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.
# S3 method for 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, …)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 must be provided instead.
an \(n \times 2\) matrix containing
coordinates of the \(n\) data locations in each row.
Defaults to geodata$coords.
a vector or matrix with data values.
If a matrix is provided each column is regarded as one variable or realization.
Defaults to geodata$data.
the number of the data column. Only used if
data is a matrix with columns corresponding to different
variables or simulations.
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.
defines the division of the points in categories.
See DETAILS below for the available options.
Defaults to pt.divide = "data.proportional".
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 a formula of the type ~X where X
is a matrix with the covariates (external trend).
If provided the trend is "removed" using the function
lm and the residuals are plotted.
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.
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.
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 no action is taken and original
data is used.
The usage of units.m is common for data objects
to be analysed using the package geoRglm.
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.
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 cex. Defaults to 1.5.
a numeric vector with the values of a variable defining the size of the points. Particularly useful for displaying 2 variables at once.
number(s) defining the graphical parameter pch.
number(s) defining the colors in the graphical parameter
col.
logical. If TRUE the points are added
to the current plot or image otherwise a display is open. Defaults to FALSE.
x and y location of the legend as
documented in legend.
the desired number of digits after the decimal
point. Printing values in the legend uses formatC with
argument format = "f".
logical. Defines whether or not the values
of the quantiles should be rounded. Defaults to FALSE.
logical indication whether the data values should be
randomly re-alocatted to the coordinates. See DETAILS below.
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:
the values of the quantiles used to divide the data.
the values of the graphics expansion parameter cex.
the values of the graphics color parameter col.
the values of the graphics pattern parameter pch.
The points can be devided in categories and have different sizes
and/or colours according to the argument
pt.divide. The options are:
sizes proportional to the data values.
sizes proportional to the rank of the data.
five different sizes according to the quintiles of the data.
four different sizes according to the quartiles of the data.
ten different sizes according to the deciles of the data.
all points with the same size.
defines a number of quantiles, the number provided defines the number of different points sizes and colors.
the values in the
vector will be used by the function cut as break
points to divide the data in classes.
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.
Further information on the package geoR can be found at: http://www.leg.ufpr.br/geoR.
plot.geodata for another display of the data and
points and plot for information on the
generic R functions. The documentation of
par provides details on graphical parameters.
For color schemes in R see gray and
rainbow.
# NOT RUN {
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)
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")
# }
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