library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
57392 <- sunrise.set(51.14593992392154,8.285579877075179, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 57392$sunrise
sunset <- 57392$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
57392["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
57392["ss"] <- as.POSIXct(sunset, format = "%H:%M")
57392["timestamp"] <- align.time(57392$sunrise, 60*10)
57392 <- 57392[c("timestamp", "sr", "ss")]
locsrss <- ggplot(57392, aes(x=57392$timestamp)) + geom_line(aes(y=57392$sr)) + geom_line(aes(y=57392$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 57392 2024", x = "Datum", y = "Zeit")
pdf("57392_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="57392_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
57392["Sonnenaufgang"] <- strftime(57392$sr, format="%H:%M")
57392["Sonnenuntergang"] <- strftime(57392$ss, format="%H:%M")
write.table(57392, file="57392_SaSu.csv", dec=',', sep=';', row.names=FALSE)