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Commit 96d4e53f authored by Lo Iacono, Giovanni Dr (School of Vet Med.)'s avatar Lo Iacono, Giovanni Dr (School of Vet Med.)
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# The code does look at how the risk of Campylobacter in humans depends on environmental variables
# The code does look at how the risk of Campylobacter in humans depends on environmental variables
# Analysis was done following an quantiles division of the range of the environmental variables, independently of the number of observations
# This is used for the reconstruction
Plot_Conditional_incidence_quantiles<-function(Data_frame_1, Pars)
{
with(as.list(c(Data_frame_1, Pars)), {
# Pars is the list of 3 variables of interest
# Select the variables of study:
variable_x<-Pars[1]
variable_y<-Pars[2]
variable_z<-Pars[3]
# Select the file with relevant information:
Conditional_incidence_quantiles <- Data_frame_1[[1]]
#Conditional_incidence_quantiles<-Conditional_incidence_quantiles[,-1]
Conditional_incidence_quantiles$incidence<-Conditional_incidence_quantiles$counts/Conditional_incidence_quantiles$residents_tot
# Conditional_incidence_quantiles<-na.omit(Conditional_incidence_quantiles)
#For visual purposes, we are removing cases when the counts were too low resulting in exceptional large incidence
#Conditional_incidence_quantiles<-subset(Conditional_incidence_quantiles, Conditional_incidence_quantiles$counts>100)
#number_days<-as.Date(last_day)-as.Date(first_day)
#number_days<-as.numeric(number_days)
#number_year<-number_days/365
norm<-1/(1e6)
################### Choose a specific day-length ###################
#Conditional_incidence_quantiles<-na.omit(Conditional_incidence_quantiles)
############################# General variables ###########################
if (variable_x=="Relative_humidity"){variable_x_char<-"Relative humidity (%)"}
if (variable_y=="Relative_humidity"){variable_y_char<-"Relative humidity (%)"}
if (variable_x=="Mean_wind_speed"){variable_x_char<-"Mean Wind Speed (knots)"}
if (variable_y=="Mean_wind_speed"){variable_y_char<-"Mean Wind Speed (knots)"}
if (variable_x=="Mean_wind_speed"){variable_x_char<-"Mean Wind Speed (knots)"}
if (variable_y=="Mean_wind_speed"){variable_y_char<-"Mean Wind Speed (knots)"}
if (variable_x=="Mean_Precipitation"){variable_x_char<-"Mean Precipitation (mm)"}
if (variable_y=="Mean_Precipitation"){variable_y_char<-"Mean Precipitation (mm)"}
if (variable_x=="daylength"){variable_x_char<-"Day-Length (hours)"}
if (variable_y=="daylength"){variable_y_char<-"Day-Length (hours)"}
if (variable_x=="Minimum_air_temperature"){variable_x_char<-expression("Minimum Air Temperature"*~degree*C)}
if (variable_y=="Minimum_air_temperature"){variable_y_char<-expression("Minimum Air Temperature"*~degree*C)}
if (variable_x=="Maximum_air_temperature"){variable_x_char<-expression("Maximum Air Temperature"*~degree*C)}
if (variable_y=="Maximum_air_temperature"){variable_y_char<-expression("Maximum Air Temperature"*~degree*C)}
labelling_char<-c()
############# 3 variable from here
if (variable_z=="daylength"){
for (i_light in c(1:length(unique(Conditional_incidence_quantiles$daylength)))) {
light_label<-round(as.numeric(unique(Conditional_incidence_quantiles$daylength)))
if (i_light<length(light_label)){
light_label_char<-paste("Day-length ",light_label[i_light],"-",light_label[i_light+1]," hours",sep="")
} else {
light_label_char<-paste("Day-length >",light_label[i_light]," hours",sep="")
}
wt<-which(Conditional_incidence_quantiles$daylength==unique(Conditional_incidence_quantiles$daylength)[i_light])
Conditional_incidence_df<-Conditional_incidence_quantiles[wt,]
Conditional_incidence_df<-Conditional_incidence_df[order(Conditional_incidence_df[variable_y]),]
conf_minus<-((Conditional_incidence_df$incidence-1.96*sqrt(Conditional_incidence_df$incidence*(1-Conditional_incidence_df$incidence)/Conditional_incidence_df$residents_tot)))/norm
