library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
85300 <- sunrise.set(36.847345557474526,27.084903717041016, "2025/01/01", timezone="MET", num.days=370)
sunrise <- 85300$sunrise
sunset <- 85300$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
85300["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
85300["ss"] <- as.POSIXct(sunset, format = "%H:%M")
85300["timestamp"] <- align.time(85300$sunrise, 60*10)
85300 <- 85300[c("timestamp", "sr", "ss")]
locsrss <- ggplot(85300, aes(x=85300$timestamp)) + geom_line(aes(y=85300$sr)) + geom_line(aes(y=85300$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 85300 2025", x = "Datum", y = "Zeit")
pdf("85300_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="85300_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
85300["Sonnenaufgang"] <- strftime(85300$sr, format="%H:%M")
85300["Sonnenuntergang"] <- strftime(85300$ss, format="%H:%M")
write.table(85300, file="85300_SaSu.csv", dec=',', sep=';', row.names=FALSE)