library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Braunschweig <- sunrise.set(52.22885087287482,10.520267486572266, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Braunschweig$sunrise
sunset <- Braunschweig$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Braunschweig["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Braunschweig["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Braunschweig["timestamp"] <- align.time(Braunschweig$sunrise, 60*10)
Braunschweig <- Braunschweig[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Braunschweig, aes(x=Braunschweig$timestamp)) + geom_line(aes(y=Braunschweig$sr)) + geom_line(aes(y=Braunschweig$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Braunschweig 2024", x = "Datum", y = "Zeit")
pdf("Braunschweig_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Braunschweig_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Braunschweig["Sonnenaufgang"] <- strftime(Braunschweig$sr, format="%H:%M")
Braunschweig["Sonnenuntergang"] <- strftime(Braunschweig$ss, format="%H:%M")
write.table(Braunschweig, file="Braunschweig_SaSu.csv", dec=',', sep=';', row.names=FALSE)