library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
55497 <- sunrise.set(49.98351592552864,7.64279913862306, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 55497$sunrise
sunset <- 55497$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
55497["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
55497["ss"] <- as.POSIXct(sunset, format = "%H:%M")
55497["timestamp"] <- align.time(55497$sunrise, 60*10)
55497 <- 55497[c("timestamp", "sr", "ss")]
locsrss <- ggplot(55497, aes(x=55497$timestamp)) + geom_line(aes(y=55497$sr)) + geom_line(aes(y=55497$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 55497 2024", x = "Datum", y = "Zeit")
pdf("55497_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="55497_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
55497["Sonnenaufgang"] <- strftime(55497$sr, format="%H:%M")
55497["Sonnenuntergang"] <- strftime(55497$ss, format="%H:%M")
write.table(55497, file="55497_SaSu.csv", dec=',', sep=';', row.names=FALSE)