library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
37284 <- sunrise.set(51.1457172,9.877205300000014, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 37284$sunrise
sunset <- 37284$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
37284["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
37284["ss"] <- as.POSIXct(sunset, format = "%H:%M")
37284["timestamp"] <- align.time(37284$sunrise, 60*10)
37284 <- 37284[c("timestamp", "sr", "ss")]
locsrss <- ggplot(37284, aes(x=37284$timestamp)) + geom_line(aes(y=37284$sr)) + geom_line(aes(y=37284$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 37284 2023", x = "Datum", y = "Zeit")
pdf("37284_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="37284_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
37284["Sonnenaufgang"] <- strftime(37284$sr, format="%H:%M")
37284["Sonnenuntergang"] <- strftime(37284$ss, format="%H:%M")
write.table(37284, file="37284_SaSu.csv", dec=',', sep=';', row.names=FALSE)