library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Bolzano <- sunrise.set(46.4967153,11.3580048, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Bolzano$sunrise
sunset <- Bolzano$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Bolzano["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Bolzano["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Bolzano["timestamp"] <- align.time(Bolzano$sunrise, 60*10)
Bolzano <- Bolzano[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Bolzano, aes(x=Bolzano$timestamp)) + geom_line(aes(y=Bolzano$sr)) + geom_line(aes(y=Bolzano$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Bolzano 2024", x = "Datum", y = "Zeit")
pdf("Bolzano_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Bolzano_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Bolzano["Sonnenaufgang"] <- strftime(Bolzano$sr, format="%H:%M")
Bolzano["Sonnenuntergang"] <- strftime(Bolzano$ss, format="%H:%M")
write.table(Bolzano, file="Bolzano_SaSu.csv", dec=',', sep=';', row.names=FALSE)