library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
79183 <- sunrise.set(48.09550476269846,7.9596689627990145, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 79183$sunrise
sunset <- 79183$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
79183["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
79183["ss"] <- as.POSIXct(sunset, format = "%H:%M")
79183["timestamp"] <- align.time(79183$sunrise, 60*10)
79183 <- 79183[c("timestamp", "sr", "ss")]
locsrss <- ggplot(79183, aes(x=79183$timestamp)) + geom_line(aes(y=79183$sr)) + geom_line(aes(y=79183$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 79183 2024", x = "Datum", y = "Zeit")
pdf("79183_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="79183_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
79183["Sonnenaufgang"] <- strftime(79183$sr, format="%H:%M")
79183["Sonnenuntergang"] <- strftime(79183$ss, format="%H:%M")
write.table(79183, file="79183_SaSu.csv", dec=',', sep=';', row.names=FALSE)