library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
99084 <- sunrise.set(50.9754314,11.02618510000002, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 99084$sunrise
sunset <- 99084$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
99084["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
99084["ss"] <- as.POSIXct(sunset, format = "%H:%M")
99084["timestamp"] <- align.time(99084$sunrise, 60*10)
99084 <- 99084[c("timestamp", "sr", "ss")]
locsrss <- ggplot(99084, aes(x=99084$timestamp)) + geom_line(aes(y=99084$sr)) + geom_line(aes(y=99084$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 99084 2024", x = "Datum", y = "Zeit")
pdf("99084_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="99084_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
99084["Sonnenaufgang"] <- strftime(99084$sr, format="%H:%M")
99084["Sonnenuntergang"] <- strftime(99084$ss, format="%H:%M")
write.table(99084, file="99084_SaSu.csv", dec=',', sep=';', row.names=FALSE)