library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Dornbirn <- sunrise.set(47.4124,9.74378999999999, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Dornbirn$sunrise
sunset <- Dornbirn$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Dornbirn["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Dornbirn["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Dornbirn["timestamp"] <- align.time(Dornbirn$sunrise, 60*10)
Dornbirn <- Dornbirn[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Dornbirn, aes(x=Dornbirn$timestamp)) + geom_line(aes(y=Dornbirn$sr)) + geom_line(aes(y=Dornbirn$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Dornbirn 2023", x = "Datum", y = "Zeit")
pdf("Dornbirn_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Dornbirn_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Dornbirn["Sonnenaufgang"] <- strftime(Dornbirn$sr, format="%H:%M")
Dornbirn["Sonnenuntergang"] <- strftime(Dornbirn$ss, format="%H:%M")
write.table(Dornbirn, file="Dornbirn_SaSu.csv", dec=',', sep=';', row.names=FALSE)