library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Barcelona <- sunrise.set(41.387917,2.169919, "2022/01/01", timezone="MET", num.days=370)
sunrise <- Barcelona$sunrise
sunset <- Barcelona$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Barcelona["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Barcelona["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Barcelona["timestamp"] <- align.time(Barcelona$sunrise, 60*10)
Barcelona <- Barcelona[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Barcelona, aes(x=Barcelona$timestamp)) + geom_line(aes(y=Barcelona$sr)) + geom_line(aes(y=Barcelona$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Barcelona 2022", x = "Datum", y = "Zeit")
pdf("Barcelona_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Barcelona_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Barcelona["Sonnenaufgang"] <- strftime(Barcelona$sr, format="%H:%M")
Barcelona["Sonnenuntergang"] <- strftime(Barcelona$ss, format="%H:%M")
write.table(Barcelona, file="Barcelona_SaSu.csv", dec=',', sep=';', row.names=FALSE)