library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
02694 <- sunrise.set(51.2663909,14.513341500000024, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 02694$sunrise
sunset <- 02694$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
02694["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
02694["ss"] <- as.POSIXct(sunset, format = "%H:%M")
02694["timestamp"] <- align.time(02694$sunrise, 60*10)
02694 <- 02694[c("timestamp", "sr", "ss")]
locsrss <- ggplot(02694, aes(x=02694$timestamp)) + geom_line(aes(y=02694$sr)) + geom_line(aes(y=02694$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 02694 2024", x = "Datum", y = "Zeit")
pdf("02694_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="02694_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
02694["Sonnenaufgang"] <- strftime(02694$sr, format="%H:%M")
02694["Sonnenuntergang"] <- strftime(02694$ss, format="%H:%M")
write.table(02694, file="02694_SaSu.csv", dec=',', sep=';', row.names=FALSE)