library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
02689 <- sunrise.set(51.0445876,14.4271742, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 02689$sunrise
sunset <- 02689$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
02689["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
02689["ss"] <- as.POSIXct(sunset, format = "%H:%M")
02689["timestamp"] <- align.time(02689$sunrise, 60*10)
02689 <- 02689[c("timestamp", "sr", "ss")]
locsrss <- ggplot(02689, aes(x=02689$timestamp)) + geom_line(aes(y=02689$sr)) + geom_line(aes(y=02689$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 02689 2024", x = "Datum", y = "Zeit")
pdf("02689_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="02689_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
02689["Sonnenaufgang"] <- strftime(02689$sr, format="%H:%M")
02689["Sonnenuntergang"] <- strftime(02689$ss, format="%H:%M")
write.table(02689, file="02689_SaSu.csv", dec=',', sep=';', row.names=FALSE)