library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Bozen <- sunrise.set(46.47,11.25, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Bozen$sunrise
sunset <- Bozen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Bozen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Bozen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Bozen["timestamp"] <- align.time(Bozen$sunrise, 60*10)
Bozen <- Bozen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Bozen, aes(x=Bozen$timestamp)) + geom_line(aes(y=Bozen$sr)) + geom_line(aes(y=Bozen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Bozen 2023", x = "Datum", y = "Zeit")
pdf("Bozen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Bozen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Bozen["Sonnenaufgang"] <- strftime(Bozen$sr, format="%H:%M")
Bozen["Sonnenuntergang"] <- strftime(Bozen$ss, format="%H:%M")
write.table(Bozen, file="Bozen_SaSu.csv", dec=',', sep=';', row.names=FALSE)