library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
91052 <- sunrise.set(49.578886999302334,11.009759902954102, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 91052$sunrise
sunset <- 91052$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
91052["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
91052["ss"] <- as.POSIXct(sunset, format = "%H:%M")
91052["timestamp"] <- align.time(91052$sunrise, 60*10)
91052 <- 91052[c("timestamp", "sr", "ss")]
locsrss <- ggplot(91052, aes(x=91052$timestamp)) + geom_line(aes(y=91052$sr)) + geom_line(aes(y=91052$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 91052 2024", x = "Datum", y = "Zeit")
pdf("91052_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="91052_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
91052["Sonnenaufgang"] <- strftime(91052$sr, format="%H:%M")
91052["Sonnenuntergang"] <- strftime(91052$ss, format="%H:%M")
write.table(91052, file="91052_SaSu.csv", dec=',', sep=';', row.names=FALSE)