library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
19395_Karow <- sunrise.set(53.538081,12.262699699999985, "2023/01/01", timezone="MET", num.days=370)
sunrise <- 19395_Karow$sunrise
sunset <- 19395_Karow$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
19395_Karow["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
19395_Karow["ss"] <- as.POSIXct(sunset, format = "%H:%M")
19395_Karow["timestamp"] <- align.time(19395_Karow$sunrise, 60*10)
19395_Karow <- 19395_Karow[c("timestamp", "sr", "ss")]
locsrss <- ggplot(19395_Karow, aes(x=19395_Karow$timestamp)) + geom_line(aes(y=19395_Karow$sr)) + geom_line(aes(y=19395_Karow$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 19395_Karow 2023", x = "Datum", y = "Zeit")
pdf("19395_Karow_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="19395_Karow_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
19395_Karow["Sonnenaufgang"] <- strftime(19395_Karow$sr, format="%H:%M")
19395_Karow["Sonnenuntergang"] <- strftime(19395_Karow$ss, format="%H:%M")
write.table(19395_Karow, file="19395_Karow_SaSu.csv", dec=',', sep=';', row.names=FALSE)