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pybel1d

A python implementations of the BEL1D codes (see the BEL1D repo)

https://github.com/hadrienmichel/pybel1d

Science Score: 36.0%

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Last synced: 10 months ago · JSON representation

Repository

A python implementations of the BEL1D codes (see the BEL1D repo)

Basic Info
  • Host: GitHub
  • Owner: hadrienmichel
  • License: bsd-2-clause
  • Language: Python
  • Default Branch: master
  • Size: 8.03 MB
Statistics
  • Stars: 7
  • Watchers: 2
  • Forks: 3
  • Open Issues: 1
  • Releases: 3
Created about 6 years ago · Last pushed about 1 year ago
Metadata Files
Readme License Citation

README.md

DOI

pyBEL1D

pyBEL1D is a python implementation of the BEL1D matlab codes (BEL1D). It is a work under devellopment and not in any form a finished product.

Installation:

The following instructions are working on Windows 10.

Build a new conda environment with python 3.7. conda create -n bel1d conda activate bel1d Install the different libraries in the new environment: ``` conda install python=3.7.6 # For the python version conda install numpy conda install scipy conda install scikit-learn conda install matplotlib conda install -c anaconda dill

For multiprocessing:

pip install pathos

For the sNMR application

conda config --add channels gimli --add channels conda-forge conda install pygimli

For DC application:

conda install libpython conda install -c msys2 m2w64-toolchain pip install git+https://github.com/miili/pysurf96 ```

For MACOS installation, replace the last 3 lines with (not tested): conda install -c anaconda gfortran_osx-64 pip install git+https://github.com/miili/pysurf96

On Linux machines, run (not tested): conda install -c anaconda gfortran_linux-64 pip install git+https://github.com/miili/pysurf96

Then run the code in this environment (bel1d for the example above).

Utilization

All the functions must be in the pyBEL1D folder to run (or you need to import the library, not yet implemented) and respect the folder architecture that is in the repository.

  • The file MASW_paper.py containes a highely detailed and commented exemple on how to run BEL1D with IPR and post-process the results.
  • The file exampleSNMR.py provides a commented example on how to run the codes for SNMR data.
  • The file exampleDC.py provides an example on how to use BEL1D with a dispersion curve originating from real data.

Acknowledgement

The forward model for sNMR is provided by pygimli.

The forward model for Surface Waves dispersion curves is a Python inteface of the Computer programs in seismology (R. Hermans) provided by miili on github.

Owner

  • Name: Hadrien Michel
  • Login: hadrienmichel
  • Kind: user
  • Company: ULiège - UGent - F.R.S.-FNRS

GitHub Events

Total
  • Issues event: 1
  • Delete event: 1
  • Push event: 6
  • Pull request event: 1
  • Fork event: 1
  • Create event: 1
Last Year
  • Issues event: 1
  • Delete event: 1
  • Push event: 6
  • Pull request event: 1
  • Fork event: 1
  • Create event: 1

Dependencies

setup.py pypi
  • dill *
  • functools *
  • math *
  • matplotlib *
  • numpy *
  • pathos *
  • pygimli *
  • pysurf96 *
  • scikit-learn *
  • scipy *
  • time *
  • typing *