library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
66271 <- sunrise.set(49.14672,7.078478, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 66271$sunrise
sunset <- 66271$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
66271["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
66271["ss"] <- as.POSIXct(sunset, format = "%H:%M")
66271["timestamp"] <- align.time(66271$sunrise, 60*10)
66271 <- 66271[c("timestamp", "sr", "ss")]
locsrss <- ggplot(66271, aes(x=66271$timestamp)) + geom_line(aes(y=66271$sr)) + geom_line(aes(y=66271$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 66271 2023", x = "Datum", y = "Zeit")
pdf("66271_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="66271_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
66271["Sonnenaufgang"] <- strftime(66271$sr, format="%H:%M")
66271["Sonnenuntergang"] <- strftime(66271$ss, format="%H:%M")
write.table(66271, file="66271_SaSu.csv", dec=',', sep=';', row.names=FALSE)