library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
74889 <- sunrise.set(49.24662499999999,8.8948387, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 74889$sunrise
sunset <- 74889$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
74889["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
74889["ss"] <- as.POSIXct(sunset, format = "%H:%M")
74889["timestamp"] <- align.time(74889$sunrise, 60*10)
74889 <- 74889[c("timestamp", "sr", "ss")]
locsrss <- ggplot(74889, aes(x=74889$timestamp)) + geom_line(aes(y=74889$sr)) + geom_line(aes(y=74889$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 74889 2024", x = "Datum", y = "Zeit")
pdf("74889_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="74889_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
74889["Sonnenaufgang"] <- strftime(74889$sr, format="%H:%M")
74889["Sonnenuntergang"] <- strftime(74889$ss, format="%H:%M")
write.table(74889, file="74889_SaSu.csv", dec=',', sep=';', row.names=FALSE)