library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
D_67549 <- sunrise.set(49.63689820448192,8.343086242675781, "2024/01/01", timezone="MET", num.days=370)
sunrise <- D_67549$sunrise
sunset <- D_67549$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
D_67549["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
D_67549["ss"] <- as.POSIXct(sunset, format = "%H:%M")
D_67549["timestamp"] <- align.time(D_67549$sunrise, 60*10)
D_67549 <- D_67549[c("timestamp", "sr", "ss")]
locsrss <- ggplot(D_67549, aes(x=D_67549$timestamp)) + geom_line(aes(y=D_67549$sr)) + geom_line(aes(y=D_67549$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - D_67549 2024", x = "Datum", y = "Zeit")
pdf("D_67549_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="D_67549_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
D_67549["Sonnenaufgang"] <- strftime(D_67549$sr, format="%H:%M")
D_67549["Sonnenuntergang"] <- strftime(D_67549$ss, format="%H:%M")
write.table(D_67549, file="D_67549_SaSu.csv", dec=',', sep=';', row.names=FALSE)