library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
88239 <- sunrise.set(47.68437377004496,9.8412645229065, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 88239$sunrise
sunset <- 88239$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
88239["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
88239["ss"] <- as.POSIXct(sunset, format = "%H:%M")
88239["timestamp"] <- align.time(88239$sunrise, 60*10)
88239 <- 88239[c("timestamp", "sr", "ss")]
locsrss <- ggplot(88239, aes(x=88239$timestamp)) + geom_line(aes(y=88239$sr)) + geom_line(aes(y=88239$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 88239 2024", x = "Datum", y = "Zeit")
pdf("88239_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="88239_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
88239["Sonnenaufgang"] <- strftime(88239$sr, format="%H:%M")
88239["Sonnenuntergang"] <- strftime(88239$ss, format="%H:%M")
write.table(88239, file="88239_SaSu.csv", dec=',', sep=';', row.names=FALSE)