library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
89440 <- sunrise.set(48.67432789999999,10.5430161, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 89440$sunrise
sunset <- 89440$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
89440["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
89440["ss"] <- as.POSIXct(sunset, format = "%H:%M")
89440["timestamp"] <- align.time(89440$sunrise, 60*10)
89440 <- 89440[c("timestamp", "sr", "ss")]
locsrss <- ggplot(89440, aes(x=89440$timestamp)) + geom_line(aes(y=89440$sr)) + geom_line(aes(y=89440$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 89440 2024", x = "Datum", y = "Zeit")
pdf("89440_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="89440_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
89440["Sonnenaufgang"] <- strftime(89440$sr, format="%H:%M")
89440["Sonnenuntergang"] <- strftime(89440$ss, format="%H:%M")
write.table(89440, file="89440_SaSu.csv", dec=',', sep=';', row.names=FALSE)