Geostatistics in Python
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.
krige3d.py
: kriging 3d data.
sgsim.py
: Sequential Gaussian Simulation.
super_block.py
: Class for performing super block search used in kriging.
krige3d.py
sgsim.py
normal_score_transform.py
: Class for NST used in Gaussian Simulation.
sgsim.py
For full documentation, including installation, tutorials and PDF documents, please see http://pygeostatistics.readthedocs.io/.