library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
63579.__D <- sunrise.set(50.1431461,9.143807299999935, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 63579.__D$sunrise
sunset <- 63579.__D$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
63579.__D["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
63579.__D["ss"] <- as.POSIXct(sunset, format = "%H:%M")
63579.__D["timestamp"] <- align.time(63579.__D$sunrise, 60*10)
63579.__D <- 63579.__D[c("timestamp", "sr", "ss")]
locsrss <- ggplot(63579.__D, aes(x=63579.__D$timestamp)) + geom_line(aes(y=63579.__D$sr)) + geom_line(aes(y=63579.__D$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 63579.__D 2024", x = "Datum", y = "Zeit")
pdf("63579.__D_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="63579.__D_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
63579.__D["Sonnenaufgang"] <- strftime(63579.__D$sr, format="%H:%M")
63579.__D["Sonnenuntergang"] <- strftime(63579.__D$ss, format="%H:%M")
write.table(63579.__D, file="63579.__D_SaSu.csv", dec=',', sep=';', row.names=FALSE)