library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
92334_Berching <- sunrise.set(49.10522049999999,11.44240220000006, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 92334_Berching$sunrise
sunset <- 92334_Berching$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
92334_Berching["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
92334_Berching["ss"] <- as.POSIXct(sunset, format = "%H:%M")
92334_Berching["timestamp"] <- align.time(92334_Berching$sunrise, 60*10)
92334_Berching <- 92334_Berching[c("timestamp", "sr", "ss")]
locsrss <- ggplot(92334_Berching, aes(x=92334_Berching$timestamp)) + geom_line(aes(y=92334_Berching$sr)) + geom_line(aes(y=92334_Berching$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 92334_Berching 2024", x = "Datum", y = "Zeit")
pdf("92334_Berching_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="92334_Berching_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
92334_Berching["Sonnenaufgang"] <- strftime(92334_Berching$sr, format="%H:%M")
92334_Berching["Sonnenuntergang"] <- strftime(92334_Berching$ss, format="%H:%M")
write.table(92334_Berching, file="92334_Berching_SaSu.csv", dec=',', sep=';', row.names=FALSE)