library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
D_58644 <- sunrise.set(51.3580473,7.6814401, "2024/01/01", timezone="MET", num.days=370)
sunrise <- D_58644$sunrise
sunset <- D_58644$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
D_58644["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
D_58644["ss"] <- as.POSIXct(sunset, format = "%H:%M")
D_58644["timestamp"] <- align.time(D_58644$sunrise, 60*10)
D_58644 <- D_58644[c("timestamp", "sr", "ss")]
locsrss <- ggplot(D_58644, aes(x=D_58644$timestamp)) + geom_line(aes(y=D_58644$sr)) + geom_line(aes(y=D_58644$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - D_58644 2024", x = "Datum", y = "Zeit")
pdf("D_58644_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="D_58644_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
D_58644["Sonnenaufgang"] <- strftime(D_58644$sr, format="%H:%M")
D_58644["Sonnenuntergang"] <- strftime(D_58644$ss, format="%H:%M")
write.table(D_58644, file="D_58644_SaSu.csv", dec=',', sep=';', row.names=FALSE)