library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
06429 <- sunrise.set(51.8449276,11.7801268, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 06429$sunrise
sunset <- 06429$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
06429["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
06429["ss"] <- as.POSIXct(sunset, format = "%H:%M")
06429["timestamp"] <- align.time(06429$sunrise, 60*10)
06429 <- 06429[c("timestamp", "sr", "ss")]
locsrss <- ggplot(06429, aes(x=06429$timestamp)) + geom_line(aes(y=06429$sr)) + geom_line(aes(y=06429$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 06429 2023", x = "Datum", y = "Zeit")
pdf("06429_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="06429_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
06429["Sonnenaufgang"] <- strftime(06429$sr, format="%H:%M")
06429["Sonnenuntergang"] <- strftime(06429$ss, format="%H:%M")
write.table(06429, file="06429_SaSu.csv", dec=',', sep=';', row.names=FALSE)