library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
64846 <- sunrise.set(49.87312,8.824643, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 64846$sunrise
sunset <- 64846$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
64846["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
64846["ss"] <- as.POSIXct(sunset, format = "%H:%M")
64846["timestamp"] <- align.time(64846$sunrise, 60*10)
64846 <- 64846[c("timestamp", "sr", "ss")]
locsrss <- ggplot(64846, aes(x=64846$timestamp)) + geom_line(aes(y=64846$sr)) + geom_line(aes(y=64846$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 64846 2023", x = "Datum", y = "Zeit")
pdf("64846_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="64846_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
64846["Sonnenaufgang"] <- strftime(64846$sr, format="%H:%M")
64846["Sonnenuntergang"] <- strftime(64846$ss, format="%H:%M")
write.table(64846, file="64846_SaSu.csv", dec=',', sep=';', row.names=FALSE)