Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

https://github.com/keurfonluu/disba

Numba-accelerated computation of surface wave dispersion
https://github.com/keurfonluu/disba

dispersion geosciences python seismology surf96 surface-wave

Last synced: about 2 months ago
JSON representation

Numba-accelerated computation of surface wave dispersion

Lists

README 

        
disba

=====



|License| |Stars| |Pyversions| |Version| |Downloads| |Code style: black| |Codacy Badge| |Codecov| |Build| |Travis| |Awesome| |DOI|



**disba** is a computationally efficient Python library for the modeling of surface wave dispersion that implements a subset of codes from `Computer Programs in Seismology (CPS) `__ in Python compiled `just-in-time `__ with `numba `__. Such implementation alleviates the usual prerequisite for a Fortran compiler needed by other libraries also based on CPS (e.g., `pysurf96 `__, `srfpython `__ and `PyLayeredModel `__) which often leads to further installation troubleshooting, especially on Windows platform.



**disba** aims to be lightweight and portable without compromising on the performance. For both Rayleigh-wave and Love-wave, it is significantly faster than CPS's *surf96* program compiled with `f2py `__, noticeably for large number of layers.



.. list-table::



   *  - |Perf Rayleigh|

      - |Perf Love|



Features

--------



Forward modeling:



-  Compute Rayleigh-wave phase or group dispersion curves using *Dunkin's matrix* or *fast delta matrix* algorithms,

-  Compute Love-wave phase or group dispersion curves using *Thomson-Haskell* method,

-  Compute Rayleigh-wave ellipticity.



Eigenfunctions and sensitivity kernels:



-  Compute Rayleigh- and Love- wave eigenfunctions,

-  Compute Rayleigh- and Love- wave phase or group velocity, and Rayleigh-wave ellipticity sensitivity kernels with respect to layer thickness, P- and S- wave velocities, and density.



Installation

------------



The recommended way to install **disba** and all its dependencies is through the Python Package Index:



.. code:: bash



   pip install disba[full] --user



Otherwise, clone and extract the package, then run from the package location:



.. code:: bash



   pip install .[full] --user



To test the integrity of the installed package, check out this repository and run:



.. code:: bash



   pytest



Documentation

-------------



Refer to the online `documentation `__ for detailed description of the API and examples.



Alternatively, the documentation can be built using `Sphinx `__:



.. code:: bash



   pip install -r doc/requirements.txt

   sphinx-build -b html doc/source doc/build



Usage

-----



The following example computes the Rayleigh- and Love- wave phase velocity dispersion curves for the 3 first modes.



.. code:: python



   import numpy as np

   from disba import PhaseDispersion



   # Velocity model

   # thickness, Vp, Vs, density

   # km, km/s, km/s, g/cm3

   velocity_model = np.array([

      [10.0, 7.00, 3.50, 2.00],

      [10.0, 6.80, 3.40, 2.00],

      [10.0, 7.00, 3.50, 2.00],

      [10.0, 7.60, 3.80, 2.00],

      [10.0, 8.40, 4.20, 2.00],

      [10.0, 9.00, 4.50, 2.00],

      [10.0, 9.40, 4.70, 2.00],

      [10.0, 9.60, 4.80, 2.00],

      [10.0, 9.50, 4.75, 2.00],

   ])



   # Periods must be sorted starting with low periods

   t = np.logspace(0.0, 3.0, 100)



   # Compute the 3 first Rayleigh- and Love- wave modal dispersion curves

   # Fundamental mode corresponds to mode 0

   pd = PhaseDispersion(*velocity_model.T)

   cpr = [pd(t, mode=i, wave="rayleigh") for i in range(3)]

   cpl = [pd(t, mode=i, wave="love") for i in range(3)]



   # pd returns a namedtuple (period, velocity, mode, wave, type)



.. list-table::



   *  - |Sample Rayleigh|

      - |Sample Love|



Likewise, ``GroupDispersion`` can be used for group velocity.



**disba**'s API is consistent across all its classes which are initialized and called in the same fashion. Thus, eigenfunctions are calculated as follow:



.. code:: python



   from disba import EigenFunction



   eigf = EigenFunction(*velocity_model.T)

   eigr = eigf(20.0, mode=0, wave="rayleigh")

   eigl = eigf(20.0, mode=0, wave="love")



   # eigf returns a namedtuple

   #  - (depth, ur, uz, tz, tr, period, mode) for Rayleigh-wave

   #  - (depth, uu, tt, period, mode) for Love-wave



.. list-table::



   *  - |Eigen Rayleigh|

      - |Eigen Love|



Phase velocity sensitivity kernels (``GroupSensitivity`` for group velocity):



.. code:: python



   from disba import PhaseSensitivity



   ps = PhaseSensitivity(*velocity_model.T)

   parameters = ["thickness", "velocity_p", "velocity_s", "density"]

   skr = [ps(20.0, mode=0, wave="rayleigh", parameter=parameter) for parameter in parameters]

   skl = [ps(20.0, mode=0, wave="love", parameter=parameter) for parameter in parameters]



   # ps returns a namedtuple (depth, kernel, period, velocity, mode,wave, type, parameter)



.. list-table::



