library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
88477 <- sunrise.set(48.1914544,9.964936999999999, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 88477$sunrise
sunset <- 88477$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
88477["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
88477["ss"] <- as.POSIXct(sunset, format = "%H:%M")
88477["timestamp"] <- align.time(88477$sunrise, 60*10)
88477 <- 88477[c("timestamp", "sr", "ss")]
locsrss <- ggplot(88477, aes(x=88477$timestamp)) + geom_line(aes(y=88477$sr)) + geom_line(aes(y=88477$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 88477 2024", x = "Datum", y = "Zeit")
pdf("88477_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="88477_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
88477["Sonnenaufgang"] <- strftime(88477$sr, format="%H:%M")
88477["Sonnenuntergang"] <- strftime(88477$ss, format="%H:%M")
write.table(88477, file="88477_SaSu.csv", dec=',', sep=';', row.names=FALSE)