library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Chiemsee <- sunrise.set(47.8709042,12.453737499999988, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Chiemsee$sunrise
sunset <- Chiemsee$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Chiemsee["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Chiemsee["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Chiemsee["timestamp"] <- align.time(Chiemsee$sunrise, 60*10)
Chiemsee <- Chiemsee[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Chiemsee, aes(x=Chiemsee$timestamp)) + geom_line(aes(y=Chiemsee$sr)) + geom_line(aes(y=Chiemsee$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Chiemsee 2023", x = "Datum", y = "Zeit")
pdf("Chiemsee_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Chiemsee_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Chiemsee["Sonnenaufgang"] <- strftime(Chiemsee$sr, format="%H:%M")
Chiemsee["Sonnenuntergang"] <- strftime(Chiemsee$ss, format="%H:%M")
write.table(Chiemsee, file="Chiemsee_SaSu.csv", dec=',', sep=';', row.names=FALSE)