library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
49479 <- sunrise.set(52.259542351420045,7.781410217285156, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 49479$sunrise
sunset <- 49479$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
49479["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
49479["ss"] <- as.POSIXct(sunset, format = "%H:%M")
49479["timestamp"] <- align.time(49479$sunrise, 60*10)
49479 <- 49479[c("timestamp", "sr", "ss")]
locsrss <- ggplot(49479, aes(x=49479$timestamp)) + geom_line(aes(y=49479$sr)) + geom_line(aes(y=49479$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 49479 2024", x = "Datum", y = "Zeit")
pdf("49479_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="49479_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
49479["Sonnenaufgang"] <- strftime(49479$sr, format="%H:%M")
49479["Sonnenuntergang"] <- strftime(49479$ss, format="%H:%M")
write.table(49479, file="49479_SaSu.csv", dec=',', sep=';', row.names=FALSE)