library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Backnang <- sunrise.set(48.97771455,9.436181299999977, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Backnang$sunrise
sunset <- Backnang$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Backnang["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Backnang["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Backnang["timestamp"] <- align.time(Backnang$sunrise, 60*10)
Backnang <- Backnang[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Backnang, aes(x=Backnang$timestamp)) + geom_line(aes(y=Backnang$sr)) + geom_line(aes(y=Backnang$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Backnang 2024", x = "Datum", y = "Zeit")
pdf("Backnang_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Backnang_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Backnang["Sonnenaufgang"] <- strftime(Backnang$sr, format="%H:%M")
Backnang["Sonnenuntergang"] <- strftime(Backnang$ss, format="%H:%M")
write.table(Backnang, file="Backnang_SaSu.csv", dec=',', sep=';', row.names=FALSE)