library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
95326 <- sunrise.set(50.095008717794315,11.455564498901367, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 95326$sunrise
sunset <- 95326$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
95326["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
95326["ss"] <- as.POSIXct(sunset, format = "%H:%M")
95326["timestamp"] <- align.time(95326$sunrise, 60*10)
95326 <- 95326[c("timestamp", "sr", "ss")]
locsrss <- ggplot(95326, aes(x=95326$timestamp)) + geom_line(aes(y=95326$sr)) + geom_line(aes(y=95326$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 95326 2024", x = "Datum", y = "Zeit")
pdf("95326_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="95326_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
95326["Sonnenaufgang"] <- strftime(95326$sr, format="%H:%M")
95326["Sonnenuntergang"] <- strftime(95326$ss, format="%H:%M")
write.table(95326, file="95326_SaSu.csv", dec=',', sep=';', row.names=FALSE)