library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Calgary <- sunrise.set(51.0453246,-114.0581012, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Calgary$sunrise
sunset <- Calgary$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Calgary["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Calgary["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Calgary["timestamp"] <- align.time(Calgary$sunrise, 60*10)
Calgary <- Calgary[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Calgary, aes(x=Calgary$timestamp)) + geom_line(aes(y=Calgary$sr)) + geom_line(aes(y=Calgary$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Calgary 2023", x = "Datum", y = "Zeit")
pdf("Calgary_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Calgary_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Calgary["Sonnenaufgang"] <- strftime(Calgary$sr, format="%H:%M")
Calgary["Sonnenuntergang"] <- strftime(Calgary$ss, format="%H:%M")
write.table(Calgary, file="Calgary_SaSu.csv", dec=',', sep=';', row.names=FALSE)