library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
79379 <- sunrise.set(47.8091623,7.618035300000001, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 79379$sunrise
sunset <- 79379$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
79379["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
79379["ss"] <- as.POSIXct(sunset, format = "%H:%M")
79379["timestamp"] <- align.time(79379$sunrise, 60*10)
79379 <- 79379[c("timestamp", "sr", "ss")]
locsrss <- ggplot(79379, aes(x=79379$timestamp)) + geom_line(aes(y=79379$sr)) + geom_line(aes(y=79379$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 79379 2023", x = "Datum", y = "Zeit")
pdf("79379_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="79379_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
79379["Sonnenaufgang"] <- strftime(79379$sr, format="%H:%M")
79379["Sonnenuntergang"] <- strftime(79379$ss, format="%H:%M")
write.table(79379, file="79379_SaSu.csv", dec=',', sep=';', row.names=FALSE)