driftmap: Interactive driftplot and map
In GeoXp: Interactive exploratory spatial data analysis

Description Usage Arguments Details Value Author(s) References See Also Examples

The function driftmap() creates two devices : a device with the map of coord coordinates(sp.obj) which permits to make selection of sites and a device divided into 2 rows and 2 columns which contains : (cell 1) the selected sites divided into m rows and q columns (m and q are selected with the tk window), (cell 2) a scatter plot with coordinates(sp.obj)[,2] in x-axis and the mean and median of name.var calculated for the m rows in y-axis, (cell 3) a scatter plot with the mean and median of name.var calculated for the q columns in x-axis and coordinates(sp.obj)[,1] in y-axis and (cell 4) a legend indicating the direction of the North, the variable used, etc.

1
2
3

driftmap(sp.obj, name.var, interpol=TRUE, nuage=TRUE, lty=1:2, cex=0.7,
names.attr=names(sp.obj), carte=NULL, identify=FALSE, cex.lab=0.8, pch=rep(16,3),
col=c("lightblue3", "black", "red"), xlab="", axes=FALSE)

`sp.obj`	object of class extending Spatial-class
`name.var`	a character; attribute name or column number in attribute table
`interpol`	if TRUE, the mean and median calculated are linearly interpoled
`nuage`	if TRUE, the values taken by var are also represented on right plot and on the left plot
`lty`	the line type for mean and median in the case of interpol=TRUE
`cex`	the amount by which plotting symbols on the cell 1 and in the case of nuage=TRUE cell 2 and cell 3
`names.attr`	names to use in panel (if different from the names of variable used in sp.obj)
`carte`	matrix with 2 columns for drawing spatial polygonal contours : x and y coordinates of the vertices of the polygon
`identify`	if not FALSE, identify plotted objects (currently only working for points plots). Labels for identification are the row.names of the attribute table row.names(as.data.frame(sp.obj)).
`cex.lab`	character size of label
`pch`	c(16,16,16) by default, list of symbols for (1) the values of var on the left and on the right plot (2) the mean points, (3) the median points
`col`	c("lightblue3", "black", "red") by default, list of colors for (1) the values of var on the left and on the right plot (2) the mean points, (3) the median points
`xlab`	name of var printed with the legend plot
`axes`	a boolean with TRUE for drawing axes on the map

Possibility to change the number of cells in the grid with the tk window, to interpolate the means and medians calculated (by default), to work on a rotated map. At the begining, all sites have been selected to the map : users have to deselect sites that they have choosen.

In the case where user click on save results button, a vector of integer is created as a global variable in last.select object. It corresponds to the number of spatial units selected just before leaving the Tk window.

Thomas-Agnan C., Aragon Y., Ruiz-Gazen A., Laurent T., Robidou L.

Thibault Laurent, Anne Ruiz-Gazen, Christine Thomas-Agnan (2012), GeoXp: An R Package for Exploratory Spatial Data Analysis. Journal of Statistical Software, 47(2), 1-23.

angleplotmap,variocloudmap,rotation

######
# data on price indices of real estate in France
data(immob)
row.names(immob)<-immob$Nom

# immob is a data.frame object. We have to create
# a Spatial object, by using first the longitude and latitude
# to create Spatial Points object ...
immob.sp = SpatialPoints(cbind(immob$longitude,immob$latitude))
# ... and then by integrating other variables to create SpatialPointsDataFrame
immob.spdf = SpatialPointsDataFrame(immob.sp, immob)
# For more details, see vignette('sp', package="sp")

# optional : we add some contours that don't correspond to the spatial unit
# but are nice for mapping
require("maptools")
midiP <- readShapePoly(system.file("shapes/region.shp", package="GeoXp")[1])
cont_midiP<-spdf2list(midiP[-c(22,23),])$poly

# a simple use of driftmap
driftmap(immob.spdf,"prix.vente", carte= cont_midiP)

# ... with options
driftmap(immob.spdf,"prix.vente", carte= cont_midiP,
interpol=FALSE, nuage=TRUE, lty=3:4,
identify=TRUE, cex.lab=0.3, xlab="Price of sell", axes=TRUE)

######
# data eire
eire <- readShapePoly(system.file("etc/shapes/eire.shp", package="spdep")[1],
ID="names", proj4string=CRS("+proj=utm +zone=30 +units=km"))

# a basic usage ...
driftmap(eire,"pale",identify=TRUE,nuage=TRUE)