library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Frauw��llesheim <- sunrise.set(50.792396874571295,6.571765740197748, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Frauw��llesheim$sunrise
sunset <- Frauw��llesheim$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Frauw��llesheim["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Frauw��llesheim["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Frauw��llesheim["timestamp"] <- align.time(Frauw��llesheim$sunrise, 60*10)
Frauw��llesheim <- Frauw��llesheim[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Frauw��llesheim, aes(x=Frauw��llesheim$timestamp)) + geom_line(aes(y=Frauw��llesheim$sr)) + geom_line(aes(y=Frauw��llesheim$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Frauw��llesheim 2023", x = "Datum", y = "Zeit")
pdf("Frauw��llesheim_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Frauw��llesheim_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Frauw��llesheim["Sonnenaufgang"] <- strftime(Frauw��llesheim$sr, format="%H:%M")
Frauw��llesheim["Sonnenuntergang"] <- strftime(Frauw��llesheim$ss, format="%H:%M")
write.table(Frauw��llesheim, file="Frauw��llesheim_SaSu.csv", dec=',', sep=';', row.names=FALSE)