library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
36284 <- sunrise.set(50.826107880542104,9.908895492553711, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 36284$sunrise
sunset <- 36284$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
36284["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
36284["ss"] <- as.POSIXct(sunset, format = "%H:%M")
36284["timestamp"] <- align.time(36284$sunrise, 60*10)
36284 <- 36284[c("timestamp", "sr", "ss")]
locsrss <- ggplot(36284, aes(x=36284$timestamp)) + geom_line(aes(y=36284$sr)) + geom_line(aes(y=36284$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 36284 2023", x = "Datum", y = "Zeit")
pdf("36284_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="36284_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
36284["Sonnenaufgang"] <- strftime(36284$sr, format="%H:%M")
36284["Sonnenuntergang"] <- strftime(36284$ss, format="%H:%M")
write.table(36284, file="36284_SaSu.csv", dec=',', sep=';', row.names=FALSE)