library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
01307 <- sunrise.set(51.0566797,13.7688263, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 01307$sunrise
sunset <- 01307$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
01307["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
01307["ss"] <- as.POSIXct(sunset, format = "%H:%M")
01307["timestamp"] <- align.time(01307$sunrise, 60*10)
01307 <- 01307[c("timestamp", "sr", "ss")]
locsrss <- ggplot(01307, aes(x=01307$timestamp)) + geom_line(aes(y=01307$sr)) + geom_line(aes(y=01307$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 01307 2024", x = "Datum", y = "Zeit")
pdf("01307_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="01307_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
01307["Sonnenaufgang"] <- strftime(01307$sr, format="%H:%M")
01307["Sonnenuntergang"] <- strftime(01307$ss, format="%H:%M")
write.table(01307, file="01307_SaSu.csv", dec=',', sep=';', row.names=FALSE)