library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Bodenkirchen <- sunrise.set(48.3843848,12.3823856, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Bodenkirchen$sunrise
sunset <- Bodenkirchen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Bodenkirchen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Bodenkirchen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Bodenkirchen["timestamp"] <- align.time(Bodenkirchen$sunrise, 60*10)
Bodenkirchen <- Bodenkirchen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Bodenkirchen, aes(x=Bodenkirchen$timestamp)) + geom_line(aes(y=Bodenkirchen$sr)) + geom_line(aes(y=Bodenkirchen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Bodenkirchen 2024", x = "Datum", y = "Zeit")
pdf("Bodenkirchen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Bodenkirchen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Bodenkirchen["Sonnenaufgang"] <- strftime(Bodenkirchen$sr, format="%H:%M")
Bodenkirchen["Sonnenuntergang"] <- strftime(Bodenkirchen$ss, format="%H:%M")
write.table(Bodenkirchen, file="Bodenkirchen_SaSu.csv", dec=',', sep=';', row.names=FALSE)