library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Cala_Milor <- sunrise.set(39.5898592,3.3851131, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Cala_Milor$sunrise
sunset <- Cala_Milor$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Cala_Milor["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Cala_Milor["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Cala_Milor["timestamp"] <- align.time(Cala_Milor$sunrise, 60*10)
Cala_Milor <- Cala_Milor[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Cala_Milor, aes(x=Cala_Milor$timestamp)) + geom_line(aes(y=Cala_Milor$sr)) + geom_line(aes(y=Cala_Milor$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Cala_Milor 2024", x = "Datum", y = "Zeit")
pdf("Cala_Milor_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Cala_Milor_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Cala_Milor["Sonnenaufgang"] <- strftime(Cala_Milor$sr, format="%H:%M")
Cala_Milor["Sonnenuntergang"] <- strftime(Cala_Milor$ss, format="%H:%M")
write.table(Cala_Milor, file="Cala_Milor_SaSu.csv", dec=',', sep=';', row.names=FALSE)