library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
DE_19205 <- sunrise.set(53.6828679,11.057933, "2021/01/01", timezone="MET", num.days=370)
sunrise <- DE_19205$sunrise
sunset <- DE_19205$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
DE_19205["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
DE_19205["ss"] <- as.POSIXct(sunset, format = "%H:%M")
DE_19205["timestamp"] <- align.time(DE_19205$sunrise, 60*10)
DE_19205 <- DE_19205[c("timestamp", "sr", "ss")]
locsrss <- ggplot(DE_19205, aes(x=DE_19205$timestamp)) + geom_line(aes(y=DE_19205$sr)) + geom_line(aes(y=DE_19205$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - DE_19205 2021", x = "Datum", y = "Zeit")
pdf("DE_19205_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="DE_19205_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
DE_19205["Sonnenaufgang"] <- strftime(DE_19205$sr, format="%H:%M")
DE_19205["Sonnenuntergang"] <- strftime(DE_19205$ss, format="%H:%M")
write.table(DE_19205, file="DE_19205_SaSu.csv", dec=',', sep=';', row.names=FALSE)