library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
31863 <- sunrise.set(52.118056,9.546538499999999, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 31863$sunrise
sunset <- 31863$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
31863["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
31863["ss"] <- as.POSIXct(sunset, format = "%H:%M")
31863["timestamp"] <- align.time(31863$sunrise, 60*10)
31863 <- 31863[c("timestamp", "sr", "ss")]
locsrss <- ggplot(31863, aes(x=31863$timestamp)) + geom_line(aes(y=31863$sr)) + geom_line(aes(y=31863$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 31863 2024", x = "Datum", y = "Zeit")
pdf("31863_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="31863_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
31863["Sonnenaufgang"] <- strftime(31863$sr, format="%H:%M")
31863["Sonnenuntergang"] <- strftime(31863$ss, format="%H:%M")
write.table(31863, file="31863_SaSu.csv", dec=',', sep=';', row.names=FALSE)