library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
37603 <- sunrise.set(51.7755136,9.4988528, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 37603$sunrise
sunset <- 37603$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
37603["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
37603["ss"] <- as.POSIXct(sunset, format = "%H:%M")
37603["timestamp"] <- align.time(37603$sunrise, 60*10)
37603 <- 37603[c("timestamp", "sr", "ss")]
locsrss <- ggplot(37603, aes(x=37603$timestamp)) + geom_line(aes(y=37603$sr)) + geom_line(aes(y=37603$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 37603 2023", x = "Datum", y = "Zeit")
pdf("37603_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="37603_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
37603["Sonnenaufgang"] <- strftime(37603$sr, format="%H:%M")
37603["Sonnenuntergang"] <- strftime(37603$ss, format="%H:%M")
write.table(37603, file="37603_SaSu.csv", dec=',', sep=';', row.names=FALSE)