Likelihood folder

operators.fvo.likelihood_folder(client, input_folder='/input_folder', points_folder='/points_folder', output_folder='/output_folder', max_distance=0.5, missing_distance=1.5, missing_knn=2, worker_instance_type='x2large', manager_instance_type='small', extension_input_file='.laz', extension_points_file='.laz', extension_output_file='.laz', skip_existing_files=False)

Compute class conditional probability distribution

likelihood_folder(client,

input_folder=’/input_folder’,

points_folder=’/points_folder’,

output_folder=’/output_folder’,

max_distance=0.5,

missing_distance=1.5,

missing_knn=2,

worker_instance_type=’x2large’,

manager_instance_type=”small”,

extension_input_folder=”.laz”,

extension_points_folder=”.laz”,

extension_output_folder=”.laz”,

skip_existing_files = False )

Parameters:

• max_distance – probability max distance

• missing_distance – interpolate missing points distance

• missing_knn – interpolate number missing neighbours

• input_folder – input LAZ folder folder

• points_folder – input LAZ folder folder

• output_folder – output LAZ folder folder

• worker_instance_type – cloud instance type of worker nodes

• manager_instance_type – cloud instance type of manager node

• extension_input_folder – File extension of files in folder for input_folder

• extension_points_folder – File extension of files in folder for points_folder

• extension_output_folder – File extension of files in folder for output_folder

• skip_existing_files – skip files that already exist in the output folder