library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Euskirchen <- sunrise.set(50.6574392,6.7899945, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Euskirchen$sunrise
sunset <- Euskirchen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Euskirchen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Euskirchen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Euskirchen["timestamp"] <- align.time(Euskirchen$sunrise, 60*10)
Euskirchen <- Euskirchen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Euskirchen, aes(x=Euskirchen$timestamp)) + geom_line(aes(y=Euskirchen$sr)) + geom_line(aes(y=Euskirchen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Euskirchen 2023", x = "Datum", y = "Zeit")
pdf("Euskirchen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Euskirchen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Euskirchen["Sonnenaufgang"] <- strftime(Euskirchen$sr, format="%H:%M")
Euskirchen["Sonnenuntergang"] <- strftime(Euskirchen$ss, format="%H:%M")
write.table(Euskirchen, file="Euskirchen_SaSu.csv", dec=',', sep=';', row.names=FALSE)