Description Usage Arguments Details Value Author(s) Examples
View source: R/geometry_features.R
Estimate geometry features of neighboring points in a cloud.
1 2 3 4 5 6 7 8 9 10 11 12 13 | geometry_features(
cloud,
method,
radius,
k,
max_neighbour,
distance = "euclidean",
target = FALSE,
threads = 1L,
verbose = FALSE,
progress = TRUE,
...
)
|
cloud |
A |
method |
A character string specifying the method to estimate the neighbors. It most be one of |
radius |
A |
k |
An |
max_neighbour |
An |
distance |
Type of distance to calculate. |
target |
Logic. If |
threads |
An |
verbose |
If |
progress |
If |
... |
Arguments passed to |
The function returns the geometry features of the neighboring points
of a given point in cloud
. Geometry features are represented by the
relative values of the eigenvalues derived from a covariance matrix of the
neighboring points. Geometry features are not estimated on target points
with less than 3 neighboring points.
A array
describing the point of the cloud
in rows,
the relative eigenvalues in columns, and the radius
or k
per slide.
If method = "radius_search"
, it add in the first column the number of
neighboring points.
J. Antonio Guzmán Q.
1 2 3 4 5 6 7 8 9 10 11 12 13 | #Create cloud
example <- data.table(X = runif(200, min=0, max=10),
Y = runif(200, min=0, max=10),
Z = runif(200, min=0, max=10))
#Using knn method with two different k
k_test <- c(5, 10)
geometry_features(example, method = "knn", k = k_test)
#Using radius search method with two different radius
radius_test <- c(3, 4)
geometry_features(example, method = "radius_search", radius = radius_test, max_neighbour = 200)
|
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