library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
82396 <- sunrise.set(47.9250485,11.1619244, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 82396$sunrise
sunset <- 82396$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
82396["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
82396["ss"] <- as.POSIXct(sunset, format = "%H:%M")
82396["timestamp"] <- align.time(82396$sunrise, 60*10)
82396 <- 82396[c("timestamp", "sr", "ss")]
locsrss <- ggplot(82396, aes(x=82396$timestamp)) + geom_line(aes(y=82396$sr)) + geom_line(aes(y=82396$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 82396 2024", x = "Datum", y = "Zeit")
pdf("82396_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="82396_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
82396["Sonnenaufgang"] <- strftime(82396$sr, format="%H:%M")
82396["Sonnenuntergang"] <- strftime(82396$ss, format="%H:%M")
write.table(82396, file="82396_SaSu.csv", dec=',', sep=';', row.names=FALSE)