library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Böbingen_ <- sunrise.set(48.8187469,9.923107500000015, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Böbingen_$sunrise
sunset <- Böbingen_$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Böbingen_["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Böbingen_["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Böbingen_["timestamp"] <- align.time(Böbingen_$sunrise, 60*10)
Böbingen_ <- Böbingen_[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Böbingen_, aes(x=Böbingen_$timestamp)) + geom_line(aes(y=Böbingen_$sr)) + geom_line(aes(y=Böbingen_$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Böbingen_ 2024", x = "Datum", y = "Zeit")
pdf("Böbingen__SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Böbingen__SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Böbingen_["Sonnenaufgang"] <- strftime(Böbingen_$sr, format="%H:%M")
Böbingen_["Sonnenuntergang"] <- strftime(Böbingen_$ss, format="%H:%M")
write.table(Böbingen_, file="Böbingen__SaSu.csv", dec=',', sep=';', row.names=FALSE)