library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
29614 <- sunrise.set(53.0057013,9.83091939999997, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 29614$sunrise
sunset <- 29614$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
29614["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
29614["ss"] <- as.POSIXct(sunset, format = "%H:%M")
29614["timestamp"] <- align.time(29614$sunrise, 60*10)
29614 <- 29614[c("timestamp", "sr", "ss")]
locsrss <- ggplot(29614, aes(x=29614$timestamp)) + geom_line(aes(y=29614$sr)) + geom_line(aes(y=29614$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 29614 2023", x = "Datum", y = "Zeit")
pdf("29614_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="29614_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
29614["Sonnenaufgang"] <- strftime(29614$sr, format="%H:%M")
29614["Sonnenuntergang"] <- strftime(29614$ss, format="%H:%M")
write.table(29614, file="29614_SaSu.csv", dec=',', sep=';', row.names=FALSE)