library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Aguilas <- sunrise.set(37.47087872377926,-1.6512673685722348, "2020/01/01", timezone="MET", num.days=370)
sunrise <- Aguilas$sunrise
sunset <- Aguilas$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Aguilas["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Aguilas["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Aguilas["timestamp"] <- align.time(Aguilas$sunrise, 60*10)
Aguilas <- Aguilas[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Aguilas, aes(x=Aguilas$timestamp)) + geom_line(aes(y=Aguilas$sr)) + geom_line(aes(y=Aguilas$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Aguilas 2020", x = "Datum", y = "Zeit")
pdf("Aguilas_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Aguilas_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Aguilas["Sonnenaufgang"] <- strftime(Aguilas$sr, format="%H:%M")
Aguilas["Sonnenuntergang"] <- strftime(Aguilas$ss, format="%H:%M")
write.table(Aguilas, file="Aguilas_SaSu.csv", dec=',', sep=';', row.names=FALSE)