library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
68163 <- sunrise.set(49.4677562,8.506636000000071, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 68163$sunrise
sunset <- 68163$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
68163["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
68163["ss"] <- as.POSIXct(sunset, format = "%H:%M")
68163["timestamp"] <- align.time(68163$sunrise, 60*10)
68163 <- 68163[c("timestamp", "sr", "ss")]
locsrss <- ggplot(68163, aes(x=68163$timestamp)) + geom_line(aes(y=68163$sr)) + geom_line(aes(y=68163$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 68163 2024", x = "Datum", y = "Zeit")
pdf("68163_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="68163_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
68163["Sonnenaufgang"] <- strftime(68163$sr, format="%H:%M")
68163["Sonnenuntergang"] <- strftime(68163$ss, format="%H:%M")
write.table(68163, file="68163_SaSu.csv", dec=',', sep=';', row.names=FALSE)