library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Alassio <- sunrise.set(43.97688114412622,8.057270050048828, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Alassio$sunrise
sunset <- Alassio$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Alassio["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Alassio["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Alassio["timestamp"] <- align.time(Alassio$sunrise, 60*10)
Alassio <- Alassio[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Alassio, aes(x=Alassio$timestamp)) + geom_line(aes(y=Alassio$sr)) + geom_line(aes(y=Alassio$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Alassio 2024", x = "Datum", y = "Zeit")
pdf("Alassio_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Alassio_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Alassio["Sonnenaufgang"] <- strftime(Alassio$sr, format="%H:%M")
Alassio["Sonnenuntergang"] <- strftime(Alassio$ss, format="%H:%M")
write.table(Alassio, file="Alassio_SaSu.csv", dec=',', sep=';', row.names=FALSE)