library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Basel <- sunrise.set(47.5674422,7.597550700000056, "2022/01/01", timezone="MET", num.days=370)
sunrise <- Basel$sunrise
sunset <- Basel$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Basel["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Basel["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Basel["timestamp"] <- align.time(Basel$sunrise, 60*10)
Basel <- Basel[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Basel, aes(x=Basel$timestamp)) + geom_line(aes(y=Basel$sr)) + geom_line(aes(y=Basel$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Basel 2022", x = "Datum", y = "Zeit")
pdf("Basel_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Basel_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Basel["Sonnenaufgang"] <- strftime(Basel$sr, format="%H:%M")
Basel["Sonnenuntergang"] <- strftime(Basel$ss, format="%H:%M")
write.table(Basel, file="Basel_SaSu.csv", dec=',', sep=';', row.names=FALSE)