library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
94439 <- sunrise.set(48.5994658,12.9409109, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 94439$sunrise
sunset <- 94439$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
94439["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
94439["ss"] <- as.POSIXct(sunset, format = "%H:%M")
94439["timestamp"] <- align.time(94439$sunrise, 60*10)
94439 <- 94439[c("timestamp", "sr", "ss")]
locsrss <- ggplot(94439, aes(x=94439$timestamp)) + geom_line(aes(y=94439$sr)) + geom_line(aes(y=94439$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 94439 2024", x = "Datum", y = "Zeit")
pdf("94439_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="94439_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
94439["Sonnenaufgang"] <- strftime(94439$sr, format="%H:%M")
94439["Sonnenuntergang"] <- strftime(94439$ss, format="%H:%M")
write.table(94439, file="94439_SaSu.csv", dec=',', sep=';', row.names=FALSE)