library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Caszand_ <- sunrise.set(51.3692317,3.4077694000000065, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Caszand_$sunrise
sunset <- Caszand_$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Caszand_["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Caszand_["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Caszand_["timestamp"] <- align.time(Caszand_$sunrise, 60*10)
Caszand_ <- Caszand_[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Caszand_, aes(x=Caszand_$timestamp)) + geom_line(aes(y=Caszand_$sr)) + geom_line(aes(y=Caszand_$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Caszand_ 2024", x = "Datum", y = "Zeit")
pdf("Caszand__SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Caszand__SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Caszand_["Sonnenaufgang"] <- strftime(Caszand_$sr, format="%H:%M")
Caszand_["Sonnenuntergang"] <- strftime(Caszand_$ss, format="%H:%M")
write.table(Caszand_, file="Caszand__SaSu.csv", dec=',', sep=';', row.names=FALSE)