library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
26605 <- sunrise.set(53.4668022,7.5382334, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 26605$sunrise
sunset <- 26605$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
26605["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
26605["ss"] <- as.POSIXct(sunset, format = "%H:%M")
26605["timestamp"] <- align.time(26605$sunrise, 60*10)
26605 <- 26605[c("timestamp", "sr", "ss")]
locsrss <- ggplot(26605, aes(x=26605$timestamp)) + geom_line(aes(y=26605$sr)) + geom_line(aes(y=26605$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 26605 2023", x = "Datum", y = "Zeit")
pdf("26605_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="26605_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
26605["Sonnenaufgang"] <- strftime(26605$sr, format="%H:%M")
26605["Sonnenuntergang"] <- strftime(26605$ss, format="%H:%M")
write.table(26605, file="26605_SaSu.csv", dec=',', sep=';', row.names=FALSE)