pyStrata

Python library for site response analysis.

Introduction

Site response analyses implemented in Python. This Python packages aims to implement many of the features found in Strata. These features include:

• Input motion characterization:
  • Time series
  • Random vibration theory
• Wave propagation or site amplification:
  • linear
  • equivalent-linear
  • equivalent-linear with frequency dependent properties
  • quarter wavelength
• Nonlinear curve models:
  • Predictive models:
    • Darendeli (2001)
    • Menq (2004)
    • Kishida (2012)
  • Curves:
    • Vucetic & Dobry (1991)
    • EPRI (1993)
    • GEI (1983)
    • GeoMatrix (1990)
    • Idriss (1990)
    • Imperial Valley Soils
    • Iwasaki
    • Peninsular Range
    • Seed & Idriss
• Site and soil property uncertainty:
  • Toro (1994) Vs correlation model
  • G/Gmax and D uncertainty:
  • Darendeli (2001)
  • EPRI SPID (2013)

Development of this software is on-going and any contributions are encouraged. Previously named pysra, but renamed after some sage and persistent advice to be better associated with Strata.

Installation

pystrata is available via pip and can be installed with:

pip install pystrata

If you are using conda and a create a pystrata specific environmental make sure you install ipykernels and nb_conda_kernels so that the environment is discoverable by Jupyter with:

conda install ipykernel nb_conda_kernels

Citation

Please cite this software using the following DOI:

Albert Kottke & Maxim Millen. (2023). arkottke/pystrata: v0.5.2 (v0.5.2). Zenodo. https://doi.org/10.5281/zenodo.7551992

or with BibTeX:

@software{albert_kottke_2023_7551992,
  author       = {Albert Kottke and
                  Maxim Millen},
  title        = {arkottke/pystrata: v0.5.2},
  month        = jan,
  year         = 2023,
  publisher    = {Zenodo},
  version      = {v0.5.2},
  doi          = {10.5281/zenodo.7551992},
  url          = {https://doi.org/10.5281/zenodo.7551992}
}

Examples

There are a variety of examples of using pystrata within the examples directory. An interactive Jupyter interface of these examples is available on .