library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
35606_Solms <- sunrise.set(50.5362029,8.4070428, "2022/01/01", timezone="MET", num.days=370)
sunrise <- 35606_Solms$sunrise
sunset <- 35606_Solms$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
35606_Solms["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
35606_Solms["ss"] <- as.POSIXct(sunset, format = "%H:%M")
35606_Solms["timestamp"] <- align.time(35606_Solms$sunrise, 60*10)
35606_Solms <- 35606_Solms[c("timestamp", "sr", "ss")]
locsrss <- ggplot(35606_Solms, aes(x=35606_Solms$timestamp)) + geom_line(aes(y=35606_Solms$sr)) + geom_line(aes(y=35606_Solms$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 35606_Solms 2022", x = "Datum", y = "Zeit")
pdf("35606_Solms_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="35606_Solms_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
35606_Solms["Sonnenaufgang"] <- strftime(35606_Solms$sr, format="%H:%M")
35606_Solms["Sonnenuntergang"] <- strftime(35606_Solms$ss, format="%H:%M")
write.table(35606_Solms, file="35606_Solms_SaSu.csv", dec=',', sep=';', row.names=FALSE)