library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
55128 <- sunrise.set(49.968576769380896,8.240214483544909, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 55128$sunrise
sunset <- 55128$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
55128["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
55128["ss"] <- as.POSIXct(sunset, format = "%H:%M")
55128["timestamp"] <- align.time(55128$sunrise, 60*10)
55128 <- 55128[c("timestamp", "sr", "ss")]
locsrss <- ggplot(55128, aes(x=55128$timestamp)) + geom_line(aes(y=55128$sr)) + geom_line(aes(y=55128$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 55128 2023", x = "Datum", y = "Zeit")
pdf("55128_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="55128_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
55128["Sonnenaufgang"] <- strftime(55128$sr, format="%H:%M")
55128["Sonnenuntergang"] <- strftime(55128$ss, format="%H:%M")
write.table(55128, file="55128_SaSu.csv", dec=',', sep=';', row.names=FALSE)