library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
38547 <- sunrise.set(52.4239563,10.621848799999952, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 38547$sunrise
sunset <- 38547$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
38547["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
38547["ss"] <- as.POSIXct(sunset, format = "%H:%M")
38547["timestamp"] <- align.time(38547$sunrise, 60*10)
38547 <- 38547[c("timestamp", "sr", "ss")]
locsrss <- ggplot(38547, aes(x=38547$timestamp)) + geom_line(aes(y=38547$sr)) + geom_line(aes(y=38547$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 38547 2024", x = "Datum", y = "Zeit")
pdf("38547_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="38547_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
38547["Sonnenaufgang"] <- strftime(38547$sr, format="%H:%M")
38547["Sonnenuntergang"] <- strftime(38547$ss, format="%H:%M")
write.table(38547, file="38547_SaSu.csv", dec=',', sep=';', row.names=FALSE)