R2BayesX (version 0.1-1)

plotmap: Plot Maps

Description

The function takes a list polygons and draws the corresponding map. Different colors for each polygon can be used. Typically used for objects of class "mrf.bayesx" and "ra.bayesx" returned from function bayesx and read.bayesx.output.

Usage

plotmap(map, x = NULL, id = NULL, c.select = NULL, legend = TRUE, 
  swap = FALSE, range = NULL, names = FALSE, values = FALSE, 
  col = NULL, ncol = 100, breaks = NULL, cex.legend = 1, 
  cex.names = 1, cex.values = cex.names, digits = 2L, 
  mar.min = 2, add = FALSE, ...)

Arguments

map

the map to be plotted, the map object must be a list of matrices with first column indicating the x coordinate and second column the y coordinate each, also see <

x

a matrix or data frame with two columns, first column indicates the region and second column the the values which will define the background colors of the polygons, e.g. fitted values from bayesx

id

if argument x is a vector, argument id should contain a character vector of the same length of x with entries indicating the polygon the $i$-th value of x belongs to, i.e. id mus

c.select

select the column of the data in x which should be used for plotting, may be an integer or character with the corresponding column name.

legend

if set to TRUE, a legend will be shown.

swap

if set to TRUE, colors will be represented in reverse order.

range

specify the range of values in x which should enter the plot, e.g. only values between -2 and 2 are of interest then range = c(-2, 2).

names

if set to TRUE the name for each polygon will also be plotted at the centroids of the corresponding polygons.

values

if set to TRUE the corresponding values for each polygon will also be plotted at the centroids of the polygons.

col

the color of the surface, may also be a function, e.g. col.surface = heat.colors.

ncol

the number of different colors that should be generated if col is a function.

breaks

a set of breakpoints for the colors: must give one more breakpoint than ncol.

cex.legend

text size of the numbers in the legend.

cex.names

text size of the names if names = TRUE.

cex.values

text size of the names if values = TRUE.

digits

specifies the legend decimal places.

mar.min

Controls the definition of boundaries. Could be either NULL for individual settings of mar or a value which defines mar as follows: The boundaries will be calculated according to the height to width ratio

add

if set to TRUE, the map will be added to an existing plot.

...

parameters to be passed to colorlegend and others, e.g. change the border of the polygons and density, see polygon

See Also

plot.bayesx, read.bnd, colorlegend.

Examples

## load a sample map
data("FantasyBnd")

## plot the map 
op <- par(no.readonly = TRUE)
plotmap(FantasyBnd, main = "Example of a plain map")
plotmap(FantasyBnd, lwd = 1, main = "Example of a plain map")
plotmap(FantasyBnd, lwd = 1, lty = 2)
plotmap(FantasyBnd, lwd = 1, lty = 2, border = "green3")
plotmap(FantasyBnd, lwd = 1, lty = 2, border = "green3",
  density = 50)
plotmap(FantasyBnd, lwd = 1, lty = 2, 
  border = c("red", "green3"),
  density = c(10, 20), angle = c(5, 45))
plotmap(FantasyBnd, lwd = 1, lty = 2, 
  border = c("red", "green3"),
  density = c(10, 20), angle = c(5, 45),
  col = c("blue", "yellow"))
plotmap(FantasyBnd, col = gray.colors(length(FantasyBnd)))

## add some values to the corresponding polygon areas
## note that the first column in matrix val contains
## the region identification index
x <- cbind(as.integer(names(FantasyBnd)), runif(length(FantasyBnd), -2, 2))
plotmap(FantasyBnd, x = x)
        
## now only plot values for some certain regions
set.seed(432)
samps <- sample(x[,1], 4)
nx <- x[samps,]
plotmap(FantasyBnd, x = nx, density = 20)

