https://gaia-unil.github.io/G2S/
A flexible MPS framework
https://gaia-unil.github.io/G2S/
geostatistics mps multiple-point-statistics narrow-distribution-selection nds qs quantile-sampling simulations stochastic texture-synthesis training-images
Last synced: 23 days ago
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A flexible MPS framework
- Host: GitHub
- URL: https://gaia-unil.github.io/G2S/
- Owner: GAIA-UNIL
- License: gpl-3.0
- Created: 2017-08-25T18:37:22.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2025-03-11T10:51:53.000Z (3 months ago)
- Last Synced: 2025-04-15T08:49:14.880Z (about 1 month ago)
- Topics: geostatistics, mps, multiple-point-statistics, narrow-distribution-selection, nds, qs, quantile-sampling, simulations, stochastic, texture-synthesis, training-images
- Language: C++
- Homepage: https://gaia-unil.github.io/G2S/
- Size: 20.6 MB
- Stars: 44
- Watchers: 2
- Forks: 10
- Open Issues: 3
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# G2S: The GeoStatistical Server
[](https://www.gnu.org/licenses/gpl-3.0)

## Brief overview
**G2S** is composed of 2 parts:
- the first one is a server that manages computations and can be compiled for each hardware to obtain optimal performance.
- the second part is composed of different interfaces that communicate with the server through ZeroMQ. Interfaces can be added for each software. Similarly, G2S can be extended for any other geostatistical simulation algorithm.Currently the **G2S** interface is available for *MATLAB* and *Python*. **G2S** is provided with both simulation algorithms **QS** (QuickSampling) and **NDS** (Narrow Distribution Selection).
**G2S** is currently only available for *UNIX*-based systems, *Linux* and *macOS*. A solution for *Windows 10+* is provided using *WSL* (Windows Subsystem for Linux). However, for previous *Windows* versions, the only solution currently available is to install a *Linux* system manually inside a virtual machine.
## Documentation
An interactive and complete documentation is available [here](https://gaia-unil.github.io/G2S/).
## Online Demo (Back! but slow)
An interactive online version is available [here](https://www.mgravey.com/mps.online/), to experiment with small unconditional simulations.