library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Dornstadt <- sunrise.set(48.4654295,9.943146500000012, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Dornstadt$sunrise
sunset <- Dornstadt$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Dornstadt["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Dornstadt["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Dornstadt["timestamp"] <- align.time(Dornstadt$sunrise, 60*10)
Dornstadt <- Dornstadt[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Dornstadt, aes(x=Dornstadt$timestamp)) + geom_line(aes(y=Dornstadt$sr)) + geom_line(aes(y=Dornstadt$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Dornstadt 2024", x = "Datum", y = "Zeit")
pdf("Dornstadt_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Dornstadt_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Dornstadt["Sonnenaufgang"] <- strftime(Dornstadt$sr, format="%H:%M")
Dornstadt["Sonnenuntergang"] <- strftime(Dornstadt$ss, format="%H:%M")
write.table(Dornstadt, file="Dornstadt_SaSu.csv", dec=',', sep=';', row.names=FALSE)