library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Craula <- sunrise.set(51.072263493308654,10.463808611425778, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Craula$sunrise
sunset <- Craula$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Craula["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Craula["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Craula["timestamp"] <- align.time(Craula$sunrise, 60*10)
Craula <- Craula[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Craula, aes(x=Craula$timestamp)) + geom_line(aes(y=Craula$sr)) + geom_line(aes(y=Craula$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Craula 2024", x = "Datum", y = "Zeit")
pdf("Craula_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Craula_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Craula["Sonnenaufgang"] <- strftime(Craula$sr, format="%H:%M")
Craula["Sonnenuntergang"] <- strftime(Craula$ss, format="%H:%M")
write.table(Craula, file="Craula_SaSu.csv", dec=',', sep=';', row.names=FALSE)