library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Erkelenz <- sunrise.set(51.0784539,6.315907, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Erkelenz$sunrise
sunset <- Erkelenz$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Erkelenz["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Erkelenz["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Erkelenz["timestamp"] <- align.time(Erkelenz$sunrise, 60*10)
Erkelenz <- Erkelenz[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Erkelenz, aes(x=Erkelenz$timestamp)) + geom_line(aes(y=Erkelenz$sr)) + geom_line(aes(y=Erkelenz$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Erkelenz 2024", x = "Datum", y = "Zeit")
pdf("Erkelenz_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Erkelenz_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Erkelenz["Sonnenaufgang"] <- strftime(Erkelenz$sr, format="%H:%M")
Erkelenz["Sonnenuntergang"] <- strftime(Erkelenz$ss, format="%H:%M")
write.table(Erkelenz, file="Erkelenz_SaSu.csv", dec=',', sep=';', row.names=FALSE)