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v1.3.1

Documentation

  • GSTools Quickstart
    • Purpose
    • Installation
      • conda
      • pip
    • Citation
    • Tutorials and Examples
    • Spatial Random Field Generation
      • Examples
        • Gaussian Covariance Model
    • Estimating and fitting variograms
      • Examples
    • Kriging and Conditioned Random Fields
      • Example
    • User defined covariance models
      • Example
    • Incompressible Vector Field Generation
      • Example
    • VTK/PyVista Export
    • Requirements
      • Optional
      • Contact
    • License
  • GSTools Tutorials
    • Random Field Generation
      • Examples
        • A Very Simple Example
        • Creating an Ensemble of Fields
        • Creating Fancier Fields
        • Using an Unstructured Grid
        • Merging two Fields
        • Generating Fields on Meshes
        • Using PyVista meshes
        • Higher Dimensions
    • The Covariance Model
      • Provided Covariance Models
      • Examples
        • Introductory example
        • Basic Methods
        • Anisotropy and Rotation
        • Spectral methods
        • Different scales
        • Additional Parameters
        • Fitting variogram data
    • Variogram Estimation
      • Examples
        • Fit Variogram
        • Finding the best fitting variogram model
        • Multi-field variogram estimation
        • Directional variogram estimation and fitting in 2D
        • Directional variogram estimation and fitting in 3D
        • Fit Variogram with automatic binning
        • Automatic binning with lat-lon data
    • Random Vector Field Generation
      • Examples
        • Generating a Random 2D Vector Field
        • Generating a Random 3D Vector Field
    • Kriging
      • Provided Kriging Methods
      • Examples
        • Simple Kriging
        • Ordinary Kriging
        • Interface to PyKrige
        • Compare Kriging
        • External Drift Kriging
        • Universal Kriging
        • Detrended Kriging
        • Detrended Ordinary Kriging
        • Incorporating measurement errors
        • Redundant data and pseudo-inverse
    • Conditioned Fields
      • Examples
        • Conditioning with Ordinary Kriging
        • Creating an Ensemble of conditioned 2D Fields
    • Field transformations
      • Examples
        • log-normal fields
        • binary fields
        • Discrete fields
        • Zinn & Harvey transformation
        • bimodal fields
        • Combinations
    • Geographic Coordinates
      • Examples
        • Working with lat-lon random fields
        • Kriging geographical data
    • Spatio-Temporal Modeling
      • Examples
        • Creating a 1D Synthetic Precipitation Field
        • Creating a 2D Synthetic Precipitation Field
    • Normalizing Data
      • Mean, Trend and Normalizers
      • Provided Normalizers
      • Examples
        • Log-Normal Kriging
        • Automatic fitting
        • Normalizer Comparison
    • Miscellaneous Tutorials
      • Examples
        • Truncated Power Law Variograms
        • Exporting Fields
        • Check Random Sampling
        • Analyzing the Herten Aquifer with GSTools
        • Standalone Field class
  • GSTools API
    • Purpose
    • Subpackages
    • Classes
      • Kriging
      • Spatial Random Field
      • Covariance Base-Class
      • Covariance Models
        • Standard Covariance Models
        • Truncated Power Law Covariance Models
    • Functions
      • VTK-Export
      • Geometric
      • Variogram Estimation
    • Misc
    • gstools.covmodel
      • Subpackages
      • Covariance Base-Class
        • gstools.covmodel.CovModel
      • Covariance Models
        • gstools.covmodel.Gaussian
        • gstools.covmodel.Exponential
        • gstools.covmodel.Matern
        • gstools.covmodel.Stable
        • gstools.covmodel.Rational
        • gstools.covmodel.Cubic
        • gstools.covmodel.Linear
