library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Braunfels <- sunrise.set(50.5169338,8.390898900000025, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Braunfels$sunrise
sunset <- Braunfels$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Braunfels["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Braunfels["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Braunfels["timestamp"] <- align.time(Braunfels$sunrise, 60*10)
Braunfels <- Braunfels[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Braunfels, aes(x=Braunfels$timestamp)) + geom_line(aes(y=Braunfels$sr)) + geom_line(aes(y=Braunfels$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Braunfels 2024", x = "Datum", y = "Zeit")
pdf("Braunfels_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Braunfels_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Braunfels["Sonnenaufgang"] <- strftime(Braunfels$sr, format="%H:%M")
Braunfels["Sonnenuntergang"] <- strftime(Braunfels$ss, format="%H:%M")
write.table(Braunfels, file="Braunfels_SaSu.csv", dec=',', sep=';', row.names=FALSE)