hydroTSM (version 0.6-0)

mspplot: Multiple spplot

Description

Plots several spatial maps in the same plotting window, with options to easily add a scale bar and north arrow. Originally, it was though to make easier the display of several maps (of the same spatial extent) obtained by different interpolation methods or for different time steps.

Usage

mspplot(x, subcatchments, IDvar = NULL, p4s=CRS(as.character(NA)), 
        plot = TRUE, ColorRamp="PCPAnomaly",col.nintv = 10, col.at = "auto", 
        main, stations.plot = FALSE, stations.gis, X, Y, 
        arrow.plot = FALSE, arrow.offset, arrow.scale, 
        scalebar.plot = FALSE, sb.offset, sb.scale, verbose = TRUE)

Arguments

x

SpatialPixelsDataFrame-class object that stores (in the @data slot) all the maps that will be plotted.

subcatchments

SpatialPolygonsDataFrame-class with all the subcatchments within the study area, OR character representing the filename (with path) of the shapefile ('polygon' type) that stores those subcatchments.

IDvar

See readShapePoly. Character string with the name of a column in the subcatchments shapefile DBF containing the ID values of the catchments - the values will be converted to a character vector.

p4s

Character with information about the projection of the GIS files, usually created by the CRS function of the sp package

plot

Logical, indicating if the interpolated values have to be plotted or not

ColorRamp

Character or function defining a personalized color ramp for plotting the maps. Valid character values are in c("Precipitation", "Temperature", "PCPAnomaly", "PCPAnomaly2" "TEMPAnomaly", "TEMPAnomaly2", "TEMPAnomaly3").

col.nintv

integer, number of colors that have to be used for plotting the interpolated values

col.at

Specify at which interpolated values colours change. Valid values are: -) R : uses the default setting of 'spplot' -) auto: default option. at <- seq(min, max,length.out=col.nintv) min <- floor( min(idw["var1.pred"]@data, na.rm=TRUE)) max <- ceiling( max(idw["var1.pred"]@data, na.rm=TRUE)) -) numeric: vector giving the exact values in which the colors have to change. Useful when the user desires the same color for the same value when comparing two or more maps with different range of values

main

Character with the title to be used for the plot

stations.plot

Logical, indicating if the gauging stations, defined by stations.gis have to be plotted

stations.gis

OPTIONAL. data.frame with the stations that will be added to the plot. ONLY required when stations.plot == TRUE.

X

OPTIONAL. character, field name in x.gis that stores the easting coordinate of the stations. ONLY required when stations.plot == TRUE.

Y

OPTIONAL. character, field name in x.gis that stores the northing coordinate of the stations. ONLY required when stations.plot == TRUE.

arrow.plot

Logical, indicating if a North Arrow have to be plotted

arrow.offset

OPTIONAL. 2D list with the numeric coordinates in which the North Arrow have to be plotted. e.g., arrow.offset = c(690000,4760000). ONLY required when arrow.plot=TRUE

arrow.scale

OPTIONAL. Scale (in the map units) to be used for plotting the North Arrow, e.g., scale = 20000. ONLY required when arrow.plot=TRUE.

scalebar.plot

Logical, indicating if a Scale Bar have to be plotted

sb.offset

OPTIONAL. 2D list with the numeric coordinates in which the North Arrow have to be plotted. e.g., sb.offset = c(400000,4490000). ONLY required when scalebar.plot=TRUE

sb.scale

OPTIONAL. Scale (in the map units) to be used for plotting the Scale Bar, e.g., scale = 100000, means that the scale bar will have a length of 100km. ONLY required when scalebar.plot=TRUE.

verbose

logical; if TRUE, progress messages are printed

References

Applied Spatial Data Analysis with R. Series: Use R. Bivand, Roger S., Pebesma, Edzer J., Gomez-Rubio, Virgilio. 2008. ISBN: 978-0-387-78170-9 http://rspatial.r-forge.r-project.org/

See Also

spplot, krige, autoKrige

Examples

# NOT RUN {
## Loading the monthly time series of precipitation within the Ebro River basin.
data(EbroPPtsMonthly)

## Loading the gis data
data(EbroPPgis)

## Loading the shapefile with the subcatchments
data(EbroCatchmentsCHE)

## Projection for the Subcatchments file
require(sp)
p4s <- CRS("+proj=utm +zone=30 +ellps=intl +units=m +no_defs")

## Field name in 'x.gis' with the ID of the station
sname <- "ID"
## Field name in 'x.gis'with the name of the catchment to which each station belongs
bname <- "CHE_BASIN_NAME"
## Field name in 'x.gis' with the Easting spatial coordinate
X     <- "EAST_ED50" 
## Field name in 'x.gis' with the Northing spatial coordinate
Y     <- "NORTH_ED50" 
## Field name in 'x.gis' with the Elevation
elevation <- "ELEVATION" 



#######
## Selecting Jan/1961 (first row) of 'EbroPPtsMonthly' in all the stations
x.ts <- as.numeric(EbroPPtsMonthly[1, 2:ncol(EbroPPtsMonthly)])

## Setting the name of the stations
names(x.ts) <- colnames(EbroPPtsMonthly[ ,2:ncol(EbroPPtsMonthly)])


########
# }
# NOT RUN {
## IDW interpolation and plot (Jan/61)
x.idw <- hydrokrige(x.ts= x.ts, x.gis=EbroPPgis, 
                    X=X, Y=Y, sname=sname, bname=bname, elevation=elevation, 
                    type= "cells", #'both'
                    subcatchments= EbroCatchmentsCHE, p4s= p4s, 
                    cell.size= 3000, nmax= 50,
		    ColorRamp= "Precipitation",
		    main= "IDW Mean Annual Precipitation on the Ebro, Jan/1961")

## Storing the interpolated values
x.idw@data["Jan1961"]   <- x.idw@data["var1.pred"]
x.idw@data["var1.pred"] <- NULL
x.idw@data["var1.var"]  <- NULL


## Selecting the Jul/1961 of 'EbroPPtsMonthly' for all the stations
x.ts <- as.numeric(EbroPPtsMonthly[7, 2:ncol(EbroPPtsMonthly)])

## Setting the name of the stations
names(x.ts) <- colnames(EbroPPtsMonthly[ , 2:ncol(EbroPPtsMonthly)])


## IDW interpolation and plot (Jul/1961)
x.idw2 <- hydrokrige(x.ts= x.ts, x.gis=EbroPPgis, 
                     X=X, Y=Y, sname=sname, bname=bname, elevation=elevation,
                     type= "cells", #'both'
                     subcatchments= EbroCatchmentsCHE, p4s= p4s, 
                     cell.size= 3000, nmax= 50,
                     ColorRamp= "Precipitation",
                     main= "IDW Mean Annual Precipitation on the Ebro, Jul/1961")

# Adding the interpolated value for Jul/1961 to 'x.idw'
x.idw@data["Jul1961"] <- x.idw2@data["var1.pred"]


## Plotting in the same graph the 2 interpolated fields
mspplot(x=x.idw, 
        subcatchments=EbroCatchmentsCHE, 
        IDvar=NULL, p4s, 
        col.nintv=50, 
        main="IDW Monthly Precipitation on the Ebro River basin, [mm]",
        stations.plot=FALSE,
        arrow.plot=TRUE, arrow.offset=c(900000,4750000), arrow.scale=20000,
        scalebar.plot=TRUE, sb.offset=c(400000,4480000), sb.scale=100000)	
# }