library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
67363 <- sunrise.set(49.2446147,8.2735222, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 67363$sunrise
sunset <- 67363$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
67363["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
67363["ss"] <- as.POSIXct(sunset, format = "%H:%M")
67363["timestamp"] <- align.time(67363$sunrise, 60*10)
67363 <- 67363[c("timestamp", "sr", "ss")]
locsrss <- ggplot(67363, aes(x=67363$timestamp)) + geom_line(aes(y=67363$sr)) + geom_line(aes(y=67363$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 67363 2024", x = "Datum", y = "Zeit")
pdf("67363_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="67363_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
67363["Sonnenaufgang"] <- strftime(67363$sr, format="%H:%M")
67363["Sonnenuntergang"] <- strftime(67363$ss, format="%H:%M")
write.table(67363, file="67363_SaSu.csv", dec=',', sep=';', row.names=FALSE)