library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Can_picafort <- sunrise.set(39.7654783,3.1486726, "2019/01/01", timezone="MET", num.days=370)
sunrise <- Can_picafort$sunrise
sunset <- Can_picafort$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Can_picafort["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Can_picafort["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Can_picafort["timestamp"] <- align.time(Can_picafort$sunrise, 60*10)
Can_picafort <- Can_picafort[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Can_picafort, aes(x=Can_picafort$timestamp)) + geom_line(aes(y=Can_picafort$sr)) + geom_line(aes(y=Can_picafort$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Can_picafort 2019", x = "Datum", y = "Zeit")
pdf("Can_picafort_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Can_picafort_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Can_picafort["Sonnenaufgang"] <- strftime(Can_picafort$sr, format="%H:%M")
Can_picafort["Sonnenuntergang"] <- strftime(Can_picafort$ss, format="%H:%M")
write.table(Can_picafort, file="Can_picafort_SaSu.csv", dec=',', sep=';', row.names=FALSE)