library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Flaesheim <- sunrise.set(51.7183333,7.2294444, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Flaesheim$sunrise
sunset <- Flaesheim$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Flaesheim["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Flaesheim["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Flaesheim["timestamp"] <- align.time(Flaesheim$sunrise, 60*10)
Flaesheim <- Flaesheim[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Flaesheim, aes(x=Flaesheim$timestamp)) + geom_line(aes(y=Flaesheim$sr)) + geom_line(aes(y=Flaesheim$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Flaesheim 2024", x = "Datum", y = "Zeit")
pdf("Flaesheim_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Flaesheim_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Flaesheim["Sonnenaufgang"] <- strftime(Flaesheim$sr, format="%H:%M")
Flaesheim["Sonnenuntergang"] <- strftime(Flaesheim$ss, format="%H:%M")
write.table(Flaesheim, file="Flaesheim_SaSu.csv", dec=',', sep=';', row.names=FALSE)