voxels_counting: Voxels Counting

In Antguz/rTLS: Tools to Process Point Clouds Derived from Terrestrial Laser Scanning

Description

Creates cube like voxels of different size on a point cloud using the voxels function, and then return a summary_voxels of their features.

Usage

voxels_counting(
  cloud,
  edge_sizes = NULL,
  min_size,
  length_out = 10,
  bootstrap = FALSE,
  R = NULL,
  progress = TRUE,
  parallel = FALSE,
  threads = NULL
)

Arguments

cloud	A data.table with xyz coordinates of the point clouds in the first three columns.
edge_sizes	A positive numeric vector describing the edge length of the different cubes to perform. If NULL, it use edge sizes by default based on the largest range of XYZ and min_size.
min_size	A positive numeric vector of length 1 describing the minimum cube edge length to perform. This is required if edge_sizes = NULL.
length_out	A positive interger of length 1 indicating the number of different edge lengths to use. This is required if edge_sizes = NULL.
bootstrap	Logical. If TRUE, it computes a bootstrap on the H index calculations. FALSE as default.
R	A positive integer of length 1 indicating the number of bootstrap replicates. This need to be used if bootstrap = TRUE.
progress	Logical, if TRUE displays a graphical progress bar. TRUE as default.
parallel	Logical, if TRUE it uses a parallel processing for the voxelization. FALSE as default.
threads	An integer >= 0 describing the number of threads to use. This need to be used if parallel = TRUE.

Value

A data.table with the summary of the voxels created with their features.

Author(s)

J. Antonio Guzmán Q.

See Also

voxels, summary_voxels, plot_voxels

Examples

data(pc_tree)

#Applying voxels counting.
voxels_counting(pc_tree, min_size = 2)

#Voxels counting using bootstrap on the H indexes with 1000 repetitions.
voxels_counting(pc_tree, min_size = 2, bootstrap = TRUE, R = 1000)

Antguz/rTLS documentation built on Dec. 14, 2021, 9:49 a.m.