library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
29459 <- sunrise.set(52.93572,10.954806100000042, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 29459$sunrise
sunset <- 29459$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
29459["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
29459["ss"] <- as.POSIXct(sunset, format = "%H:%M")
29459["timestamp"] <- align.time(29459$sunrise, 60*10)
29459 <- 29459[c("timestamp", "sr", "ss")]
locsrss <- ggplot(29459, aes(x=29459$timestamp)) + geom_line(aes(y=29459$sr)) + geom_line(aes(y=29459$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 29459 2024", x = "Datum", y = "Zeit")
pdf("29459_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="29459_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
29459["Sonnenaufgang"] <- strftime(29459$sr, format="%H:%M")
29459["Sonnenuntergang"] <- strftime(29459$ss, format="%H:%M")
write.table(29459, file="29459_SaSu.csv", dec=',', sep=';', row.names=FALSE)