library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
26632 <- sunrise.set(53.4000234,7.390383999999999, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 26632$sunrise
sunset <- 26632$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
26632["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
26632["ss"] <- as.POSIXct(sunset, format = "%H:%M")
26632["timestamp"] <- align.time(26632$sunrise, 60*10)
26632 <- 26632[c("timestamp", "sr", "ss")]
locsrss <- ggplot(26632, aes(x=26632$timestamp)) + geom_line(aes(y=26632$sr)) + geom_line(aes(y=26632$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 26632 2024", x = "Datum", y = "Zeit")
pdf("26632_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="26632_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
26632["Sonnenaufgang"] <- strftime(26632$sr, format="%H:%M")
26632["Sonnenuntergang"] <- strftime(26632$ss, format="%H:%M")
write.table(26632, file="26632_SaSu.csv", dec=',', sep=';', row.names=FALSE)