library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
80992 <- sunrise.set(48.1757295,11.5182935, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 80992$sunrise
sunset <- 80992$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
80992["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
80992["ss"] <- as.POSIXct(sunset, format = "%H:%M")
80992["timestamp"] <- align.time(80992$sunrise, 60*10)
80992 <- 80992[c("timestamp", "sr", "ss")]
locsrss <- ggplot(80992, aes(x=80992$timestamp)) + geom_line(aes(y=80992$sr)) + geom_line(aes(y=80992$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 80992 2024", x = "Datum", y = "Zeit")
pdf("80992_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="80992_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
80992["Sonnenaufgang"] <- strftime(80992$sr, format="%H:%M")
80992["Sonnenuntergang"] <- strftime(80992$ss, format="%H:%M")
write.table(80992, file="80992_SaSu.csv", dec=',', sep=';', row.names=FALSE)