Skip to main content

Ground motion models implemented in Python.

Project description

pyGMM

PyPi Cheese Shop Build Status Code Quality Test Coverage License DOI

Ground motion models implemented in Python.

I have recently learned that additional ground motion models have been implemented through GEM’s OpenQuake Hazardlib, which I recommend checking out.

Features

Models currently supported:

  • Akkar, Sandikkaya, & Bommer (2014) with unit tests

  • Atkinson & Boore (2006)

  • Abrahamson, Silva, & Kamai (2014) with unit tests

  • Abrahamson, Gregor, & Addo (2016) with unit tests

  • Boore, Stewart, Seyhan, & Atkinson (2014) with unit tests

  • Campbell (2003)

  • Campbell & Bozorgnia (2014) with unit tests

  • Chiou & Youngs (2014) with unit tests

  • Derras, Bard & Cotton (2013) with unit tests

  • Idriss (2014) with unit tests

  • Pezeshk, Zandieh, & Tavakoli (2001)

  • Tavakoli & Pezeshk (2005)

Conditional spectra models:

  • Baker & Jayaram (2008) with unit tests

  • Kishida (2017) with unit tests

Unit tests means that each test cases are used to test the implemention of the model.

Citation

Please cite this software using the DOI.

History

0.6.1 (2020-06-03)

  • Added Coppersmith & Bommer (2014) model for Hanford

  • Factored tests

0.6.0 (2019-08-12)

  • Added Abrahamson, Gregor, Addo (2014)

  • Added Abrahamson & Gulerce (2011)

  • Added conditional mean spectra models.

  • Added Scenario objects.

  • Added typing for all classes.

0.4.0 (2016-04-08)

  • Added Hermkes et al. (2014).

  • Improved documentation.

  • Added Baker & Jayaram (2008), Kishida (2017)

0.3.2 (2016-03-30)

  • Nothing changed yet.

0.3.1 (2016-03-30)

  • First release on PyPI.

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

pygmm-0.6.1.tar.gz (857.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pygmm-0.6.1-py2.py3-none-any.whl (862.7 kB view details)

Uploaded Python 2Python 3

File details

Details for the file pygmm-0.6.1.tar.gz.

File metadata

  • Download URL: pygmm-0.6.1.tar.gz
  • Upload date:
  • Size: 857.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/47.1.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.7.1

File hashes

Hashes for pygmm-0.6.1.tar.gz
Algorithm Hash digest
SHA256 669ba175df6fc8822d880c3eb216400970616a0f99ff27d3a574adc727322714
MD5 6832c19dd97b4a520fddabd75c64ad85
BLAKE2b-256 dd70cba3548dec8b8877cb2cf8a0f6a4f6b7d97f79c13b17323cbaa022e7c5d4

See more details on using hashes here.

File details

Details for the file pygmm-0.6.1-py2.py3-none-any.whl.

File metadata

  • Download URL: pygmm-0.6.1-py2.py3-none-any.whl
  • Upload date:
  • Size: 862.7 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/47.1.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.7.1

File hashes

Hashes for pygmm-0.6.1-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 1f7566908ce22833dc999294d37dd30cdf0b73cb76b637b51e92393b19388ad3
MD5 95c7031e004e67eb2de14a6808844e9f
BLAKE2b-256 4b0e7f9f8109d3e0f2a0c216f2649a04dbd22fd83f252a3331f6f630f49669af

See more details on using hashes here.

Supported by

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