nkde_worker: NKDE worker

In spNetwork: Spatial Analysis on Network

NKDE worker

Description

The worker function for nkde and nkde.mc

Usage

nkde_worker(
  lines,
  events,
  samples,
  kernel_name,
  bw,
  bws,
  method,
  div,
  digits,
  tol,
  sparse,
  max_depth,
  verbose = FALSE
)

Arguments

lines	A feature collection of linestrings representing the network. The geometries must be simple lines (may crash if some geometries are invalid)
events	A feature collection of points representing the events on the network. The points will be snapped on the network.
samples	A feature collection of points representing the locations for which the densities will be estimated.
kernel_name	The name of the kernel to use
bw	The global kernel bandwidth
bws	The kernel bandwidth (in meters) for each event. Is usually a vector but could also be a matrix if several global bandwidths were used. In this case, the output value is also a matrix.
method	The method to use when calculating the NKDE, must be one of simple / discontinuous / continuous (see details for more information)
div	The divisor to use for the kernel. Must be "n" (the number of events within the radius around each sampling point), "bw" (the bandwidth) "none" (the simple sum).
digits	The number of digits to keep in the spatial coordinates. It ensures that topology is good when building the network. Default is 3
tol	When adding the events and the sampling points to the network, the minimum distance between these points and the lines extremities. When points are closer, they are added at the extremity of the lines.
sparse	A Boolean indicating if sparse or regular matrices should be used by the Rcpp functions. Regular matrices are faster, but require more memory and could lead to error, in particular with multiprocessing. Sparse matrices are slower, but require much less memory.
max_depth	When using the continuous and discontinuous methods, the calculation time and memory use can go wild if the network has a lot of small edges (area with a lot of intersections and a lot of events). To avoid it, it is possible to set here a maximum depth. Considering that the kernel is divided at intersections, a value of 8 should yield good estimates. A larger value can be used without problem for the discontinuous method. For the continuous method, a larger value will strongly impact calculation speed.
verbose	A Boolean, indicating if the function should print messages about the process.

Value

A numeric vector with the nkde values

Examples

#This is an internal function, no example provided

spNetwork documentation built on June 22, 2024, 9:40 a.m.