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 Documentation Status PyPI Version 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-1.0.2.6.tar.gz (194.5 kB view details)

Uploaded Source

Built Distribution

pyTMD-1.0.2.6-py3-none-any.whl (225.4 kB view details)

Uploaded Python 3

File details

Details for the file pyTMD-1.0.2.6.tar.gz.

File metadata

  • Download URL: pyTMD-1.0.2.6.tar.gz
  • Upload date:
  • Size: 194.5 kB
  • 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/4.48.2 CPython/3.8.5

File hashes

Hashes for pyTMD-1.0.2.6.tar.gz
Algorithm Hash digest
SHA256 75b4779faea1588243f328bcf8a468f7f7098de8949df6f248951b54c560448c
MD5 56fee1d4eb1614a1bff47bc4669c9326
BLAKE2b-256 e6f305dbcfa97216136297f7b637930d55fa44d2daa2b8a27011c02dca8cb2e2

See more details on using hashes here.

File details

Details for the file pyTMD-1.0.2.6-py3-none-any.whl.

File metadata

  • Download URL: pyTMD-1.0.2.6-py3-none-any.whl
  • Upload date:
  • Size: 225.4 kB
  • 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/4.48.2 CPython/3.8.5

File hashes

Hashes for pyTMD-1.0.2.6-py3-none-any.whl
Algorithm Hash digest
SHA256 68021468558d1c8b578db53b80e47a1bf39f2185c0d0f510894275ec27abdfda
MD5 4c35d18dcb1dedc5233f4818311f4183
BLAKE2b-256 dbe6d30aeea3edabcedf6ca13807cda014c988b934e159810590052468518cd9

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