library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Ense <- sunrise.set(51.5021739,7.964883999999984, "2021/01/01", timezone="MET", num.days=370)
sunrise <- Ense$sunrise
sunset <- Ense$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Ense["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Ense["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Ense["timestamp"] <- align.time(Ense$sunrise, 60*10)
Ense <- Ense[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Ense, aes(x=Ense$timestamp)) + geom_line(aes(y=Ense$sr)) + geom_line(aes(y=Ense$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Ense 2021", x = "Datum", y = "Zeit")
pdf("Ense_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Ense_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Ense["Sonnenaufgang"] <- strftime(Ense$sr, format="%H:%M")
Ense["Sonnenuntergang"] <- strftime(Ense$ss, format="%H:%M")
write.table(Ense, file="Ense_SaSu.csv", dec=',', sep=';', row.names=FALSE)