library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
24109 <- sunrise.set(54.3171885,10.0477345, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 24109$sunrise
sunset <- 24109$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
24109["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
24109["ss"] <- as.POSIXct(sunset, format = "%H:%M")
24109["timestamp"] <- align.time(24109$sunrise, 60*10)
24109 <- 24109[c("timestamp", "sr", "ss")]
locsrss <- ggplot(24109, aes(x=24109$timestamp)) + geom_line(aes(y=24109$sr)) + geom_line(aes(y=24109$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 24109 2023", x = "Datum", y = "Zeit")
pdf("24109_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="24109_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
24109["Sonnenaufgang"] <- strftime(24109$sr, format="%H:%M")
24109["Sonnenuntergang"] <- strftime(24109$ss, format="%H:%M")
write.table(24109, file="24109_SaSu.csv", dec=',', sep=';', row.names=FALSE)