library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
8330 <- sunrise.set(47.3661671,8.7866772, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 8330$sunrise
sunset <- 8330$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
8330["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
8330["ss"] <- as.POSIXct(sunset, format = "%H:%M")
8330["timestamp"] <- align.time(8330$sunrise, 60*10)
8330 <- 8330[c("timestamp", "sr", "ss")]
locsrss <- ggplot(8330, aes(x=8330$timestamp)) + geom_line(aes(y=8330$sr)) + geom_line(aes(y=8330$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 8330 2024", x = "Datum", y = "Zeit")
pdf("8330_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="8330_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
8330["Sonnenaufgang"] <- strftime(8330$sr, format="%H:%M")
8330["Sonnenuntergang"] <- strftime(8330$ss, format="%H:%M")
write.table(8330, file="8330_SaSu.csv", dec=',', sep=';', row.names=FALSE)