voxelize {curveDepth} R Documentation

## Voxelization of functions

### Description

Convertes a pice-wise linear parametrized funtion into a discretized voxel representation.

### Usage

voxelize(f, from, to, by)


### Arguments

 f A parametrized function as a list containing a vector "args" (arguments), and a matrix "vals" (values, d columns). from A vector of d numbers, each giving a starting discretization point for one dimension. to A vector of d numbers, each giving a finishing discretization point for one dimension. by A vector of d numbers, each giving discretization step for one dimension.

### Value

A list containing two matrices: "voxels" with rows being voxel numbers, and "coords" with rows being coordinates of voxel centers.

### References

Lafaye De Micheaux, P., Mozharovskyi, P. and Vimond, M. (2018). Depth for curve data and applications.

### Examples

library(curveDepth)
# Create some data based on growth curves
g1d <- dataf.growth()
g3d <- list("")
set.seed(1)
for (i in 1:length(g1d$dataf)){ g3d[[i]] <- list( args = g1d$dataf[]$args, vals = cbind(g1d$dataf[[i]]$vals, g1d$dataf[[i]]$vals[length(g1d$dataf[[i]]$vals):1], rnorm(length(g1d$dataf[[i]]$vals), sd = 1) + rnorm(1, mean = 0, sd = 10))) } # Define voxels' bounds and resolution from <- c(65, 65, -25) to <- c(196, 196, 25) steps <- 100 by <- (to - from) / steps # Voxelize all curves fs <- list("") for (i in 1:length(g3d)){ fs[[i]] <- voxelize(g3d[[i]], from, to, by) } ## Not run: # Plot first 10 curves library(rgl) rgl.open() rgl.bg(color = "white") for (i in 1:10){ spheres3d(fs[[i]]$voxels[, 1], fs[[i]]$voxels[, 2], fs[[i]]$voxels[, 3],
col = "red", radius = 0.5)
}
## End(Not run)


[Package curveDepth version 0.1.0.9 Index]