library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
94250 <- sunrise.set(48.93,12.91, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 94250$sunrise
sunset <- 94250$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
94250["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
94250["ss"] <- as.POSIXct(sunset, format = "%H:%M")
94250["timestamp"] <- align.time(94250$sunrise, 60*10)
94250 <- 94250[c("timestamp", "sr", "ss")]
locsrss <- ggplot(94250, aes(x=94250$timestamp)) + geom_line(aes(y=94250$sr)) + geom_line(aes(y=94250$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 94250 2024", x = "Datum", y = "Zeit")
pdf("94250_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="94250_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
94250["Sonnenaufgang"] <- strftime(94250$sr, format="%H:%M")
94250["Sonnenuntergang"] <- strftime(94250$ss, format="%H:%M")
write.table(94250, file="94250_SaSu.csv", dec=',', sep=';', row.names=FALSE)