library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
AT_1090 <- sunrise.set(48.2253633,16.3561956, "2024/01/01", timezone="MET", num.days=370)
sunrise <- AT_1090$sunrise
sunset <- AT_1090$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
AT_1090["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
AT_1090["ss"] <- as.POSIXct(sunset, format = "%H:%M")
AT_1090["timestamp"] <- align.time(AT_1090$sunrise, 60*10)
AT_1090 <- AT_1090[c("timestamp", "sr", "ss")]
locsrss <- ggplot(AT_1090, aes(x=AT_1090$timestamp)) + geom_line(aes(y=AT_1090$sr)) + geom_line(aes(y=AT_1090$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - AT_1090 2024", x = "Datum", y = "Zeit")
pdf("AT_1090_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="AT_1090_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
AT_1090["Sonnenaufgang"] <- strftime(AT_1090$sr, format="%H:%M")
AT_1090["Sonnenuntergang"] <- strftime(AT_1090$ss, format="%H:%M")
write.table(AT_1090, file="AT_1090_SaSu.csv", dec=',', sep=';', row.names=FALSE)