        • gstools.covmodel.Circular
        • gstools.covmodel.Spherical
        • gstools.covmodel.HyperSpherical
        • gstools.covmodel.SuperSpherical
        • gstools.covmodel.JBessel
        • gstools.covmodel.TPLGaussian
        • gstools.covmodel.TPLExponential
        • gstools.covmodel.TPLStable
        • gstools.covmodel.TPLSimple
      • gstools.covmodel.plot
    • gstools.field
      • Subpackages
      • Spatial Random Field
        • gstools.field.SRF
        • gstools.field.CondSRF
      • Field Base Class
        • gstools.field.Field
      • gstools.field.generator
      • gstools.field.upscaling
    • gstools.variogram
      • Variogram estimation
        • gstools.variogram.vario_estimate
        • gstools.variogram.vario_estimate_axis
      • Binning
        • gstools.variogram.standard_bins
    • gstools.krige
      • Kriging Classes
        • gstools.krige.Krige
        • gstools.krige.Simple
        • gstools.krige.Ordinary
        • gstools.krige.Universal
        • gstools.krige.ExtDrift
        • gstools.krige.Detrended
    • gstools.random
      • Random Number Generator
      • Seed Generator
      • Distribution factory
    • gstools.tools
      • Export
      • Special functions
      • Geometric
      • Misc
    • gstools.transform
      • Field-Transformations
    • gstools.normalizer
      • Base-Normalizer
        • gstools.normalizer.Normalizer
      • Field-Normalizer
        • gstools.normalizer.LogNormal
        • gstools.normalizer.BoxCox
        • gstools.normalizer.BoxCoxShift
        • gstools.normalizer.YeoJohnson
        • gstools.normalizer.Modulus
        • gstools.normalizer.Manly
      • Convenience Routines
        • gstools.normalizer.apply_mean_norm_trend
        • gstools.normalizer.remove_trend_norm_mean
  • Changelog
    • 1.3.1 - Pure Pink - 2021-06
      • Enhancements
      • Bugfixes
    • 1.3.0 - Pure Pink - 2021-04
      • Topics
        • Geographical Coordinates Support (#113)
        • Krige Unification (#97)
        • Directional Variograms and Auto-binning (#87, #106, #131)
        • Better Variogram fitting (#78, #145)
        • CovModel update (#109, #122, #157)
        • Normalizer, Trend and Mean (#124)
        • Arbitrary dimensions (#112)
        • New Class for Conditioned Random Fields (#130)
      • Enhancements
      • Changes
      • Bugfixes
    • 1.2.1 - Volatile Violet - 2020-04-14
      • Bugfixes
    • 1.2.0 - Volatile Violet - 2020-03-20
      • Enhancements
      • Changes
      • Bugfixes
    • 1.1.1 - Reverberating Red - 2019-11-08
      • Enhancements
      • Changes
      • Bugfixes
    • 1.1.0 - Reverberating Red - 2019-10-01
      • Enhancements
      • Changes
      • Bugfixes
    • 1.0.1 - Bouncy Blue - 2019-01-18
      • Bugfixes
    • 1.0.0 - Bouncy Blue - 2019-01-16
      • Enhancements
      • Changes
      • Bugfixes
    • 0.4.0 - Glorious Green - 2018-07-17
      • Bugfixes
    • 0.3.6 - Original Orange - 2018-07-17

GSTools Links

GSTools GitHub GSTools Zenodo DOI GSTools PyPI

GeoStat Framework

GeoStat Website GeoStat Github GeoStat Examples GeoStat ReadTheDocs GeoStat PyPI

Index Sitemap
GSTools
  • »
  • Overview: module code

All modules for which code is available

  • gstools.covmodel.base
  • gstools.covmodel.models
  • gstools.covmodel.plot
  • gstools.covmodel.tpl_models
  • gstools.field.base
  • gstools.field.cond_srf
  • gstools.field.generator
  • gstools.field.srf
  • gstools.field.upscaling
  • gstools.krige.base
  • gstools.krige.methods
  • gstools.normalizer.base
  • gstools.normalizer.methods
  • gstools.normalizer.tools
  • gstools.random.rng
  • gstools.random.tools
  • gstools.tools.export
  • gstools.tools.geometric
  • gstools.tools.special
  • gstools.transform.field
  • gstools.variogram.binning
  • gstools.variogram.variogram

© Copyright 2018 - 2021, Sebastian Müller, Lennart Schüler. Revision b6374a7d.

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