library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
12349 <- sunrise.set(52.427903,13.414976300000035, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 12349$sunrise
sunset <- 12349$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
12349["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
12349["ss"] <- as.POSIXct(sunset, format = "%H:%M")
12349["timestamp"] <- align.time(12349$sunrise, 60*10)
12349 <- 12349[c("timestamp", "sr", "ss")]
locsrss <- ggplot(12349, aes(x=12349$timestamp)) + geom_line(aes(y=12349$sr)) + geom_line(aes(y=12349$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 12349 2023", x = "Datum", y = "Zeit")
pdf("12349_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="12349_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
12349["Sonnenaufgang"] <- strftime(12349$sr, format="%H:%M")
12349["Sonnenuntergang"] <- strftime(12349$ss, format="%H:%M")
write.table(12349, file="12349_SaSu.csv", dec=',', sep=';', row.names=FALSE)