library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
18107 <- sunrise.set(54.1395318,12.033020599999986, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 18107$sunrise
sunset <- 18107$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
18107["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
18107["ss"] <- as.POSIXct(sunset, format = "%H:%M")
18107["timestamp"] <- align.time(18107$sunrise, 60*10)
18107 <- 18107[c("timestamp", "sr", "ss")]
locsrss <- ggplot(18107, aes(x=18107$timestamp)) + geom_line(aes(y=18107$sr)) + geom_line(aes(y=18107$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 18107 2024", x = "Datum", y = "Zeit")
pdf("18107_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="18107_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
18107["Sonnenaufgang"] <- strftime(18107$sr, format="%H:%M")
18107["Sonnenuntergang"] <- strftime(18107$ss, format="%H:%M")
write.table(18107, file="18107_SaSu.csv", dec=',', sep=';', row.names=FALSE)