library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
39010 <- sunrise.set(46.5656863,11.169671999999991, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 39010$sunrise
sunset <- 39010$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
39010["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
39010["ss"] <- as.POSIXct(sunset, format = "%H:%M")
39010["timestamp"] <- align.time(39010$sunrise, 60*10)
39010 <- 39010[c("timestamp", "sr", "ss")]
locsrss <- ggplot(39010, aes(x=39010$timestamp)) + geom_line(aes(y=39010$sr)) + geom_line(aes(y=39010$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 39010 2024", x = "Datum", y = "Zeit")
pdf("39010_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="39010_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
39010["Sonnenaufgang"] <- strftime(39010$sr, format="%H:%M")
39010["Sonnenuntergang"] <- strftime(39010$ss, format="%H:%M")
write.table(39010, file="39010_SaSu.csv", dec=',', sep=';', row.names=FALSE)