library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
33106 <- sunrise.set(51.759005,8.633572, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 33106$sunrise
sunset <- 33106$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
33106["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
33106["ss"] <- as.POSIXct(sunset, format = "%H:%M")
33106["timestamp"] <- align.time(33106$sunrise, 60*10)
33106 <- 33106[c("timestamp", "sr", "ss")]
locsrss <- ggplot(33106, aes(x=33106$timestamp)) + geom_line(aes(y=33106$sr)) + geom_line(aes(y=33106$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 33106 2024", x = "Datum", y = "Zeit")
pdf("33106_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="33106_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
33106["Sonnenaufgang"] <- strftime(33106$sr, format="%H:%M")
33106["Sonnenuntergang"] <- strftime(33106$ss, format="%H:%M")
write.table(33106, file="33106_SaSu.csv", dec=',', sep=';', row.names=FALSE)