library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Elmenhorst <- sunrise.set(54.15996224256665,12.019631542382854, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Elmenhorst$sunrise
sunset <- Elmenhorst$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Elmenhorst["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Elmenhorst["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Elmenhorst["timestamp"] <- align.time(Elmenhorst$sunrise, 60*10)
Elmenhorst <- Elmenhorst[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Elmenhorst, aes(x=Elmenhorst$timestamp)) + geom_line(aes(y=Elmenhorst$sr)) + geom_line(aes(y=Elmenhorst$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Elmenhorst 2023", x = "Datum", y = "Zeit")
pdf("Elmenhorst_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Elmenhorst_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Elmenhorst["Sonnenaufgang"] <- strftime(Elmenhorst$sr, format="%H:%M")
Elmenhorst["Sonnenuntergang"] <- strftime(Elmenhorst$ss, format="%H:%M")
write.table(Elmenhorst, file="Elmenhorst_SaSu.csv", dec=',', sep=';', row.names=FALSE)