Skip to main content

pySRA

PyPi Cheese Shop Build Status Documentation Status Code Quality Test Coverage License Zenodo MyBinder

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:
    • Darendeli (2001)

    • Menq (2004)

    • Kishida (2012)

  • 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.

Installation

pysra is available via pip and can be installed with:

pip install pysra

If you are using conda and a create a pysra 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.

Examples

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

History

v0.5.0 (2022-06-14)

  • Renamed to pyStrata.

v0.4.11 (2020-03-31)

  • Added: Depth dependent velocity variation model

  • Added: Output plotting functionality

  • Added: Ability to exclude soil type variation from bedrock

v0.4.10 (2020-03-27)

  • Fixed: Error in SPID variation of G/Gmax

  • Added: Scaling during read of SMC and AT2 input motions

v0.4.9 (2020-03-09)

  • Add InitialVelProfile and CompatVelProfile outputs

v0.4.8 (2019-12-11)

  • Remove Cython and cyko as dependencies

  • Added a numba based Konno-Ohmachi smoothing

v0.4.6 (2019-11-12)

  • FIXED #11: Dependencies missing on install.

v0.4.5 (2019-10-24)

  • FIXED #9: Wrong stress for some Menq components.

v0.4.4 (2019-05-22)

  • Incremented version because of issue with automated builds.

v0.4.3 (2019-05-22)

  • FIXED: Bug in MANIFEST.in

v0.4.2 (2019-05-22)

  • Incremented version because of issue with automated builds.

v0.4.1 (2019-05-22)

  • Fixed strain profile to use max_strain.

  • Changed README and HISTORY to markdown.

v0.4.0 (2019-03-11)

  • Added smoothed FourierAmplitudeSpectrum output.

v0.3.2 (2018-12-02)

  • Fixed building of docs.

  • Removed stickler.

  • Version double increment due to pypi naming conflict.

v0.3.0 (2018-11-30)

  • Converted all damping to decimal.

  • Added tests for KishidaSoilType.

  • Added tests against Deepsoil.

v0.0.1 (2016-04-30)

  • First release on PyPI.

Metadata

Release files for pySRA 0.5.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pySRA 0.5.0
File Size Uploaded
pySRA-0.5.0.tar.gz 44.4 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for pySRA 0.5.0
File Interpreter ABI Platform
pySRA-0.5.0-py2.py3-none-any.whl Python 2, Python 3 none any Details

Total release size: 98.5 kB

Release files / pySRA-0.5.0.tar.gz

Download URL pySRA-0.5.0.tar.gz
Size 44.4 kB
Tags Source
SHA-256 checksum
How to use checksums
29c632de32fc8cb951feb761cdc38876d1d688a28afd5b8743a675f13732d722
BLAKE2b-256 checksum
How to use checksums
820a5e580c155029d32a9368249fef04c12ed20d1bb5d7dfc504746746d808b2
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.12

Release files / pySRA-0.5.0-py2.py3-none-any.whl

Download URL pySRA-0.5.0-py2.py3-none-any.whl
Size 54.1 kB
Tags Python 2 Python 3
SHA-256 checksum
How to use checksums
758e9f325c3664c89977a5855b19866a1d35632c14f5b0f3d78d751b1eea6feb
BLAKE2b-256 checksum
How to use checksums
f01f61323d89f588dcbc9d0ee6c5f5f13e05c8c7b937dab43d9f34a95792cc0f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.12

Release history Release notifications | RSS feed

This release

0.5.0 This release

2 release files

0.4.11

2 release files

0.4.10

2 release files

0.4.9

2 release files

0.4.8

1 release file

0.4.7

1 release file

0.4.6

1 release file

0.4.5

1 release file

0.4.4

1 release file

0.4.3

1 release file

0.4.2

1 release file

0.4.1

1 release file

0.4.0

1 release file

0.3.2

1 release file

0.3.0

1 release file

0.2.1

1 release file

0.2.0

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page