library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
29331 <- sunrise.set(52.61445089174273,10.24755369475099, "2022/01/01", timezone="MET", num.days=370)
sunrise <- 29331$sunrise
sunset <- 29331$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
29331["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
29331["ss"] <- as.POSIXct(sunset, format = "%H:%M")
29331["timestamp"] <- align.time(29331$sunrise, 60*10)
29331 <- 29331[c("timestamp", "sr", "ss")]
locsrss <- ggplot(29331, aes(x=29331$timestamp)) + geom_line(aes(y=29331$sr)) + geom_line(aes(y=29331$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 29331 2022", x = "Datum", y = "Zeit")
pdf("29331_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="29331_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
29331["Sonnenaufgang"] <- strftime(29331$sr, format="%H:%M")
29331["Sonnenuntergang"] <- strftime(29331$ss, format="%H:%M")
write.table(29331, file="29331_SaSu.csv", dec=',', sep=';', row.names=FALSE)