library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
49565 <- sunrise.set(52.41864944326604,7.974700927734375, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 49565$sunrise
sunset <- 49565$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
49565["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
49565["ss"] <- as.POSIXct(sunset, format = "%H:%M")
49565["timestamp"] <- align.time(49565$sunrise, 60*10)
49565 <- 49565[c("timestamp", "sr", "ss")]
locsrss <- ggplot(49565, aes(x=49565$timestamp)) + geom_line(aes(y=49565$sr)) + geom_line(aes(y=49565$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 49565 2024", x = "Datum", y = "Zeit")
pdf("49565_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="49565_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
49565["Sonnenaufgang"] <- strftime(49565$sr, format="%H:%M")
49565["Sonnenuntergang"] <- strftime(49565$ss, format="%H:%M")
write.table(49565, file="49565_SaSu.csv", dec=',', sep=';', row.names=FALSE)