library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Eichst��tt <- sunrise.set(48.89125079999999,11.1899861, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Eichst��tt$sunrise
sunset <- Eichst��tt$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Eichst��tt["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Eichst��tt["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Eichst��tt["timestamp"] <- align.time(Eichst��tt$sunrise, 60*10)
Eichst��tt <- Eichst��tt[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Eichst��tt, aes(x=Eichst��tt$timestamp)) + geom_line(aes(y=Eichst��tt$sr)) + geom_line(aes(y=Eichst��tt$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Eichst��tt 2023", x = "Datum", y = "Zeit")
pdf("Eichst��tt_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Eichst��tt_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Eichst��tt["Sonnenaufgang"] <- strftime(Eichst��tt$sr, format="%H:%M")
Eichst��tt["Sonnenuntergang"] <- strftime(Eichst��tt$ss, format="%H:%M")
write.table(Eichst��tt, file="Eichst��tt_SaSu.csv", dec=',', sep=';', row.names=FALSE)