library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Altenberge <- sunrise.set(52.0468114,7.46993150000003, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Altenberge$sunrise
sunset <- Altenberge$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Altenberge["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Altenberge["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Altenberge["timestamp"] <- align.time(Altenberge$sunrise, 60*10)
Altenberge <- Altenberge[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Altenberge, aes(x=Altenberge$timestamp)) + geom_line(aes(y=Altenberge$sr)) + geom_line(aes(y=Altenberge$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Altenberge 2023", x = "Datum", y = "Zeit")
pdf("Altenberge_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Altenberge_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Altenberge["Sonnenaufgang"] <- strftime(Altenberge$sr, format="%H:%M")
Altenberge["Sonnenuntergang"] <- strftime(Altenberge$ss, format="%H:%M")
write.table(Altenberge, file="Altenberge_SaSu.csv", dec=',', sep=';', row.names=FALSE)