conf_plus<- ((Conditional_incidence_df$incidence+1.96*sqrt(Conditional_incidence_df$incidence*(1-Conditional_incidence_df$incidence)/Conditional_incidence_df$residents_tot)))/norm
Conditional_incidence_df$incidence<-Conditional_incidence_df$incidence/norm
Conditional_incidence_df$conf_minus<-conf_minus
Conditional_incidence_df$conf_plus<-conf_plus
#Conditional_incidence_df<-na.omit(Conditional_incidence_df)
Conditional_incidence_df[variable_y]<-round(Conditional_incidence_df[variable_y])
if (variable_x=="Maximum_air_temperature" & variable_y=="Relative_humidity"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Maximum_air_temperature,y=incidence,color=factor(Relative_humidity),fill=factor(Relative_humidity)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(0,5))+scale_x_continuous(limits=c(-5,30))
}
if (variable_x=="Relative_humidity" & variable_y=="Maximum_air_temperature"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Relative_humidity,y=incidence,color=factor(Maximum_air_temperature),fill=factor(Maximum_air_temperature)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(0,5))+scale_x_continuous(limits=c(60,100))
}
if (variable_x=="Maximum_air_temperature" & variable_y=="Mean_wind_speed"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Maximum_air_temperature,y=incidence,color=factor(Mean_wind_speed),fill=factor(Mean_wind_speed)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(0,5))+scale_x_continuous(limits=c(-5,30))
}
if (variable_x=="Mean_wind_speed" & variable_y=="Maximum_air_temperature"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Mean_wind_speed,y=incidence,color=factor(Maximum_air_temperature),fill=factor(Maximum_air_temperature)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(0,5))+scale_x_continuous(limits=c(0,15))
}
if (variable_x=="Maximum_air_temperature" & variable_y=="Mean_Precipitation"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Maximum_air_temperature,y=incidence,color=factor(Mean_Precipitation),fill=factor(Mean_Precipitation)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(0,5))+scale_x_continuous(limits=c(-5,30))
}
if (variable_x=="Mean_Precipitation" & variable_y=="Maximum_air_temperature"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Mean_Precipitation,y=incidence,color=factor(Maximum_air_temperature),fill=factor(Maximum_air_temperature)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(0,5))+scale_x_continuous(limits=c(0,5))
}
if (variable_x=="Maximum_air_temperature" & variable_y=="daylength"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Maximum_air_temperature,y=incidence,color=factor(daylength),fill=factor(daylength)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(0,5))+scale_x_continuous(limits=c(-5,30))
}
Conditional_incidence_plot <- Conditional_incidence_plot+theme_bw(20)
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_colour_discrete(name =variable_y_char)
Conditional_incidence_plot <- Conditional_incidence_plot+ylab("Conditional Incidence of Campylobacter Cases ")
Conditional_incidence_plot <- Conditional_incidence_plot+xlab(variable_x_char)
Conditional_incidence_plot <- Conditional_incidence_plot+ ggtitle(light_label_char)
labelling<-c(round(as.numeric(unique(Conditional_incidence_df[variable_y])[,1])))
n_labelling<-length(labelling)
for (j in c(1:(n_labelling-1))) {
labelling_char[j]<-paste(as.character(labelling[j]), "-", as.character(labelling[j+1]) )
}
labelling_char[n_labelling]<-paste(">",as.character(labelling[n_labelling]))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_fill_discrete(name =variable_y_char, labels=labelling_char)
Conditional_incidence_plot <- Conditional_incidence_plot+ geom_point(size=3.5)+ guides(colour="none") # guides(colour="none")
Conditional_incidence_plot <- Conditional_incidence_plot+ geom_line(size=1)
