library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
A_8580 <- sunrise.set(47.05050504599396,15.078864097595215, "2024/01/01", timezone="MET", num.days=370)
sunrise <- A_8580$sunrise
sunset <- A_8580$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
A_8580["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
A_8580["ss"] <- as.POSIXct(sunset, format = "%H:%M")
A_8580["timestamp"] <- align.time(A_8580$sunrise, 60*10)
A_8580 <- A_8580[c("timestamp", "sr", "ss")]
locsrss <- ggplot(A_8580, aes(x=A_8580$timestamp)) + geom_line(aes(y=A_8580$sr)) + geom_line(aes(y=A_8580$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - A_8580 2024", x = "Datum", y = "Zeit")
pdf("A_8580_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="A_8580_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
A_8580["Sonnenaufgang"] <- strftime(A_8580$sr, format="%H:%M")
A_8580["Sonnenuntergang"] <- strftime(A_8580$ss, format="%H:%M")
write.table(A_8580, file="A_8580_SaSu.csv", dec=',', sep=';', row.names=FALSE)