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GEONE
GEONE is a Python3 package providing a set of tools for geostatistical modeling, including:
- multiple-point statistics (MPS) simulation as "DEESSE wrapper"
- geostatistical tools based on two-point statistics, including "GEOSCLASSIC wrapper"
- miscellaneous algorithms based on random processes
Documentation, examples and references
The documentation of GEONE is on https://geone.readthedocs.io.
<!-- The notebooks (examples) from the documentation are available in [docs/source/notebooks](./docs/source/notebooks). -->The notebooks (examples) from the documentation are available in docs/source/notebooks.
Installation
GEONE relies on pre-compiled C libraries (DEESSE and GEOSCLASSIC core)
GEONE is available:
- on PyPI (The Python Package Index), for:
- linux (x86_64 with GLIBC 2.35 or GLIBC 2.27) and python 3.9 to 3.12
- mac (x86_64 or arm64) and python 3.9 to 3.12
- windows and python 3.9 to 3.12
- on the Github repository, for:
- linux (x86_64 with GLIBC 2.35 or GLIBC 2.27) and python 3.7 to 3.12
- mac (x86_64 or arm64) and python 3.8 to 3.12
- windows and python 3.7 to 3.12
Installation from PyPI
In a terminal type
pip install geone
Or, equivalently: python -m pip install geone.
Installation from the Github repository
In a terminal, change directory where to download GEONE, and type
git clone https://github.com/randlab/geone.git
cd geone
pip install .
Note: use pip install . --verbose or pip install . -v for printing (more) messages during the installation.
Alternatively:
- Instead of
git clone ..., you can download GEONE from the Github repository: click on the green button "code" and choose "Download ZIP". - Then, unzip the archive on your computer
- Finally, in a terminal, go into the unzipped directory, and type
pip install .
Warning - Using GEONE
If the installation has been done from github, do not launch python from the directory containing the downloaded sources and where the installation has been done (with pip), otherwise import geone will fail.
Requirements
The following python packages are used by GEONE (tested on python 3.11.5):
- matplotlib (3.8.1)
- multiprocessing (for parallel processes)
- numpy (tested with version 1.26.0)
- pandas (tested with version 2.1.2)
- pyvista (tested with version 0.42.3)
- scipy (tested with version 1.11.3)
Warning
numpy version less than 2. is required
Removing GEONE
In a terminal type
pip uninstall -y geone
Note: First remove the directory 'geone.egg-info' from the current directory (if present).
<!-- ## References ### Some references about DEESSE - J. Straubhaar, P. Renard (2021) Conditioning Multiple-Point Statistics Simulation to Inequality Data. Earth and Space Science, [doi:10.1029/2020EA001515](https://dx.doi.org/10.1029/2020EA001515) - J. Straubhaar, P. Renard, T. Chugunova (2020) Multiple-point statistics using multi-resolution images. Stochastic Environmental Research and Risk Assessment 20, 251-273, [doi:10.1007/s00477-020-01770-8](https://dx.doi.org/10.1007/s00477-020-01770-8) - J. Straubhaar, P. Renard, G. Mariethoz (2016) Conditioning multiple-point statistics simulations to block data. Spatial Statistics 16, 53-71, [doi:10.1016/j.spasta.2016.02.005](https://dx.doi.org/10.1016/j.spasta.2016.02.005) - G. Mariethoz, J. Straubhaar, P. Renard, T. Chugunova, P. Biver (2015) Constraining distance-based multipoint simulations to proportions and trends. Environmental Modelling & Software 72, 184-197, [doi:10.1016/j.envsoft.2015.07.007](https://dx.doi.org/10.1016/j.envsoft.2015.07.007) - G. Mariethoz, P. Renard, J. Straubhaar (2010) The Direct Sampling method to perform multiple-point geostatistical simulation. Water Resources Research 46, W11536, [doi:10.1029/2008WR007621](https://dx.doi.org/10.1029/2008WR007621) ### Reference about DEESSEX - A. Comunian, P. Renard, J. Straubhaar (2012) 3D multiple-point statistics simulation using 2D training images. Computers & Geosciences 40, 49-65, [doi:10.1016/j.cageo.2011.07.009](https://dx.doi.org/10.1016/j.cageo.2011.07.009) ### Some references about GRF - J. W. Cooley and J. W. Tukey (1965) An algorithm for machine calculation of complex fourier series. Mathematics of Computation 19(90):297-301, [doi:10.2307/2003354](https://dx.doi.org/10.2307/2003354) - C. R. Dietrich and G. N. Newsam (1993) A fast and exact method for multidimensional gaussian stochastic simulations. Water Resources Research 29(8):2861-2869, [doi:10.1029/93WR01070](https://dx.doi.org/10.1029/93WR01070) - A. T. A. Wood and G. Chan (1994) Simulation of stationary gaussian processes in [0,1]^d. Journal of Computational and Graphical Statistics 3(4):409-432, [doi:10.2307/1390903](https://dx.doi.org/10.2307/1390903) ### Other references - C. Lantuéjoul (2002) Geostatistical Simulation, Models and Algorithms. Springer Verlag, Berlin, 256 p. - P. Renard, D. Allard (2013), Connectivity metrics for subsurface flow and transport. Advances in Water Resources 51:168-196, `doi:10.1016/j.advwatres.2011.12.001 <https://doi.org/10.1016/j.advwatres.2011.12.001>`_ - J. Straubhaar, P. Renard (2024), Exploring substitution random functions composed of stationary multi-Gaussian processes. Stochastic Environmental Research and Risk Assessment, `doi:10.1007/s00477-024-02662-x <https://doi.org/10.1007/s00477-024-02662-x>`_ -->License
<!-- See [LICENSE](LICENSE) file. --> <!-- See [LICENSE](https://geone.readthedocs.io/en/latest/LICENSE.html) file. -->See LICENSE file.
Authors
GEONE is developed by Julien Straubhaar and Philippe Renard.