library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
33332 <- sunrise.set(51.897298,8.3938455, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 33332$sunrise
sunset <- 33332$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
33332["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
33332["ss"] <- as.POSIXct(sunset, format = "%H:%M")
33332["timestamp"] <- align.time(33332$sunrise, 60*10)
33332 <- 33332[c("timestamp", "sr", "ss")]
locsrss <- ggplot(33332, aes(x=33332$timestamp)) + geom_line(aes(y=33332$sr)) + geom_line(aes(y=33332$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 33332 2024", x = "Datum", y = "Zeit")
pdf("33332_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="33332_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
33332["Sonnenaufgang"] <- strftime(33332$sr, format="%H:%M")
33332["Sonnenuntergang"] <- strftime(33332$ss, format="%H:%M")
write.table(33332, file="33332_SaSu.csv", dec=',', sep=';', row.names=FALSE)