library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
10999 <- sunrise.set(52.4952683,13.4308614, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 10999$sunrise
sunset <- 10999$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
10999["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
10999["ss"] <- as.POSIXct(sunset, format = "%H:%M")
10999["timestamp"] <- align.time(10999$sunrise, 60*10)
10999 <- 10999[c("timestamp", "sr", "ss")]
locsrss <- ggplot(10999, aes(x=10999$timestamp)) + geom_line(aes(y=10999$sr)) + geom_line(aes(y=10999$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 10999 2024", x = "Datum", y = "Zeit")
pdf("10999_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="10999_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
10999["Sonnenaufgang"] <- strftime(10999$sr, format="%H:%M")
10999["Sonnenuntergang"] <- strftime(10999$ss, format="%H:%M")
write.table(10999, file="10999_SaSu.csv", dec=',', sep=';', row.names=FALSE)