library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
48683_de <- sunrise.set(52.0935826,6.9375891, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 48683_de$sunrise
sunset <- 48683_de$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
48683_de["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
48683_de["ss"] <- as.POSIXct(sunset, format = "%H:%M")
48683_de["timestamp"] <- align.time(48683_de$sunrise, 60*10)
48683_de <- 48683_de[c("timestamp", "sr", "ss")]
locsrss <- ggplot(48683_de, aes(x=48683_de$timestamp)) + geom_line(aes(y=48683_de$sr)) + geom_line(aes(y=48683_de$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 48683_de 2024", x = "Datum", y = "Zeit")
pdf("48683_de_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="48683_de_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
48683_de["Sonnenaufgang"] <- strftime(48683_de$sr, format="%H:%M")
48683_de["Sonnenuntergang"] <- strftime(48683_de$ss, format="%H:%M")
write.table(48683_de, file="48683_de_SaSu.csv", dec=',', sep=';', row.names=FALSE)