library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Cap_Horn_ <- sunrise.set(-55.062963056847885,-67.3985027375, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Cap_Horn_$sunrise
sunset <- Cap_Horn_$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Cap_Horn_["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Cap_Horn_["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Cap_Horn_["timestamp"] <- align.time(Cap_Horn_$sunrise, 60*10)
Cap_Horn_ <- Cap_Horn_[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Cap_Horn_, aes(x=Cap_Horn_$timestamp)) + geom_line(aes(y=Cap_Horn_$sr)) + geom_line(aes(y=Cap_Horn_$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Cap_Horn_ 2024", x = "Datum", y = "Zeit")
pdf("Cap_Horn__SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Cap_Horn__SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Cap_Horn_["Sonnenaufgang"] <- strftime(Cap_Horn_$sr, format="%H:%M")
Cap_Horn_["Sonnenuntergang"] <- strftime(Cap_Horn_$ss, format="%H:%M")
write.table(Cap_Horn_, file="Cap_Horn__SaSu.csv", dec=',', sep=';', row.names=FALSE)