library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Abano_terme <- sunrise.set(45.3587173,11.7882998, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Abano_terme$sunrise
sunset <- Abano_terme$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Abano_terme["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Abano_terme["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Abano_terme["timestamp"] <- align.time(Abano_terme$sunrise, 60*10)
Abano_terme <- Abano_terme[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Abano_terme, aes(x=Abano_terme$timestamp)) + geom_line(aes(y=Abano_terme$sr)) + geom_line(aes(y=Abano_terme$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Abano_terme 2024", x = "Datum", y = "Zeit")
pdf("Abano_terme_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Abano_terme_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Abano_terme["Sonnenaufgang"] <- strftime(Abano_terme$sr, format="%H:%M")
Abano_terme["Sonnenuntergang"] <- strftime(Abano_terme$ss, format="%H:%M")
write.table(Abano_terme, file="Abano_terme_SaSu.csv", dec=',', sep=';', row.names=FALSE)