library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
08289 <- sunrise.set(50.593678781631944,12.64502763748169, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 08289$sunrise
sunset <- 08289$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
08289["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
08289["ss"] <- as.POSIXct(sunset, format = "%H:%M")
08289["timestamp"] <- align.time(08289$sunrise, 60*10)
08289 <- 08289[c("timestamp", "sr", "ss")]
locsrss <- ggplot(08289, aes(x=08289$timestamp)) + geom_line(aes(y=08289$sr)) + geom_line(aes(y=08289$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 08289 2024", x = "Datum", y = "Zeit")
pdf("08289_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="08289_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
08289["Sonnenaufgang"] <- strftime(08289$sr, format="%H:%M")
08289["Sonnenuntergang"] <- strftime(08289$ss, format="%H:%M")
write.table(08289, file="08289_SaSu.csv", dec=',', sep=';', row.names=FALSE)