library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Blankenstein <- sunrise.set(50.4047504,11.6951129, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Blankenstein$sunrise
sunset <- Blankenstein$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Blankenstein["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Blankenstein["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Blankenstein["timestamp"] <- align.time(Blankenstein$sunrise, 60*10)
Blankenstein <- Blankenstein[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Blankenstein, aes(x=Blankenstein$timestamp)) + geom_line(aes(y=Blankenstein$sr)) + geom_line(aes(y=Blankenstein$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Blankenstein 2024", x = "Datum", y = "Zeit")
pdf("Blankenstein_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Blankenstein_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Blankenstein["Sonnenaufgang"] <- strftime(Blankenstein$sr, format="%H:%M")
Blankenstein["Sonnenuntergang"] <- strftime(Blankenstein$ss, format="%H:%M")
write.table(Blankenstein, file="Blankenstein_SaSu.csv", dec=',', sep=';', row.names=FALSE)