library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
02994 <- sunrise.set(51.373395,14.067913299999987, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 02994$sunrise
sunset <- 02994$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
02994["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
02994["ss"] <- as.POSIXct(sunset, format = "%H:%M")
02994["timestamp"] <- align.time(02994$sunrise, 60*10)
02994 <- 02994[c("timestamp", "sr", "ss")]
locsrss <- ggplot(02994, aes(x=02994$timestamp)) + geom_line(aes(y=02994$sr)) + geom_line(aes(y=02994$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 02994 2024", x = "Datum", y = "Zeit")
pdf("02994_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="02994_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
02994["Sonnenaufgang"] <- strftime(02994$sr, format="%H:%M")
02994["Sonnenuntergang"] <- strftime(02994$ss, format="%H:%M")
write.table(02994, file="02994_SaSu.csv", dec=',', sep=';', row.names=FALSE)