library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
92360 <- sunrise.set(49.1756443,11.4264509, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 92360$sunrise
sunset <- 92360$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
92360["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
92360["ss"] <- as.POSIXct(sunset, format = "%H:%M")
92360["timestamp"] <- align.time(92360$sunrise, 60*10)
92360 <- 92360[c("timestamp", "sr", "ss")]
locsrss <- ggplot(92360, aes(x=92360$timestamp)) + geom_line(aes(y=92360$sr)) + geom_line(aes(y=92360$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 92360 2024", x = "Datum", y = "Zeit")
pdf("92360_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="92360_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
92360["Sonnenaufgang"] <- strftime(92360$sr, format="%H:%M")
92360["Sonnenuntergang"] <- strftime(92360$ss, format="%H:%M")
write.table(92360, file="92360_SaSu.csv", dec=',', sep=';', row.names=FALSE)