README
This is the README file of the s2Dcd
, a Python package that allows
to obtain 3D multiple-point statistics (MPS) simulations by using only
2D training images (TIs). More details about the methodology can be
found in the paper by Comunian, Renard and Straubhaar, DOI:
10.1016/j.cageo.2011.07.009.
Requirements
This version of s2Dcd
heavily relies on the geone
module. You can
find more info about it and installation instructions at the link
https://github.com/randlab/geone.
Quick start installation
NOTE: To run the
s2Dcd
, a MPS simulation engine like the DeeSse is needed! If you have installed the modulegeone
then that should be already included. Note however that the version of the DeeSse included in thegeone
repository has some limitations. If you want to use the full functionalities of the package, please ask for a license.
Clone or download the s2Dcd
package on a local directory, by using for example:
git clone git@github.com:randlab/s2Dcd.git
or
git clone git@bitbucket.org:alecomunian/s2dcd.git
(actually, the two repositories should contain exactly the same version of the code.)
Then inside the downloaded directory
pip install .
If the installation worked properly, then you should be able to perform an
import s2Dcd
from a Python console without any error/warning.
Examples
Animation
For an animation that illustrates how the s2Dcd
approach works, check this link.
Simple example
Have a look at examples/01_Strebelle/s2Dcd_run-ex01.ipynb for a commented Jupyter notebook. You can also find the same file as Python script in examples/01_Strebelle/s2Dcd_run-ex01.py.
More info
Maintainers
At the moment, the code is maintained by
A.Comunian. Don't hesitate to
contact him if you have some suggestions of questions about the
s2Dcd
.
Source
The source file of the s2Dcd
package is available both on GitHub and Bitbucket at the following links: