library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
44649 <- sunrise.set(51.5318677114238,7.151155471801758, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 44649$sunrise
sunset <- 44649$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
44649["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
44649["ss"] <- as.POSIXct(sunset, format = "%H:%M")
44649["timestamp"] <- align.time(44649$sunrise, 60*10)
44649 <- 44649[c("timestamp", "sr", "ss")]
locsrss <- ggplot(44649, aes(x=44649$timestamp)) + geom_line(aes(y=44649$sr)) + geom_line(aes(y=44649$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 44649 2023", x = "Datum", y = "Zeit")
pdf("44649_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="44649_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
44649["Sonnenaufgang"] <- strftime(44649$sr, format="%H:%M")
44649["Sonnenuntergang"] <- strftime(44649$ss, format="%H:%M")
write.table(44649, file="44649_SaSu.csv", dec=',', sep=';', row.names=FALSE)