library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Avalus <- sunrise.set(62.60345318745799,23.5986328125, "2022/01/01", timezone="MET", num.days=370)
sunrise <- Avalus$sunrise
sunset <- Avalus$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Avalus["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Avalus["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Avalus["timestamp"] <- align.time(Avalus$sunrise, 60*10)
Avalus <- Avalus[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Avalus, aes(x=Avalus$timestamp)) + geom_line(aes(y=Avalus$sr)) + geom_line(aes(y=Avalus$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Avalus 2022", x = "Datum", y = "Zeit")
pdf("Avalus_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Avalus_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Avalus["Sonnenaufgang"] <- strftime(Avalus$sr, format="%H:%M")
Avalus["Sonnenuntergang"] <- strftime(Avalus$ss, format="%H:%M")
write.table(Avalus, file="Avalus_SaSu.csv", dec=',', sep=';', row.names=FALSE)