KrigingParameters

evo.compute.tasks.kriging.KrigingParameters

Parameters for the kriging task.

Defines all inputs needed to run a kriging interpolation task.

Example: >>> from evo.compute.tasks import run, SearchNeighborhood, Ellipsoid, EllipsoidRanges >>> from evo.compute.tasks.kriging import KrigingParameters, RegionFilter >>> >>> params = KrigingParameters( ... source=pointset.attributes["grade"], # Source attribute ... target=block_model.attributes["kriged_grade"], # Target attribute (creates if doesn't exist) ... variogram=variogram, # Variogram model ... search=SearchNeighborhood( ... ellipsoid=Ellipsoid(ranges=EllipsoidRanges(200, 150, 100)), ... max_samples=20, ... ), ... # method defaults to ordinary kriging ... ) >>> >>> # With region filter to restrict kriging to specific categories on target: >>> params_filtered = KrigingParameters( ... source=pointset.attributes["grade"], ... target=block_model.attributes["kriged_grade"], ... variogram=variogram, ... search=SearchNeighborhood(...), ... target_region_filter=RegionFilter( ... attribute=block_model.attributes["domain"], ... names=["LMS1", "LMS2"], ... ), ... )

source

source: AnySourceAttribute

The source object and attribute containing known values.

target

target: AnyTargetAttribute

The target object and attribute to create or update with kriging results.

variogram

variogram: GeoscienceObjectReference

Model of the covariance within the domain (Variogram object or reference).

search

search: SearchNeighborhood = Field(alias='neighborhood')

Search neighborhood parameters.

method

method: SimpleKriging | OrdinaryKriging = Field(default_factory=OrdinaryKriging, alias='kriging_method')

The kriging method to use. Defaults to ordinary kriging if not specified.

target_region_filter

target_region_filter: RegionFilter | None = Field(None, exclude=True)

Optional region filter to restrict kriging to specific categories on the target object.

block_discretisation

block_discretisation: BlockDiscretisation | None = None

Optional sub-block discretisation for block kriging.

When provided, each target block is subdivided into nx × ny × nz sub-cells and the kriged value is averaged across these sub-cells. When omitted, point kriging is performed. Only applicable when the target is a 3D grid or block model.