library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Dahn <- sunrise.set(49.150843,7.778506, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Dahn$sunrise
sunset <- Dahn$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Dahn["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Dahn["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Dahn["timestamp"] <- align.time(Dahn$sunrise, 60*10)
Dahn <- Dahn[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Dahn, aes(x=Dahn$timestamp)) + geom_line(aes(y=Dahn$sr)) + geom_line(aes(y=Dahn$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Dahn 2024", x = "Datum", y = "Zeit")
pdf("Dahn_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Dahn_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Dahn["Sonnenaufgang"] <- strftime(Dahn$sr, format="%H:%M")
Dahn["Sonnenuntergang"] <- strftime(Dahn$ss, format="%H:%M")
write.table(Dahn, file="Dahn_SaSu.csv", dec=',', sep=';', row.names=FALSE)