Updated 2 months ago


MPSlib provides a C++ class, and a set of algorithms for simulation of models based on a multiple point statistical (MPS) models inferred from a training image.

As example the following algorithms has been implemented

A Matlab/Octave interface to these algorithms, is available, from which all parameters can be set.

The latest stable code can be downloaded from

The current development version is available through GitHub at


Along with the first version of MPSlib a manuscript was published in SoftwareX. Please use this for referencing MPSlib:

Hansen, T.M., Vu. L.T., and Bach, T. 2016. MPSLIB: A C++ class for sequential simulation of multiple-point statistical models, in SoftwareX, doi:10.1016/j.softx.2016.07.001. [pdf,www]


The goal of developing these codes has been to produce a set of algorithms, based on sequential simulation, for simulation of multiple point statistical models. The code should be easy to compile and extend, and should be allowed for both commercial and non-commercial use.

MPSlib (version 1.0) has been developed by I-GIS and Solid Earth Physics, Niels Bohr Institute.

Development has been funded by the Danish National Hightech Foundation (now: the Innovation fund) through the ERGO (Effective high-resolution Geological Modeling) project, a collaboration between IGIS, GEUS, and Niels Bohr Institute.

License (LGPL)

This library is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with this program; if not, write to the Free Software Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.