library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
38154 <- sunrise.set(52.2732142,10.7929697, "2022/01/01", timezone="MET", num.days=370)
sunrise <- 38154$sunrise
sunset <- 38154$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
38154["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
38154["ss"] <- as.POSIXct(sunset, format = "%H:%M")
38154["timestamp"] <- align.time(38154$sunrise, 60*10)
38154 <- 38154[c("timestamp", "sr", "ss")]
locsrss <- ggplot(38154, aes(x=38154$timestamp)) + geom_line(aes(y=38154$sr)) + geom_line(aes(y=38154$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 38154 2022", x = "Datum", y = "Zeit")
pdf("38154_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="38154_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
38154["Sonnenaufgang"] <- strftime(38154$sr, format="%H:%M")
38154["Sonnenuntergang"] <- strftime(38154$ss, format="%H:%M")
write.table(38154, file="38154_SaSu.csv", dec=',', sep=';', row.names=FALSE)