library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Eching <- sunrise.set(48.2983793,11.62120630000004, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Eching$sunrise
sunset <- Eching$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Eching["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Eching["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Eching["timestamp"] <- align.time(Eching$sunrise, 60*10)
Eching <- Eching[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Eching, aes(x=Eching$timestamp)) + geom_line(aes(y=Eching$sr)) + geom_line(aes(y=Eching$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Eching 2024", x = "Datum", y = "Zeit")
pdf("Eching_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Eching_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Eching["Sonnenaufgang"] <- strftime(Eching$sr, format="%H:%M")
Eching["Sonnenuntergang"] <- strftime(Eching$ss, format="%H:%M")
write.table(Eching, file="Eching_SaSu.csv", dec=',', sep=';', row.names=FALSE)