library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
94315 <- sunrise.set(48.87961871879027,12.630500793457031, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 94315$sunrise
sunset <- 94315$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
94315["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
94315["ss"] <- as.POSIXct(sunset, format = "%H:%M")
94315["timestamp"] <- align.time(94315$sunrise, 60*10)
94315 <- 94315[c("timestamp", "sr", "ss")]
locsrss <- ggplot(94315, aes(x=94315$timestamp)) + geom_line(aes(y=94315$sr)) + geom_line(aes(y=94315$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 94315 2024", x = "Datum", y = "Zeit")
pdf("94315_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="94315_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
94315["Sonnenaufgang"] <- strftime(94315$sr, format="%H:%M")
94315["Sonnenuntergang"] <- strftime(94315$ss, format="%H:%M")
write.table(94315, file="94315_SaSu.csv", dec=',', sep=';', row.names=FALSE)