library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Alcudia <- sunrise.set(39.8532672,3.1240238999999974, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Alcudia$sunrise
sunset <- Alcudia$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Alcudia["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Alcudia["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Alcudia["timestamp"] <- align.time(Alcudia$sunrise, 60*10)
Alcudia <- Alcudia[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Alcudia, aes(x=Alcudia$timestamp)) + geom_line(aes(y=Alcudia$sr)) + geom_line(aes(y=Alcudia$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Alcudia 2024", x = "Datum", y = "Zeit")
pdf("Alcudia_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Alcudia_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Alcudia["Sonnenaufgang"] <- strftime(Alcudia$sr, format="%H:%M")
Alcudia["Sonnenuntergang"] <- strftime(Alcudia$ss, format="%H:%M")
write.table(Alcudia, file="Alcudia_SaSu.csv", dec=',', sep=';', row.names=FALSE)