library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Bottrop <- sunrise.set(51.52534807382396,6.9319857581054976, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Bottrop$sunrise
sunset <- Bottrop$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Bottrop["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Bottrop["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Bottrop["timestamp"] <- align.time(Bottrop$sunrise, 60*10)
Bottrop <- Bottrop[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Bottrop, aes(x=Bottrop$timestamp)) + geom_line(aes(y=Bottrop$sr)) + geom_line(aes(y=Bottrop$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Bottrop 2024", x = "Datum", y = "Zeit")
pdf("Bottrop_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Bottrop_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Bottrop["Sonnenaufgang"] <- strftime(Bottrop$sr, format="%H:%M")
Bottrop["Sonnenuntergang"] <- strftime(Bottrop$ss, format="%H:%M")
write.table(Bottrop, file="Bottrop_SaSu.csv", dec=',', sep=';', row.names=FALSE)