library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
26789_Leer <- sunrise.set(53.235657,7.4679018, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 26789_Leer$sunrise
sunset <- 26789_Leer$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
26789_Leer["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
26789_Leer["ss"] <- as.POSIXct(sunset, format = "%H:%M")
26789_Leer["timestamp"] <- align.time(26789_Leer$sunrise, 60*10)
26789_Leer <- 26789_Leer[c("timestamp", "sr", "ss")]
locsrss <- ggplot(26789_Leer, aes(x=26789_Leer$timestamp)) + geom_line(aes(y=26789_Leer$sr)) + geom_line(aes(y=26789_Leer$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 26789_Leer 2024", x = "Datum", y = "Zeit")
pdf("26789_Leer_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="26789_Leer_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
26789_Leer["Sonnenaufgang"] <- strftime(26789_Leer$sr, format="%H:%M")
26789_Leer["Sonnenuntergang"] <- strftime(26789_Leer$ss, format="%H:%M")
write.table(26789_Leer, file="26789_Leer_SaSu.csv", dec=',', sep=';', row.names=FALSE)