Point Sets • ramp.micro

library(ramp.micro)

Introduction

Models in ramp.micro are developed around point sets describing the locations of resources. Point sets are passed to functions that set up models. For these purposes, the point sets are stored in two columns as a pair of named vectors.

For example:

x= c(1,0,1,0)
y= c(0,1,1,0)
xy0 <- cbind(x,y) 
xy0

##      x y
## [1,] 1 0
## [2,] 0 1
## [3,] 1 1
## [4,] 0 0

Note that the points are returned as a pair of named vectors – the first column is named x and the next one y

To develop code and facilitate methods development, we developed several utilities for creating point sets.

Uniform

The function unif_xy(n, mn, mx) generates random uniform point sets within a square bounding box:

mn $< x <$ mx
mn $< y <$ mx

This creates a set of 150 points that are uniformly, randomly distributed in a 10 unit box:

xy1 <- unif_xy(50, 0, 10)
head(xy1, 4)

##              x        y
## [1,] 0.8075014 4.611865
## [2,] 8.3433304 3.152418
## [3,] 6.0076089 1.746759
## [4,] 1.5720844 5.315735

Note that xy1 is $150 \times 2$

dim(xy1)

## [1] 50  2

par(mar = c(2,2,1,1), bty = "o")
plot(xy1)

Lattice

The function lattice(n, mn, mx) generates an $n \times n$ lattice inside a box:

mn $< x <$ mx
mn $< y <$ mx

p2 <- lattice(7, 0, 10)
par(mar = c(2,2,1,1), bty = "o")
plot(p2)

dim(p2)

## [1] 49  2

Clusters

Two functions were developed to generate clusters. The first one, clusters_xy(xy, nc, vr) generates a poisson number of points (mean = nc) around a set of seeds. The distance from the center of each seed is a normal variate with variance vr.

seeds <- unif_xy(23, 0, 50)
p3 <- clusters_xy(seeds, 8, 1)

par(mar = c(2,2,1,1), bty = "o")
plot(p3)