library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Ansbach <- sunrise.set(49.3004246,10.57193570000004, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Ansbach$sunrise
sunset <- Ansbach$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Ansbach["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Ansbach["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Ansbach["timestamp"] <- align.time(Ansbach$sunrise, 60*10)
Ansbach <- Ansbach[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Ansbach, aes(x=Ansbach$timestamp)) + geom_line(aes(y=Ansbach$sr)) + geom_line(aes(y=Ansbach$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Ansbach 2023", x = "Datum", y = "Zeit")
pdf("Ansbach_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Ansbach_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Ansbach["Sonnenaufgang"] <- strftime(Ansbach$sr, format="%H:%M")
Ansbach["Sonnenuntergang"] <- strftime(Ansbach$ss, format="%H:%M")
write.table(Ansbach, file="Ansbach_SaSu.csv", dec=',', sep=';', row.names=FALSE)