library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Davensberg <- sunrise.set(51.8175172,7.595306100000016, "2022/01/01", timezone="MET", num.days=370)
sunrise <- Davensberg$sunrise
sunset <- Davensberg$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Davensberg["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Davensberg["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Davensberg["timestamp"] <- align.time(Davensberg$sunrise, 60*10)
Davensberg <- Davensberg[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Davensberg, aes(x=Davensberg$timestamp)) + geom_line(aes(y=Davensberg$sr)) + geom_line(aes(y=Davensberg$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Davensberg 2022", x = "Datum", y = "Zeit")
pdf("Davensberg_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Davensberg_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Davensberg["Sonnenaufgang"] <- strftime(Davensberg$sr, format="%H:%M")
Davensberg["Sonnenuntergang"] <- strftime(Davensberg$ss, format="%H:%M")
write.table(Davensberg, file="Davensberg_SaSu.csv", dec=',', sep=';', row.names=FALSE)