library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Altenebken <- sunrise.set(51.742549461489006,8.954801559448242, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Altenebken$sunrise
sunset <- Altenebken$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Altenebken["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Altenebken["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Altenebken["timestamp"] <- align.time(Altenebken$sunrise, 60*10)
Altenebken <- Altenebken[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Altenebken, aes(x=Altenebken$timestamp)) + geom_line(aes(y=Altenebken$sr)) + geom_line(aes(y=Altenebken$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Altenebken 2024", x = "Datum", y = "Zeit")
pdf("Altenebken_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Altenebken_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Altenebken["Sonnenaufgang"] <- strftime(Altenebken$sr, format="%H:%M")
Altenebken["Sonnenuntergang"] <- strftime(Altenebken$ss, format="%H:%M")
write.table(Altenebken, file="Altenebken_SaSu.csv", dec=',', sep=';', row.names=FALSE)