   *  - |Kernel Rayleigh|

      - |Kernel Love|



Ellipticity and ellipticity sensitivity kernels:



.. code:: python



   from disba import Ellipticity, EllipticitySensitivity



   ell = Ellipticity(*velocity_model.T)

   rel = ell(t, mode=0)



   # ell returns a namedtuple (period, ellipticity, mode)



   es = EllipticitySensitivity(*velocity_model.T)

   ek = [es(20.0, mode=0, parameter=parameter) for parameter in parameters]



   # es returns a namedtuple (depth, kernel, period, velocity, mode, wave, type, parameter)



.. list-table::



   *  - |Sample Ellipticity|

      - |Kernel Ellipticity|



Contributing

------------



Please refer to the `Contributing

Guidelines `__ to see how you can help. This project is released with a `Code of Conduct `__ which you agree to abide by when contributing.



.. |License| image:: https://img.shields.io/github/license/keurfonluu/disba

   :target: https://github.com/keurfonluu/disba/blob/master/LICENSE



.. |Stars| image:: https://img.shields.io/github/stars/keurfonluu/disba?logo=github

   :target: https://github.com/keurfonluu/disba



.. |Pyversions| image:: https://img.shields.io/pypi/pyversions/disba.svg?style=flat

   :target: https://pypi.org/pypi/disba/



.. |Version| image:: https://img.shields.io/pypi/v/disba.svg?style=flat

   :target: https://pypi.org/project/disba



.. |Downloads| image:: https://pepy.tech/badge/disba

   :target: https://pepy.tech/project/disba



.. |Code style: black| image:: https://img.shields.io/badge/code%20style-black-000000.svg?style=flat

   :target: https://github.com/psf/black



.. |Codacy Badge| image:: https://img.shields.io/codacy/grade/1d2218bb7d0e4e0fb2dec26fa32fe92e.svg?style=flat

   :target: https://www.codacy.com/manual/keurfonluu/disba?utm_source=github.com&utm_medium=referral&utm_content=keurfonluu/disba&utm_campaign=Badge_Grade



.. |Codecov| image:: https://img.shields.io/codecov/c/github/keurfonluu/disba.svg?style=flat

   :target: https://codecov.io/gh/keurfonluu/disba



.. |DOI| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3987395.svg?style=flat

   :target: https://doi.org/10.5281/zenodo.3987395



.. |Build| image:: https://img.shields.io/github/workflow/status/keurfonluu/disba/Python%20package

   :target: https://github.com/keurfonluu/disba



.. |Travis| image:: https://img.shields.io/travis/com/keurfonluu/disba/master?label=docs

   :target: https://keurfonluu.github.io/disba/



.. |Awesome| image:: https://img.shields.io/badge/awesome-yes-C6A4BF

   :target: https://github.com/softwareunderground/awesome-open-geoscience



.. |Perf Rayleigh| image:: https://raw.githubusercontent.com/keurfonluu/disba/e29865fb0b385b295bc55b733a138a741787879d/.github/perf_rayleigh.svg

   :alt: perf-rayleigh



.. |Perf Love| image:: https://raw.githubusercontent.com/keurfonluu/disba/5d23a8bb3967fd59c1a38b59ce1bf800749c7eb2/.github/perf_love.svg

   :alt: perf-love



.. |Sample Rayleigh| image:: https://raw.githubusercontent.com/keurfonluu/disba/5d23a8bb3967fd59c1a38b59ce1bf800749c7eb2/.github/sample_rayleigh.svg

   :alt: sample-rayleigh



.. |Sample Love| image:: https://raw.githubusercontent.com/keurfonluu/disba/5d23a8bb3967fd59c1a38b59ce1bf800749c7eb2/.github/sample_love.svg

   :alt: sample-love



.. |Sample Ellipticity| image:: https://raw.githubusercontent.com/keurfonluu/disba/5f9b95a144e3751ffa98b5860663af874c02ae1c/.github/sample_ellipticity.svg

   :alt: sample-ellipticity



.. |Eigen Rayleigh| image:: https://raw.githubusercontent.com/keurfonluu/disba/5f9b95a144e3751ffa98b5860663af874c02ae1c/.github/eigen_rayleigh.svg

   :alt: eigen-rayleigh



.. |Eigen Love| image:: https://raw.githubusercontent.com/keurfonluu/disba/5f9b95a144e3751ffa98b5860663af874c02ae1c/.github/eigen_love.svg

   :alt: eigen-love



.. |Kernel Rayleigh| image:: https://raw.githubusercontent.com/keurfonluu/disba/5f9b95a144e3751ffa98b5860663af874c02ae1c/.github/kernel_rayleigh.svg

   :alt: kernel-rayleigh



.. |Kernel Love| image:: https://raw.githubusercontent.com/keurfonluu/disba/5f9b95a144e3751ffa98b5860663af874c02ae1c/.github/kernel_love.svg

   :alt: kernel-love



.. |Kernel Ellipticity| image:: https://raw.githubusercontent.com/keurfonluu/disba/5f9b95a144e3751ffa98b5860663af874c02ae1c/.github/kernel_ellipticity.svg

   :alt: kernel-ellipticity