library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
01189 <- sunrise.set(51.02154061139504,13.717141169958495, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 01189$sunrise
sunset <- 01189$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
01189["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
01189["ss"] <- as.POSIXct(sunset, format = "%H:%M")
01189["timestamp"] <- align.time(01189$sunrise, 60*10)
01189 <- 01189[c("timestamp", "sr", "ss")]
locsrss <- ggplot(01189, aes(x=01189$timestamp)) + geom_line(aes(y=01189$sr)) + geom_line(aes(y=01189$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 01189 2024", x = "Datum", y = "Zeit")
pdf("01189_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="01189_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
01189["Sonnenaufgang"] <- strftime(01189$sr, format="%H:%M")
01189["Sonnenuntergang"] <- strftime(01189$ss, format="%H:%M")
write.table(01189, file="01189_SaSu.csv", dec=',', sep=';', row.names=FALSE)