library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Angers <- sunrise.set(47.478419,-0.563166, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Angers$sunrise
sunset <- Angers$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Angers["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Angers["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Angers["timestamp"] <- align.time(Angers$sunrise, 60*10)
Angers <- Angers[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Angers, aes(x=Angers$timestamp)) + geom_line(aes(y=Angers$sr)) + geom_line(aes(y=Angers$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Angers 2024", x = "Datum", y = "Zeit")
pdf("Angers_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Angers_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Angers["Sonnenaufgang"] <- strftime(Angers$sr, format="%H:%M")
Angers["Sonnenuntergang"] <- strftime(Angers$ss, format="%H:%M")
write.table(Angers, file="Angers_SaSu.csv", dec=',', sep=';', row.names=FALSE)