library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Appenzell <- sunrise.set(47.3308044,9.408706299999949, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Appenzell$sunrise
sunset <- Appenzell$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Appenzell["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Appenzell["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Appenzell["timestamp"] <- align.time(Appenzell$sunrise, 60*10)
Appenzell <- Appenzell[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Appenzell, aes(x=Appenzell$timestamp)) + geom_line(aes(y=Appenzell$sr)) + geom_line(aes(y=Appenzell$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Appenzell 2023", x = "Datum", y = "Zeit")
pdf("Appenzell_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Appenzell_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Appenzell["Sonnenaufgang"] <- strftime(Appenzell$sr, format="%H:%M")
Appenzell["Sonnenuntergang"] <- strftime(Appenzell$ss, format="%H:%M")
write.table(Appenzell, file="Appenzell_SaSu.csv", dec=',', sep=';', row.names=FALSE)