library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
10405 <- sunrise.set(52.53419359999999,13.423006499999929, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 10405$sunrise
sunset <- 10405$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
10405["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
10405["ss"] <- as.POSIXct(sunset, format = "%H:%M")
10405["timestamp"] <- align.time(10405$sunrise, 60*10)
10405 <- 10405[c("timestamp", "sr", "ss")]
locsrss <- ggplot(10405, aes(x=10405$timestamp)) + geom_line(aes(y=10405$sr)) + geom_line(aes(y=10405$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 10405 2024", x = "Datum", y = "Zeit")
pdf("10405_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="10405_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
10405["Sonnenaufgang"] <- strftime(10405$sr, format="%H:%M")
10405["Sonnenuntergang"] <- strftime(10405$ss, format="%H:%M")
write.table(10405, file="10405_SaSu.csv", dec=',', sep=';', row.names=FALSE)