#' @param date_format How date/time are stored (e.g. year/month/day hour:minutes;
#' see \code{strptime})
#' @param working_tz Timezone to work with ("GMT" or e.g. "Europe/Paris")
-#' @param predict_at When does the prediction take place ? ab[:cd][:ef] where a,b,c,d,e,f
-#' in (0,9) and define an hour[minute[second]]; time must be present in the file
+#' @param predict_at When does the prediction take place ? Integer, in hours. Default: 0
#'
#' @return An object of class Data
#'
#' @export
getData = function(ts_data, exo_data,
- input_tz="GMT", date_format="%d/%m/%Y %H:%M", working_tz="GMT", predict_at="00")
+ input_tz="GMT", date_format="%d/%m/%Y %H:%M", working_tz="GMT", predict_at=0)
{
# Sanity checks (not full, but sufficient at this stage)
if (!is.character(input_tz) || !is.character(working_tz))
stop("Bad time-series input (data frame or CSV file)")
if (is.character(ts_data))
ts_data = ts_data[1]
- pattern_index_in_predict_at = grep("^[0-9]{2}(:[0-9]{2}){0,2}$", predict_at)
- if (!is.character(predict_at) || length(pattern_index_in_predict_at) == 0)
- stop("Bad predict_at ( ^[0-9]{2}(:[0-9]{2}){0,2}$ )")
- predict_at = predict_at[ pattern_index_in_predict_at[1] ]
+ predict_at = as.integer(predict_at)[1]
+ if (predict_at<0 || predict_at>23)
+ stop("Bad predict_at (0-23)")
if (!is.character(date_format))
stop("Bad date_format (character)")
date_format = date_format[1]
formatted_dates_POSIXlt = strptime(as.character(ts_df[,1]), date_format, tz=input_tz)
ts_df[,1] = format(as.POSIXct(formatted_dates_POSIXlt), tz=working_tz, usetz=TRUE)
- if (nchar(predict_at) == 2)
- predict_at = paste(predict_at,":00",sep="")
- if (nchar(predict_at) == 5)
- predict_at = paste(predict_at,":00",sep="")
-
line = 1 #index in PM10 file (24 lines for 1 cell)
nb_lines = nrow(ts_df)
nb_exos = ( ncol(exo_df) - 1 ) / 2
{
time = c()
serie = c()
- repeat {
- {
- time = c(time, ts_df[line,1])
- serie = c(serie, ts_df[line,2])
- line = line + 1
- };
- if (line >= nb_lines + 1
- # NOTE: always second part of date/time, because it has been formatted
- || strsplit(as.character(ts_df[line-1,1])," ")[[1]][2] == predict_at)
+ repeat
{
- break
- }}
+ {
+ time = c(time, ts_df[line,1])
+ serie = c(serie, ts_df[line,2])
+ line = line + 1
+ };
+ if (line >= nb_lines + 1 || as.POSIXlt(ts_df[line-1,1])$hour == predict_at)
+ break
+ }
# NOTE: if predict_at does not cut days at midnight,
# for the exogenous to be synchronized they need to be shifted
- if (predict_at != "00:00:00")
+ if (predict_at > 0)
{
exo_hat = as.data.frame(exo_df[max(1,i-1),(1+nb_exos+1):(1+2*nb_exos)])
exo_Dm1 = if (i>=3) as.data.frame(exo_df[i-1,2:(1+nb_exos)]) else NA