X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2FR%2FgetData.R;h=a4e1e17b2e1808568dc5b0dd88cbaf5f86abbb26;hb=a66a84b56467194852f2faee15f4725759b24158;hp=205ee5d516a89099b2a99aaf969d4d4c0e2d6754;hpb=6d97bfecf7310ed6682eecce1b7aa2f8185d4742;p=talweg.git diff --git a/pkg/R/getData.R b/pkg/R/getData.R index 205ee5d..a4e1e17 100644 --- a/pkg/R/getData.R +++ b/pkg/R/getData.R @@ -2,8 +2,7 @@ #' #' @description Take in input data frames and/or files containing raw data, and timezones, and #' output a Data object, roughly corresponding to a list where each cell contains all value -#' for one day (see \code{?Data}). Current limitation: series (in working_tz) must start at -#' right after midnight (to keep in sync with exogenous vars) +#' for one day (see \code{?Data}). #' #' @param ts_data Time-series, as a data frame (DB style: 2 columns, first is date/time, #' second is value) or a CSV file @@ -14,9 +13,14 @@ #' 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 ? Integer, in hours. Default: 0 +#' @param limit Number of days to extract (default: Inf, for "all") #' #' @return An object of class Data #' +#' @examples +#' ts_data = read.csv(system.file("extdata","pm10_mesures_H_loc.csv",package="talweg")) +#' exo_data = read.csv(system.file("extdata","meteo_extra_noNAs.csv",package="talweg")) +#' data = getData(ts_data, exo_data, limit=120) #' @export getData = function(ts_data, exo_data, input_tz="GMT", date_format="%d/%m/%Y %H:%M", working_tz="GMT", predict_at=0, limit=Inf) @@ -28,7 +32,7 @@ getData = function(ts_data, exo_data, input_tz="GMT", date_format="%d/%m/%Y %H:% working_tz = working_tz[1] if ( (!is.data.frame(ts_data) && !is.character(ts_data)) || (!is.data.frame(exo_data) && !is.character(exo_data)) ) - stop("Bad time-series / exogenous input (data [frame] or CSV file)") + stop("Bad time-series / exogenous input (data frame or CSV file)") if (is.character(ts_data)) ts_data = ts_data[1] if (is.character(exo_data)) @@ -41,29 +45,15 @@ getData = function(ts_data, exo_data, input_tz="GMT", date_format="%d/%m/%Y %H:% date_format = date_format[1] ts_df = - if (is.character(ts_data)) { - if (ts_data %in% data(package="talweg")$results[,"Item"]) - ts_data = - - - - - ############CONTINUE: http://r-pkgs.had.co.nz/data.html - - - - - - read.csv(ts_data) - } else { + if (is.character(ts_data)) + read.csv(ts_data) + else ts_data - } exo_df = - if (is.character(exo_data)) { + if (is.character(exo_data)) read.csv(exo_data) - } else { + else exo_data - } # Convert to the desired timezone (usually "GMT" or "Europe/Paris") formatted_dates_POSIXlt = strptime(as.character(ts_df[,1]), date_format, tz=input_tz) ts_df[,1] = format(as.POSIXct(formatted_dates_POSIXlt), tz=working_tz, usetz=TRUE) @@ -71,7 +61,7 @@ getData = function(ts_data, exo_data, input_tz="GMT", date_format="%d/%m/%Y %H:% line = 1 #index in PM10 file (24 lines for 1 cell) nb_lines = nrow(ts_df) nb_exos = ( ncol(exo_df) - 1 ) / 2 - data = list() #new("Data") + data = Data$new() i = 1 #index of a cell in data while (line <= nb_lines) { @@ -88,18 +78,21 @@ getData = function(ts_data, exo_data, input_tz="GMT", date_format="%d/%m/%Y %H:% break } - # NOTE: if predict_at does not cut days at midnight, exogenous vars need to be shifted - exo_hat = as.data.frame( exo_df[ - ifelse(predict_at>0,max(1,i-1),i) , (1+nb_exos+1):(1+2*nb_exos) ] ) - exo = as.data.frame( exo_df[ ifelse(predict_at>0,max(1,i-1),i) , 2:(1+nb_exos) ] ) + exo = as.data.frame( exo_df[i,2:(1+nb_exos)] ) + exo_hat = as.data.frame( exo_df[i,(1+nb_exos+1):(1+2*nb_exos)] ) level = mean(serie, na.rm=TRUE) centered_serie = serie - level - #data$append(time, centered_serie, level, exo_hat, exo_Jm1) #too slow; TODO: use R6 class - data[[length(data)+1]] = list("time"=time, "serie"=centered_serie, "level"=level, - "exo_hat"=exo_hat, "exo"=exo) + data$append(time, centered_serie, level, exo, exo_hat) if (i >= limit) break i = i + 1 } - new("Data",data=data) + if (length(data$getCenteredSerie(1)) < length(data$getCenteredSerie(2))) + data$removeFirst() + if (length(data$getCenteredSerie(data$getSize())) + < length(data$getCenteredSerie(data$getSize()-1))) + { + data$removeLast() + } + data }