library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Dresden <- sunrise.set(51.00728782754986,13.804192543029785, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Dresden$sunrise
sunset <- Dresden$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Dresden["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Dresden["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Dresden["timestamp"] <- align.time(Dresden$sunrise, 60*10)
Dresden <- Dresden[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Dresden, aes(x=Dresden$timestamp)) + geom_line(aes(y=Dresden$sr)) + geom_line(aes(y=Dresden$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Dresden 2024", x = "Datum", y = "Zeit")
pdf("Dresden_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Dresden_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Dresden["Sonnenaufgang"] <- strftime(Dresden$sr, format="%H:%M")
Dresden["Sonnenuntergang"] <- strftime(Dresden$ss, format="%H:%M")
write.table(Dresden, file="Dresden_SaSu.csv", dec=',', sep=';', row.names=FALSE)