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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.


Last update: 2023-10-09