library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
83376 <- sunrise.set(47.9611706,12.500551200000018, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 83376$sunrise
sunset <- 83376$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
83376["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
83376["ss"] <- as.POSIXct(sunset, format = "%H:%M")
83376["timestamp"] <- align.time(83376$sunrise, 60*10)
83376 <- 83376[c("timestamp", "sr", "ss")]
locsrss <- ggplot(83376, aes(x=83376$timestamp)) + geom_line(aes(y=83376$sr)) + geom_line(aes(y=83376$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 83376 2023", x = "Datum", y = "Zeit")
pdf("83376_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="83376_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
83376["Sonnenaufgang"] <- strftime(83376$sr, format="%H:%M")
83376["Sonnenuntergang"] <- strftime(83376$ss, format="%H:%M")
write.table(83376, file="83376_SaSu.csv", dec=',', sep=';', row.names=FALSE)