library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Donsieders <- sunrise.set(49.2651645,7.6414464, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Donsieders$sunrise
sunset <- Donsieders$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Donsieders["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Donsieders["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Donsieders["timestamp"] <- align.time(Donsieders$sunrise, 60*10)
Donsieders <- Donsieders[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Donsieders, aes(x=Donsieders$timestamp)) + geom_line(aes(y=Donsieders$sr)) + geom_line(aes(y=Donsieders$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Donsieders 2024", x = "Datum", y = "Zeit")
pdf("Donsieders_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Donsieders_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Donsieders["Sonnenaufgang"] <- strftime(Donsieders$sr, format="%H:%M")
Donsieders["Sonnenuntergang"] <- strftime(Donsieders$ss, format="%H:%M")
write.table(Donsieders, file="Donsieders_SaSu.csv", dec=',', sep=';', row.names=FALSE)