library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Bochum_langendreer <- sunrise.set(51.473081,7.325448, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Bochum_langendreer$sunrise
sunset <- Bochum_langendreer$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Bochum_langendreer["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Bochum_langendreer["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Bochum_langendreer["timestamp"] <- align.time(Bochum_langendreer$sunrise, 60*10)
Bochum_langendreer <- Bochum_langendreer[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Bochum_langendreer, aes(x=Bochum_langendreer$timestamp)) + geom_line(aes(y=Bochum_langendreer$sr)) + geom_line(aes(y=Bochum_langendreer$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Bochum_langendreer 2023", x = "Datum", y = "Zeit")
pdf("Bochum_langendreer_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Bochum_langendreer_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Bochum_langendreer["Sonnenaufgang"] <- strftime(Bochum_langendreer$sr, format="%H:%M")
Bochum_langendreer["Sonnenuntergang"] <- strftime(Bochum_langendreer$ss, format="%H:%M")
write.table(Bochum_langendreer, file="Bochum_langendreer_SaSu.csv", dec=',', sep=';', row.names=FALSE)