library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
39288 <- sunrise.set(52.2978506,11.871637899999996, "2022/01/01", timezone="MET", num.days=370)
sunrise <- 39288$sunrise
sunset <- 39288$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
39288["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
39288["ss"] <- as.POSIXct(sunset, format = "%H:%M")
39288["timestamp"] <- align.time(39288$sunrise, 60*10)
39288 <- 39288[c("timestamp", "sr", "ss")]
locsrss <- ggplot(39288, aes(x=39288$timestamp)) + geom_line(aes(y=39288$sr)) + geom_line(aes(y=39288$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 39288 2022", x = "Datum", y = "Zeit")
pdf("39288_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="39288_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
39288["Sonnenaufgang"] <- strftime(39288$sr, format="%H:%M")
39288["Sonnenuntergang"] <- strftime(39288$ss, format="%H:%M")
write.table(39288, file="39288_SaSu.csv", dec=',', sep=';', row.names=FALSE)