library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
84367_Tann <- sunrise.set(48.3147593,12.88904309999998, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 84367_Tann$sunrise
sunset <- 84367_Tann$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
84367_Tann["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
84367_Tann["ss"] <- as.POSIXct(sunset, format = "%H:%M")
84367_Tann["timestamp"] <- align.time(84367_Tann$sunrise, 60*10)
84367_Tann <- 84367_Tann[c("timestamp", "sr", "ss")]
locsrss <- ggplot(84367_Tann, aes(x=84367_Tann$timestamp)) + geom_line(aes(y=84367_Tann$sr)) + geom_line(aes(y=84367_Tann$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 84367_Tann 2024", x = "Datum", y = "Zeit")
pdf("84367_Tann_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="84367_Tann_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
84367_Tann["Sonnenaufgang"] <- strftime(84367_Tann$sr, format="%H:%M")
84367_Tann["Sonnenuntergang"] <- strftime(84367_Tann$ss, format="%H:%M")
write.table(84367_Tann, file="84367_Tann_SaSu.csv", dec=',', sep=';', row.names=FALSE)