library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Erfurt <- sunrise.set(50.9737341,11.0224351, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Erfurt$sunrise
sunset <- Erfurt$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Erfurt["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Erfurt["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Erfurt["timestamp"] <- align.time(Erfurt$sunrise, 60*10)
Erfurt <- Erfurt[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Erfurt, aes(x=Erfurt$timestamp)) + geom_line(aes(y=Erfurt$sr)) + geom_line(aes(y=Erfurt$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Erfurt 2024", x = "Datum", y = "Zeit")
pdf("Erfurt_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Erfurt_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Erfurt["Sonnenaufgang"] <- strftime(Erfurt$sr, format="%H:%M")
Erfurt["Sonnenuntergang"] <- strftime(Erfurt$ss, format="%H:%M")
write.table(Erfurt, file="Erfurt_SaSu.csv", dec=',', sep=';', row.names=FALSE)