library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
DA_Nang <- sunrise.set(16.051571,108.214897, "2024/01/01", timezone="MET", num.days=370)
sunrise <- DA_Nang$sunrise
sunset <- DA_Nang$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
DA_Nang["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
DA_Nang["ss"] <- as.POSIXct(sunset, format = "%H:%M")
DA_Nang["timestamp"] <- align.time(DA_Nang$sunrise, 60*10)
DA_Nang <- DA_Nang[c("timestamp", "sr", "ss")]
locsrss <- ggplot(DA_Nang, aes(x=DA_Nang$timestamp)) + geom_line(aes(y=DA_Nang$sr)) + geom_line(aes(y=DA_Nang$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - DA_Nang 2024", x = "Datum", y = "Zeit")
pdf("DA_Nang_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="DA_Nang_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
DA_Nang["Sonnenaufgang"] <- strftime(DA_Nang$sr, format="%H:%M")
DA_Nang["Sonnenuntergang"] <- strftime(DA_Nang$ss, format="%H:%M")
write.table(DA_Nang, file="DA_Nang_SaSu.csv", dec=',', sep=';', row.names=FALSE)