Conditional_incidence_plot <- Conditional_incidence_plot+ geom_ribbon(aes(ymin=conf_minus, ymax=conf_plus),alpha=0.35)
Conditional_incidence_plot <- Conditional_incidence_plot+
theme(legend.position= c(0.25,0.75),legend.title = element_text( size = 11),
legend.text = element_text( size = 10),legend.background = element_blank(),
legend.key=element_rect(colour=NA))
Conditional_incidence_plot <- Conditional_incidence_plot+ theme(axis.title.x =element_text( colour="#990000", size=15))
Conditional_incidence_plot <- Conditional_incidence_plot+ theme(axis.title.y =element_text( colour="#990000", size=15))
Conditional_incidence_plot <- Conditional_incidence_plot+ theme(axis.title.x =element_text(size=15))
Conditional_incidence_plot <- Conditional_incidence_plot+ theme(axis.title.y =element_text(size=15))
print(Conditional_incidence_plot)
file_name<-paste("../Graphs/Campylobacter_",variable_x,"_",variable_y,"_",variable_z,"_",
round(unique(Conditional_incidence_quantiles$daylength)[i_light]),"_",time_lag_char,"_quantile.tiff", sep = "")
tiff(filename = file_name,width = 17.35, height = 17.35, units = "cm", pointsize = 12, res = 1200,compression = "lzw",antialias="default")
print(Conditional_incidence_plot)
dev.off()
}
}
if (variable_z=="Relative_humidity"){
for (i_light in c(1:length(unique(Conditional_incidence_quantiles$Relative_humidity)))) {
light_label<-round(as.numeric(unique(Conditional_incidence_quantiles$Relative_humidity)))
if (i_light<length(light_label)){
light_label_char<-paste("Relative Humidity ",light_label[i_light],"-",light_label[i_light+1]," %",sep="")
} else {
light_label_char<-paste("Relative Humidity >",light_label[i_light]," %",sep="")
}
wt<-which(Conditional_incidence_quantiles$Relative_humidity==unique(Conditional_incidence_quantiles$Relative_humidity)[i_light])
Conditional_incidence_df<-Conditional_incidence_quantiles[wt,]
Conditional_incidence_df<-Conditional_incidence_df[order(Conditional_incidence_df[variable_y]),]
conf_minus<-((Conditional_incidence_df$incidence-1.96*sqrt(Conditional_incidence_df$incidence*(1-Conditional_incidence_df$incidence)/Conditional_incidence_df$residents_tot)))/norm
conf_plus<- ((Conditional_incidence_df$incidence+1.96*sqrt(Conditional_incidence_df$incidence*(1-Conditional_incidence_df$incidence)/Conditional_incidence_df$residents_tot)))/norm
Conditional_incidence_df$incidence<-Conditional_incidence_df$incidence/norm
Conditional_incidence_df$conf_minus<-conf_minus
Conditional_incidence_df$conf_plus<-conf_plus
#Conditional_incidence_df<-na.omit(Conditional_incidence_df)
Conditional_incidence_df[variable_y]<-round(Conditional_incidence_df[variable_y])
if (variable_x=="Maximum_air_temperature" & variable_y=="Relative_humidity"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Maximum_air_temperature,y=incidence,color=factor(Relative_humidity),fill=factor(Relative_humidity)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(0,5))+scale_x_continuous(limits=c(-5,30))
}
if (variable_x=="Relative_humidity" & variable_y=="Maximum_air_temperature"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Relative_humidity,y=incidence,color=factor(Maximum_air_temperature),fill=factor(Maximum_air_temperature)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(0,5))+scale_x_continuous(limits=c(60,100))
}
if (variable_x=="Maximum_air_temperature" & variable_y=="Mean_wind_speed"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Maximum_air_temperature,y=incidence,color=factor(Mean_wind_speed),fill=factor(Mean_wind_speed)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(0,5))+scale_x_continuous(limits=c(-5,30))
}
if (variable_x=="Mean_wind_speed" & variable_y=="Maximum_air_temperature"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Mean_wind_speed,y=incidence,color=factor(Maximum_air_temperature),fill=factor(Maximum_air_temperature)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(0,5))+scale_x_continuous(limits=c(0,15))
