library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Breitbrunn <- sunrise.set(47.8895134,12.397551199999953, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Breitbrunn$sunrise
sunset <- Breitbrunn$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Breitbrunn["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Breitbrunn["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Breitbrunn["timestamp"] <- align.time(Breitbrunn$sunrise, 60*10)
Breitbrunn <- Breitbrunn[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Breitbrunn, aes(x=Breitbrunn$timestamp)) + geom_line(aes(y=Breitbrunn$sr)) + geom_line(aes(y=Breitbrunn$ss)) + labs(title = " Sunrise/Sunset - Breitbrunn 2024", x = "Date", y = "Time")
pdf("Breitbrunn_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Breitbrunn_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Breitbrunn["Sunrise"] <- strftime(Breitbrunn$sr, format="%H:%M")
Breitbrunn["Sunset"] <- strftime(Breitbrunn$ss, format="%H:%M")
write.table(Breitbrunn, file="Breitbrunn_SaSu.csv", dec=',', sep=';', row.names=FALSE)