library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Egeln <- sunrise.set(51.9411082,11.4281059, "2022/01/01", timezone="MET", num.days=370)
sunrise <- Egeln$sunrise
sunset <- Egeln$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Egeln["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Egeln["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Egeln["timestamp"] <- align.time(Egeln$sunrise, 60*10)
Egeln <- Egeln[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Egeln, aes(x=Egeln$timestamp)) + geom_line(aes(y=Egeln$sr)) + geom_line(aes(y=Egeln$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Egeln 2022", x = "Datum", y = "Zeit")
pdf("Egeln_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Egeln_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Egeln["Sonnenaufgang"] <- strftime(Egeln$sr, format="%H:%M")
Egeln["Sonnenuntergang"] <- strftime(Egeln$ss, format="%H:%M")
write.table(Egeln, file="Egeln_SaSu.csv", dec=',', sep=';', row.names=FALSE)