}
if (variable_x=="Maximum_air_temperature" & variable_y=="Mean_Precipitation"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Maximum_air_temperature,y=incidence,color=factor(Mean_Precipitation),fill=factor(Mean_Precipitation)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(0,5))+scale_x_continuous(limits=c(-5,30))
}
if (variable_x=="Mean_Precipitation" & variable_y=="Maximum_air_temperature"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Mean_Precipitation,y=incidence,color=factor(Maximum_air_temperature),fill=factor(Maximum_air_temperature)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(0,5))+scale_x_continuous(limits=c(0,5))
}
if (variable_x=="Maximum_air_temperature" & variable_y=="daylength"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Maximum_air_temperature,y=incidence,color=factor(daylength),fill=factor(daylength)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(0,5))+scale_x_continuous(limits=c(-5,30))
}
if (variable_x=="daylength" & variable_y=="Maximum_air_temperature"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=daylength,y=incidence,color=factor(Maximum_air_temperature),fill=factor(Maximum_air_temperature)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(0,5))+scale_x_continuous(limits=c(6,18))
}
Conditional_incidence_plot <- Conditional_incidence_plot+theme_bw(20)
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_colour_discrete(name =variable_y_char)
Conditional_incidence_plot <- Conditional_incidence_plot+ylab("Conditional Incidence of Campylobacter Cases ")
Conditional_incidence_plot <- Conditional_incidence_plot+xlab(variable_x_char)
Conditional_incidence_plot <- Conditional_incidence_plot+ ggtitle(light_label_char)
labelling<-c(round(as.numeric(unique(Conditional_incidence_df[variable_y])[,1])))
n_labelling<-length(labelling)
for (j in c(1:(n_labelling-1))) {
labelling_char[j]<-paste(as.character(labelling[j]), "-", as.character(labelling[j+1]) )
}
labelling_char[n_labelling]<-paste(">",as.character(labelling[n_labelling]))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_fill_discrete(name =variable_y_char, labels=labelling_char)
Conditional_incidence_plot <- Conditional_incidence_plot+ geom_point(size=3.5)+ guides(colour="none") # guides(colour="none")
Conditional_incidence_plot <- Conditional_incidence_plot+ geom_line(size=1)
Conditional_incidence_plot <- Conditional_incidence_plot+ geom_ribbon(aes(ymin=conf_minus, ymax=conf_plus),alpha=0.35)
Conditional_incidence_plot <- Conditional_incidence_plot+
theme(legend.position= c(0.25,0.75),legend.title = element_text( size = 11),
legend.text = element_text( size = 10),legend.background = element_blank(),
legend.key=element_rect(colour=NA))
Conditional_incidence_plot <- Conditional_incidence_plot+ theme(axis.title.x =element_text( colour="#990000", size=15))
Conditional_incidence_plot <- Conditional_incidence_plot+ theme(axis.title.y =element_text( colour="#990000", size=15))
Conditional_incidence_plot <- Conditional_incidence_plot+ theme(axis.title.x =element_text(size=15))
Conditional_incidence_plot <- Conditional_incidence_plot+ theme(axis.title.y =element_text(size=15))
print(Conditional_incidence_plot)
file_name<-paste("../Graphs/Campylobacter_",variable_x,"_",variable_y,"_",variable_z,"_",
round(unique(Conditional_incidence_quantiles$Relative_humidity)[i_light]),"_",time_lag_char,"_quantile.tiff", sep = "")
tiff(filename = file_name,width = 17.35, height = 17.35, units = "cm", pointsize = 12, res = 1200,compression = "lzw",antialias="default")
print(Conditional_incidence_plot)
dev.off()
}
}
})
}
Plot_Conditional_incidence_quantiles_two_factors<-function(Data_frame_1, Pars)
{
with(as.list(c(Data_frame_1, Pars)), {
# Pars is the list of 3 variables of interest
# Select the variables of study:
variable_x<-Pars[1]
variable_y<-Pars[2]
variable_z<-Pars[3]
