library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
45134 <- sunrise.set(51.41486,7.030300699999998, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 45134$sunrise
sunset <- 45134$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
45134["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
45134["ss"] <- as.POSIXct(sunset, format = "%H:%M")
45134["timestamp"] <- align.time(45134$sunrise, 60*10)
45134 <- 45134[c("timestamp", "sr", "ss")]
locsrss <- ggplot(45134, aes(x=45134$timestamp)) + geom_line(aes(y=45134$sr)) + geom_line(aes(y=45134$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 45134 2023", x = "Datum", y = "Zeit")
pdf("45134_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="45134_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
45134["Sonnenaufgang"] <- strftime(45134$sr, format="%H:%M")
45134["Sonnenuntergang"] <- strftime(45134$ss, format="%H:%M")
write.table(45134, file="45134_SaSu.csv", dec=',', sep=';', row.names=FALSE)