library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Forchheim <- sunrise.set(49.7213064,11.06988339999998, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Forchheim$sunrise
sunset <- Forchheim$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Forchheim["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Forchheim["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Forchheim["timestamp"] <- align.time(Forchheim$sunrise, 60*10)
Forchheim <- Forchheim[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Forchheim, aes(x=Forchheim$timestamp)) + geom_line(aes(y=Forchheim$sr)) + geom_line(aes(y=Forchheim$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Forchheim 2024", x = "Datum", y = "Zeit")
pdf("Forchheim_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Forchheim_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Forchheim["Sonnenaufgang"] <- strftime(Forchheim$sr, format="%H:%M")
Forchheim["Sonnenuntergang"] <- strftime(Forchheim$ss, format="%H:%M")
write.table(Forchheim, file="Forchheim_SaSu.csv", dec=',', sep=';', row.names=FALSE)