# Select the file with relevant information:
Conditional_incidence_quantiles <- Data_frame_1[[1]]
#Conditional_incidence_quantiles<-Conditional_incidence_quantiles[,-1]
Conditional_incidence_quantiles$incidence<-Conditional_incidence_quantiles$counts/Conditional_incidence_quantiles$residents_tot
# Conditional_incidence_quantiles<-na.omit(Conditional_incidence_quantiles)
#For visual purposes, we are removing cases when the counts were too low resulting in exceptional large incidence
#Conditional_incidence_quantiles<-subset(Conditional_incidence_quantiles, Conditional_incidence_quantiles$counts>100)
#number_days<-as.Date(last_day)-as.Date(first_day)
#number_days<-as.numeric(number_days)
#number_year<-number_days/365
norm<-1/(1e6)
################### Choose a specific day-length ###################
#Conditional_incidence_quantiles<-na.omit(Conditional_incidence_quantiles)
############################# General variables ###########################
if (variable_x=="Relative_humidity"){variable_x_char<-"Relative humidity (%)"}
if (variable_y=="Relative_humidity"){variable_y_char<-"Relative humidity (%)"}
if (variable_x=="Mean_wind_speed"){variable_x_char<-"Mean Wind Speed (knots)"}
if (variable_y=="Mean_wind_speed"){variable_y_char<-"Mean Wind Speed (knots)"}
if (variable_x=="Mean_wind_speed"){variable_x_char<-"Mean Wind Speed (knots)"}
if (variable_y=="Mean_wind_speed"){variable_y_char<-"Mean Wind Speed (knots)"}
if (variable_x=="Mean_Precipitation"){variable_x_char<-"Mean Precipitation (mm)"}
if (variable_y=="Mean_Precipitation"){variable_y_char<-"Mean Precipitation (mm)"}
if (variable_x=="daylength"){variable_x_char<-"Day-Length (hours)"}
if (variable_y=="daylength"){variable_y_char<-"Day-Length (hours)"}
if (variable_x=="Minimum_air_temperature"){variable_x_char<-expression("Minimum Air Temperature"*~degree*C)}
if (variable_y=="Minimum_air_temperature"){variable_y_char<-expression("Minimum Air Temperature"*~degree*C)}
if (variable_x=="Maximum_air_temperature"){variable_x_char<-expression("Maximum Air Temperature"*~degree*C)}
if (variable_y=="Maximum_air_temperature"){variable_y_char<-expression("Maximum Air Temperature"*~degree*C)}
labelling_char<-c()
############# variables from here
Conditional_incidence_df<-Conditional_incidence_quantiles
Conditional_incidence_df<-Conditional_incidence_df[order(Conditional_incidence_df[variable_y]),]
conf_minus<-((Conditional_incidence_df$incidence-1.96*sqrt(Conditional_incidence_df$incidence*(1-Conditional_incidence_df$incidence)/Conditional_incidence_df$residents_tot)))/norm
conf_plus<- ((Conditional_incidence_df$incidence+1.96*sqrt(Conditional_incidence_df$incidence*(1-Conditional_incidence_df$incidence)/Conditional_incidence_df$residents_tot)))/norm
Conditional_incidence_df$incidence<-Conditional_incidence_df$incidence/norm
Conditional_incidence_df$conf_minus<-conf_minus
Conditional_incidence_df$conf_plus<-conf_plus
Conditional_incidence_df[variable_y]<-round(Conditional_incidence_df[variable_y])
if (variable_x=="Maximum_air_temperature" & variable_y=="Relative_humidity"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Maximum_air_temperature,y=incidence,color=factor(Relative_humidity),fill=factor(Relative_humidity)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(1,4))+scale_x_continuous(limits=c(-5,30))
}
if (variable_x=="Maximum_air_temperature" & variable_y=="Mean_wind_speed"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Maximum_air_temperature,y=incidence,color=factor(Mean_wind_speed),fill=factor(Mean_wind_speed)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(1,4))+scale_x_continuous(limits=c(-5,30))
}
if (variable_x=="Maximum_air_temperature" & variable_y=="Mean_Precipitation"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Maximum_air_temperature,y=incidence,color=factor(Mean_Precipitation),fill=factor(Mean_Precipitation)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(1,4))+scale_x_continuous(limits=c(-5,30))
