# Read a file with data
library("phenology")
#' 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")
# Fix parameter FLat to 0
pfixed=c(Flat=0)
# Generate initial points for the optimisation
parg<-par_init(data_Gratiot, parametersfixed=pfixed)
# Fit is done
# result_Gratiot_Flat<-fit_phenology(data=data_Gratiot, parametersfit=parg, parametersfixed=pfixed, trace=1)
data(result_Gratiot_Flat)
parg<-extract_result(result_Gratiot_Flat)
# Add data for one sinusoid superimposed [day d amplitude=(Alpha+Nd*Beta)^Tau with Nd being the number of counts for day d]
parg<-c(parg, Alpha=0.5, Beta=0.8, Delta=3, Phi=15)
# Tau is fixed to 1
pfixed=c(Flat=0, Tau=1)
# Run the optimisation
# result_Gratiot1<-fit_phenology(data=data_Gratiot, parametersfit=parg, parametersfixed=pfixed, trace=1)
data(result_Gratiot1)
# Plot the phenology
output1<-plot_phenology(result_Gratiot1, moon=TRUE)
# Extract the fitted parameters
parg1<-extract_result(result_Gratiot1)
# Shift sunusoid information to the '1'
parg2<-shift_sinusoid(parameters=parg1, from="", to="1")
# Tau is fixed to 1
pfixed=c(Flat=0, Tau1=1, Tau=1)
# Add data for another sinusoid superimposed [day d amplitude=(Alpha+Nd*Beta)^Tau with Nd being the number of counts for day d]
parg<-c(parg2, Alpha=0.5, Beta=0.8, Delta=3, Phi=10)
# Run the optimisation
# result_Gratiot2<-fit_phenology(data=data_Gratiot, parametersfit=parg, parametersfixed=pfixed, trace=1)
data(result_Gratiot2)
# Plot the phenology
output2<-plot_phenology(result_Gratiot2, moon=TRUE)Run the code above in your browser using DataLab