library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
41236 <- sunrise.set(51.15302436124946,6.441249847412109, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 41236$sunrise
sunset <- 41236$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
41236["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
41236["ss"] <- as.POSIXct(sunset, format = "%H:%M")
41236["timestamp"] <- align.time(41236$sunrise, 60*10)
41236 <- 41236[c("timestamp", "sr", "ss")]
locsrss <- ggplot(41236, aes(x=41236$timestamp)) + geom_line(aes(y=41236$sr)) + geom_line(aes(y=41236$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 41236 2023", x = "Datum", y = "Zeit")
pdf("41236_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="41236_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
41236["Sonnenaufgang"] <- strftime(41236$sr, format="%H:%M")
41236["Sonnenuntergang"] <- strftime(41236$ss, format="%H:%M")
write.table(41236, file="41236_SaSu.csv", dec=',', sep=';', row.names=FALSE)