library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Bremerv��rde <- sunrise.set(53.4871321,9.139978499999984, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Bremerv��rde$sunrise
sunset <- Bremerv��rde$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Bremerv��rde["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Bremerv��rde["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Bremerv��rde["timestamp"] <- align.time(Bremerv��rde$sunrise, 60*10)
Bremerv��rde <- Bremerv��rde[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Bremerv��rde, aes(x=Bremerv��rde$timestamp)) + geom_line(aes(y=Bremerv��rde$sr)) + geom_line(aes(y=Bremerv��rde$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Bremerv��rde 2023", x = "Datum", y = "Zeit")
pdf("Bremerv��rde_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Bremerv��rde_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Bremerv��rde["Sonnenaufgang"] <- strftime(Bremerv��rde$sr, format="%H:%M")
Bremerv��rde["Sonnenuntergang"] <- strftime(Bremerv��rde$ss, format="%H:%M")
write.table(Bremerv��rde, file="Bremerv��rde_SaSu.csv", dec=',', sep=';', row.names=FALSE)