library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Dittingen <- sunrise.set(47.4420708,7.4962108, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Dittingen$sunrise
sunset <- Dittingen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Dittingen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Dittingen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Dittingen["timestamp"] <- align.time(Dittingen$sunrise, 60*10)
Dittingen <- Dittingen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Dittingen, aes(x=Dittingen$timestamp)) + geom_line(aes(y=Dittingen$sr)) + geom_line(aes(y=Dittingen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Dittingen 2023", x = "Datum", y = "Zeit")
pdf("Dittingen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Dittingen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Dittingen["Sonnenaufgang"] <- strftime(Dittingen$sr, format="%H:%M")
Dittingen["Sonnenuntergang"] <- strftime(Dittingen$ss, format="%H:%M")
write.table(Dittingen, file="Dittingen_SaSu.csv", dec=',', sep=';', row.names=FALSE)