library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Coesfeld <- sunrise.set(51.9382944,7.1675831, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Coesfeld$sunrise
sunset <- Coesfeld$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Coesfeld["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Coesfeld["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Coesfeld["timestamp"] <- align.time(Coesfeld$sunrise, 60*10)
Coesfeld <- Coesfeld[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Coesfeld, aes(x=Coesfeld$timestamp)) + geom_line(aes(y=Coesfeld$sr)) + geom_line(aes(y=Coesfeld$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Coesfeld 2024", x = "Datum", y = "Zeit")
pdf("Coesfeld_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Coesfeld_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Coesfeld["Sonnenaufgang"] <- strftime(Coesfeld$sr, format="%H:%M")
Coesfeld["Sonnenuntergang"] <- strftime(Coesfeld$ss, format="%H:%M")
write.table(Coesfeld, file="Coesfeld_SaSu.csv", dec=',', sep=';', row.names=FALSE)