GSTools
v1.1.1

Documentation

  • GSTools Quickstart
    • Installation
    • Citation
    • Tutorials and Examples
    • Spatial Random Field Generation
      • Examples
        • Gaussian Covariance Model
        • Truncated Power Law 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
    • License
  • GSTools Tutorials
    • Tutorial 1: Random Field Generation
      • Theoretical Background
      • A very Simple Example
      • Creating an Ensemble of Fields
        • Using better Seeds
      • Creating Fancier Fields
      • Using an Unstructured Grid
      • Exporting a Field
      • Merging two Fields
    • Tutorial 2: The Covariance Model
      • Theoretical Backgound
      • Example
      • Parameters
      • Anisotropy
      • Rotation Angles
      • Methods
        • Basics
        • Spectral methods
      • Different scales
        • Integral scale
        • Percentile scale
      • Additional Parameters
      • Fitting variogram data
      • Provided Covariance Models
    • Tutorial 3: Variogram Estimation
      • Theoretical Background
      • An Example with Actual Data
        • The Data
        • Retrieving the Data
        • Preprocessing the Data
        • Estimating the Variogram
        • Fitting the Variogram
        • Estimating the Variogram in Specific Directions
        • Creating a Spatial Random Field from the Herten Parameters
        • And Now for Some Cleanup
    • Tutorial 4: Random Vector Field Generation
      • Theoretical Background
      • Generating a Random Vector Field
      • Applications
    • Tutorial 5: Kriging
      • Theoretical Background
      • Implementation
      • Simple Kriging
        • Example
      • Ordinary Kriging
        • Example
      • Interface to PyKrige
    • Tutorial 6: Conditioned Fields
      • Theoretical Background
      • Example: Conditioning with Ordinary Kriging
    • Tutorial 7: Field transformations
      • Implementation
      • 1. Example: log-normal fields
      • 2. Example: binary fields
      • 3. Example: Zinn & Harvey transformation
      • 4. Example: bimodal fields
      • 5. Example: Combinations
  • GSTools API
    • Purpose
    • Subpackages
    • Classes
      • Spatial Random Field
      • Covariance Base-Class
      • Covariance Models
        • Standard Covariance Models
        • Truncated Power Law Covariance Models
    • Functions
      • VTK-Export
      • variogram estimation
    • gstools.covmodel
      • Subpackages
      • Covariance Base-Class
      • Covariance Models
      • gstools.covmodel.base
      • gstools.covmodel.models
      • gstools.covmodel.tpl_models
      • gstools.covmodel.plot
    • gstools.field
      • Subpackages
      • Spatial Random Field
      • gstools.field.generator
      • gstools.field.upscaling
      • gstools.field.base
    • gstools.variogram
      • Variogram estimation
    • gstools.krige
      • Kriging Classes
    • gstools.random
      • Random Number Generator
      • Seed Generator
      • Distribution factory
    • gstools.tools
      • Export
      • Special functions
      • Geometric
    • gstools.transform
      • Field-Transformations

GSTools Links

GSTools GitHub GSTools Zenodo DOI GSTools PyPI

GeoStat Framework

GeoStat Website GeoStat Github GeoStat ReadTheDocs GeoStat PyPI

Index Sitemap
GSTools
  • Docs »
  • GSTools Tutorials
  • Edit on GitHub
Next Previous

GSTools TutorialsΒΆ

In the following you will find several Tutorials on how to use GSTools to explore its whole beauty and power.

  • Tutorial 1: Random Field Generation
  • Tutorial 2: The Covariance Model
  • Tutorial 3: Variogram Estimation
  • Tutorial 4: Random Vector Field Generation
  • Tutorial 5: Kriging
  • Tutorial 6: Conditioned Fields
  • Tutorial 7: Field transformations

© Copyright 2018 - 2019, Lennart Schueler, Sebastian Mueller Revision f5b05f95.

Built with Sphinx using a theme provided by Read the Docs.