library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
32549 <- sunrise.set(52.2357817,8.801618500000018, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 32549$sunrise
sunset <- 32549$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
32549["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
32549["ss"] <- as.POSIXct(sunset, format = "%H:%M")
32549["timestamp"] <- align.time(32549$sunrise, 60*10)
32549 <- 32549[c("timestamp", "sr", "ss")]
locsrss <- ggplot(32549, aes(x=32549$timestamp)) + geom_line(aes(y=32549$sr)) + geom_line(aes(y=32549$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 32549 2023", x = "Datum", y = "Zeit")
pdf("32549_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="32549_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
32549["Sonnenaufgang"] <- strftime(32549$sr, format="%H:%M")
32549["Sonnenuntergang"] <- strftime(32549$ss, format="%H:%M")
write.table(32549, file="32549_SaSu.csv", dec=',', sep=';', row.names=FALSE)