library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Apöolda <- sunrise.set(51.0260095,11.51554950000002, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Apöolda$sunrise
sunset <- Apöolda$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Apöolda["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Apöolda["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Apöolda["timestamp"] <- align.time(Apöolda$sunrise, 60*10)
Apöolda <- Apöolda[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Apöolda, aes(x=Apöolda$timestamp)) + geom_line(aes(y=Apöolda$sr)) + geom_line(aes(y=Apöolda$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Apöolda 2024", x = "Datum", y = "Zeit")
pdf("Apöolda_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Apöolda_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Apöolda["Sonnenaufgang"] <- strftime(Apöolda$sr, format="%H:%M")
Apöolda["Sonnenuntergang"] <- strftime(Apöolda$ss, format="%H:%M")
write.table(Apöolda, file="Apöolda_SaSu.csv", dec=',', sep=';', row.names=FALSE)