library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Akumal <- sunrise.set(20.3959736,-87.315901, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Akumal$sunrise
sunset <- Akumal$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Akumal["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Akumal["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Akumal["timestamp"] <- align.time(Akumal$sunrise, 60*10)
Akumal <- Akumal[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Akumal, aes(x=Akumal$timestamp)) + geom_line(aes(y=Akumal$sr)) + geom_line(aes(y=Akumal$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Akumal 2024", x = "Datum", y = "Zeit")
pdf("Akumal_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Akumal_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Akumal["Sonnenaufgang"] <- strftime(Akumal$sr, format="%H:%M")
Akumal["Sonnenuntergang"] <- strftime(Akumal$ss, format="%H:%M")
write.table(Akumal, file="Akumal_SaSu.csv", dec=',', sep=';', row.names=FALSE)