library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
48149 <- sunrise.set(51.967961587186856,7.610006332397461, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 48149$sunrise
sunset <- 48149$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
48149["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
48149["ss"] <- as.POSIXct(sunset, format = "%H:%M")
48149["timestamp"] <- align.time(48149$sunrise, 60*10)
48149 <- 48149[c("timestamp", "sr", "ss")]
locsrss <- ggplot(48149, aes(x=48149$timestamp)) + geom_line(aes(y=48149$sr)) + geom_line(aes(y=48149$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 48149 2024", x = "Datum", y = "Zeit")
pdf("48149_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="48149_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
48149["Sonnenaufgang"] <- strftime(48149$sr, format="%H:%M")
48149["Sonnenuntergang"] <- strftime(48149$ss, format="%H:%M")
write.table(48149, file="48149_SaSu.csv", dec=',', sep=';', row.names=FALSE)