library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
72766_Reutlingen <- sunrise.set(48.5245228,9.2345127, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 72766_Reutlingen$sunrise
sunset <- 72766_Reutlingen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
72766_Reutlingen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
72766_Reutlingen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
72766_Reutlingen["timestamp"] <- align.time(72766_Reutlingen$sunrise, 60*10)
72766_Reutlingen <- 72766_Reutlingen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(72766_Reutlingen, aes(x=72766_Reutlingen$timestamp)) + geom_line(aes(y=72766_Reutlingen$sr)) + geom_line(aes(y=72766_Reutlingen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 72766_Reutlingen 2023", x = "Datum", y = "Zeit")
pdf("72766_Reutlingen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="72766_Reutlingen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
72766_Reutlingen["Sonnenaufgang"] <- strftime(72766_Reutlingen$sr, format="%H:%M")
72766_Reutlingen["Sonnenuntergang"] <- strftime(72766_Reutlingen$ss, format="%H:%M")
write.table(72766_Reutlingen, file="72766_Reutlingen_SaSu.csv", dec=',', sep=';', row.names=FALSE)