library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
42799,de <- sunrise.set(51.1079268,7.059227, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 42799,de$sunrise
sunset <- 42799,de$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
42799,de["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
42799,de["ss"] <- as.POSIXct(sunset, format = "%H:%M")
42799,de["timestamp"] <- align.time(42799,de$sunrise, 60*10)
42799,de <- 42799,de[c("timestamp", "sr", "ss")]
locsrss <- ggplot(42799,de, aes(x=42799,de$timestamp)) + geom_line(aes(y=42799,de$sr)) + geom_line(aes(y=42799,de$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 42799,de 2024", x = "Datum", y = "Zeit")
pdf("42799,de_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="42799,de_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
42799,de["Sonnenaufgang"] <- strftime(42799,de$sr, format="%H:%M")
42799,de["Sonnenuntergang"] <- strftime(42799,de$ss, format="%H:%M")
write.table(42799,de, file="42799,de_SaSu.csv", dec=',', sep=';', row.names=FALSE)