library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Cabarete <- sunrise.set(19.7511111,-70.4083333, "2022/01/01", timezone="MET", num.days=370)
sunrise <- Cabarete$sunrise
sunset <- Cabarete$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Cabarete["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Cabarete["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Cabarete["timestamp"] <- align.time(Cabarete$sunrise, 60*10)
Cabarete <- Cabarete[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Cabarete, aes(x=Cabarete$timestamp)) + geom_line(aes(y=Cabarete$sr)) + geom_line(aes(y=Cabarete$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Cabarete 2022", x = "Datum", y = "Zeit")
pdf("Cabarete_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Cabarete_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Cabarete["Sonnenaufgang"] <- strftime(Cabarete$sr, format="%H:%M")
Cabarete["Sonnenuntergang"] <- strftime(Cabarete$ss, format="%H:%M")
write.table(Cabarete, file="Cabarete_SaSu.csv", dec=',', sep=';', row.names=FALSE)