library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Augsburg <- sunrise.set(48.40387316906471,10.905207485766596, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Augsburg$sunrise
sunset <- Augsburg$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Augsburg["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Augsburg["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Augsburg["timestamp"] <- align.time(Augsburg$sunrise, 60*10)
Augsburg <- Augsburg[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Augsburg, aes(x=Augsburg$timestamp)) + geom_line(aes(y=Augsburg$sr)) + geom_line(aes(y=Augsburg$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Augsburg 2024", x = "Datum", y = "Zeit")
pdf("Augsburg_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Augsburg_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Augsburg["Sonnenaufgang"] <- strftime(Augsburg$sr, format="%H:%M")
Augsburg["Sonnenuntergang"] <- strftime(Augsburg$ss, format="%H:%M")
write.table(Augsburg, file="Augsburg_SaSu.csv", dec=',', sep=';', row.names=FALSE)