library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Aerzen <- sunrise.set(52.0468529,9.259778, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Aerzen$sunrise
sunset <- Aerzen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Aerzen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Aerzen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Aerzen["timestamp"] <- align.time(Aerzen$sunrise, 60*10)
Aerzen <- Aerzen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Aerzen, aes(x=Aerzen$timestamp)) + geom_line(aes(y=Aerzen$sr)) + geom_line(aes(y=Aerzen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Aerzen 2024", x = "Datum", y = "Zeit")
pdf("Aerzen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Aerzen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Aerzen["Sonnenaufgang"] <- strftime(Aerzen$sr, format="%H:%M")
Aerzen["Sonnenuntergang"] <- strftime(Aerzen$ss, format="%H:%M")
write.table(Aerzen, file="Aerzen_SaSu.csv", dec=',', sep=';', row.names=FALSE)