library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Damp <- sunrise.set(54.5811595,10.0181568, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Damp$sunrise
sunset <- Damp$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Damp["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Damp["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Damp["timestamp"] <- align.time(Damp$sunrise, 60*10)
Damp <- Damp[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Damp, aes(x=Damp$timestamp)) + geom_line(aes(y=Damp$sr)) + geom_line(aes(y=Damp$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Damp 2024", x = "Datum", y = "Zeit")
pdf("Damp_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Damp_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Damp["Sonnenaufgang"] <- strftime(Damp$sr, format="%H:%M")
Damp["Sonnenuntergang"] <- strftime(Damp$ss, format="%H:%M")
write.table(Damp, file="Damp_SaSu.csv", dec=',', sep=';', row.names=FALSE)