library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Ankara <- sunrise.set(39.92448212528485,32.853240966796875, "2022/01/01", timezone="MET", num.days=370)
sunrise <- Ankara$sunrise
sunset <- Ankara$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Ankara["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Ankara["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Ankara["timestamp"] <- align.time(Ankara$sunrise, 60*10)
Ankara <- Ankara[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Ankara, aes(x=Ankara$timestamp)) + geom_line(aes(y=Ankara$sr)) + geom_line(aes(y=Ankara$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Ankara 2022", x = "Datum", y = "Zeit")
pdf("Ankara_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Ankara_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Ankara["Sonnenaufgang"] <- strftime(Ankara$sr, format="%H:%M")
Ankara["Sonnenuntergang"] <- strftime(Ankara$ss, format="%H:%M")
write.table(Ankara, file="Ankara_SaSu.csv", dec=',', sep=';', row.names=FALSE)