library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Diepholz <- sunrise.set(52.603445006855104,8.375165462493896, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Diepholz$sunrise
sunset <- Diepholz$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Diepholz["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Diepholz["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Diepholz["timestamp"] <- align.time(Diepholz$sunrise, 60*10)
Diepholz <- Diepholz[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Diepholz, aes(x=Diepholz$timestamp)) + geom_line(aes(y=Diepholz$sr)) + geom_line(aes(y=Diepholz$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Diepholz 2024", x = "Datum", y = "Zeit")
pdf("Diepholz_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Diepholz_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Diepholz["Sonnenaufgang"] <- strftime(Diepholz$sr, format="%H:%M")
Diepholz["Sonnenuntergang"] <- strftime(Diepholz$ss, format="%H:%M")
write.table(Diepholz, file="Diepholz_SaSu.csv", dec=',', sep=';', row.names=FALSE)