library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
A_2201 <- sunrise.set(48.31393345330619,16.49394392967224, "2024/01/01", timezone="MET", num.days=370)
sunrise <- A_2201$sunrise
sunset <- A_2201$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
A_2201["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
A_2201["ss"] <- as.POSIXct(sunset, format = "%H:%M")
A_2201["timestamp"] <- align.time(A_2201$sunrise, 60*10)
A_2201 <- A_2201[c("timestamp", "sr", "ss")]
locsrss <- ggplot(A_2201, aes(x=A_2201$timestamp)) + geom_line(aes(y=A_2201$sr)) + geom_line(aes(y=A_2201$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - A_2201 2024", x = "Datum", y = "Zeit")
pdf("A_2201_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="A_2201_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
A_2201["Sonnenaufgang"] <- strftime(A_2201$sr, format="%H:%M")
A_2201["Sonnenuntergang"] <- strftime(A_2201$ss, format="%H:%M")
write.table(A_2201, file="A_2201_SaSu.csv", dec=',', sep=';', row.names=FALSE)