Skip to content

pemn/vtk_krig

Repository files navigation

📌 Description

vtk grid data krigging using pykrige

📸 Screenshot

screenshot1

📝 Parameters

name optional description
soft_db vtk grid to be estimated
hard_db samples with hard data
lito ☑️ run a distinct pass for each lito value
variables select which variables from hard data will be interpolated in the soft data
variogram ☑️ a json or yaml file with variogram parameters. check notes for details.
output ☑️ save updated grid on this file path
display show results in a chart window

📓 Notes

  • Empty grids can be created using the tool vtk_create_grid.py
  • Hard data must contain x,y,z columns, either with those exact names or popular synonyms. Ex.: x, easting, mid_x, leste
  • Results can be visualized with tools such as db_voxel_view.py or softwares such as Paraview and F3D.
  • check sample_data folder on this project for some test files

Possible Variogram parameters and their default values

name default
algorithm ordinary
variogram_model gaussian
variogram_parameters None
nlags 6
anisotropy_scaling_y 1.0
anisotropy_scaling_z 1.0
anisotropy_angle_x 0.0
anisotropy_angle_y 0.0
anisotropy_angle_z 0.0

📚 Examples

input hard data

screenshot3

output estimated grid

screenshot2

🧩 Compatibility

distribution status
winpython_icon
vulcan_icon
anaconda_icon

🙋 Support

Any question or problem contact:

  • paulo.ernesto

💎 License

Apache 2.0 Copyright vale_logo_only Vale 2024