library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Alert_Kanada <- sunrise.set(82.516305,-62.308482, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Alert_Kanada$sunrise
sunset <- Alert_Kanada$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Alert_Kanada["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Alert_Kanada["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Alert_Kanada["timestamp"] <- align.time(Alert_Kanada$sunrise, 60*10)
Alert_Kanada <- Alert_Kanada[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Alert_Kanada, aes(x=Alert_Kanada$timestamp)) + geom_line(aes(y=Alert_Kanada$sr)) + geom_line(aes(y=Alert_Kanada$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Alert_Kanada 2023", x = "Datum", y = "Zeit")
pdf("Alert_Kanada_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Alert_Kanada_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Alert_Kanada["Sonnenaufgang"] <- strftime(Alert_Kanada$sr, format="%H:%M")
Alert_Kanada["Sonnenuntergang"] <- strftime(Alert_Kanada$ss, format="%H:%M")
write.table(Alert_Kanada, file="Alert_Kanada_SaSu.csv", dec=',', sep=';', row.names=FALSE)