library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
26133 <- sunrise.set(53.1015899,8.219192699999999, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 26133$sunrise
sunset <- 26133$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
26133["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
26133["ss"] <- as.POSIXct(sunset, format = "%H:%M")
26133["timestamp"] <- align.time(26133$sunrise, 60*10)
26133 <- 26133[c("timestamp", "sr", "ss")]
locsrss <- ggplot(26133, aes(x=26133$timestamp)) + geom_line(aes(y=26133$sr)) + geom_line(aes(y=26133$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 26133 2024", x = "Datum", y = "Zeit")
pdf("26133_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="26133_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
26133["Sonnenaufgang"] <- strftime(26133$sr, format="%H:%M")
26133["Sonnenuntergang"] <- strftime(26133$ss, format="%H:%M")
write.table(26133, file="26133_SaSu.csv", dec=',', sep=';', row.names=FALSE)