library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
BESCHENDORF <- sunrise.set(54.1824412,10.8756855, "2023/01/01", timezone="MET", num.days=370)
sunrise <- BESCHENDORF$sunrise
sunset <- BESCHENDORF$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
BESCHENDORF["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
BESCHENDORF["ss"] <- as.POSIXct(sunset, format = "%H:%M")
BESCHENDORF["timestamp"] <- align.time(BESCHENDORF$sunrise, 60*10)
BESCHENDORF <- BESCHENDORF[c("timestamp", "sr", "ss")]
locsrss <- ggplot(BESCHENDORF, aes(x=BESCHENDORF$timestamp)) + geom_line(aes(y=BESCHENDORF$sr)) + geom_line(aes(y=BESCHENDORF$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - BESCHENDORF 2023", x = "Datum", y = "Zeit")
pdf("BESCHENDORF_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="BESCHENDORF_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
BESCHENDORF["Sonnenaufgang"] <- strftime(BESCHENDORF$sr, format="%H:%M")
BESCHENDORF["Sonnenuntergang"] <- strftime(BESCHENDORF$ss, format="%H:%M")
write.table(BESCHENDORF, file="BESCHENDORF_SaSu.csv", dec=',', sep=';', row.names=FALSE)