plotrix (version 3.8-2)

makeDensityMatrix: Compute a matrix of counts from a list of x,y positions

Description

Compute a matrix in which the counts in each cell represent the number of occurrences of that cell's coordinates in a list of x,y cooordinate values, optionally computing a second matrix of the average of the values attached to the coordinate observations.

Usage

makeDensityMatrix(x,y,z=NULL,nx=100,ny=50,zfun=c("mean","sum"),
 xlim=c(-180,180),ylim=c(-90,90),geocoord=TRUE)

Value

Either a matrix of counts of coordinate pairs within each cell or a list of two such matrices, the second containing the mean or sum of values associated with coordinate pairs.

Arguments

x,y

Vectors of x and y coordinates. These are usually combined in a matrix or data frame of two columns.

z

Optional values attached to each coordinate pair. If these are present, it can be in a matrix or data frame of three columns, x, y and z.

nx

The number of "x" cells in the output matrix.

ny

The number of "y" cells in the output matrix.

zfun

The function to apply to the summed values attached to each coordinate pair. Currently defaults to mean, otherwise the sum is returned.

xlim

The extreme coordinates in the horizontal direction (see Details).

ylim

The extreme coordinates in the vertical direction (see Details).

geocoord

Whether to correct the matrix values for the areal distortion of the Mercator projection.

Author

Jim Lemon

Details

makeDensityMatrix expects two vectors or a matrix or data frame with at least two columns. The function was written for geographic coordinates, but will also work for other numeric coordinates. An optional third vector or column of values for each coordinate will be processed.

Each coordinate pair adds to the count in that cell of the matrix. If there is a third element, that value is added to a second matrix in the same position. By default, the function computes the mean of all values in each cell. If zfun="sum", the sum of values in each cell will be returned.

As geograhic data sets may be very large, leading to memory problems, makeDensityMatrix can be run on small sections of the data set and the resulting matrices added together as long as the coordinate limits are consistent throughout.

See Also

densityGrid

Examples

 x<-sample(1:20,400,TRUE)
 y<-sample(1:20,400,TRUE)
 z<-runif(400,5,20)
 xyz<-makeDensityMatrix(x,y,z,nx=20,ny=20,xlim=c(1,10),ylim=c(1,10),
  geocoord=FALSE)
 par(mar=c(7,3,2,3))
 plot(0,xlim=c(1,10),ylim=c(1,10),type="n",xlab="",axes=FALSE)
 box()
 densityGrid(xyz,range.cex=c(1,4),xlim=c(1,10),ylim=c(1,10),
  red=c(0,0.5,0.8,1),green=c(1,0.8,0.5,0),blue=0,pch=15)
 color.legend(3,-0.7,7,-0.2,c(5,10,15,20),
  rect.col=color.scale(1:4,cs1=c(0,0.5,0.8,1),cs2=c(1,0.8,0.5,0),cs3=0,alpha=1))
 par(xpd=TRUE)
 text(5,0.3,"Intensity")
 points(c(3.5,4.5,5.5,6.5),rep(-1.7,4),pch=15,cex=1:4)
 text(c(3.5,4.5,5.5,6.5),rep(-1.3,4),1:4)
 text(5,-1,"Density")
 par(xpd=FALSE)