library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Brackenheim <- sunrise.set(49.0808636,9.070313700000042, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Brackenheim$sunrise
sunset <- Brackenheim$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Brackenheim["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Brackenheim["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Brackenheim["timestamp"] <- align.time(Brackenheim$sunrise, 60*10)
Brackenheim <- Brackenheim[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Brackenheim, aes(x=Brackenheim$timestamp)) + geom_line(aes(y=Brackenheim$sr)) + geom_line(aes(y=Brackenheim$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Brackenheim 2024", x = "Datum", y = "Zeit")
pdf("Brackenheim_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Brackenheim_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Brackenheim["Sonnenaufgang"] <- strftime(Brackenheim$sr, format="%H:%M")
Brackenheim["Sonnenuntergang"] <- strftime(Brackenheim$ss, format="%H:%M")
write.table(Brackenheim, file="Brackenheim_SaSu.csv", dec=',', sep=';', row.names=FALSE)