library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
De,_W��rrstadt <- sunrise.set(49.8423554,8.116063599999961, "2023/01/01", timezone="MET", num.days=370)
sunrise <- De,_W��rrstadt$sunrise
sunset <- De,_W��rrstadt$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
De,_W��rrstadt["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
De,_W��rrstadt["ss"] <- as.POSIXct(sunset, format = "%H:%M")
De,_W��rrstadt["timestamp"] <- align.time(De,_W��rrstadt$sunrise, 60*10)
De,_W��rrstadt <- De,_W��rrstadt[c("timestamp", "sr", "ss")]
locsrss <- ggplot(De,_W��rrstadt, aes(x=De,_W��rrstadt$timestamp)) + geom_line(aes(y=De,_W��rrstadt$sr)) + geom_line(aes(y=De,_W��rrstadt$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - De,_W��rrstadt 2023", x = "Datum", y = "Zeit")
pdf("De,_W��rrstadt_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="De,_W��rrstadt_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
De,_W��rrstadt["Sonnenaufgang"] <- strftime(De,_W��rrstadt$sr, format="%H:%M")
De,_W��rrstadt["Sonnenuntergang"] <- strftime(De,_W��rrstadt$ss, format="%H:%M")
write.table(De,_W��rrstadt, file="De,_W��rrstadt_SaSu.csv", dec=',', sep=';', row.names=FALSE)