library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Casablanca <- sunrise.set(33.5333333,-7.583333300000049, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Casablanca$sunrise
sunset <- Casablanca$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Casablanca["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Casablanca["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Casablanca["timestamp"] <- align.time(Casablanca$sunrise, 60*10)
Casablanca <- Casablanca[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Casablanca, aes(x=Casablanca$timestamp)) + geom_line(aes(y=Casablanca$sr)) + geom_line(aes(y=Casablanca$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Casablanca 2023", x = "Datum", y = "Zeit")
pdf("Casablanca_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Casablanca_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Casablanca["Sonnenaufgang"] <- strftime(Casablanca$sr, format="%H:%M")
Casablanca["Sonnenuntergang"] <- strftime(Casablanca$ss, format="%H:%M")
write.table(Casablanca, file="Casablanca_SaSu.csv", dec=',', sep=';', row.names=FALSE)