library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
37359 <- sunrise.set(51.2659733,10.249725, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 37359$sunrise
sunset <- 37359$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
37359["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
37359["ss"] <- as.POSIXct(sunset, format = "%H:%M")
37359["timestamp"] <- align.time(37359$sunrise, 60*10)
37359 <- 37359[c("timestamp", "sr", "ss")]
locsrss <- ggplot(37359, aes(x=37359$timestamp)) + geom_line(aes(y=37359$sr)) + geom_line(aes(y=37359$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 37359 2023", x = "Datum", y = "Zeit")
pdf("37359_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="37359_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
37359["Sonnenaufgang"] <- strftime(37359$sr, format="%H:%M")
37359["Sonnenuntergang"] <- strftime(37359$ss, format="%H:%M")
write.table(37359, file="37359_SaSu.csv", dec=',', sep=';', row.names=FALSE)