library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
50374_DE <- sunrise.set(50.806585609679104,6.823968887329102, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 50374_DE$sunrise
sunset <- 50374_DE$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
50374_DE["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
50374_DE["ss"] <- as.POSIXct(sunset, format = "%H:%M")
50374_DE["timestamp"] <- align.time(50374_DE$sunrise, 60*10)
50374_DE <- 50374_DE[c("timestamp", "sr", "ss")]
locsrss <- ggplot(50374_DE, aes(x=50374_DE$timestamp)) + geom_line(aes(y=50374_DE$sr)) + geom_line(aes(y=50374_DE$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 50374_DE 2024", x = "Datum", y = "Zeit")
pdf("50374_DE_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="50374_DE_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
50374_DE["Sonnenaufgang"] <- strftime(50374_DE$sr, format="%H:%M")
50374_DE["Sonnenuntergang"] <- strftime(50374_DE$ss, format="%H:%M")
write.table(50374_DE, file="50374_DE_SaSu.csv", dec=',', sep=';', row.names=FALSE)