library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
40882 <- sunrise.set(51.3005563,6.914847399999985, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 40882$sunrise
sunset <- 40882$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
40882["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
40882["ss"] <- as.POSIXct(sunset, format = "%H:%M")
40882["timestamp"] <- align.time(40882$sunrise, 60*10)
40882 <- 40882[c("timestamp", "sr", "ss")]
locsrss <- ggplot(40882, aes(x=40882$timestamp)) + geom_line(aes(y=40882$sr)) + geom_line(aes(y=40882$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 40882 2023", x = "Datum", y = "Zeit")
pdf("40882_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="40882_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
40882["Sonnenaufgang"] <- strftime(40882$sr, format="%H:%M")
40882["Sonnenuntergang"] <- strftime(40882$ss, format="%H:%M")
write.table(40882, file="40882_SaSu.csv", dec=',', sep=';', row.names=FALSE)