library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
94209 <- sunrise.set(48.9614732,13.12902710000003, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 94209$sunrise
sunset <- 94209$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
94209["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
94209["ss"] <- as.POSIXct(sunset, format = "%H:%M")
94209["timestamp"] <- align.time(94209$sunrise, 60*10)
94209 <- 94209[c("timestamp", "sr", "ss")]
locsrss <- ggplot(94209, aes(x=94209$timestamp)) + geom_line(aes(y=94209$sr)) + geom_line(aes(y=94209$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 94209 2024", x = "Datum", y = "Zeit")
pdf("94209_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="94209_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
94209["Sonnenaufgang"] <- strftime(94209$sr, format="%H:%M")
94209["Sonnenuntergang"] <- strftime(94209$ss, format="%H:%M")
write.table(94209, file="94209_SaSu.csv", dec=',', sep=';', row.names=FALSE)