library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
26954 <- sunrise.set(53.4927518,8.447880999999999, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 26954$sunrise
sunset <- 26954$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
26954["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
26954["ss"] <- as.POSIXct(sunset, format = "%H:%M")
26954["timestamp"] <- align.time(26954$sunrise, 60*10)
26954 <- 26954[c("timestamp", "sr", "ss")]
locsrss <- ggplot(26954, aes(x=26954$timestamp)) + geom_line(aes(y=26954$sr)) + geom_line(aes(y=26954$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 26954 2023", x = "Datum", y = "Zeit")
pdf("26954_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="26954_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
26954["Sonnenaufgang"] <- strftime(26954$sr, format="%H:%M")
26954["Sonnenuntergang"] <- strftime(26954$ss, format="%H:%M")
write.table(26954, file="26954_SaSu.csv", dec=',', sep=';', row.names=FALSE)