library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
23774_DE <- sunrise.set(54.36967989999999,10.97560999999996, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 23774_DE$sunrise
sunset <- 23774_DE$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
23774_DE["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
23774_DE["ss"] <- as.POSIXct(sunset, format = "%H:%M")
23774_DE["timestamp"] <- align.time(23774_DE$sunrise, 60*10)
23774_DE <- 23774_DE[c("timestamp", "sr", "ss")]
locsrss <- ggplot(23774_DE, aes(x=23774_DE$timestamp)) + geom_line(aes(y=23774_DE$sr)) + geom_line(aes(y=23774_DE$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 23774_DE 2024", x = "Datum", y = "Zeit")
pdf("23774_DE_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="23774_DE_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
23774_DE["Sonnenaufgang"] <- strftime(23774_DE$sr, format="%H:%M")
23774_DE["Sonnenuntergang"] <- strftime(23774_DE$ss, format="%H:%M")
write.table(23774_DE, file="23774_DE_SaSu.csv", dec=',', sep=';', row.names=FALSE)