library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Auhagen <- sunrise.set(52.3936165,9.284018199999991, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Auhagen$sunrise
sunset <- Auhagen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Auhagen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Auhagen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Auhagen["timestamp"] <- align.time(Auhagen$sunrise, 60*10)
Auhagen <- Auhagen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Auhagen, aes(x=Auhagen$timestamp)) + geom_line(aes(y=Auhagen$sr)) + geom_line(aes(y=Auhagen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Auhagen 2024", x = "Datum", y = "Zeit")
pdf("Auhagen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Auhagen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Auhagen["Sonnenaufgang"] <- strftime(Auhagen$sr, format="%H:%M")
Auhagen["Sonnenuntergang"] <- strftime(Auhagen$ss, format="%H:%M")
write.table(Auhagen, file="Auhagen_SaSu.csv", dec=',', sep=';', row.names=FALSE)