library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
AT_4672 <- sunrise.set(48.1330883,13.799184700000069, "2023/01/01", timezone="MET", num.days=370)
sunrise <- AT_4672$sunrise
sunset <- AT_4672$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
AT_4672["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
AT_4672["ss"] <- as.POSIXct(sunset, format = "%H:%M")
AT_4672["timestamp"] <- align.time(AT_4672$sunrise, 60*10)
AT_4672 <- AT_4672[c("timestamp", "sr", "ss")]
locsrss <- ggplot(AT_4672, aes(x=AT_4672$timestamp)) + geom_line(aes(y=AT_4672$sr)) + geom_line(aes(y=AT_4672$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - AT_4672 2023", x = "Datum", y = "Zeit")
pdf("AT_4672_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="AT_4672_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
AT_4672["Sonnenaufgang"] <- strftime(AT_4672$sr, format="%H:%M")
AT_4672["Sonnenuntergang"] <- strftime(AT_4672$ss, format="%H:%M")
write.table(AT_4672, file="AT_4672_SaSu.csv", dec=',', sep=';', row.names=FALSE)