Octree
pydantic-model
Bases: BaseModel, Iterator[Node]
Config:
ignored_types:(cached_property,)
Fields:
-
location(Location) -
root_node_size(PositiveFloat) -
n_levels(int) -
east_bounds(Range) -
north_bounds(Range) -
depth_bounds(Range) -
_root_nodes(list[Node]) -
_semblance(ndarray | None) -
_cached_coordinates(dict[CoordSystem, ndarray]) -
_nodes(list[Node])
Validators:
-
check_reference→location -
check_limits
pydantic-field
Depth bounds of the octree in meters.
pydantic-field
East bounds of the octree in meters.
property
effective_depth_bounds: Range
Effective depth bounds of the octree in meters.
cached
property
leaf_nodes: list[Node]
Get all leaf nodes of the octree.
Returns:
| Type | Description |
|---|---|
list[Node]
|
list[Node]: List of leaf nodes. |
pydantic-field
The geographical center of the octree.
pydantic-field
n_levels: int = 5
Number of levels in the octree, defining the final resolution of the detection. Default is 5.
pydantic-field
North bounds of the octree in meters.
pydantic-field
root_node_size: PositiveFloat = 1 * KM
Size of the root node at the initial level (level 0) in meters.
Returns a copy of the octree refined to the cached bottom nodes.
Raises:
| Type | Description |
|---|---|
EnvironmentError
|
If the octree has never been split. |
Returns:
| Name | Type | Description |
|---|---|---|
Self |
Self
|
Copy of the octree with cached bottom nodes. |
async
interpolate_max_semblance(peak_node: Node) -> Location
Interpolate the location of the maximum semblance value.
This method calculates the location of the maximum semblance value by performing interpolation using surrounding nodes. It uses the scipy Rbf (Radial basis function) interpolation method to fit a smooth function to the given data points. The function is then minimized to find the location of the maximum value.
Returns:
| Name | Type | Description |
|---|---|---|
Location |
Location
|
Location of the maximum semblance value. |
Raises:
| Type | Description |
|---|---|
AttributeError
|
If no semblance values are set. |
model_post_init(__context: Any) -> None
Initialize octree. This method is called by the pydantic model.
reduce_axis(surface: Literal['NE', 'ED', 'ND'] = 'NE', max_level: int = -1, accumulator: Callable[ndarray] = max) -> ndarray
Reduce the octree's nodes to the surface.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
surface
|
Literal['NE', 'ED', 'ND']
|
Surface to reduce to. Defaults to "NE". |
'NE'
|
max_level
|
int
|
Maximum level to reduce to. Defaults to -1. |
-1
|
accumulator
|
Callable
|
Accumulator function. Defaults to np.max. |
max
|
Returns:
| Type | Description |
|---|---|
ndarray
|
np.ndarray: Of shape (n-nodes, 4) with columns (east, north, depth, value). |
save_pickle(filename: Path) -> None
Save the octree to a pickle file.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filename
|
Path
|
Filename to save to. |
required |
set_level(level: int) -> None
Set the octree to a specific level.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
level
|
int
|
Level to set the octree to. |
required |