library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Bad_lausick <- sunrise.set(51.1449012,12.645053200000007, "2020/01/01", timezone="MET", num.days=370)
sunrise <- Bad_lausick$sunrise
sunset <- Bad_lausick$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Bad_lausick["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Bad_lausick["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Bad_lausick["timestamp"] <- align.time(Bad_lausick$sunrise, 60*10)
Bad_lausick <- Bad_lausick[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Bad_lausick, aes(x=Bad_lausick$timestamp)) + geom_line(aes(y=Bad_lausick$sr)) + geom_line(aes(y=Bad_lausick$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Bad_lausick 2020", x = "Datum", y = "Zeit")
pdf("Bad_lausick_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Bad_lausick_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Bad_lausick["Sonnenaufgang"] <- strftime(Bad_lausick$sr, format="%H:%M")
Bad_lausick["Sonnenuntergang"] <- strftime(Bad_lausick$ss, format="%H:%M")
write.table(Bad_lausick, file="Bad_lausick_SaSu.csv", dec=',', sep=';', row.names=FALSE)