library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
1160 <- sunrise.set(55.6783559,12.5774005, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 1160$sunrise
sunset <- 1160$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
1160["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
1160["ss"] <- as.POSIXct(sunset, format = "%H:%M")
1160["timestamp"] <- align.time(1160$sunrise, 60*10)
1160 <- 1160[c("timestamp", "sr", "ss")]
locsrss <- ggplot(1160, aes(x=1160$timestamp)) + geom_line(aes(y=1160$sr)) + geom_line(aes(y=1160$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 1160 2023", x = "Datum", y = "Zeit")
pdf("1160_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="1160_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
1160["Sonnenaufgang"] <- strftime(1160$sr, format="%H:%M")
1160["Sonnenuntergang"] <- strftime(1160$ss, format="%H:%M")
write.table(1160, file="1160_SaSu.csv", dec=',', sep=';', row.names=FALSE)