library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Eislingen <- sunrise.set(48.70003,9.706552, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Eislingen$sunrise
sunset <- Eislingen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Eislingen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Eislingen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Eislingen["timestamp"] <- align.time(Eislingen$sunrise, 60*10)
Eislingen <- Eislingen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Eislingen, aes(x=Eislingen$timestamp)) + geom_line(aes(y=Eislingen$sr)) + geom_line(aes(y=Eislingen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Eislingen 2024", x = "Datum", y = "Zeit")
pdf("Eislingen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Eislingen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Eislingen["Sonnenaufgang"] <- strftime(Eislingen$sr, format="%H:%M")
Eislingen["Sonnenuntergang"] <- strftime(Eislingen$ss, format="%H:%M")
write.table(Eislingen, file="Eislingen_SaSu.csv", dec=',', sep=';', row.names=FALSE)