library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
86473 <- sunrise.set(48.28787619074567,10.532369613647461, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 86473$sunrise
sunset <- 86473$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
86473["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
86473["ss"] <- as.POSIXct(sunset, format = "%H:%M")
86473["timestamp"] <- align.time(86473$sunrise, 60*10)
86473 <- 86473[c("timestamp", "sr", "ss")]
locsrss <- ggplot(86473, aes(x=86473$timestamp)) + geom_line(aes(y=86473$sr)) + geom_line(aes(y=86473$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 86473 2023", x = "Datum", y = "Zeit")
pdf("86473_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="86473_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
86473["Sonnenaufgang"] <- strftime(86473$sr, format="%H:%M")
86473["Sonnenuntergang"] <- strftime(86473$ss, format="%H:%M")
write.table(86473, file="86473_SaSu.csv", dec=',', sep=';', row.names=FALSE)