library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Binenwalde <- sunrise.set(53.0538642,12.7972244, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Binenwalde$sunrise
sunset <- Binenwalde$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Binenwalde["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Binenwalde["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Binenwalde["timestamp"] <- align.time(Binenwalde$sunrise, 60*10)
Binenwalde <- Binenwalde[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Binenwalde, aes(x=Binenwalde$timestamp)) + geom_line(aes(y=Binenwalde$sr)) + geom_line(aes(y=Binenwalde$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Binenwalde 2023", x = "Datum", y = "Zeit")
pdf("Binenwalde_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Binenwalde_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Binenwalde["Sonnenaufgang"] <- strftime(Binenwalde$sr, format="%H:%M")
Binenwalde["Sonnenuntergang"] <- strftime(Binenwalde$ss, format="%H:%M")
write.table(Binenwalde, file="Binenwalde_SaSu.csv", dec=',', sep=';', row.names=FALSE)