library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
71083 <- sunrise.set(48.5879291,8.879328, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 71083$sunrise
sunset <- 71083$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
71083["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
71083["ss"] <- as.POSIXct(sunset, format = "%H:%M")
71083["timestamp"] <- align.time(71083$sunrise, 60*10)
71083 <- 71083[c("timestamp", "sr", "ss")]
locsrss <- ggplot(71083, aes(x=71083$timestamp)) + geom_line(aes(y=71083$sr)) + geom_line(aes(y=71083$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 71083 2023", x = "Datum", y = "Zeit")
pdf("71083_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="71083_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
71083["Sonnenaufgang"] <- strftime(71083$sr, format="%H:%M")
71083["Sonnenuntergang"] <- strftime(71083$ss, format="%H:%M")
write.table(71083, file="71083_SaSu.csv", dec=',', sep=';', row.names=FALSE)