}
if (variable_x=="Maximum_air_temperature" & variable_y=="daylength"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Maximum_air_temperature,y=incidence,color=factor(daylength),fill=factor(daylength)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(1,4))+scale_x_continuous(limits=c(-5,30))
}
if (variable_x=="Minimum_air_temperature" & variable_y=="Relative_humidity"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Minimum_air_temperature,y=incidence,color=factor(Relative_humidity),fill=factor(Relative_humidity)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(1,4))+scale_x_continuous(limits=c(-10,25))
}
if (variable_x=="Minimum_air_temperature" & variable_y=="Mean_wind_speed"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Minimum_air_temperature,y=incidence,color=factor(Mean_wind_speed),fill=factor(Mean_wind_speed)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(1,4))+scale_x_continuous(limits=c(-10,25))
}
if (variable_x=="Minimum_air_temperature" & variable_y=="Mean_Precipitation"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Minimum_air_temperature,y=incidence,color=factor(Mean_Precipitation),fill=factor(Mean_Precipitation)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(1,4))+scale_x_continuous(limits=c(-10,25))
}
if (variable_x=="Minimum_air_temperature" & variable_y=="daylength"){
Conditional_incidence_plot <-
ggplot(Conditional_incidence_df,aes(x=Minimum_air_temperature,y=incidence,color=factor(daylength),fill=factor(daylength)))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_y_continuous(limits=c(1,4))+scale_x_continuous(limits=c(-10,25))
}
Conditional_incidence_plot <- Conditional_incidence_plot+theme_bw(20)
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_colour_discrete(name =variable_y_char)
Conditional_incidence_plot <- Conditional_incidence_plot+ylab("Conditional Incidence of Campylobacter Cases ")
Conditional_incidence_plot <- Conditional_incidence_plot+xlab(variable_x_char)
labelling<-c(round(as.numeric(unique(Conditional_incidence_df[variable_y])[,1])))
n_labelling<-length(labelling)
for (j in c(1:(n_labelling-1))) {
labelling_char[j]<-paste(as.character(labelling[j]), "-", as.character(labelling[j+1]) )
}
labelling_char[n_labelling]<-paste(">",as.character(labelling[n_labelling]))
Conditional_incidence_plot <- Conditional_incidence_plot+ scale_fill_discrete(name =variable_y_char, labels=labelling_char)
Conditional_incidence_plot <- Conditional_incidence_plot+ geom_point(size=3.5)+ guides(colour="none") # guides(colour="none")
Conditional_incidence_plot <- Conditional_incidence_plot+ geom_line(size=1)
Conditional_incidence_plot <- Conditional_incidence_plot+ geom_ribbon(aes(ymin=conf_minus, ymax=conf_plus),alpha=0.35)
Conditional_incidence_plot <- Conditional_incidence_plot+
theme(legend.position= c(0.25,0.75),legend.title = element_text( size = 11),
legend.text = element_text( size = 10),legend.background = element_blank(),
legend.key=element_rect(colour=NA))
Conditional_incidence_plot <- Conditional_incidence_plot+ theme(axis.title.x =element_text( colour="#990000", size=15))
Conditional_incidence_plot <- Conditional_incidence_plot+ theme(axis.title.y =element_text( colour="#990000", size=15))
Conditional_incidence_plot <- Conditional_incidence_plot+ theme(axis.title.x =element_text(size=15))
Conditional_incidence_plot <- Conditional_incidence_plot+ theme(axis.title.y =element_text(size=15))
Conditional_incidence_plot
file_name<-paste("../Graphs/Campylobacter_",variable_x,"_",variable_y,"_",time_lag_char,"_quantile.tiff", sep = "")
tiff(filename = file_name,width = 17.35, height = 17.35, units = "cm", pointsize = 12, res = 1200,compression = "lzw",antialias="default")
print(Conditional_incidence_plot)
dev.off()
})
}
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