library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Cala_Millor <- sunrise.set(39.6054815,3.3862244, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Cala_Millor$sunrise
sunset <- Cala_Millor$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Cala_Millor["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Cala_Millor["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Cala_Millor["timestamp"] <- align.time(Cala_Millor$sunrise, 60*10)
Cala_Millor <- Cala_Millor[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Cala_Millor, aes(x=Cala_Millor$timestamp)) + geom_line(aes(y=Cala_Millor$sr)) + geom_line(aes(y=Cala_Millor$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Cala_Millor 2024", x = "Datum", y = "Zeit")
pdf("Cala_Millor_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Cala_Millor_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Cala_Millor["Sonnenaufgang"] <- strftime(Cala_Millor$sr, format="%H:%M")
Cala_Millor["Sonnenuntergang"] <- strftime(Cala_Millor$ss, format="%H:%M")
write.table(Cala_Millor, file="Cala_Millor_SaSu.csv", dec=',', sep=';', row.names=FALSE)