library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
53474 <- sunrise.set(50.5347286,7.1175897, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 53474$sunrise
sunset <- 53474$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
53474["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
53474["ss"] <- as.POSIXct(sunset, format = "%H:%M")
53474["timestamp"] <- align.time(53474$sunrise, 60*10)
53474 <- 53474[c("timestamp", "sr", "ss")]
locsrss <- ggplot(53474, aes(x=53474$timestamp)) + geom_line(aes(y=53474$sr)) + geom_line(aes(y=53474$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 53474 2023", x = "Datum", y = "Zeit")
pdf("53474_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="53474_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
53474["Sonnenaufgang"] <- strftime(53474$sr, format="%H:%M")
53474["Sonnenuntergang"] <- strftime(53474$ss, format="%H:%M")
write.table(53474, file="53474_SaSu.csv", dec=',', sep=';', row.names=FALSE)