library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
90766 <- sunrise.set(49.4832225,10.9600774, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 90766$sunrise
sunset <- 90766$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
90766["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
90766["ss"] <- as.POSIXct(sunset, format = "%H:%M")
90766["timestamp"] <- align.time(90766$sunrise, 60*10)
90766 <- 90766[c("timestamp", "sr", "ss")]
locsrss <- ggplot(90766, aes(x=90766$timestamp)) + geom_line(aes(y=90766$sr)) + geom_line(aes(y=90766$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 90766 2024", x = "Datum", y = "Zeit")
pdf("90766_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="90766_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
90766["Sonnenaufgang"] <- strftime(90766$sr, format="%H:%M")
90766["Sonnenuntergang"] <- strftime(90766$ss, format="%H:%M")
write.table(90766, file="90766_SaSu.csv", dec=',', sep=';', row.names=FALSE)