library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
22083 <- sunrise.set(53.5798405,10.029462700000067, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 22083$sunrise
sunset <- 22083$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
22083["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
22083["ss"] <- as.POSIXct(sunset, format = "%H:%M")
22083["timestamp"] <- align.time(22083$sunrise, 60*10)
22083 <- 22083[c("timestamp", "sr", "ss")]
locsrss <- ggplot(22083, aes(x=22083$timestamp)) + geom_line(aes(y=22083$sr)) + geom_line(aes(y=22083$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 22083 2024", x = "Datum", y = "Zeit")
pdf("22083_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="22083_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
22083["Sonnenaufgang"] <- strftime(22083$sr, format="%H:%M")
22083["Sonnenuntergang"] <- strftime(22083$ss, format="%H:%M")
write.table(22083, file="22083_SaSu.csv", dec=',', sep=';', row.names=FALSE)