library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
En_bokek <- sunrise.set(31.205117579477648,35.347548112081085, "2023/01/01", timezone="MET", num.days=370)
sunrise <- En_bokek$sunrise
sunset <- En_bokek$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
En_bokek["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
En_bokek["ss"] <- as.POSIXct(sunset, format = "%H:%M")
En_bokek["timestamp"] <- align.time(En_bokek$sunrise, 60*10)
En_bokek <- En_bokek[c("timestamp", "sr", "ss")]
locsrss <- ggplot(En_bokek, aes(x=En_bokek$timestamp)) + geom_line(aes(y=En_bokek$sr)) + geom_line(aes(y=En_bokek$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - En_bokek 2023", x = "Datum", y = "Zeit")
pdf("En_bokek_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="En_bokek_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
En_bokek["Sonnenaufgang"] <- strftime(En_bokek$sr, format="%H:%M")
En_bokek["Sonnenuntergang"] <- strftime(En_bokek$ss, format="%H:%M")
write.table(En_bokek, file="En_bokek_SaSu.csv", dec=',', sep=';', row.names=FALSE)