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
🍋
covariance_model: Union[Covariance, CovarianceElem]
property
🍋
Return Covariance Model.
Returns:
| Type | Description |
|---|---|
Union[Covariance, CovarianceElem]
|
Covariance model. |
neighborhood_model: Neighborhood
property
🍋
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. |
axes: List[Coord]
property
🍋
covariance_model: Union[Covariance, CovarianceElem]
property
🍋
Return Covariance Model.
Returns:
| Type | Description |
|---|---|
Union[Covariance, CovarianceElem]
|
Covariance model. |
neighborhood_model: Neighborhood
property
🍋
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. |
solve_api(neighborhood_model, covariance_model, dim, obj_coords, obj_data, support_coords, support_cell_size, mean=None, discr=None)
staticmethod
🍋
Low-level Ordinary Krigging solving method.
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 |
dim
|
int
|
Number of dimensions. |
required |
obj_coords
|
ndarray
|
Conditioning object coordinates in region along specified axes. |
required |
obj_data
|
ndarray
|
Values in selected region. |
required |
support_coords
|
ndarray
|
Support coordinates in region along specified axes. |
required |
support_cell_size
|
ndarray
|
Cell size for support effect determination. |
required |
mean
|
float
|
mean? |
None
|
discr
|
Optional[Vector]
|
Discretisation of each block if block kriging. Defaults to None. |
None
|
Returns:
| Type | Description |
|---|---|
Tuple[ndarray, ndarray, ndarray, ndarray, ndarray]
|
Kriging results, variance, variance estimation, slope and efficiency ndarrays. |
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]. |
axes: List[Coord]
property
🍋
covariance_model: Union[Covariance, CovarianceElem]
property
🍋
Return Covariance Model.
Returns:
| Type | Description |
|---|---|
Union[Covariance, CovarianceElem]
|
Covariance model. |
neighborhood_model: Neighborhood
property
🍋
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. |
solve_api(neighborhood_model, covariance_model, dim, obj_coords, obj_data, support_coords, support_cell_size, mean=None, discr=None)
staticmethod
🍋
Low-level Ordinary Krigging solving method.
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 |
dim
|
int
|
Number of dimensions. |
required |
obj_coords
|
ndarray
|
Conditioning object coordinates in region along specified axes. |
required |
obj_data
|
ndarray
|
Values in selected region. |
required |
support_coords
|
ndarray
|
Support coordinates in region along specified axes. |
required |
support_cell_size
|
ndarray
|
Cell size for support effect determination. |
required |
mean
|
float
|
mean? |
None
|
discr
|
Optional[Vector]
|
Discretisation of each block if block kriging. Defaults to None. |
None
|
Returns:
| Type | Description |
|---|---|
Tuple[ndarray, ndarray, ndarray, ndarray, ndarray]
|
Kriging results, variance, variance estimation, slope and efficiency ndarrays. |
Raises:
| Type | Description |
|---|---|
Warning
|
Maximum allowed neighbors is higher than number of conditioning data. |