library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
65428 <- sunrise.set(49.982019,8.453074, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 65428$sunrise
sunset <- 65428$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
65428["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
65428["ss"] <- as.POSIXct(sunset, format = "%H:%M")
65428["timestamp"] <- align.time(65428$sunrise, 60*10)
65428 <- 65428[c("timestamp", "sr", "ss")]
locsrss <- ggplot(65428, aes(x=65428$timestamp)) + geom_line(aes(y=65428$sr)) + geom_line(aes(y=65428$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 65428 2023", x = "Datum", y = "Zeit")
pdf("65428_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="65428_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
65428["Sonnenaufgang"] <- strftime(65428$sr, format="%H:%M")
65428["Sonnenuntergang"] <- strftime(65428$ss, format="%H:%M")
write.table(65428, file="65428_SaSu.csv", dec=',', sep=';', row.names=FALSE)