library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
86157 <- sunrise.set(48.36095413690657,10.867152214050293, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 86157$sunrise
sunset <- 86157$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
86157["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
86157["ss"] <- as.POSIXct(sunset, format = "%H:%M")
86157["timestamp"] <- align.time(86157$sunrise, 60*10)
86157 <- 86157[c("timestamp", "sr", "ss")]
locsrss <- ggplot(86157, aes(x=86157$timestamp)) + geom_line(aes(y=86157$sr)) + geom_line(aes(y=86157$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 86157 2024", x = "Datum", y = "Zeit")
pdf("86157_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="86157_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
86157["Sonnenaufgang"] <- strftime(86157$sr, format="%H:%M")
86157["Sonnenuntergang"] <- strftime(86157$ss, format="%H:%M")
write.table(86157, file="86157_SaSu.csv", dec=',', sep=';', row.names=FALSE)