library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Bannewitz <- sunrise.set(50.99378129999999,13.718033300000002, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Bannewitz$sunrise
sunset <- Bannewitz$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Bannewitz["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Bannewitz["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Bannewitz["timestamp"] <- align.time(Bannewitz$sunrise, 60*10)
Bannewitz <- Bannewitz[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Bannewitz, aes(x=Bannewitz$timestamp)) + geom_line(aes(y=Bannewitz$sr)) + geom_line(aes(y=Bannewitz$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Bannewitz 2023", x = "Datum", y = "Zeit")
pdf("Bannewitz_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Bannewitz_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Bannewitz["Sonnenaufgang"] <- strftime(Bannewitz$sr, format="%H:%M")
Bannewitz["Sonnenuntergang"] <- strftime(Bannewitz$ss, format="%H:%M")
write.table(Bannewitz, file="Bannewitz_SaSu.csv", dec=',', sep=';', row.names=FALSE)