HPGL

"HPGL stands for High Performance Geostatistics Library.

HPGL is written in C++ / Python to realize some geostatistical algorithms (see full list below). The algorithms are called in Python, by executing the corresponding commands.


HPGL boasts the following features:

• High performance (even in comparison to commercial software)
• Low memory consumption
• Parallel Kriging (shared memory, OpenMP)
• Cross-platform functionality (Windows / Linux)
• Easy development of geo-modeling scenarios using Python
• NumPy/SciPy compatibility (properties are stored as NumPy arrays)
• Built-it functions for writing and reading GSLIB and Eclipse Property text files
• LAPACK solvers for linear equation problems in Kriging and Simulation
• The algorithms are performed on a Cartesian Grid (IJK-grid)

The current version of HPGL (0.9.9) implements the following algorithms:

• Simple Kriging (SK)
• Ordinary Kriging (OK)
• Indicator Kriging (IK)
• Local Varying Mean Kriging (LVM Kriging)
• Simple CoKriging (Markov Models 1 & 2)
• Sequential Indicator Simulation (SIS)
• Corellogram Local Varying Mean SIS (CLVM SIS)
• Local Varying Mean SIS (LVM SIS)
• Sequential Gaussian Simulation (SGS)

http://hpgl.github.io/hpgl/

https://github.com/hpgl/hpgl