library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Brüggen <- sunrise.set(51.27668767105864,6.19370073500977, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Brüggen$sunrise
sunset <- Brüggen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Brüggen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Brüggen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Brüggen["timestamp"] <- align.time(Brüggen$sunrise, 60*10)
Brüggen <- Brüggen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Brüggen, aes(x=Brüggen$timestamp)) + geom_line(aes(y=Brüggen$sr)) + geom_line(aes(y=Brüggen$ss)) + labs(title = " Sunrise/Sunset - Brüggen 2024", x = "Date", y = "Time")
pdf("Brüggen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Brüggen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Brüggen["Sunrise"] <- strftime(Brüggen$sr, format="%H:%M")
Brüggen["Sunset"] <- strftime(Brüggen$ss, format="%H:%M")
write.table(Brüggen, file="Brüggen_SaSu.csv", dec=',', sep=';', row.names=FALSE)