library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Exmouth <- sunrise.set(-21.9307242,114.1223888, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Exmouth$sunrise
sunset <- Exmouth$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Exmouth["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Exmouth["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Exmouth["timestamp"] <- align.time(Exmouth$sunrise, 60*10)
Exmouth <- Exmouth[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Exmouth, aes(x=Exmouth$timestamp)) + geom_line(aes(y=Exmouth$sr)) + geom_line(aes(y=Exmouth$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Exmouth 2023", x = "Datum", y = "Zeit")
pdf("Exmouth_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Exmouth_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Exmouth["Sonnenaufgang"] <- strftime(Exmouth$sr, format="%H:%M")
Exmouth["Sonnenuntergang"] <- strftime(Exmouth$ss, format="%H:%M")
write.table(Exmouth, file="Exmouth_SaSu.csv", dec=',', sep=';', row.names=FALSE)