library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Elsteraue <- sunrise.set(51.075,12.2180556, "2022/01/01", timezone="MET", num.days=370)
sunrise <- Elsteraue$sunrise
sunset <- Elsteraue$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Elsteraue["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Elsteraue["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Elsteraue["timestamp"] <- align.time(Elsteraue$sunrise, 60*10)
Elsteraue <- Elsteraue[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Elsteraue, aes(x=Elsteraue$timestamp)) + geom_line(aes(y=Elsteraue$sr)) + geom_line(aes(y=Elsteraue$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Elsteraue 2022", x = "Datum", y = "Zeit")
pdf("Elsteraue_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Elsteraue_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Elsteraue["Sonnenaufgang"] <- strftime(Elsteraue$sr, format="%H:%M")
Elsteraue["Sonnenuntergang"] <- strftime(Elsteraue$ss, format="%H:%M")
write.table(Elsteraue, file="Elsteraue_SaSu.csv", dec=',', sep=';', row.names=FALSE)