library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Buenos_Aires <- sunrise.set(-34.6036844,-58.381559100000004, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Buenos_Aires$sunrise
sunset <- Buenos_Aires$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Buenos_Aires["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Buenos_Aires["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Buenos_Aires["timestamp"] <- align.time(Buenos_Aires$sunrise, 60*10)
Buenos_Aires <- Buenos_Aires[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Buenos_Aires, aes(x=Buenos_Aires$timestamp)) + geom_line(aes(y=Buenos_Aires$sr)) + geom_line(aes(y=Buenos_Aires$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Buenos_Aires 2024", x = "Datum", y = "Zeit")
pdf("Buenos_Aires_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Buenos_Aires_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Buenos_Aires["Sonnenaufgang"] <- strftime(Buenos_Aires$sr, format="%H:%M")
Buenos_Aires["Sonnenuntergang"] <- strftime(Buenos_Aires$ss, format="%H:%M")
write.table(Buenos_Aires, file="Buenos_Aires_SaSu.csv", dec=',', sep=';', row.names=FALSE)