library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
DK_Esbjerg <- sunrise.set(55.4672695,8.4490779, "2024/01/01", timezone="MET", num.days=370)
sunrise <- DK_Esbjerg$sunrise
sunset <- DK_Esbjerg$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
DK_Esbjerg["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
DK_Esbjerg["ss"] <- as.POSIXct(sunset, format = "%H:%M")
DK_Esbjerg["timestamp"] <- align.time(DK_Esbjerg$sunrise, 60*10)
DK_Esbjerg <- DK_Esbjerg[c("timestamp", "sr", "ss")]
locsrss <- ggplot(DK_Esbjerg, aes(x=DK_Esbjerg$timestamp)) + geom_line(aes(y=DK_Esbjerg$sr)) + geom_line(aes(y=DK_Esbjerg$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - DK_Esbjerg 2024", x = "Datum", y = "Zeit")
pdf("DK_Esbjerg_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="DK_Esbjerg_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
DK_Esbjerg["Sonnenaufgang"] <- strftime(DK_Esbjerg$sr, format="%H:%M")
DK_Esbjerg["Sonnenuntergang"] <- strftime(DK_Esbjerg$ss, format="%H:%M")
write.table(DK_Esbjerg, file="DK_Esbjerg_SaSu.csv", dec=',', sep=';', row.names=FALSE)