library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Catania <- sunrise.set(37.5080386,15.0828512, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Catania$sunrise
sunset <- Catania$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Catania["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Catania["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Catania["timestamp"] <- align.time(Catania$sunrise, 60*10)
Catania <- Catania[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Catania, aes(x=Catania$timestamp)) + geom_line(aes(y=Catania$sr)) + geom_line(aes(y=Catania$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Catania 2024", x = "Datum", y = "Zeit")
pdf("Catania_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Catania_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Catania["Sonnenaufgang"] <- strftime(Catania$sr, format="%H:%M")
Catania["Sonnenuntergang"] <- strftime(Catania$ss, format="%H:%M")
write.table(Catania, file="Catania_SaSu.csv", dec=',', sep=';', row.names=FALSE)