library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
61381 <- sunrise.set(50.2596965,8.6406273, "2022/01/01", timezone="MET", num.days=370)
sunrise <- 61381$sunrise
sunset <- 61381$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
61381["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
61381["ss"] <- as.POSIXct(sunset, format = "%H:%M")
61381["timestamp"] <- align.time(61381$sunrise, 60*10)
61381 <- 61381[c("timestamp", "sr", "ss")]
locsrss <- ggplot(61381, aes(x=61381$timestamp)) + geom_line(aes(y=61381$sr)) + geom_line(aes(y=61381$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 61381 2022", x = "Datum", y = "Zeit")
pdf("61381_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="61381_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
61381["Sonnenaufgang"] <- strftime(61381$sr, format="%H:%M")
61381["Sonnenuntergang"] <- strftime(61381$ss, format="%H:%M")
write.table(61381, file="61381_SaSu.csv", dec=',', sep=';', row.names=FALSE)