library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Völkersbach <- sunrise.set(48.87057069999999,8.395163300000036, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Völkersbach$sunrise
sunset <- Völkersbach$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Völkersbach["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Völkersbach["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Völkersbach["timestamp"] <- align.time(Völkersbach$sunrise, 60*10)
Völkersbach <- Völkersbach[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Völkersbach, aes(x=Völkersbach$timestamp)) + geom_line(aes(y=Völkersbach$sr)) + geom_line(aes(y=Völkersbach$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Völkersbach 2024", x = "Datum", y = "Zeit")
pdf("Völkersbach_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Völkersbach_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Völkersbach["Sonnenaufgang"] <- strftime(Völkersbach$sr, format="%H:%M")
Völkersbach["Sonnenuntergang"] <- strftime(Völkersbach$ss, format="%H:%M")
write.table(Völkersbach, file="Völkersbach_SaSu.csv", dec=',', sep=';', row.names=FALSE)