library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
90562 <- sunrise.set(49.5474583,11.1485947, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 90562$sunrise
sunset <- 90562$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
90562["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
90562["ss"] <- as.POSIXct(sunset, format = "%H:%M")
90562["timestamp"] <- align.time(90562$sunrise, 60*10)
90562 <- 90562[c("timestamp", "sr", "ss")]
locsrss <- ggplot(90562, aes(x=90562$timestamp)) + geom_line(aes(y=90562$sr)) + geom_line(aes(y=90562$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 90562 2024", x = "Datum", y = "Zeit")
pdf("90562_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="90562_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
90562["Sonnenaufgang"] <- strftime(90562$sr, format="%H:%M")
90562["Sonnenuntergang"] <- strftime(90562$ss, format="%H:%M")
write.table(90562, file="90562_SaSu.csv", dec=',', sep=';', row.names=FALSE)