library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
44267 <- sunrise.set(51.4578808,7.5261488, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 44267$sunrise
sunset <- 44267$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
44267["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
44267["ss"] <- as.POSIXct(sunset, format = "%H:%M")
44267["timestamp"] <- align.time(44267$sunrise, 60*10)
44267 <- 44267[c("timestamp", "sr", "ss")]
locsrss <- ggplot(44267, aes(x=44267$timestamp)) + geom_line(aes(y=44267$sr)) + geom_line(aes(y=44267$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 44267 2023", x = "Datum", y = "Zeit")
pdf("44267_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="44267_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
44267["Sonnenaufgang"] <- strftime(44267$sr, format="%H:%M")
44267["Sonnenuntergang"] <- strftime(44267$ss, format="%H:%M")
write.table(44267, file="44267_SaSu.csv", dec=',', sep=';', row.names=FALSE)