library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Can_Picafort <- sunrise.set(39.765278,3.14861099999996, "2024/01/01", 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 2024", 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)