library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
44879 <- sunrise.set(51.4284308,7.1544452, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 44879$sunrise
sunset <- 44879$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
44879["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
44879["ss"] <- as.POSIXct(sunset, format = "%H:%M")
44879["timestamp"] <- align.time(44879$sunrise, 60*10)
44879 <- 44879[c("timestamp", "sr", "ss")]
locsrss <- ggplot(44879, aes(x=44879$timestamp)) + geom_line(aes(y=44879$sr)) + geom_line(aes(y=44879$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 44879 2023", x = "Datum", y = "Zeit")
pdf("44879_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="44879_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
44879["Sonnenaufgang"] <- strftime(44879$sr, format="%H:%M")
44879["Sonnenuntergang"] <- strftime(44879$ss, format="%H:%M")
write.table(44879, file="44879_SaSu.csv", dec=',', sep=';', row.names=FALSE)