library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Ammersbek <- sunrise.set(53.7072526,10.21440389999998, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Ammersbek$sunrise
sunset <- Ammersbek$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Ammersbek["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Ammersbek["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Ammersbek["timestamp"] <- align.time(Ammersbek$sunrise, 60*10)
Ammersbek <- Ammersbek[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Ammersbek, aes(x=Ammersbek$timestamp)) + geom_line(aes(y=Ammersbek$sr)) + geom_line(aes(y=Ammersbek$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Ammersbek 2023", x = "Datum", y = "Zeit")
pdf("Ammersbek_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Ammersbek_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Ammersbek["Sonnenaufgang"] <- strftime(Ammersbek$sr, format="%H:%M")
Ammersbek["Sonnenuntergang"] <- strftime(Ammersbek$ss, format="%H:%M")
write.table(Ammersbek, file="Ammersbek_SaSu.csv", dec=',', sep=';', row.names=FALSE)