library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
86161 <- sunrise.set(48.3459285,10.9160825, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 86161$sunrise
sunset <- 86161$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
86161["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
86161["ss"] <- as.POSIXct(sunset, format = "%H:%M")
86161["timestamp"] <- align.time(86161$sunrise, 60*10)
86161 <- 86161[c("timestamp", "sr", "ss")]
locsrss <- ggplot(86161, aes(x=86161$timestamp)) + geom_line(aes(y=86161$sr)) + geom_line(aes(y=86161$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 86161 2024", x = "Datum", y = "Zeit")
pdf("86161_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="86161_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
86161["Sonnenaufgang"] <- strftime(86161$sr, format="%H:%M")
86161["Sonnenuntergang"] <- strftime(86161$ss, format="%H:%M")
write.table(86161, file="86161_SaSu.csv", dec=',', sep=';', row.names=FALSE)