library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
37079 <- sunrise.set(51.5551958,9.888394199999993, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 37079$sunrise
sunset <- 37079$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
37079["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
37079["ss"] <- as.POSIXct(sunset, format = "%H:%M")
37079["timestamp"] <- align.time(37079$sunrise, 60*10)
37079 <- 37079[c("timestamp", "sr", "ss")]
locsrss <- ggplot(37079, aes(x=37079$timestamp)) + geom_line(aes(y=37079$sr)) + geom_line(aes(y=37079$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 37079 2024", x = "Datum", y = "Zeit")
pdf("37079_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="37079_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
37079["Sonnenaufgang"] <- strftime(37079$sr, format="%H:%M")
37079["Sonnenuntergang"] <- strftime(37079$ss, format="%H:%M")
write.table(37079, file="37079_SaSu.csv", dec=',', sep=';', row.names=FALSE)