library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
De_Elmstein_ <- sunrise.set(49.34846856026764,7.9388362280640195, "2023/01/01", timezone="MET", num.days=370)
sunrise <- De_Elmstein_$sunrise
sunset <- De_Elmstein_$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
De_Elmstein_["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
De_Elmstein_["ss"] <- as.POSIXct(sunset, format = "%H:%M")
De_Elmstein_["timestamp"] <- align.time(De_Elmstein_$sunrise, 60*10)
De_Elmstein_ <- De_Elmstein_[c("timestamp", "sr", "ss")]
locsrss <- ggplot(De_Elmstein_, aes(x=De_Elmstein_$timestamp)) + geom_line(aes(y=De_Elmstein_$sr)) + geom_line(aes(y=De_Elmstein_$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - De_Elmstein_ 2023", x = "Datum", y = "Zeit")
pdf("De_Elmstein__SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="De_Elmstein__SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
De_Elmstein_["Sonnenaufgang"] <- strftime(De_Elmstein_$sr, format="%H:%M")
De_Elmstein_["Sonnenuntergang"] <- strftime(De_Elmstein_$ss, format="%H:%M")
write.table(De_Elmstein_, file="De_Elmstein__SaSu.csv", dec=',', sep=';', row.names=FALSE)