library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
XYZ <- sunrise.set(49.9000902,9.2265032, "2024/01/01", timezone="MET", num.days=370)
sunrise <- XYZ$sunrise
sunset <- XYZ$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
XYZ["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
XYZ["ss"] <- as.POSIXct(sunset, format = "%H:%M")
XYZ["timestamp"] <- align.time(XYZ$sunrise, 60*10)
XYZ <- XYZ[c("timestamp", "sr", "ss")]
locsrss <- ggplot(XYZ, aes(x=XYZ$timestamp)) + geom_line(aes(y=XYZ$sr)) + geom_line(aes(y=XYZ$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - XYZ 2024", x = "Datum", y = "Zeit")
pdf("XYZ_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="XYZ_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
XYZ["Sonnenaufgang"] <- strftime(XYZ$sr, format="%H:%M")
XYZ["Sonnenuntergang"] <- strftime(XYZ$ss, format="%H:%M")
write.table(XYZ, file="XYZ_SaSu.csv", dec=',', sep=';', row.names=FALSE)