library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Bad_Sulza <- sunrise.set(51.087991,11.628562800000054, "2025/01/01", timezone="MET", num.days=370)
sunrise <- Bad_Sulza$sunrise
sunset <- Bad_Sulza$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Bad_Sulza["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Bad_Sulza["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Bad_Sulza["timestamp"] <- align.time(Bad_Sulza$sunrise, 60*10)
Bad_Sulza <- Bad_Sulza[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Bad_Sulza, aes(x=Bad_Sulza$timestamp)) + geom_line(aes(y=Bad_Sulza$sr)) + geom_line(aes(y=Bad_Sulza$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Bad_Sulza 2025", x = "Datum", y = "Zeit")
pdf("Bad_Sulza_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Bad_Sulza_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Bad_Sulza["Sonnenaufgang"] <- strftime(Bad_Sulza$sr, format="%H:%M")
Bad_Sulza["Sonnenuntergang"] <- strftime(Bad_Sulza$ss, format="%H:%M")
write.table(Bad_Sulza, file="Bad_Sulza_SaSu.csv", dec=',', sep=';', row.names=FALSE)