library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
86860 <- sunrise.set(47.9941857,10.702901, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 86860$sunrise
sunset <- 86860$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
86860["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
86860["ss"] <- as.POSIXct(sunset, format = "%H:%M")
86860["timestamp"] <- align.time(86860$sunrise, 60*10)
86860 <- 86860[c("timestamp", "sr", "ss")]
locsrss <- ggplot(86860, aes(x=86860$timestamp)) + geom_line(aes(y=86860$sr)) + geom_line(aes(y=86860$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 86860 2023", x = "Datum", y = "Zeit")
pdf("86860_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="86860_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
86860["Sonnenaufgang"] <- strftime(86860$sr, format="%H:%M")
86860["Sonnenuntergang"] <- strftime(86860$ss, format="%H:%M")
write.table(86860, file="86860_SaSu.csv", dec=',', sep=';', row.names=FALSE)