library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
45772 <- sunrise.set(51.6895398,7.12050099999999, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 45772$sunrise
sunset <- 45772$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
45772["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
45772["ss"] <- as.POSIXct(sunset, format = "%H:%M")
45772["timestamp"] <- align.time(45772$sunrise, 60*10)
45772 <- 45772[c("timestamp", "sr", "ss")]
locsrss <- ggplot(45772, aes(x=45772$timestamp)) + geom_line(aes(y=45772$sr)) + geom_line(aes(y=45772$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 45772 2023", x = "Datum", y = "Zeit")
pdf("45772_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="45772_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
45772["Sonnenaufgang"] <- strftime(45772$sr, format="%H:%M")
45772["Sonnenuntergang"] <- strftime(45772$ss, format="%H:%M")
write.table(45772, file="45772_SaSu.csv", dec=',', sep=';', row.names=FALSE)