library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Vienenburg <- sunrise.set(51.9520394,10.5567652, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Vienenburg$sunrise
sunset <- Vienenburg$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Vienenburg["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Vienenburg["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Vienenburg["timestamp"] <- align.time(Vienenburg$sunrise, 60*10)
Vienenburg <- Vienenburg[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Vienenburg, aes(x=Vienenburg$timestamp)) + geom_line(aes(y=Vienenburg$sr)) + geom_line(aes(y=Vienenburg$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Vienenburg 2024", x = "Datum", y = "Zeit")
pdf("Vienenburg_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Vienenburg_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Vienenburg["Sonnenaufgang"] <- strftime(Vienenburg$sr, format="%H:%M")
Vienenburg["Sonnenuntergang"] <- strftime(Vienenburg$ss, format="%H:%M")
write.table(Vienenburg, file="Vienenburg_SaSu.csv", dec=',', sep=';', row.names=FALSE)