library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
18182 <- sunrise.set(54.1743805,12.236192999999957, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 18182$sunrise
sunset <- 18182$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
18182["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
18182["ss"] <- as.POSIXct(sunset, format = "%H:%M")
18182["timestamp"] <- align.time(18182$sunrise, 60*10)
18182 <- 18182[c("timestamp", "sr", "ss")]
locsrss <- ggplot(18182, aes(x=18182$timestamp)) + geom_line(aes(y=18182$sr)) + geom_line(aes(y=18182$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 18182 2024", x = "Datum", y = "Zeit")
pdf("18182_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="18182_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
18182["Sonnenaufgang"] <- strftime(18182$sr, format="%H:%M")
18182["Sonnenuntergang"] <- strftime(18182$ss, format="%H:%M")
write.table(18182, file="18182_SaSu.csv", dec=',', sep=';', row.names=FALSE)