mcpotential: Compute the Potential Model using Parallelization

In riatelab/potential: Implementation of the Potential Model

Compute the Potential Model using Parallelization

Description

This function computes the potential model with a cutoff distance and parallel computation.

Usage

mcpotential(x, y, var, fun, span, beta, limit = 3 * span, ncl, size = 500)

Arguments

x	an sf object (POINT), the set of known observations to estimate the potentials from.
y	an sf object (POINT), the set of unknown units for which the function computes the estimates.
var	names of the variables in x from which potentials are computed. Quantitative variables with no negative values.
fun	spatial interaction function. Options are "p" (pareto, power law) or "e" (exponential). For pareto the interaction is defined as: (1 + alpha * mDistance) ^ (-beta). For "exponential" the interaction is defined as: exp(- alpha * mDistance ^ beta). The alpha parameter is computed from parameters given by the user (beta and span).
span	distance where the density of probability of the spatial interaction function equals 0.5.
beta	impedance factor for the spatial interaction function.
limit	maximum distance used to retrieve x points, in map units.
ncl	number of clusters. ncl is set to parallel::detectCores() - 1 by default.
size	mcpotential splits y in smaller chunks and dispatches the computation in ncl cores, size indicates the size of each chunks.

Value

If only one variable is computed a vector is returned, if more than one variable is computed a matrix is returned.

Examples

library(sf)
g <- create_grid(x = n3_poly, res = 20000)
pot <- mcpotential(
  x = n3_pt, y = g, var = "POP19",
  fun = "e", span = 75000, beta = 2, 
  limit = 300000, 
  ncl = 2
)
g$OUTPUT <- pot
equipot <- equipotential(g, var = "OUTPUT", mask = n3_poly)
plot(equipot["center"], pal = hcl.colors(nrow(equipot), "cividis"))

riatelab/potential documentation built on Jan. 2, 2023, 7:15 a.m.