multiple.plot: Plot and compare prediction maps within BIOMOD
In BIOMOD: Ensemble platform for species distribution modeling

Description Usage Arguments Author(s) See Also Examples

This function allows direct comparisons of the predictions across models. The maps produced are the same than with the level.plot function

1	multiple.plot(Data, coor, color.gradient='red', plots.per.window=9, cex=1, save.file="no", name="multiple plot", ImageSize = "small", AddPresAbs = NULL, PresAbsSymbol = c(cex * 0.8, 16, 4))

`Data`	the data you want to visualise
`coor`	a 2 columns matrix of the same length as data.in giving the coordinates of the data points
`color.gradient`	available : 'red', 'grey' and 'blue'
`plots.per.window`	the number of plots you wish to visualise per window
`cex`	to change the point size : >1 will increase size, <1 will decrease it
`save.file`	can be set to "pdf", "jpeg" or "tiff" to save the plot. Pdf options can be changed by setting the default values of pdf.options().
`name`	the name of the file produced if save.file is different to "no" (extensions are already included)
`ImageSize`	The image size for JPEG and TIFF files saved to disk. Available : 'small', 'standard' and 'large'
`AddPresAbs`	Optional: adds the presences and absences used for calibration to the plot. Data must be entered as a matrix/dataframe with 3 columns (in this order): X-coordinate, Y-coordinate, Presence(1) or Absence(0). X and Y coordinates must be in the same system as the plot.
`PresAbsSymbol`	Optional: a 3 element vector giving the symbols to be used by the AddPresAbs argument for plotting. The elements of the vector must be in this order: size of presence/absence symbols given as a multiplication factor of the 'cex' value entered in the function (e.g. a value of 0.5 means that the symbols will be drawn at a size = 0.5*cex value entered in the function), symbol (in PCH code) to be used for presences, symbol (in PCH code) to be used for absences. An example of input vector for this parameter is 'c(0.4,16,4)'

Wilfried Thuiller, Bruno Lafourcade

level.plot

data(Sp.Env)
data(CoorXY)

#multiple.plot(Sp.Env[,4:18], CoorXY, plots.per.window=16, cex=0.8)

#just the set of environmental variables 
#multiple.plot(Sp.Env[,4:10], CoorXY, cex=0.8)