library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
02943 <- sunrise.set(51.4269314,14.5988026, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 02943$sunrise
sunset <- 02943$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
02943["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
02943["ss"] <- as.POSIXct(sunset, format = "%H:%M")
02943["timestamp"] <- align.time(02943$sunrise, 60*10)
02943 <- 02943[c("timestamp", "sr", "ss")]
locsrss <- ggplot(02943, aes(x=02943$timestamp)) + geom_line(aes(y=02943$sr)) + geom_line(aes(y=02943$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 02943 2024", x = "Datum", y = "Zeit")
pdf("02943_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="02943_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
02943["Sonnenaufgang"] <- strftime(02943$sr, format="%H:%M")
02943["Sonnenuntergang"] <- strftime(02943$ss, format="%H:%M")
write.table(02943, file="02943_SaSu.csv", dec=',', sep=';', row.names=FALSE)