library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
10629 <- sunrise.set(52.5018362,13.3026692, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 10629$sunrise
sunset <- 10629$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
10629["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
10629["ss"] <- as.POSIXct(sunset, format = "%H:%M")
10629["timestamp"] <- align.time(10629$sunrise, 60*10)
10629 <- 10629[c("timestamp", "sr", "ss")]
locsrss <- ggplot(10629, aes(x=10629$timestamp)) + geom_line(aes(y=10629$sr)) + geom_line(aes(y=10629$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 10629 2024", x = "Datum", y = "Zeit")
pdf("10629_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="10629_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
10629["Sonnenaufgang"] <- strftime(10629$sr, format="%H:%M")
10629["Sonnenuntergang"] <- strftime(10629$ss, format="%H:%M")
write.table(10629, file="10629_SaSu.csv", dec=',', sep=';', row.names=FALSE)