library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Altenstadt <- sunrise.set(50.2877277,8.9434385, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Altenstadt$sunrise
sunset <- Altenstadt$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Altenstadt["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Altenstadt["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Altenstadt["timestamp"] <- align.time(Altenstadt$sunrise, 60*10)
Altenstadt <- Altenstadt[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Altenstadt, aes(x=Altenstadt$timestamp)) + geom_line(aes(y=Altenstadt$sr)) + geom_line(aes(y=Altenstadt$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Altenstadt 2023", x = "Datum", y = "Zeit")
pdf("Altenstadt_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Altenstadt_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Altenstadt["Sonnenaufgang"] <- strftime(Altenstadt$sr, format="%H:%M")
Altenstadt["Sonnenuntergang"] <- strftime(Altenstadt$ss, format="%H:%M")
write.table(Altenstadt, file="Altenstadt_SaSu.csv", dec=',', sep=';', row.names=FALSE)