library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Den_Haag <- sunrise.set(52.0704978,4.3006999, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Den_Haag$sunrise
sunset <- Den_Haag$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Den_Haag["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Den_Haag["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Den_Haag["timestamp"] <- align.time(Den_Haag$sunrise, 60*10)
Den_Haag <- Den_Haag[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Den_Haag, aes(x=Den_Haag$timestamp)) + geom_line(aes(y=Den_Haag$sr)) + geom_line(aes(y=Den_Haag$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Den_Haag 2024", x = "Datum", y = "Zeit")
pdf("Den_Haag_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Den_Haag_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Den_Haag["Sonnenaufgang"] <- strftime(Den_Haag$sr, format="%H:%M")
Den_Haag["Sonnenuntergang"] <- strftime(Den_Haag$ss, format="%H:%M")
write.table(Den_Haag, file="Den_Haag_SaSu.csv", dec=',', sep=';', row.names=FALSE)