library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Achtel <- sunrise.set(49.5724213,11.5826169, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Achtel$sunrise
sunset <- Achtel$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Achtel["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Achtel["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Achtel["timestamp"] <- align.time(Achtel$sunrise, 60*10)
Achtel <- Achtel[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Achtel, aes(x=Achtel$timestamp)) + geom_line(aes(y=Achtel$sr)) + geom_line(aes(y=Achtel$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Achtel 2023", x = "Datum", y = "Zeit")
pdf("Achtel_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Achtel_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Achtel["Sonnenaufgang"] <- strftime(Achtel$sr, format="%H:%M")
Achtel["Sonnenuntergang"] <- strftime(Achtel$ss, format="%H:%M")
write.table(Achtel, file="Achtel_SaSu.csv", dec=',', sep=';', row.names=FALSE)