## play with legend
plotmap(FantasyBnd, x = x, names = TRUE, legend = FALSE)
plotmap(FantasyBnd, x = nx, density = 20, pos = c(0, 1))
plotmap(FantasyBnd, x = nx, density = 20, pos = c(0, 0.8),
  side.legend = 2)
plotmap(FantasyBnd, x = nx, density = 20, pos = c(0, 0.8),
  side.legend = 2, side.tick = 2)
plotmap(FantasyBnd, x = nx, density = 20, pos = c(0, 0.8),
  side.legend = 2, side.tick = 2, cex.legend = 0.5)
plotmap(FantasyBnd, x = x, values = TRUE, 
  pos = c(-0.15, -0.12))
plotmap(FantasyBnd, x = nx, values = TRUE, 
  pos = c(-0.07, -0.22), width = 2, 
  at = nx[,2], side.legend = 2, distance.labels = 3,
  density = 20)
plotmap(FantasyBnd, x = nx, values = TRUE, 
  pos = c(-0.07, -0.22), width = 2, 
  at = nx[,2], side.legend = 2, distance.labels = 3,
  density = 20, symmetric = FALSE, 
  col = heat_hcl, swap = TRUE)
plotmap(FantasyBnd, x = nx, values = TRUE, 
  pos = c(-0.07, -0.22), width = 2, 
  at = nx[,2], side.legend = 2, distance.labels = 3,
  density = 20, symmetric = FALSE, 
  col = heat_hcl, swap = TRUE, range = c(-5, 5))
plotmap(FantasyBnd, x = nx, values = TRUE, 
  pos = c(-0.07, -0.22), width = 2, 
  at = nx[,2], side.legend = 2, distance.labels = 3,
  density = 20, symmetric = FALSE, 
  col = heat_hcl, swap = TRUE, lrange = c(-5, 5))
plotmap(FantasyBnd, x = nx, values = TRUE, 
  pos = c(-0.07, -0.22), width = 2, 
  at = nx[,2], side.legend = 2, distance.labels = 3,
  density = 20, symmetric = FALSE, 
  col = heat_hcl, swap = TRUE, 
  ncol = 4, breaks = seq(-2, 2, length = 5))

## more position options
plotmap(FantasyBnd, x = nx, density = 20, pos = "bottomleft")
plotmap(FantasyBnd, x = nx, density = 20, pos = "topleft")
plotmap(FantasyBnd, x = nx, density = 20, pos = "topright")
plotmap(FantasyBnd, x = nx, density = 20, pos = "bottomright")
plotmap(FantasyBnd, x = nx, density = 20, pos = "right")
par(op)

# load and plot a map from GermanyBnd
op <- par(no.readonly = TRUE)
data("GermanyBnd")
plotmap(GermanyBnd, main = "Map of GermanyBnd")
n <- length(GermanyBnd)

# add some colors
plotmap(GermanyBnd, col = rainbow(n))
plotmap(GermanyBnd, col = heat.colors(n))
plotmap(GermanyBnd, col = topo.colors(n))
plotmap(GermanyBnd, col = cm.colors(n))
plotmap(GermanyBnd, col = gray.colors(n))
plotmap(GermanyBnd, col = c("green", "green3"))
par(op)


## now with bayesx
set.seed(333)

## simulate some geographical data
data("MunichBnd")
N <- length(MunichBnd); names(MunichBnd) <- 1:N
n <- N*5

## regressors
dat <- data.frame(id = rep(1:N, n/N))
dat$sp <- with(dat, sort(runif(N, -2, 2), decreasing = TRUE)[id])

## response
dat$y <- with(dat, 1.5 + sp + rnorm(n, sd = 0.6))

## estimate model
b <- bayesx(y ~ sx(id, bs = "mrf", map = MunichBnd),
  method = "MCMC", data = dat)

## summary statistics
summary(b)

## plot spatial effect
op <- par(no.readonly = TRUE)
plot(b, map = MunichBnd)
plot(b, map = MunichBnd, c.select = "97.5plot(b, map = MunichBnd, c.select = "2.5plot(b, map = MunichBnd, c.select = "50plot(b, map = MunichBnd, names = TRUE, 
  cex.names = 0.5, cex.legend = 0.8)
plot(b, map = MunichBnd, range = c(-0.5, 0.5))
plot(b, map = MunichBnd, range = c(-5, 5))
plot(b, map = MunichBnd, col = heat_hcl, 
  swap = TRUE, symmetric = FALSE)
par(op)