library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Frankfurt_Oder <- sunrise.set(52.342491,14.53813, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Frankfurt_Oder$sunrise
sunset <- Frankfurt_Oder$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Frankfurt_Oder["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Frankfurt_Oder["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Frankfurt_Oder["timestamp"] <- align.time(Frankfurt_Oder$sunrise, 60*10)
Frankfurt_Oder <- Frankfurt_Oder[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Frankfurt_Oder, aes(x=Frankfurt_Oder$timestamp)) + geom_line(aes(y=Frankfurt_Oder$sr)) + geom_line(aes(y=Frankfurt_Oder$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Frankfurt_Oder 2023", x = "Datum", y = "Zeit")
pdf("Frankfurt_Oder_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Frankfurt_Oder_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Frankfurt_Oder["Sonnenaufgang"] <- strftime(Frankfurt_Oder$sr, format="%H:%M")
Frankfurt_Oder["Sonnenuntergang"] <- strftime(Frankfurt_Oder$ss, format="%H:%M")
write.table(Frankfurt_Oder, file="Frankfurt_Oder_SaSu.csv", dec=',', sep=';', row.names=FALSE)