phenology (version 3.40)

plot_map: Plot a likelihood map with Delta and Phi varying.

Description

This function plots a likelihood map obtained after map_phenology.

Usage

plot_map(map = NULL, pdf = FALSE, pdfname = "Map.pdf",
    col = heat.colors(128), help = FALSE)

Arguments

map

A map generated with map_phenology.

pdf

TRUE or FALSE, indicates if a pdf file is generated.

pdfname

Name of file if pdf=TRUE

col

Colors could be heat.colors(128) or rainbow(64) or col=gray(c(seq(0, 1, length.out=128)))

help

If TRUE, an help is displayed

Value

• Return None

Details

plot_map plots a likelihood map with Delta and Phi varying.

Examples

library("phenology")
# Read a file with data
# Gratiot<-read.delim("http://max2.ese.u-psud.fr/epc/conservation/BI/Complete.txt", , header=FALSE)
data(Gratiot)
# Generate a formatted list nammed data_Gratiot
data_Gratiot<-add_format(origin=NULL, add=Gratiot, name="Complete", reference=as.Date("2001-01-01"), format="%d/%m/%Y")
# Generate initial points for the optimisation
parg<-par_init(data_Gratiot, parametersfixed=NULL)
# Run the optimisation
# result_Gratiot<-fit_phenology(data=data_Gratiot, parametersfit=parg, parametersfixed=NULL, trace=1)
data(result_Gratiot)
# Extract the fitted parameters
parg1<-extract_result(result_Gratiot)
# Add constant Alpha and Tau values [day d amplitude=(Alpha+Nd*Beta)^Tau with Nd being the number of counts for day d]
pfixed<-c(parg1, Alpha=0, Tau=1)
pfixed<-pfixed[-which(names(pfixed)=="Theta")]
# The only fitted parameter will be Beta
parg2<-c(Beta=0.5, parg1["Theta"])
# Generate a likelihood map [default Phi=seq(from=0.1, to=20, length.out=100) but it is very long]
# Take care, it takes 20 hours ! The data map_Gratiot has the result
# map_Gratiot<-map_phenology(data=data_Gratiot, Phi=seq(from=0.1, to=20, length.out=100), parametersfit=parg2, parametersfixed=pfixed)
data(map_Gratiot)
# Plot the map
plot_map(map=map_Gratiot, pdf=FALSE, col=heat.colors(128))