library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
BRD_44651 <- sunrise.set(49.6638947,13.7638435, "2023/01/01", timezone="MET", num.days=370)
sunrise <- BRD_44651$sunrise
sunset <- BRD_44651$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
BRD_44651["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
BRD_44651["ss"] <- as.POSIXct(sunset, format = "%H:%M")
BRD_44651["timestamp"] <- align.time(BRD_44651$sunrise, 60*10)
BRD_44651 <- BRD_44651[c("timestamp", "sr", "ss")]
locsrss <- ggplot(BRD_44651, aes(x=BRD_44651$timestamp)) + geom_line(aes(y=BRD_44651$sr)) + geom_line(aes(y=BRD_44651$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - BRD_44651 2023", x = "Datum", y = "Zeit")
pdf("BRD_44651_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="BRD_44651_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
BRD_44651["Sonnenaufgang"] <- strftime(BRD_44651$sr, format="%H:%M")
BRD_44651["Sonnenuntergang"] <- strftime(BRD_44651$ss, format="%H:%M")
write.table(BRD_44651, file="BRD_44651_SaSu.csv", dec=',', sep=';', row.names=FALSE)