Reference

jakteristics

jakteristics.compute_features(points, search_radius, *, kdtree=None, num_threads=-1, max_k_neighbors=50000, euclidean_distance=True, feature_names=None, eps=0.0)

Compute features for a set of points.

Parameters

  • points (ndarray) – A contiguous (n, 3) array of xyz coordinates to query.

  • search_radius (float) – The radius to query neighbors at each point.

  • kdtree (Optional[cKDTree]) – If None, the kdtree is computed from the list of points. Must be an instance of jakteristics.cKDTree (and not scipy.spatial.cKDTree).

  • num_threads (int) – The number of threads (OpenMP) to use when doing the computation. Default: The number of cores on the machine.

  • max_k_neighbors (int) – The maximum number of neighbors to query Larger number will use more memory, but the neighbor points are not all kept at the same time in memory. Note: if this number is smaller, the neighbor search will not be faster. The radius is used to do the query, and the neighbors are then removed according to this parameter.

  • euclidean_distance (bool) – How to compute the distance between 2 points. If true, the Euclidean distance is used. If false, the sum-of-absolute-values is used (“Manhattan” distance).

  • feature_names (Optional[List[str]]) – The feature names to compute (see constants.FEATURE_NAMES for possible values) Default: all features

  • eps (float) – Return approximate nearest neighbors; the k-th returned value is guaranteed to be no further than (1+eps) times the distance to the real k-th nearest neighbor.

Return type

ndarray

Returns

The computed features, one row per query point, and one column per requested feature.

jakteristics.las_utils

jakteristics.las_utils.read_las_xyz(filename, with_offset=False)

Reads xyz coordinates of a las file, optionally as single precision floating point.

Parameters

  • filename (Union[str, Path]) – The las file to read

  • with_offset (bool) – If True, returns a tuple of a float32 array of coordinates, and the las header offset If False, returns only float64 coordinates Default: False

Return type

Union[array, Tuple[ndarray, List[float]]]

Returns

Depending on the with_offset parameter, either an (n x 3) array, or a tuple of an (n x 3) array and the file offset.

jakteristics.las_utils.write_with_extra_dims(input_path, output_path, extra_dims, extra_dims_names)

From an existing las file, create a new las file with extra dimensions

Parameters

  • input_path (Path) – The input las file.

  • output_path (Path) – The output las file.

  • extra_dims (array) – The numpy array containing geometric features.

  • extra_dims_names (List) – A list of names corresponding to each column of extra_dims.