library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
AT_8072 <- sunrise.set(46.97304923353434,15.498790740966797, "2024/01/01", timezone="MET", num.days=370)
sunrise <- AT_8072$sunrise
sunset <- AT_8072$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
AT_8072["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
AT_8072["ss"] <- as.POSIXct(sunset, format = "%H:%M")
AT_8072["timestamp"] <- align.time(AT_8072$sunrise, 60*10)
AT_8072 <- AT_8072[c("timestamp", "sr", "ss")]
locsrss <- ggplot(AT_8072, aes(x=AT_8072$timestamp)) + geom_line(aes(y=AT_8072$sr)) + geom_line(aes(y=AT_8072$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - AT_8072 2024", x = "Datum", y = "Zeit")
pdf("AT_8072_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="AT_8072_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
AT_8072["Sonnenaufgang"] <- strftime(AT_8072$sr, format="%H:%M")
AT_8072["Sonnenuntergang"] <- strftime(AT_8072$ss, format="%H:%M")
write.table(AT_8072, file="AT_8072_SaSu.csv", dec=',', sep=';', row.names=FALSE)