library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Asperg <- sunrise.set(48.9041527,9.1400293, "2019/01/01", timezone="MET", num.days=370)
sunrise <- Asperg$sunrise
sunset <- Asperg$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Asperg["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Asperg["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Asperg["timestamp"] <- align.time(Asperg$sunrise, 60*10)
Asperg <- Asperg[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Asperg, aes(x=Asperg$timestamp)) + geom_line(aes(y=Asperg$sr)) + geom_line(aes(y=Asperg$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Asperg 2019", x = "Datum", y = "Zeit")
pdf("Asperg_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Asperg_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Asperg["Sonnenaufgang"] <- strftime(Asperg$sr, format="%H:%M")
Asperg["Sonnenuntergang"] <- strftime(Asperg$ss, format="%H:%M")
write.table(Asperg, file="Asperg_SaSu.csv", dec=',', sep=';', row.names=FALSE)