library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Esslingen <- sunrise.set(48.736210444037766,9.30663678190922, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Esslingen$sunrise
sunset <- Esslingen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Esslingen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Esslingen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Esslingen["timestamp"] <- align.time(Esslingen$sunrise, 60*10)
Esslingen <- Esslingen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Esslingen, aes(x=Esslingen$timestamp)) + geom_line(aes(y=Esslingen$sr)) + geom_line(aes(y=Esslingen$ss)) + labs(title = " Sunrise/Sunset - Esslingen 2024", x = "Date", y = "Time")
pdf("Esslingen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Esslingen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Esslingen["Sunrise"] <- strftime(Esslingen$sr, format="%H:%M")
Esslingen["Sunset"] <- strftime(Esslingen$ss, format="%H:%M")
write.table(Esslingen, file="Esslingen_SaSu.csv", dec=',', sep=';', row.names=FALSE)