library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
22587 <- sunrise.set(53.56263141118875,9.810075664123525, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 22587$sunrise
sunset <- 22587$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
22587["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
22587["ss"] <- as.POSIXct(sunset, format = "%H:%M")
22587["timestamp"] <- align.time(22587$sunrise, 60*10)
22587 <- 22587[c("timestamp", "sr", "ss")]
locsrss <- ggplot(22587, aes(x=22587$timestamp)) + geom_line(aes(y=22587$sr)) + geom_line(aes(y=22587$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 22587 2024", x = "Datum", y = "Zeit")
pdf("22587_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="22587_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
22587["Sonnenaufgang"] <- strftime(22587$sr, format="%H:%M")
22587["Sonnenuntergang"] <- strftime(22587$ss, format="%H:%M")
write.table(22587, file="22587_SaSu.csv", dec=',', sep=';', row.names=FALSE)