library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
42551 <- sunrise.set(51.3501692,7.054053299999964, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 42551$sunrise
sunset <- 42551$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
42551["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
42551["ss"] <- as.POSIXct(sunset, format = "%H:%M")
42551["timestamp"] <- align.time(42551$sunrise, 60*10)
42551 <- 42551[c("timestamp", "sr", "ss")]
locsrss <- ggplot(42551, aes(x=42551$timestamp)) + geom_line(aes(y=42551$sr)) + geom_line(aes(y=42551$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 42551 2023", x = "Datum", y = "Zeit")
pdf("42551_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="42551_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
42551["Sonnenaufgang"] <- strftime(42551$sr, format="%H:%M")
42551["Sonnenuntergang"] <- strftime(42551$ss, format="%H:%M")
write.table(42551, file="42551_SaSu.csv", dec=',', sep=';', row.names=FALSE)