library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
66484 <- sunrise.set(49.193356156245315,7.452890765631395, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 66484$sunrise
sunset <- 66484$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
66484["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
66484["ss"] <- as.POSIXct(sunset, format = "%H:%M")
66484["timestamp"] <- align.time(66484$sunrise, 60*10)
66484 <- 66484[c("timestamp", "sr", "ss")]
locsrss <- ggplot(66484, aes(x=66484$timestamp)) + geom_line(aes(y=66484$sr)) + geom_line(aes(y=66484$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 66484 2024", x = "Datum", y = "Zeit")
pdf("66484_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="66484_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
66484["Sonnenaufgang"] <- strftime(66484$sr, format="%H:%M")
66484["Sonnenuntergang"] <- strftime(66484$ss, format="%H:%M")
write.table(66484, file="66484_SaSu.csv", dec=',', sep=';', row.names=FALSE)