library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Brannenburg_ <- sunrise.set(47.742414,12.104085199999986, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Brannenburg_$sunrise
sunset <- Brannenburg_$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Brannenburg_["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Brannenburg_["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Brannenburg_["timestamp"] <- align.time(Brannenburg_$sunrise, 60*10)
Brannenburg_ <- Brannenburg_[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Brannenburg_, aes(x=Brannenburg_$timestamp)) + geom_line(aes(y=Brannenburg_$sr)) + geom_line(aes(y=Brannenburg_$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Brannenburg_ 2023", x = "Datum", y = "Zeit")
pdf("Brannenburg__SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Brannenburg__SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Brannenburg_["Sonnenaufgang"] <- strftime(Brannenburg_$sr, format="%H:%M")
Brannenburg_["Sonnenuntergang"] <- strftime(Brannenburg_$ss, format="%H:%M")
write.table(Brannenburg_, file="Brannenburg__SaSu.csv", dec=',', sep=';', row.names=FALSE)