library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
22145 <- sunrise.set(53.6154895,10.2206985, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 22145$sunrise
sunset <- 22145$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
22145["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
22145["ss"] <- as.POSIXct(sunset, format = "%H:%M")
22145["timestamp"] <- align.time(22145$sunrise, 60*10)
22145 <- 22145[c("timestamp", "sr", "ss")]
locsrss <- ggplot(22145, aes(x=22145$timestamp)) + geom_line(aes(y=22145$sr)) + geom_line(aes(y=22145$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 22145 2024", x = "Datum", y = "Zeit")
pdf("22145_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="22145_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
22145["Sonnenaufgang"] <- strftime(22145$sr, format="%H:%M")
22145["Sonnenuntergang"] <- strftime(22145$ss, format="%H:%M")
write.table(22145, file="22145_SaSu.csv", dec=',', sep=';', row.names=FALSE)