geoR (version 1.6-35)

points.geodata: Plots Spatial Locations and Data Values

Description

This function produces a plot with points indicating the data locations. Arguments can control the points sizes, patterns and colors. These can be set to be proportional to data values, ranks or quantiles. Alternatively, points can be added to the current plot.

Usage

## S3 method for class 'geodata':
points(x, coords=x$coords, data=x$data, data.col = 1, borders,
               pt.divide=c("data.proportional","rank.proportional",
                           "quintiles", "quartiles", "deciles", "equal"),
               lambda = 1, trend = "cte", abs.residuals = FALSE,
               weights.divide = "units.m", cex.min, cex.max, cex.var,
               pch.seq, col.seq, add.to.plot = FALSE,
               x.leg, y.leg = NULL, dig.leg = 2, 
               round.quantiles = FALSE, permute = FALSE, ...)

Arguments

x

a list containing elements coords and data described next. Typically an object of the class "geodata" - a geoR data-set. If not provided the arguments coords and data

coords

an $n \times 2$ matrix containing coordinates of the $n$ data locations in each row. Defaults to geodata$coords.

data

a vector or matrix with data values. If a matrix is provided each column is regarded as one variable or realization. Defaults to geodata$data.

data.col

the number of the data column. Only used if data is a matrix with columns corresponding to different variables or simulations.

borders

If an $n \times 2$ matrix or data-frame with the coordinates of the borders of the regions is provided, the borders are added to the plot. By default it searches for a element named "borders" in the geodata object.

pt.divide

defines the division of the points in categories. See DETAILS below for the available options. Defaults to pt.divide = "data.proportional".

trend

specifies the mean part of the model. The options are: "cte" (constant mean - default option), "1st" (a first order polynomial on the coordinates), "2nd" (a second order polynomial on the coordinates), or

abs.residuals

logical. If TRUE and the value passed to the argument trend is different from "cte" the point sizes are proportional to absolute values of the residuals.

lambda

value of the Box-Cox transformation parameter. Two particular cases are $\lambda = 1$ which corresponds to no transformation and $\lambda = 0$ corresponding to the log-transformation.

weights.divide

if a vector of weights with the same length as the data is provided each data is divided by the corresponding element in this vector. Defaults divides the data by the element units.m in the data object, if present, otherwise

cex.min

minimum value for the graphical parameter cex. This value defines the size of the point corresponding the minimum of the data. Defaults to 0.5.

cex.max

maximum value for the graphical parameter cex. This value defines the size of the point corresponding the maximum of the data. If pt.divide = "equal" it is used to set the value for the graphical parameter c

cex.var

a numeric vector with the values of a variable defining the size of the points. Particularly useful for displaying 2 variables at once.

pch.seq

number(s) defining the graphical parameter pch.

col.seq

number(s) defining the colors in the graphical parameter col.

add.to.plot

logical. If TRUE the points are added to the current plot or image otherwise a display is open. Defaults to FALSE.

x.leg, y.leg

x and y location of the legend as documented in legend.

dig.leg

the desired number of digits after the decimal point. Printing values in the legend uses formatC with argument format = "f".

round.quantiles

logical. Defines whether or not the values of the quantiles should be rounded. Defaults to FALSE.

permute

logical indication whether the data values should be randomly re-alocatted to the coordinates. See DETAILS below.

...

further arguments to be passed to the function plot, if add.to.plot = FALSE; or to the function points, if add.to.plot = TRUE.

Value

• A plot is created or points are added to the current graphics device. A list with graphical parameters used to produce the plot is returned invisibily. According to the input options, the list has some or all of the following components:
• quantiles
  the values of the quantiles used to divide the data.
• cex
  the values of the graphics expansion parameter cex.
• col
  the values of the graphics color parameter col.
• pch
  the values of the graphics pattern parameter pch.

Details

The points can be devided in categories and have different sizes and/or colours according to the argument pt.divide. The options are: [object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

For cases where points have different sizes the arguments cex.min and cex.max set the minimum and the maximum point sizes. Additionally, pch.seq can set different patterns for the points and col.seq can be used to define colors. For example, different colors can be used for quartiles, quintiles and deciles while a sequence of gray tones (or a color sequence) can be used for point sizes proportional to the data or their ranks. For more details see the section EXAMPLES.

The argument cex.var allows for displaying 2 variables at once. In this case one variable defines the backgroung colour of the points and the other defines the points size. The argument permute if set to TRUE randomly realocates the data in the coordinates. This may be used to contrast the spatial pattern of original data against another situation where there is no spatial dependence (when setting permute = TRUE). If a trend is provided the residuals (and not the original data) are permuted.

References

Further information on the package geoR can be found at: http://www.leg.ufpr.br/geoR.

See Also

plot.geodata for another display of the data and points and plot for information on the generic Rfunctions. The documentation of par provides details on graphical parameters. For color schemes in Rsee gray and rainbow.

Examples

op <- par(no.readonly = TRUE)
par(mfrow=c(2,2), mar=c(3,3,1,1), mgp = c(2,1,0))
points(s100, xlab="Coord X", ylab="Coord Y")
points(s100, xlab="Coord X", ylab="Coord Y", pt.divide="rank.prop")
points(s100, xlab="Coord X", ylab="Coord Y", cex.max=1.7,
               col=gray(seq(1, 0.1, l=100)), pt.divide="equal")
points(s100, pt.divide="quintile", xlab="Coord X", ylab="Coord Y")
par(op)

points(ca20, pt.div='quartile', x.leg=4900, y.leg=5850, bor=borders)

par(mfrow=c(1,2), mar=c(3,3,1,1), mgp = c(2,1,0))
points(s100, main="Original data")
points(s100, permute=TRUE, main="Permuting locations")

## Now an example using 2 variable, 1 defining the
## gray scale and the other the points size
points.geodata(coords=camg[,1:2], data=camg[,3], col="gray",
               cex.var=camg[,5])
points.geodata(coords=camg[,1:2], data=camg[,3], col="gray",
               cex.var=camg[,5], pt.div="quint")