library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
66693 <- sunrise.set(49.53373052105352,6.541712879712804, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 66693$sunrise
sunset <- 66693$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
66693["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
66693["ss"] <- as.POSIXct(sunset, format = "%H:%M")
66693["timestamp"] <- align.time(66693$sunrise, 60*10)
66693 <- 66693[c("timestamp", "sr", "ss")]
locsrss <- ggplot(66693, aes(x=66693$timestamp)) + geom_line(aes(y=66693$sr)) + geom_line(aes(y=66693$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 66693 2023", x = "Datum", y = "Zeit")
pdf("66693_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="66693_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
66693["Sonnenaufgang"] <- strftime(66693$sr, format="%H:%M")
66693["Sonnenuntergang"] <- strftime(66693$ss, format="%H:%M")
write.table(66693, file="66693_SaSu.csv", dec=',', sep=';', row.names=FALSE)