library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
25524 <- sunrise.set(53.93669670000001,9.51920389999998, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 25524$sunrise
sunset <- 25524$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
25524["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
25524["ss"] <- as.POSIXct(sunset, format = "%H:%M")
25524["timestamp"] <- align.time(25524$sunrise, 60*10)
25524 <- 25524[c("timestamp", "sr", "ss")]
locsrss <- ggplot(25524, aes(x=25524$timestamp)) + geom_line(aes(y=25524$sr)) + geom_line(aes(y=25524$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 25524 2024", x = "Datum", y = "Zeit")
pdf("25524_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="25524_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
25524["Sonnenaufgang"] <- strftime(25524$sr, format="%H:%M")
25524["Sonnenuntergang"] <- strftime(25524$ss, format="%H:%M")
write.table(25524, file="25524_SaSu.csv", dec=',', sep=';', row.names=FALSE)