src.clustering.min_dist_decorated_clusterer

Classes

MinDistDecoratedClusterer(**kwargs)

class src.clustering.min_dist_decorated_clusterer.MinDistDecoratedClusterer(**kwargs)
Author:

Alberto M. Esmoris Pena

Decorator for clusterers that makes the clustering process on a minimum distance decimation-based representation of the point cloud.

The minimum distance decorated clusterer (MinDistDecoratedClusterer) constructs a representation of the point cloud, then it runs the clustering process on this representation and, finally, it propagates the clusters back to the original point cloud.

See MinDistDecimatorDecorator and SamplingDecoratedClusterer.

Variables:

  • decorated_clusterer_spec (dict) – The specification of the decorated clusterer.

  • mindist_decorator_spec (dict) – The specification of the minimum distance decimation defining the decorator.

  • mindist_decorator (MinDistDecimatorDecorator) – The minimum distance decimator decorator to be applied on input point clouds.

static extract_clustering_args(spec)

Extract the arguments to initialize/instantiate a MinDistDecoratedClusterer from a key-word specification.

Parameters:

spec – The key-word specification containing the arguments.

Returns:

The arguments to initialize/instantiate a MinDistDecoratedClusterer.

Return type:

dict

__init__(**kwargs)

Initialization for any instance of type MinDistDecoratedClusterer.

transform_pcloud(pcloud)

Transform the given input point cloud to its minimum distance decimation-based representation.

Parameters:

pcloud (PointCloud) – The input point cloud to be transformed.

Returns:

The minimum distance decimation-based representation of the input point cloud.

Return type:

PointCloud

propagate(mdd_pcloud, pcloud)

Propagate the cluster labels from the FPS version of the point cloud back to the original one.

See SamplingDecoratedClusterer._propagate().