library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Aglasterhausen <- sunrise.set(49.3543442,8.988520300000005, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Aglasterhausen$sunrise
sunset <- Aglasterhausen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Aglasterhausen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Aglasterhausen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Aglasterhausen["timestamp"] <- align.time(Aglasterhausen$sunrise, 60*10)
Aglasterhausen <- Aglasterhausen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Aglasterhausen, aes(x=Aglasterhausen$timestamp)) + geom_line(aes(y=Aglasterhausen$sr)) + geom_line(aes(y=Aglasterhausen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Aglasterhausen 2023", x = "Datum", y = "Zeit")
pdf("Aglasterhausen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Aglasterhausen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Aglasterhausen["Sonnenaufgang"] <- strftime(Aglasterhausen$sr, format="%H:%M")
Aglasterhausen["Sonnenuntergang"] <- strftime(Aglasterhausen$ss, format="%H:%M")
write.table(Aglasterhausen, file="Aglasterhausen_SaSu.csv", dec=',', sep=';', row.names=FALSE)