influences on the Antarctic and Greenland Ice Sheets", Reviews of Geophysics, 56, 142-184, (2018). doi:10.1002/2016RG000546

Download

The program homepage is:
https://github.com/tsutterley/pyTMD
A zip archive of the latest version is available directly at:
https://github.com/tsutterley/pyTMD/archive/master.zip

Software

Matlab Tide Model Driver from Earth & Space Research is available at:
https://github.com/EarthAndSpaceResearch/TMD_Matlab_Toolbox_v2.5
Fortran OSU Tidal Prediction Software OTPS is available at:
https://www.tpxo.net/otps
pyTMD was incorporated into the NASA Cryosphere Altimetry Processing Toolkit at:
https://github.com/fspaolo/captoolkit

Disclaimer

This program is not sponsored or maintained by the Universities Space Research Association (USRA) or NASA. It is provided here for your convenience but with no guarantees whatsoever.

Credits

The Tidal Model Driver (TMD) Matlab Toolbox was developed by Laurie Padman, Lana Erofeeva and Susan Howard. The OSU Tidal Inversion Software (OTIS) and OSU Tidal Prediction Software (OTPS) were developed by Lana Erofeeva and Gary Egbert (copyright OSU, licensed for non-commercial use). The NASA Goddard Space Flight Center (GSFC) PREdict Tidal Heights (PERTH3) software was developed by Richard Ray and Remko Scharroo.

License

The content of this project is licensed under the Creative Commons Attribution 4.0 Attribution license and the source code is licensed under the MIT license.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyTMD-1.0.2.12.tar.gz (6.4 MB view details)

Uploaded Source

Built Distribution

pyTMD-1.0.2.12-py3-none-any.whl (6.4 MB view details)

Uploaded Python 3

File details

Details for the file pyTMD-1.0.2.12.tar.gz.

File metadata

  • Download URL: pyTMD-1.0.2.12.tar.gz
  • Upload date:
  • Size: 6.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.1.0 requests-toolbelt/0.9.1 tqdm/4.49.0 CPython/3.8.5

File hashes

Hashes for pyTMD-1.0.2.12.tar.gz
Algorithm Hash digest
SHA256 d4f6c7c59b91f677f981e51bdb2fd553cf10f26ae7d3ef927d7cdd4aa11257e8
MD5 cac6f50d92ace05232a939ab42b8dc3b
BLAKE2b-256 fd4566ccb21e1623a5751393a952676972178adc49570ffdb6a4071e252b77ec

See more details on using hashes here.

File details

Details for the file pyTMD-1.0.2.12-py3-none-any.whl.

File metadata

  • Download URL: pyTMD-1.0.2.12-py3-none-any.whl
  • Upload date:
  • Size: 6.4 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.1.0 requests-toolbelt/0.9.1 tqdm/4.49.0 CPython/3.8.5

File hashes

Hashes for pyTMD-1.0.2.12-py3-none-any.whl
Algorithm Hash digest
SHA256 560ac8670900c5056743804e7c4909ae9bdf048ef7b5c38e4d2a84853fed20c4
MD5 5118566bf11289099d36a4619b0513d8
BLAKE2b-256 c133c6b3ea1750d88e322899cf720eb4f8e8b76e186bb46a1e86ffd753009b55

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page