library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
07937 <- sunrise.set(50.6292435,12.0391162, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 07937$sunrise
sunset <- 07937$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
07937["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
07937["ss"] <- as.POSIXct(sunset, format = "%H:%M")
07937["timestamp"] <- align.time(07937$sunrise, 60*10)
07937 <- 07937[c("timestamp", "sr", "ss")]
locsrss <- ggplot(07937, aes(x=07937$timestamp)) + geom_line(aes(y=07937$sr)) + geom_line(aes(y=07937$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 07937 2023", x = "Datum", y = "Zeit")
pdf("07937_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="07937_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
07937["Sonnenaufgang"] <- strftime(07937$sr, format="%H:%M")
07937["Sonnenuntergang"] <- strftime(07937$ss, format="%H:%M")
write.table(07937, file="07937_SaSu.csv", dec=',', sep=';', row.names=FALSE)