library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
FR <- sunrise.set(48.772563,1.8154250000000047, "2024/01/01", timezone="MET", num.days=370)
sunrise <- FR$sunrise
sunset <- FR$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
FR["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
FR["ss"] <- as.POSIXct(sunset, format = "%H:%M")
FR["timestamp"] <- align.time(FR$sunrise, 60*10)
FR <- FR[c("timestamp", "sr", "ss")]
locsrss <- ggplot(FR, aes(x=FR$timestamp)) + geom_line(aes(y=FR$sr)) + geom_line(aes(y=FR$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - FR 2024", x = "Datum", y = "Zeit")
pdf("FR_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="FR_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
FR["Sonnenaufgang"] <- strftime(FR$sr, format="%H:%M")
FR["Sonnenuntergang"] <- strftime(FR$ss, format="%H:%M")
write.table(FR, file="FR_SaSu.csv", dec=',', sep=';', row.names=FALSE)