library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
85586 <- sunrise.set(48.1664523,11.8051563, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 85586$sunrise
sunset <- 85586$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
85586["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
85586["ss"] <- as.POSIXct(sunset, format = "%H:%M")
85586["timestamp"] <- align.time(85586$sunrise, 60*10)
85586 <- 85586[c("timestamp", "sr", "ss")]
locsrss <- ggplot(85586, aes(x=85586$timestamp)) + geom_line(aes(y=85586$sr)) + geom_line(aes(y=85586$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 85586 2024", x = "Datum", y = "Zeit")
pdf("85586_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="85586_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
85586["Sonnenaufgang"] <- strftime(85586$sr, format="%H:%M")
85586["Sonnenuntergang"] <- strftime(85586$ss, format="%H:%M")
write.table(85586, file="85586_SaSu.csv", dec=',', sep=';', row.names=FALSE)