Skip to main content

An Efficient and Integrated Python Package for Computing Synthetic Seismograms in a Layered Half-Space Model

Project description

Image 2

GitHub code size in bytes GitHub Actions Workflow Status Github Tag GitHub License

Like this project? Give it a Star!

中文文档

Overview

PyGRT: An Efficient and Integrated C/Python Package for Computing Synthetic Seismograms, Strain, Rotation and Stress Tensor in a Layered Half-Space Model (Dynamic & Static Cases)

  • PyGRT now can compute following properties in both dynamic and static case.

    • Displacements and its spatial derivatives
    • Strain Tensor
    • Rotation Tensor
    • Stress Tensor
  • At present, PyGRT can run on

    • Linux
    • MacOS
    • Windows
  • PyGRT is extremely easy to install by distributing precompiled binary files.

  • PyGRT is still evolving, and more features will be released in the future.

Features

  • Dual-Language:
    To optimize performance, PyGRT uses C for its core computational tasks, while Python provides a user-friendly interface. Support script style and command line style to run the program.

  • Parallelization:
    Accelerated with OpenMP for parallel processing.

  • Integration:
    Built on the Generalized Reflection-Transmission matrix Method (GRTM) and the Discrete Wavenumber Method (DWM), PyGRT integrates the Peak-Trough Averaging Method (PTAM) and Filon’s Integration Method (FIM) to handle diverse source-receiver distributions.

  • Modular Design:
    Clean and organized code structure, making it easy to extend and maintain.

  • Compatibility:
    PyGRT provides pre-compiled static files, ensuring ease of installation, usage, and portability across different systems.

Image 2

Pre-Requisite

  • For Thread-Level Parallel Computing
    • OpenMP

      • For Linux and macOS users: If the GNU compiler is installed on your system, the OpenMP library is usually included.
      • For Windows users: OpenMP has been statically linked.

      In general, you don't have to worry about it. However, if the program complains that "libgomp.so not found" or "needs more dependencies", you should install OpenMP.


  • For Python Script Style
    • Anaconda (recommend), to build your virtual environment.
    • Other dependencies are declared in setup.py, automatically handled by pip install.

  • For Command Line Style
    the output waveforms are binary files in SAC format, you need Seismic Analysis Code (SAC) to view and process.

Installation

In PyGRT, the C programs and libraries operate independently of Python (not CPython or Cython). If you are not familiar with Python and pip, and prefer the Command Line Style, you can quickly run the program by downloading the latest GitHub release for your machine. The necessary files are located in the pygrt/C_extension/bin and pygrt/C_extension/lib folders.


Two ways, choose one:

  1. PYPI (recommend)
    Run the following command in your virtual environment:

    pip install -v pygrt-kit
    
  2. Github release

    • Download the latest release for your machine, uncompress, and change the directory.

    • Run the following command in your virtual environment:

      pip install -v .
      
  3. Build from Source Code.
    Not recommend.

Setting

For Command Line Style, run

python -m pygrt.print

the outputs are

PyGRT installation directory: </path/to/installation>
PyGRT executable file directory: </path/to/installation/bin>
PyGRT library directory: </path/to/installation/lib>

and you can

  • add "executable file directory" to PATH environment variable.

Then you can run the command like grt in terminal.
For each command, use -h to see the help message.

Usage Example

example/ folder shows some examples in paper. More examples are coming soon.

multi traces lamb problem far-field record

static_dc static_sf static_exp

imag_G

imag_G

Contact

If you have any questions or suggestions, feel free to reach out:

Citation

Zhu D., J. Wang*, J. Hao, S. Yao, Y. Xu, T. Xu and Z. Yao (2025). PyGRT: An Efficient and Integrated Python Package for Computing Synthetic Seismograms in a Layered Half-Space Model. Seismological Research Letters. (under review)

Project details


Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

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

pygrt_kit-0.6.0-py3-none-win_amd64.whl (6.2 MB view details)

Uploaded Python 3Windows x86-64

pygrt_kit-0.6.0-py3-none-manylinux2014_x86_64.whl (3.2 MB view details)

Uploaded Python 3

pygrt_kit-0.6.0-py3-none-macosx_11_0_arm64.whl (1.9 MB view details)

Uploaded Python 3macOS 11.0+ ARM64

pygrt_kit-0.6.0-py3-none-macosx_10_9_x86_64.whl (3.6 MB view details)

Uploaded Python 3macOS 10.9+ x86-64

File details

Details for the file pygrt_kit-0.6.0-py3-none-win_amd64.whl.

File metadata

  • Download URL: pygrt_kit-0.6.0-py3-none-win_amd64.whl
  • Upload date:
  • Size: 6.2 MB
  • Tags: Python 3, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for pygrt_kit-0.6.0-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 e32c76732546d532a59d3867f037de98ba382162fba4e5692184689822a0c640
MD5 7ed79fe20b3e4297ea02426176ab3364
BLAKE2b-256 6fee872403528c83060716109228ac043d0e8e900f60e3fffecd21620d021e7c

See more details on using hashes here.

Provenance

The following attestation bundles were made for pygrt_kit-0.6.0-py3-none-win_amd64.whl:

Publisher: build.yml on Dengda98/PyGRT

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file pygrt_kit-0.6.0-py3-none-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pygrt_kit-0.6.0-py3-none-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 e99d4ed61bfa0ae2c2dba78f6bb9c0017a47307cbbb75dcc7a3e6728b58970d7
MD5 799e78b64ac0849c0a690b884ad3095c
BLAKE2b-256 2b73425783eb89793215452fd020406e26db4209ae4b95a5650dc4cea2516da0

See more details on using hashes here.

Provenance

The following attestation bundles were made for pygrt_kit-0.6.0-py3-none-manylinux2014_x86_64.whl:

Publisher: build.yml on Dengda98/PyGRT

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file pygrt_kit-0.6.0-py3-none-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pygrt_kit-0.6.0-py3-none-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 68ca67a22254051acaa57b4c223cde569cb03e8982ad467f5a273e2ad1ff1e7d
MD5 6e5e616918a001efb41c420b7f34d6fb
BLAKE2b-256 fd3e23e0bc865358c616e42e32a20abbccde9e2c9dbcbf6e2a2a1973c178bc93

See more details on using hashes here.

Provenance

The following attestation bundles were made for pygrt_kit-0.6.0-py3-none-macosx_11_0_arm64.whl:

Publisher: build.yml on Dengda98/PyGRT

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file pygrt_kit-0.6.0-py3-none-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pygrt_kit-0.6.0-py3-none-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 8ef586a4cd5da46a561473df72c68bfca34fff5e837cdedfaf6d2357ee34cd28
MD5 af6330efaf5f71f8e99dbd24e1bb2d89
BLAKE2b-256 2aa4e65f6ae4ae1a2f2a67a2d2a32753dc91c7d17245bde8b971e84bcefd3a8e

See more details on using hashes here.

Provenance

The following attestation bundles were made for pygrt_kit-0.6.0-py3-none-macosx_10_9_x86_64.whl:

Publisher: build.yml on Dengda98/PyGRT

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

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