library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Agde <- sunrise.set(43.28820468161824,3.449473825720247, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Agde$sunrise
sunset <- Agde$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Agde["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Agde["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Agde["timestamp"] <- align.time(Agde$sunrise, 60*10)
Agde <- Agde[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Agde, aes(x=Agde$timestamp)) + geom_line(aes(y=Agde$sr)) + geom_line(aes(y=Agde$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Agde 2024", x = "Datum", y = "Zeit")
pdf("Agde_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Agde_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Agde["Sonnenaufgang"] <- strftime(Agde$sr, format="%H:%M")
Agde["Sonnenuntergang"] <- strftime(Agde$ss, format="%H:%M")
write.table(Agde, file="Agde_SaSu.csv", dec=',', sep=';', row.names=FALSE)