library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
12437 <- sunrise.set(52.4609077,13.481547399999954, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 12437$sunrise
sunset <- 12437$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
12437["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
12437["ss"] <- as.POSIXct(sunset, format = "%H:%M")
12437["timestamp"] <- align.time(12437$sunrise, 60*10)
12437 <- 12437[c("timestamp", "sr", "ss")]
locsrss <- ggplot(12437, aes(x=12437$timestamp)) + geom_line(aes(y=12437$sr)) + geom_line(aes(y=12437$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 12437 2023", x = "Datum", y = "Zeit")
pdf("12437_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="12437_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
12437["Sonnenaufgang"] <- strftime(12437$sr, format="%H:%M")
12437["Sonnenuntergang"] <- strftime(12437$ss, format="%H:%M")
write.table(12437, file="12437_SaSu.csv", dec=',', sep=';', row.names=FALSE)