library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
D_07927 <- sunrise.set(50.41497177461547,11.771507263183593, "2024/01/01", timezone="MET", num.days=370)
sunrise <- D_07927$sunrise
sunset <- D_07927$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
D_07927["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
D_07927["ss"] <- as.POSIXct(sunset, format = "%H:%M")
D_07927["timestamp"] <- align.time(D_07927$sunrise, 60*10)
D_07927 <- D_07927[c("timestamp", "sr", "ss")]
locsrss <- ggplot(D_07927, aes(x=D_07927$timestamp)) + geom_line(aes(y=D_07927$sr)) + geom_line(aes(y=D_07927$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - D_07927 2024", x = "Datum", y = "Zeit")
pdf("D_07927_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="D_07927_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
D_07927["Sonnenaufgang"] <- strftime(D_07927$sr, format="%H:%M")
D_07927["Sonnenuntergang"] <- strftime(D_07927$ss, format="%H:%M")
write.table(D_07927, file="D_07927_SaSu.csv", dec=',', sep=';', row.names=FALSE)