library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
22605 <- sunrise.set(53.5508168,9.886819, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 22605$sunrise
sunset <- 22605$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
22605["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
22605["ss"] <- as.POSIXct(sunset, format = "%H:%M")
22605["timestamp"] <- align.time(22605$sunrise, 60*10)
22605 <- 22605[c("timestamp", "sr", "ss")]
locsrss <- ggplot(22605, aes(x=22605$timestamp)) + geom_line(aes(y=22605$sr)) + geom_line(aes(y=22605$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 22605 2024", x = "Datum", y = "Zeit")
pdf("22605_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="22605_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
22605["Sonnenaufgang"] <- strftime(22605$sr, format="%H:%M")
22605["Sonnenuntergang"] <- strftime(22605$ss, format="%H:%M")
write.table(22605, file="22605_SaSu.csv", dec=',', sep=';', row.names=FALSE)