library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Flekke <- sunrise.set(61.31751289999999,5.361911700000064, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Flekke$sunrise
sunset <- Flekke$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Flekke["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Flekke["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Flekke["timestamp"] <- align.time(Flekke$sunrise, 60*10)
Flekke <- Flekke[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Flekke, aes(x=Flekke$timestamp)) + geom_line(aes(y=Flekke$sr)) + geom_line(aes(y=Flekke$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Flekke 2024", x = "Datum", y = "Zeit")
pdf("Flekke_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Flekke_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Flekke["Sonnenaufgang"] <- strftime(Flekke$sr, format="%H:%M")
Flekke["Sonnenuntergang"] <- strftime(Flekke$ss, format="%H:%M")
write.table(Flekke, file="Flekke_SaSu.csv", dec=',', sep=';', row.names=FALSE)