library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
26135 <- sunrise.set(53.1208397,8.2538737, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 26135$sunrise
sunset <- 26135$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
26135["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
26135["ss"] <- as.POSIXct(sunset, format = "%H:%M")
26135["timestamp"] <- align.time(26135$sunrise, 60*10)
26135 <- 26135[c("timestamp", "sr", "ss")]
locsrss <- ggplot(26135, aes(x=26135$timestamp)) + geom_line(aes(y=26135$sr)) + geom_line(aes(y=26135$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 26135 2023", x = "Datum", y = "Zeit")
pdf("26135_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="26135_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
26135["Sonnenaufgang"] <- strftime(26135$sr, format="%H:%M")
26135["Sonnenuntergang"] <- strftime(26135$ss, format="%H:%M")
write.table(26135, file="26135_SaSu.csv", dec=',', sep=';', row.names=FALSE)