library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
26907 <- sunrise.set(52.93436201715625,7.277412414550781, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 26907$sunrise
sunset <- 26907$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
26907["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
26907["ss"] <- as.POSIXct(sunset, format = "%H:%M")
26907["timestamp"] <- align.time(26907$sunrise, 60*10)
26907 <- 26907[c("timestamp", "sr", "ss")]
locsrss <- ggplot(26907, aes(x=26907$timestamp)) + geom_line(aes(y=26907$sr)) + geom_line(aes(y=26907$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 26907 2024", x = "Datum", y = "Zeit")
pdf("26907_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="26907_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
26907["Sonnenaufgang"] <- strftime(26907$sr, format="%H:%M")
26907["Sonnenuntergang"] <- strftime(26907$ss, format="%H:%M")
write.table(26907, file="26907_SaSu.csv", dec=',', sep=';', row.names=FALSE)