library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
42289 <- sunrise.set(51.26894069999999,7.211937799999987, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 42289$sunrise
sunset <- 42289$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
42289["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
42289["ss"] <- as.POSIXct(sunset, format = "%H:%M")
42289["timestamp"] <- align.time(42289$sunrise, 60*10)
42289 <- 42289[c("timestamp", "sr", "ss")]
locsrss <- ggplot(42289, aes(x=42289$timestamp)) + geom_line(aes(y=42289$sr)) + geom_line(aes(y=42289$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 42289 2024", x = "Datum", y = "Zeit")
pdf("42289_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="42289_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
42289["Sonnenaufgang"] <- strftime(42289$sr, format="%H:%M")
42289["Sonnenuntergang"] <- strftime(42289$ss, format="%H:%M")
write.table(42289, file="42289_SaSu.csv", dec=',', sep=';', row.names=FALSE)