library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Br��ggen <- sunrise.set(51.2442461,6.1818561000000045, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Br��ggen$sunrise
sunset <- Br��ggen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Br��ggen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Br��ggen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Br��ggen["timestamp"] <- align.time(Br��ggen$sunrise, 60*10)
Br��ggen <- Br��ggen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Br��ggen, aes(x=Br��ggen$timestamp)) + geom_line(aes(y=Br��ggen$sr)) + geom_line(aes(y=Br��ggen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Br��ggen 2023", x = "Datum", y = "Zeit")
pdf("Br��ggen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Br��ggen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Br��ggen["Sonnenaufgang"] <- strftime(Br��ggen$sr, format="%H:%M")
Br��ggen["Sonnenuntergang"] <- strftime(Br��ggen$ss, format="%H:%M")
write.table(Br��ggen, file="Br��ggen_SaSu.csv", dec=',', sep=';', row.names=FALSE)