library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
91629 <- sunrise.set(49.3570194,10.6079594, "2025/01/01", timezone="MET", num.days=370)
sunrise <- 91629$sunrise
sunset <- 91629$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
91629["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
91629["ss"] <- as.POSIXct(sunset, format = "%H:%M")
91629["timestamp"] <- align.time(91629$sunrise, 60*10)
91629 <- 91629[c("timestamp", "sr", "ss")]
locsrss <- ggplot(91629, aes(x=91629$timestamp)) + geom_line(aes(y=91629$sr)) + geom_line(aes(y=91629$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 91629 2025", x = "Datum", y = "Zeit")
pdf("91629_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="91629_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
91629["Sonnenaufgang"] <- strftime(91629$sr, format="%H:%M")
91629["Sonnenuntergang"] <- strftime(91629$ss, format="%H:%M")
write.table(91629, file="91629_SaSu.csv", dec=',', sep=';', row.names=FALSE)