library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Duisburg_ <- sunrise.set(51.4344079,6.7623293, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Duisburg_$sunrise
sunset <- Duisburg_$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Duisburg_["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Duisburg_["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Duisburg_["timestamp"] <- align.time(Duisburg_$sunrise, 60*10)
Duisburg_ <- Duisburg_[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Duisburg_, aes(x=Duisburg_$timestamp)) + geom_line(aes(y=Duisburg_$sr)) + geom_line(aes(y=Duisburg_$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Duisburg_ 2024", x = "Datum", y = "Zeit")
pdf("Duisburg__SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Duisburg__SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Duisburg_["Sonnenaufgang"] <- strftime(Duisburg_$sr, format="%H:%M")
Duisburg_["Sonnenuntergang"] <- strftime(Duisburg_$ss, format="%H:%M")
write.table(Duisburg_, file="Duisburg__SaSu.csv", dec=',', sep=';', row.names=FALSE)