library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
14169,DE <- sunrise.set(52.4424884,13.264024, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 14169,DE$sunrise
sunset <- 14169,DE$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
14169,DE["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
14169,DE["ss"] <- as.POSIXct(sunset, format = "%H:%M")
14169,DE["timestamp"] <- align.time(14169,DE$sunrise, 60*10)
14169,DE <- 14169,DE[c("timestamp", "sr", "ss")]
locsrss <- ggplot(14169,DE, aes(x=14169,DE$timestamp)) + geom_line(aes(y=14169,DE$sr)) + geom_line(aes(y=14169,DE$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 14169,DE 2024", x = "Datum", y = "Zeit")
pdf("14169,DE_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="14169,DE_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
14169,DE["Sonnenaufgang"] <- strftime(14169,DE$sr, format="%H:%M")
14169,DE["Sonnenuntergang"] <- strftime(14169,DE$ss, format="%H:%M")
write.table(14169,DE, file="14169,DE_SaSu.csv", dec=',', sep=';', row.names=FALSE)