library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
78166 <- sunrise.set(47.96308873956989,8.47294807434082, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 78166$sunrise
sunset <- 78166$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
78166["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
78166["ss"] <- as.POSIXct(sunset, format = "%H:%M")
78166["timestamp"] <- align.time(78166$sunrise, 60*10)
78166 <- 78166[c("timestamp", "sr", "ss")]
locsrss <- ggplot(78166, aes(x=78166$timestamp)) + geom_line(aes(y=78166$sr)) + geom_line(aes(y=78166$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 78166 2024", x = "Datum", y = "Zeit")
pdf("78166_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="78166_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
78166["Sonnenaufgang"] <- strftime(78166$sr, format="%H:%M")
78166["Sonnenuntergang"] <- strftime(78166$ss, format="%H:%M")
write.table(78166, file="78166_SaSu.csv", dec=',', sep=';', row.names=FALSE)