library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
21339 <- sunrise.set(53.272891,10.3927673, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 21339$sunrise
sunset <- 21339$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
21339["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
21339["ss"] <- as.POSIXct(sunset, format = "%H:%M")
21339["timestamp"] <- align.time(21339$sunrise, 60*10)
21339 <- 21339[c("timestamp", "sr", "ss")]
locsrss <- ggplot(21339, aes(x=21339$timestamp)) + geom_line(aes(y=21339$sr)) + geom_line(aes(y=21339$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 21339 2023", x = "Datum", y = "Zeit")
pdf("21339_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="21339_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
21339["Sonnenaufgang"] <- strftime(21339$sr, format="%H:%M")
21339["Sonnenuntergang"] <- strftime(21339$ss, format="%H:%M")
write.table(21339, file="21339_SaSu.csv", dec=',', sep=';', row.names=FALSE)