library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
82387 <- sunrise.set(47.750657195662185,11.302158236503601, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 82387$sunrise
sunset <- 82387$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
82387["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
82387["ss"] <- as.POSIXct(sunset, format = "%H:%M")
82387["timestamp"] <- align.time(82387$sunrise, 60*10)
82387 <- 82387[c("timestamp", "sr", "ss")]
locsrss <- ggplot(82387, aes(x=82387$timestamp)) + geom_line(aes(y=82387$sr)) + geom_line(aes(y=82387$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 82387 2024", x = "Datum", y = "Zeit")
pdf("82387_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="82387_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
82387["Sonnenaufgang"] <- strftime(82387$sr, format="%H:%M")
82387["Sonnenuntergang"] <- strftime(82387$ss, format="%H:%M")
write.table(82387, file="82387_SaSu.csv", dec=',', sep=';', row.names=FALSE)