library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Engen <- sunrise.set(47.854144,8.7737404, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Engen$sunrise
sunset <- Engen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Engen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Engen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Engen["timestamp"] <- align.time(Engen$sunrise, 60*10)
Engen <- Engen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Engen, aes(x=Engen$timestamp)) + geom_line(aes(y=Engen$sr)) + geom_line(aes(y=Engen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Engen 2024", x = "Datum", y = "Zeit")
pdf("Engen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Engen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Engen["Sonnenaufgang"] <- strftime(Engen$sr, format="%H:%M")
Engen["Sonnenuntergang"] <- strftime(Engen$ss, format="%H:%M")
write.table(Engen, file="Engen_SaSu.csv", dec=',', sep=';', row.names=FALSE)