library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
44379 <- sunrise.set(51.514941,7.379774, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 44379$sunrise
sunset <- 44379$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
44379["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
44379["ss"] <- as.POSIXct(sunset, format = "%H:%M")
44379["timestamp"] <- align.time(44379$sunrise, 60*10)
44379 <- 44379[c("timestamp", "sr", "ss")]
locsrss <- ggplot(44379, aes(x=44379$timestamp)) + geom_line(aes(y=44379$sr)) + geom_line(aes(y=44379$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 44379 2023", x = "Datum", y = "Zeit")
pdf("44379_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="44379_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
44379["Sonnenaufgang"] <- strftime(44379$sr, format="%H:%M")
44379["Sonnenuntergang"] <- strftime(44379$ss, format="%H:%M")
write.table(44379, file="44379_SaSu.csv", dec=',', sep=';', row.names=FALSE)