library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Älmhult <- sunrise.set(56.5524461,14.137404699999934, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Älmhult$sunrise
sunset <- Älmhult$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Älmhult["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Älmhult["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Älmhult["timestamp"] <- align.time(Älmhult$sunrise, 60*10)
Älmhult <- Älmhult[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Älmhult, aes(x=Älmhult$timestamp)) + geom_line(aes(y=Älmhult$sr)) + geom_line(aes(y=Älmhult$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Älmhult 2024", x = "Datum", y = "Zeit")
pdf("Älmhult_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Älmhult_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Älmhult["Sonnenaufgang"] <- strftime(Älmhult$sr, format="%H:%M")
Älmhult["Sonnenuntergang"] <- strftime(Älmhult$ss, format="%H:%M")
write.table(Älmhult, file="Älmhult_SaSu.csv", dec=',', sep=';', row.names=FALSE)