src.mining.miner

Classes

Miner(**kwargs)

Exceptions

MinerException([message])

exception src.mining.miner.MinerException(message='')

Author:

Alberto M. Esmoris Pena

Class for exceptions related to data mining components. See VL3DException.

__init__(message='')

class src.mining.miner.Miner(**kwargs)

Author:

Alberto M. Esmoris Pena

Interface governing any miner.

__init__(**kwargs)

Initialize a Miner.

Parameters:

kwargs – The key-word arguments for the initialization of any Miner. It must contain the name of the data mining to be computed.

abstractmethod mine(pcloud)

Mine features from a given input point cloud.

Parameters:

pcloud (src.pcloud.point_cloud.PointCloud) – The input point cloud for which features must be mined.

Returns:

The point cloud extended with the mined features.

Return type:

PointCloud

static get_structure_space_matrix(pcloud)

Obtain the structure space matrix (i.e., matrix of point-wise coordinates) considering the mining config.

If the structure space must be represented with less than 64 bits, then it will be shifted before the conversion (the bounding box center defines the translation vector) to prevent coordinate corruption when the input coordinates are given in a CRS with high numbers.

Parameters:

pcloud (PointCloud) – The point cloud whose structure space matrix must be obtained.

Returns:

The structure space matrix representing the point cloud.

Return type:

np.ndarray

static get_feature_type()

Determine the data type to be used to represent the feature space.

Returns:

The type to be used to represent the features.

Return type:

np.dtype

static get_feature_space_matrix(pcloud, fnames)

Obtain the feature space matrix (i.e., matrix of point-wise features) considering the mining config.

Parameters:

• pcloud (PointCloud) – The point cloud whose feature space matrix must be obtained.

• fnames (list of str) – The names of the features.

Returns:

The feature space matrix representing the point cloud.

Return type:

np.ndarray