library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Brocken <- sunrise.set(51.8005556,10.6172222, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Brocken$sunrise
sunset <- Brocken$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Brocken["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Brocken["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Brocken["timestamp"] <- align.time(Brocken$sunrise, 60*10)
Brocken <- Brocken[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Brocken, aes(x=Brocken$timestamp)) + geom_line(aes(y=Brocken$sr)) + geom_line(aes(y=Brocken$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Brocken 2024", x = "Datum", y = "Zeit")
pdf("Brocken_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Brocken_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Brocken["Sonnenaufgang"] <- strftime(Brocken$sr, format="%H:%M")
Brocken["Sonnenuntergang"] <- strftime(Brocken$ss, format="%H:%M")
write.table(Brocken, file="Brocken_SaSu.csv", dec=',', sep=';', row.names=FALSE)