library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
47669 <- sunrise.set(51.37952627180411,6.3086679025025205, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 47669$sunrise
sunset <- 47669$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
47669["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
47669["ss"] <- as.POSIXct(sunset, format = "%H:%M")
47669["timestamp"] <- align.time(47669$sunrise, 60*10)
47669 <- 47669[c("timestamp", "sr", "ss")]
locsrss <- ggplot(47669, aes(x=47669$timestamp)) + geom_line(aes(y=47669$sr)) + geom_line(aes(y=47669$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 47669 2023", x = "Datum", y = "Zeit")
pdf("47669_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="47669_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
47669["Sonnenaufgang"] <- strftime(47669$sr, format="%H:%M")
47669["Sonnenuntergang"] <- strftime(47669$ss, format="%H:%M")
write.table(47669, file="47669_SaSu.csv", dec=',', sep=';', row.names=FALSE)