library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
16303 <- sunrise.set(53.0718571,14.286279599999943, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 16303$sunrise
sunset <- 16303$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
16303["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
16303["ss"] <- as.POSIXct(sunset, format = "%H:%M")
16303["timestamp"] <- align.time(16303$sunrise, 60*10)
16303 <- 16303[c("timestamp", "sr", "ss")]
locsrss <- ggplot(16303, aes(x=16303$timestamp)) + geom_line(aes(y=16303$sr)) + geom_line(aes(y=16303$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 16303 2024", x = "Datum", y = "Zeit")
pdf("16303_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="16303_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
16303["Sonnenaufgang"] <- strftime(16303$sr, format="%H:%M")
16303["Sonnenuntergang"] <- strftime(16303$ss, format="%H:%M")
write.table(16303, file="16303_SaSu.csv", dec=',', sep=';', row.names=FALSE)