Kriging

Kriging

Bases: Entity

Kriging Solver class.

Parameters:

Name	Type	Description	Default
covariance_model	Union[Covariance, CovarianceElem]	Covariance used for distance computation.	required
neighborhood_model	Neighborhood	Neighborhood model used for weights computation.	required
axes	List[Coord]	If solver is 2D or 3D. Defaults to [Coord.U, Coord.V, Coord.W].	[U, V, W]

Attributes:

Name	Type	Description
covariance_model	Union[Covariance, CovarianceElem]	Covariance used for distance computation.
neighborhood_model	Neighborhood	Neighborhood model used for weights computation.
axes	List[Coord]	If solver is 2D or 3D.

axes: List[Coord] property

Return Solver Axis.

Returns:

Type	Description
List[Coord]	List of axes.

covariance_model: Union[Covariance, CovarianceElem] property

Return Covariance Model.

Returns:

Type	Description
Union[Covariance, CovarianceElem]	Covariance model.

neighborhood_model: Neighborhood property

Return Neighborhood Model.

Returns:

Type	Description
Neighborhood	Neighborhood model.

solve() abstractmethod

Use the defined method to interpolate onto target locations.

OrdinaryKriging

Bases: Kriging

Ordinary Kriging Solver class.

Kriging Solver where mean of data is supposed to be unknown.

Parameters:

Name	Type	Description	Default
covariance_model	Union[Covariance, CovarianceElem]	Covariance used for distance computation.	required
neighborhood_model	Neighborhood	Neighborhood model used for weights computation.	required
axes	List[Coord]	If solver is 2D or 3D. Defaults to [Coord.U, Coord.V, Coord.W].	[U, V, W]

Attributes:

Name	Type	Description
covariance_model		Covariance used for distance computation.
neighborhood_model		Neighborhood model used for weights computation.
axes		If solver is 2D or 3D.

solve(obj, obj_region, obj_attribute, support, support_region, support_attribute, discr=None, kriging_slope=False, kriging_efficiency=False)

Solve Ordinary Kriging on a support using a conditioning object.

Parameters:

Name	Type	Description	Default
obj	GeoRefObject	Conditioning Object.	required
obj_region	Optional[str]	Spatial subset of conditioning.	required
obj_attribute	str	Property to estimate.	required
support	GeoRefObject	Object to estimate onto.	required
support_region	Optional[str]	Spatial subset of estimation.	required
support_attribute	str	Property name to add in support.	required
discr	Optional[Vector]	Discretisation of each block if block kriging. Defaults to None.	None
kriging_slope	bool	Extraction of kriging slope as attribute in support.	False
kriging_efficiency	bool	Extraction of kriging efficiency as attribute in support.	False

Raises:

Type	Description
Warning	Maximum allowed neighbors is higher than number of conditioning data.

SimpleKriging

Bases: OrdinaryKriging

Simple Kriging Solver class.

Kriging Solver where mean of data is supposed to be known and spatially constant.

Parameters:

Name	Type	Description	Default
covariance_model	Union[Covariance, CovarianceElem]	Covariance used for distance computation.	required
neighborhood_model	Neighborhood	Neighborhood model used for weights computation.	required
mean	float	Mean of values for estimation.	required
axes	List[Coord]	If solver is 2D or 3D. Defaults to [Coord.U, Coord.V, Coord.W].	[U, V, W]

Attributes:

Name	Type	Description
covariance_model		Covariance used for distance computation.
neighborhood_model		Neighborhood model used for weights computation.
mean	float	Mean of values for estimation.
axes	float	If solver is 2D or 3D. Defaults to [Coord.U, Coord.V, Coord.W].

mean: float property

Return means of Kriging solver.

Returns:

Type	Description
float	Mean value.

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Last update: 2023-10-09