library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Ahaus_Nrw <- sunrise.set(52.0804618,7.0100956, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Ahaus_Nrw$sunrise
sunset <- Ahaus_Nrw$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Ahaus_Nrw["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Ahaus_Nrw["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Ahaus_Nrw["timestamp"] <- align.time(Ahaus_Nrw$sunrise, 60*10)
Ahaus_Nrw <- Ahaus_Nrw[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Ahaus_Nrw, aes(x=Ahaus_Nrw$timestamp)) + geom_line(aes(y=Ahaus_Nrw$sr)) + geom_line(aes(y=Ahaus_Nrw$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Ahaus_Nrw 2024", x = "Datum", y = "Zeit")
pdf("Ahaus_Nrw_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Ahaus_Nrw_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Ahaus_Nrw["Sonnenaufgang"] <- strftime(Ahaus_Nrw$sr, format="%H:%M")
Ahaus_Nrw["Sonnenuntergang"] <- strftime(Ahaus_Nrw$ss, format="%H:%M")
write.table(Ahaus_Nrw, file="Ahaus_Nrw_SaSu.csv", dec=',', sep=';', row.names=FALSE)