library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
37441 <- sunrise.set(51.588384,10.545028, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 37441$sunrise
sunset <- 37441$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
37441["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
37441["ss"] <- as.POSIXct(sunset, format = "%H:%M")
37441["timestamp"] <- align.time(37441$sunrise, 60*10)
37441 <- 37441[c("timestamp", "sr", "ss")]
locsrss <- ggplot(37441, aes(x=37441$timestamp)) + geom_line(aes(y=37441$sr)) + geom_line(aes(y=37441$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 37441 2023", x = "Datum", y = "Zeit")
pdf("37441_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="37441_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
37441["Sonnenaufgang"] <- strftime(37441$sr, format="%H:%M")
37441["Sonnenuntergang"] <- strftime(37441$ss, format="%H:%M")
write.table(37441, file="37441_SaSu.csv", dec=',', sep=';', row.names=FALSE)