library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
22397 <- sunrise.set(53.69171189999999,10.0975465, "2022/01/01", timezone="MET", num.days=370)
sunrise <- 22397$sunrise
sunset <- 22397$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
22397["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
22397["ss"] <- as.POSIXct(sunset, format = "%H:%M")
22397["timestamp"] <- align.time(22397$sunrise, 60*10)
22397 <- 22397[c("timestamp", "sr", "ss")]
locsrss <- ggplot(22397, aes(x=22397$timestamp)) + geom_line(aes(y=22397$sr)) + geom_line(aes(y=22397$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 22397 2022", x = "Datum", y = "Zeit")
pdf("22397_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="22397_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
22397["Sonnenaufgang"] <- strftime(22397$sr, format="%H:%M")
22397["Sonnenuntergang"] <- strftime(22397$ss, format="%H:%M")
write.table(22397, file="22397_SaSu.csv", dec=',', sep=';', row.names=FALSE)