Spatial analysis of Barnes and Noble bookstores in CA

CaliforniaBN.R

#Packages
library(fields)
library(sm)  
library(spatstat)
library(splancs)
library(spatial)
library(geoR)
library(maps)
library(maptools)

#Getting the data going
data1 <- read.csv("barnesnoble.csv", header=F)
data1 <- data1[1:120,]
lat <- data1$V1
lon <- data1$V2

#Preparing the image grid
howmuch <- .5
latrange <- 9
lonrange <- 7
irange <- (1/howmuch)*lonrange
jrange <- (1/howmuch)*latrange
x1 = matrix(0,nrow=irange,ncol=jrange) 
for(i in 1:irange){
    for(j in 1:jrange){
	x1[i,j] = sum((lon < (floor(range(lon)[1]) + howmuch*i)) & (lon > (floor(range(lon)[1])-howmuch + howmuch*i -.001)) & 
	    (lat < (floor(range(lat)[1]) +howmuch + howmuch*j)) & (lat > (floor(range(lat)[1]) + howmuch*j - .001)))
    }
}

#Plotting
image(seq(from=-123, to=-116, by=howmuch), seq(from=32.5, to=41.5, by=howmuch), x1, col=gray((64:20)/64), axes=F, xlab="", ylab="")

xrange <- c(-124, -116) 
yrange <- c(32, 42)

map("county", c("california"), xlim=xrange, ylim=yrange, add=T)
map.axes()
points(lon, lat, xlim=xrange, ylim=yrange, cex=0.5, pch=19, col="blue")
title(xlab="Longitude", ylab="Latitude", main="Locations of Barnes and Noble bookstores")

zmin = min(x1)
zmax = max(x1)
zmid = (zmin+zmax)/2
z1 = (zmin + zmid)/2
z2 = (zmid + zmax)/2
legend("topright", title="Legend", as.character(c(zmax,z2,zmid,z1,zmin)),fill=gray(c(20,31,42,53,64)/64), bg="white")