library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
80939_Mnchen <- sunrise.set(48.201196,11.614567699999952, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 80939_Mnchen$sunrise
sunset <- 80939_Mnchen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
80939_Mnchen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
80939_Mnchen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
80939_Mnchen["timestamp"] <- align.time(80939_Mnchen$sunrise, 60*10)
80939_Mnchen <- 80939_Mnchen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(80939_Mnchen, aes(x=80939_Mnchen$timestamp)) + geom_line(aes(y=80939_Mnchen$sr)) + geom_line(aes(y=80939_Mnchen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 80939_Mnchen 2023", x = "Datum", y = "Zeit")
pdf("80939_Mnchen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="80939_Mnchen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
80939_Mnchen["Sonnenaufgang"] <- strftime(80939_Mnchen$sr, format="%H:%M")
80939_Mnchen["Sonnenuntergang"] <- strftime(80939_Mnchen$ss, format="%H:%M")
write.table(80939_Mnchen, file="80939_Mnchen_SaSu.csv", dec=',', sep=';', row.names=FALSE)