A collection of python routines (accelerated with Numba) and jupyter notebooks for geostatistics, which is immensely inspired by gslib (in Fortran).

Every routine reads its parameters from a parameter file written in json. All parameters including input/output file path need to be specified in these parameter files.

I've created scripts that assist in creating parameter files, they could be found in \parameters folder.

I tried to adhere to the naming convention of gslib when it comes to parameter names.

Markdown files describing parameters needed for each routine are in \gslib_help.

from pygeostatistics import Sgsim

sgsimulator = Sgsim("testData/test_sgsim.par")
sgsimulator.simulate()

• eda.py: exploratory data anaylysis.

• nst.py: apply normal score transform to data.

• gam.py: calculate variogram for regular data.

• gamv.py: calculate variogram for irregular data.

• sa.ipynb: interactive structural analysis.

• krige2d.py: kriging 2d data.

  • Simple Kriging
  • Ordinary Kriging

• krige3d.py: kriging 3d data.

  • Simple Kriging
  • Ordinary Kriging
  • Universal Kriging (Kriging with a Trend)
  • Kriging the Trend
  • Kriging with External drift
  • SK with non-stationary drift

• sgsim.py: Sequential Gaussian Simulation.

• super_block.py: Class for performing super block search used in kriging.

  • used in krige3d.py
  • used in sgsim.py

• normal_score_transform.py: Class for NST used in Gaussian Simulation.

  • used in sgsim.py

For full documentation, including installation, tutorials and PDF documents, please see http://pygeostatistics.readthedocs.io/.