library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Bad_Salzuflen <- sunrise.set(52.0765209,8.7521109, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Bad_Salzuflen$sunrise
sunset <- Bad_Salzuflen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Bad_Salzuflen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Bad_Salzuflen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Bad_Salzuflen["timestamp"] <- align.time(Bad_Salzuflen$sunrise, 60*10)
Bad_Salzuflen <- Bad_Salzuflen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Bad_Salzuflen, aes(x=Bad_Salzuflen$timestamp)) + geom_line(aes(y=Bad_Salzuflen$sr)) + geom_line(aes(y=Bad_Salzuflen$ss)) + labs(title = " Sunrise/Sunset - Bad_Salzuflen 2024", x = "Date", y = "Time")
pdf("Bad_Salzuflen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Bad_Salzuflen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Bad_Salzuflen["Sunrise"] <- strftime(Bad_Salzuflen$sr, format="%H:%M")
Bad_Salzuflen["Sunset"] <- strftime(Bad_Salzuflen$ss, format="%H:%M")
write.table(Bad_Salzuflen, file="Bad_Salzuflen_SaSu.csv", dec=',', sep=';', row.names=FALSE)