library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Bad_Blankenburg <- sunrise.set(50.68522937657268,11.265192031860352, "2025/01/01", timezone="MET", num.days=370)
sunrise <- Bad_Blankenburg$sunrise
sunset <- Bad_Blankenburg$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Bad_Blankenburg["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Bad_Blankenburg["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Bad_Blankenburg["timestamp"] <- align.time(Bad_Blankenburg$sunrise, 60*10)
Bad_Blankenburg <- Bad_Blankenburg[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Bad_Blankenburg, aes(x=Bad_Blankenburg$timestamp)) + geom_line(aes(y=Bad_Blankenburg$sr)) + geom_line(aes(y=Bad_Blankenburg$ss)) + labs(title = " Sunrise/Sunset - Bad_Blankenburg 2025", x = "Date", y = "Time")
pdf("Bad_Blankenburg_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Bad_Blankenburg_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Bad_Blankenburg["Sunrise"] <- strftime(Bad_Blankenburg$sr, format="%H:%M")
Bad_Blankenburg["Sunset"] <- strftime(Bad_Blankenburg$ss, format="%H:%M")
write.table(Bad_Blankenburg, file="Bad_Blankenburg_SaSu.csv", dec=',', sep=';', row.names=FALSE)