library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Unna <- sunrise.set(51.5426349,7.685311400000046, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Unna$sunrise
sunset <- Unna$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Unna["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Unna["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Unna["timestamp"] <- align.time(Unna$sunrise, 60*10)
Unna <- Unna[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Unna, aes(x=Unna$timestamp)) + geom_line(aes(y=Unna$sr)) + geom_line(aes(y=Unna$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Unna 2024", x = "Datum", y = "Zeit")
pdf("Unna_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Unna_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Unna["Sonnenaufgang"] <- strftime(Unna$sr, format="%H:%M")
Unna["Sonnenuntergang"] <- strftime(Unna$ss, format="%H:%M")
write.table(Unna, file="Unna_SaSu.csv", dec=',', sep=';', row.names=FALSE)