library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Dorsten <- sunrise.set(51.659089,6.966174, "2025/01/01", timezone="MET", num.days=370)
sunrise <- Dorsten$sunrise
sunset <- Dorsten$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Dorsten["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Dorsten["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Dorsten["timestamp"] <- align.time(Dorsten$sunrise, 60*10)
Dorsten <- Dorsten[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Dorsten, aes(x=Dorsten$timestamp)) + geom_line(aes(y=Dorsten$sr)) + geom_line(aes(y=Dorsten$ss)) + labs(title = " Sunrise/Sunset - Dorsten 2025", x = "Date", y = "Time")
pdf("Dorsten_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Dorsten_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Dorsten["Sunrise"] <- strftime(Dorsten$sr, format="%H:%M")
Dorsten["Sunset"] <- strftime(Dorsten$ss, format="%H:%M")
write.table(Dorsten, file="Dorsten_SaSu.csv", dec=',', sep=';', row.names=FALSE)