Examples - Notebooks List
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Various examples are provided in notebooks below to get started with GEONE.
The notebooks (with related data files) from this doc are available on Github at https://github.com/randlab/geone/tree/master/docs/source/notebooks
Note
In the list below, abbreviations are used for the beginning of the original notebook file names:
ex_gc stands for ex_geosclassic
ex_VA stands for ex_vario_analysis
Images and point sets
The following notebooks show how to deal with the classes geone.img.Img for “images” and geone.img.PointSet for “point sets”.
Multiple-point statistics - DEESSE
The following notebooks show how to run DEESSE with its functionalities (options).
- ex_deesse_01 - Getting started
- ex_deesse_02 - Simulation path and additional outputs
- ex_deesse_03 - Search neighborhood
- ex_deesse_04 - Continuous simulations
- ex_deesse_05 - Geometrical transformation
- ex_deesse_06 - Proportion constraints
- ex_deesse_07 - Connectivity data
- ex_deesse_08 - Multivariate simulations (I)
- ex_deesse_09 - Multivariate simulations (II)
- ex_deesse_10 - Incomplete images
- ex_deesse_11 - Using a mask
- ex_deesse_12 - Multiple training data sets
- ex_deesse_13 - Inequality data
- ex_deesse_14 - Rotation in 3D
- ex_deesse_15 - Block data
- ex_deesse_16 - Advanced use of pyramids
Multiple-point statistics - DEESSEX (“X-simulation”)
The following notebooks show how some examples of crossing-simulation (X-simulation) with DEESSEX.
MultiGaussian estimation and simulation (general function)
The following notebook shows elementary covariance models, and examples of covariance model in 1D, 2D, 3D, and the use of a general function (wrapper) allowing to launch the other functions of GEONE for multiGaussian estimation and simulation (based on FFT / search neighborhood (GEOSCLASSIC), see below).
GRF based on FFT
Gaussian random fields (GRF) - simulation and estimation (kriging) in a grid - based on Fast Fourier Transform (FFT).
SGS / SIS and kriging based on search neighborhood
Sequential Gaussian Simulation (SGS), Sequential Indicator Simulation (SIS) and estimation (kriging) in a grid - based on (limited) search neigborhood; tools for image analysis : covariance variogram, connectivity of images (GEOSCLASSIC wrapper).
- ex_gc_1d_1 - 1D
- ex_gc_1d_2 - 1D with non stationary covariance
- ex_gc_2d_1 - 2D
- ex_gc_2d_2 - 2D with non stationary covariance
- ex_gc_3d_1 - 3D
- ex_gc_3d_2 - 3D with non stationary covariance
- ex_gc_indicator_1d_1 - categorical variable (indicator) in 1D
- ex_gc_indicator_1d_2 - ind. var. 1D with non stationary covariance
- ex_gc_indicator_2d_1 - categorical variable (indicator) in 2D
- ex_gc_indicator_2d_2 - ind. var. 2D with non stationary covariance
- ex_gc_indicator_3d_1 - categorical variable (indicator) in 3D
- ex_gc_indicator_3d_2 - ind. var. 1D with non stationary covariance
- ex_gc_image_analysis - tools for image analysis
Variogram analysis tools
Tools for variogram analysis - variogram fitting - illustrated in various cases.
- ex_VA_data1D_1 - 1D
- ex_VA_data1D_2 - 1D with non-stationarity
- ex_VA_data2D_1 - 2D omni-directional
- ex_VA_data2D_2 - 2D with anisotropy
- ex_VA_data2D_3 - 2D with non-stationarity
- ex_VA_data3D_1 - 3D omni-directional
- ex_VA_data3D_2 - 3D with anisotropy
- ex_VA_data3D_3 - 3D omni horizonally only
- ex_VA_data3D_4 - 3D with non-stationarity
Pluri-Gaussian simulation (PGS)
Substitution Random Function (SRF)
Miscellaneous algorithms based on random processes
Other algorithms based on random processes such accept-reject sampler, Markov chain on finite set, homogeneous and non-homogeneous Poisson point process, Chentsov simulations.
Logging
Some functions of GEONE allow for logging, based on the standard package logging.