library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Aalen <- sunrise.set(48.8366887,10.097116300000039, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Aalen$sunrise
sunset <- Aalen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Aalen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Aalen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Aalen["timestamp"] <- align.time(Aalen$sunrise, 60*10)
Aalen <- Aalen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Aalen, aes(x=Aalen$timestamp)) + geom_line(aes(y=Aalen$sr)) + geom_line(aes(y=Aalen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Aalen 2024", x = "Datum", y = "Zeit")
pdf("Aalen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Aalen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Aalen["Sonnenaufgang"] <- strftime(Aalen$sr, format="%H:%M")
Aalen["Sonnenuntergang"] <- strftime(Aalen$ss, format="%H:%M")
write.table(Aalen, file="Aalen_SaSu.csv", dec=',', sep=';', row.names=FALSE)