library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Bremen_ <- sunrise.set(53.00581316346376,8.78487088505858, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Bremen_$sunrise
sunset <- Bremen_$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Bremen_["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Bremen_["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Bremen_["timestamp"] <- align.time(Bremen_$sunrise, 60*10)
Bremen_ <- Bremen_[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Bremen_, aes(x=Bremen_$timestamp)) + geom_line(aes(y=Bremen_$sr)) + geom_line(aes(y=Bremen_$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Bremen_ 2024", x = "Datum", y = "Zeit")
pdf("Bremen__SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Bremen__SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Bremen_["Sonnenaufgang"] <- strftime(Bremen_$sr, format="%H:%M")
Bremen_["Sonnenuntergang"] <- strftime(Bremen_$ss, format="%H:%M")
write.table(Bremen_, file="Bremen__SaSu.csv", dec=',', sep=';', row.names=FALSE)