Usage

From python

If your input is a las file, you can use the jakteristics.las_utils.read_las_xyz() function to read the xyz coordinates from your input file as a numpy array.

If your input is already a numpy array, you can use the jakteristics.compute_features() directly. By default, every geometry feature will be computed.

Once you have the features, you can use them like any numpy array, or write them to a las file using jakteristics.write_with_extra_dims().

Example:

from jakteristics import las_utils, compute_features, FEATURE_NAMES

input_path = "/path/to/a/las_file.las"
xyz = las_utils.read_las_xyz(input_path)

features = compute_features(xyz, search_radius=0.15)

output_path = "/path/to/output_file.las"
las_utils.write_with_extra_dims(input_path, output_path, features, FEATURE_NAMES)

# or for a specific feature:
omnivariance = compute_features(xyz, search_radius=0.15, feature_names=["omnivariance"])
output_omnivariance = "/path/to/output_omnivariance.las"
las_utils.write_with_extra_dims(input_path, output_omnivariance, omnivariance, ["omnivariance"])

If you want to to all of these steps (read a las file, compute certain features and write it back to disk), you can use the command line:

jakteristics input/las/file.las output/file.las --search-radius 0.15 --num-threads 4

CLI

jakteristics

jakteristics [OPTIONS] LAS_INPUT OUTPUT

Options

-s, --search-radius <search_radius>

Required The search radius to use to query neighbors.

-t, --num-threads <num_threads>

The number of threads to use for computation. Defaults to the number of cpu on the machine.

Default

-1

-f, --feature <feature_names>

The feature names to compute. Repeat this parameter to compute multiple features. Use –show-features to see the list of possible choices. Default: All features.

Default

eigenvalue_sum, omnivariance, eigenentropy, anisotropy, planarity, linearity, PCA1, PCA2, surface_variation, sphericity, verticality, nx, ny, nz

-m, --manhattan-distance

How to compute the distance between 2 points. If provided, the sum-of-absolute-values is used (‘Manhattan’ distance).By default, the standard Euclidean distance is used.

Default

False

-e, --eps <eps>

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.

Default

0

--show-features

Show a list of possible feature names and exit.

--install-completion <install_completion>

Install completion for the specified shell.

Options

bash | zsh | fish | powershell | pwsh

--show-completion <show_completion>

Show completion for the specified shell, to copy it or customize the installation.

Options

bash | zsh | fish | powershell | pwsh

Arguments

LAS_INPUT

Required argument

OUTPUT

Required argument