library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
74219 <- sunrise.set(49.32297070000001,9.349578999999949, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 74219$sunrise
sunset <- 74219$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
74219["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
74219["ss"] <- as.POSIXct(sunset, format = "%H:%M")
74219["timestamp"] <- align.time(74219$sunrise, 60*10)
74219 <- 74219[c("timestamp", "sr", "ss")]
locsrss <- ggplot(74219, aes(x=74219$timestamp)) + geom_line(aes(y=74219$sr)) + geom_line(aes(y=74219$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 74219 2023", x = "Datum", y = "Zeit")
pdf("74219_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="74219_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
74219["Sonnenaufgang"] <- strftime(74219$sr, format="%H:%M")
74219["Sonnenuntergang"] <- strftime(74219$ss, format="%H:%M")
write.table(74219, file="74219_SaSu.csv", dec=',', sep=';', row.names=FALSE)