'update'

[talweg.git] / pkg / R / plot.R

diff --git a/pkg/R/plot.R b/pkg/R/plot.R
index 52b077b..fe2fb4e 100644 (file)
--- a/pkg/R/plot.R
+++ b/pkg/R/plot.R
@@ -1,8 +1,8 @@
 #' Plot curves
 #'
-#' Plot a range of curves in data
+#' Plot a range of curves in data.
 #'
-#' @param data Object of class Data
+#' @inheritParams computeError
 #' @param indices Range of indices (integers or dates)
 #'
 #' @export
@@ -22,14 +22,14 @@ plotCurves <- function(data, indices=seq_len(data$getSize()))
 
 #' Plot error
 #'
-#' Draw error graphs, potentially from several runs of \code{computeForecast}
+#' Draw error graphs, potentially from several runs of \code{computeForecast()}.
 #'
-#' @param err Error as returned by \code{computeError}
+#' @param err Error as returned by \code{computeError()}
 #' @param cols Colors for each error (default: 1,2,3,...)
 #'
 #' @seealso \code{\link{plotCurves}}, \code{\link{plotPredReal}},
-#'   \code{\link{plotSimils}}, \code{\link{plotFbox}},
-#'   \code{\link{computeFilaments}, }\code{\link{plotFilamentsBox}}, \code{\link{plotRelVar}}
+#'   \code{\link{plotSimils}}, \code{\link{plotFbox}}, \code{\link{computeFilaments}},
+#'   \code{\link{plotFilamentsBox}}, \code{\link{plotRelVar}}
 #'
 #' @export
 plotError <- function(err, cols=seq_along(err))
@@ -74,18 +74,17 @@ plotError <- function(err, cols=seq_along(err))
 
 #' Plot measured / predicted
 #'
-#' Plot measured curve (in black) and predicted curve (in blue)
+#' Plot measured curve (in black) and predicted curve (in blue).
 #'
-#' @param data Object return by \code{getData}
-#' @param pred Object as returned by \code{computeForecast}
+#' @inheritParams computeError
 #' @param index Index in forecasts (integer or date)
 #'
 #' @export
 plotPredReal <- function(data, pred, index)
 {
-       horizon = length(pred$getSerie(1))
+       horizon = length(pred$getForecast(1))
        measure = data$getSerie( pred$getIndexInData(index)+1 )[1:horizon]
-       prediction = pred$getSerie(index)
+       prediction = pred$getForecast(index)
        yrange = range(measure, prediction)
        par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=3)
        plot(measure, type="l", ylim=yrange, xlab="Time (hours)", ylab="PM10")
@@ -95,9 +94,9 @@ plotPredReal <- function(data, pred, index)
 
 #' Plot similarities
 #'
-#' Plot histogram of similarities (weights)
+#' Plot histogram of similarities (weights), for 'Neighbors' method.
 #'
-#' @param pred Object as returned by \code{computeForecast}
+#' @inheritParams computeError
 #' @param index Index in forecasts (integer or date)
 #'
 #' @export
@@ -112,10 +111,10 @@ plotSimils <- function(pred, index)
 
 #' Functional boxplot
 #'
-#' Draw the functional boxplot on the left, and bivariate plot on the right
+#' Draw the functional boxplot on the left, and bivariate plot on the right.
 #'
-#' @param data Object return by \code{getData}
-#' @param indices integer or date indices to process
+#' @inheritParams computeError
+#' @inheritParams plotCurves
 #'
 #' @export
 plotFbox <- function(data, indices=seq_len(data$getSize()))
@@ -138,10 +137,10 @@ plotFbox <- function(data, indices=seq_len(data$getSize()))
 
 #' Compute filaments
 #'
-#' Get similar days in the past, as black as distances are small
+#' Obtain similar days in the past, and (optionally) plot them -- as black as distances
+#' are small.
 #'
-#' @param data Object as returned by \code{getData}
-#' @param pred Object of class Forecast
+#' @inheritParams computeError
 #' @param index Index in forecast (integer or date)
 #' @param limit Number of neighbors to consider
 #' @param plot Should the result be plotted?
@@ -175,7 +174,8 @@ computeFilaments <- function(data, pred, index, limit=60, plot=TRUE)
                centered_series = rbind(
                        data$getCenteredSeries( pred$getParams(index)$indices ),
                        data$getCenteredSeries( pred$getParams(index)$indices+1 ) )
-               yrange = range( ref_serie, quantile(centered_series, probs=c(0.025,0.975), na.rm=TRUE) )
+               yrange = range( ref_serie,
+                       quantile(centered_series, probs=c(0.025,0.975), na.rm=TRUE) )
                par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=2)
                for (i in nn:1)
                {
@@ -196,9 +196,9 @@ computeFilaments <- function(data, pred, index, limit=60, plot=TRUE)
 
 #' Functional boxplot on filaments
 #'
-#' Draw the functional boxplot on filaments obtained by \code{computeFilaments}
+#' Draw the functional boxplot on filaments obtained by \code{computeFilaments()}.
 #'
-#' @param data Object return by \code{getData}
+#' @inheritParams computeError
 #' @param fil Output of \code{computeFilaments}
 #'
 #' @export
@@ -214,7 +214,7 @@ plotFilamentsBox = function(data, fil)
        rainbow::fboxplot(series_fds, "functional", "hdr", xlab="Time (hours)", ylab="PM10",
                plotlegend=FALSE, lwd=2)
 
-       # "Magic" found at http://stackoverflow.com/questions/13842560/get-xlim-from-a-plot-in-r
+       # "Magic": http://stackoverflow.com/questions/13842560/get-xlim-from-a-plot-in-r
        usr <- par("usr")
        yr <- (usr[4] - usr[3]) / 27
        par(new=TRUE)
@@ -226,18 +226,20 @@ plotFilamentsBox = function(data, fil)
 #' Plot relative conditional variability / absolute variability
 #'
 #' Draw the relative conditional variability / absolute variability based on filaments
-#' obtained by \code{computeFilaments}
+#' obtained by \code{computeFilaments()}.
 #'
-#' @param data Object return by \code{getData}
-#' @param fil Output of \code{computeFilaments}
+#' @inheritParams computeError
+#' @inheritParams plotFilamentsBox
 #'
 #' @export
 plotRelVar = function(data, fil)
 {
        ref_var = c( apply(data$getSeries(fil$neighb_indices),1,sd),
                apply(data$getSeries(fil$neighb_indices+1),1,sd) )
-       fdays = getNoNA2(data, 1, fil$index-1)
-       global_var = c( apply(data$getSeries(fdays),1,sd), apply(data$getSeries(fdays+1),1,sd) )
+       fdays = .getNoNA2(data, 1, fil$index-1)
+       global_var = c(
+               apply(data$getSeries(fdays),1,sd),
+               apply(data$getSeries(fdays+1),1,sd) )
 
        yrange = range(ref_var, global_var)
        par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)