TODO: check my plots, re-run reports with relative variability
[talweg.git] / pkg / R / plot.R
CommitLineData
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1#' @title plot curves
2#'
3#' @description Plot a range of curves in data
4#'
5#' @param data Object of class Data
6#' @param indices Range of indices (integers or dates)
7#'
8#' @export
9plotCurves <- function(data, indices)
10{
fa8078f9 11 yrange = quantile( range( sapply( indices, function(i) {
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12 serie = c(data$getCenteredSerie(i))
13 if (!all(is.na(serie)))
14 range(serie, na.rm=TRUE)
15 c()
fa8078f9 16 }) ), probs=c(0.05,0.95) )
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17 par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
18 for (i in seq_along(indices))
19 {
20 plot(data$getSerie(indices[i]), type="l", ylim=yrange,
21 xlab=ifelse(i==1,"Temps (en heures)",""), ylab=ifelse(i==1,"PM10",""))
22 if (ii < length(indices))
23 par(new=TRUE)
24 }
25}
26
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27#' @title plot measured / predicted
28#'
29#' @description Plot measured curve (in black) and predicted curve (in red)
30#'
31#' @param data Object return by \code{getData}
32#' @param pred Object as returned by \code{getForecast}
33#' @param index Index in forecasts
34#'
35#' @export
36plotPredReal <- function(data, pred, index)
37{
38 horizon = length(pred$getSerie(1))
4e95ec8f 39 par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=3)
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40 measure = data$getSerie(pred$getIndexInData(index)+1)[1:horizon]
41 yrange = range( pred$getSerie(index), measure )
4e95ec8f 42 plot(measure, type="l", ylim=yrange, xlab="Temps (en heures)", ylab="PM10")
3d69ff21 43 par(new=TRUE)
4e95ec8f 44 plot(pred$getSerie(index), type="l", col="#0000FF", ylim=yrange, xlab="", ylab="")
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45}
46
fa8078f9 47#' @title Compute filaments
3d69ff21 48#'
fa8078f9 49#' @description Get similar days in the past + "past tomorrow", as black as distances are small
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50#'
51#' @param data Object as returned by \code{getData}
52#' @param index Index in data
53#' @param limit Number of neighbors to consider
fa8078f9 54#' @param plot Should the result be plotted?
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55#'
56#' @export
fa8078f9 57computeFilaments <- function(data, index, limit=60, plot=TRUE)
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58{
59 index = dateIndexToInteger(index, data)
60 ref_serie = data$getCenteredSerie(index)
61 if (any(is.na(ref_serie)))
fa8078f9 62 stop("computeFilaments requires a serie without NAs")
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63 L = length(ref_serie)
64 first_day = ifelse(length(data$getCenteredSerie(1)<L), 2, 1)
65 distances = sapply(first_day:(index-1), function(i) {
66 sqrt( sum( (ref_serie - data$getCenteredSerie(i))^2 ) / L )
67 })
68 # HACK to suppress NA effect while keeping indexation
69 distances[is.na(distances)] = max(distances,na.rm=TRUE) + 1
70 indices = sort(distances, index.return=TRUE)$ix[1:min(limit,index-first_day)]
fa8078f9 71 yrange = quantile( range( ref_serie, sapply( indices, function(i) {
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72 index = i - first_day + 1
73 serie = c(data$getCenteredSerie(index), data$getCenteredSerie(index+1))
74 if (!all(is.na(serie)))
e5aa669a 75 return (range(serie, na.rm=TRUE))
e030a6e3 76 c()
fa8078f9 77 }) ), probs=c(0.1,0.9) )
3d69ff21 78 grays = gray.colors(20, 0.1, 0.9) #TODO: 20 == magic number
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79 color_values = floor( 20.5 * distances[indices] / (1+max(distances[indices])) )
80 plot_order = sort(color_values, index.return=TRUE)$ix
81 colors = c(grays[ color_values[plot_order] ], "#FF0000")
82 if (plot)
3d69ff21 83 {
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84 par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=2)
85 for ( i in c(plot_order,length(indices)+1) )
86 {
87 ind = ifelse(i<=length(indices), indices[i] - first_day + 1, index)
88 plot(c(data$getCenteredSerie(ind),data$getCenteredSerie(ind+1)),
89 ylim=yrange, type="l", col=colors[i],
90 xlab=ifelse(i==1,"Temps (en heures)",""), ylab=ifelse(i==1,"PM10 centré",""))
91 if (i <= length(indices))
92 par(new=TRUE)
93 }
3d69ff21 94 }
fa8078f9 95 list("indices"=c(indices[plot_order]-first_day+1,index), "colors"=colors)
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96}
97
98#' @title Plot similarities
99#'
100#' @description Plot histogram of similarities (weights)
101#'
102#' @param pred Object as returned by \code{getForecast}
103#' @param index Index in forecasts (not in data)
104#'
105#' @export
106plotSimils <- function(pred, index)
107{
108 weights = pred$getParams(index)$weights
109 if (is.null(weights))
110 stop("plotSimils only works on 'Neighbors' forecasts")
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111 par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
112 hist(pred$getParams(index)$weights, nclass=20, xlab="Poids", ylab="Effectif")
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113}
114
115#' @title Plot error
116#'
117#' @description Draw error graphs, potentially from several runs of \code{getForecast}
118#'
119#' @param err Error as returned by \code{getError}
09cf9c19 120#' @param cols Colors for each error (default: 1,2,3,...)
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121#'
122#' @seealso \code{\link{plotPredReal}}, \code{\link{plotFilaments}}, \code{\link{plotSimils}}
123#' \code{\link{plotFbox}}
124#'
125#' @export
09cf9c19 126plotError <- function(err, cols=seq_along(err))
3d69ff21 127{
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128 if (!is.null(err$abs))
129 err = list(err)
4e95ec8f 130 par(mfrow=c(2,2), mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=2)
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131 L = length(err)
132 yrange = range( sapply(1:L, function(index) ( err[[index]]$abs$day ) ), na.rm=TRUE )
133 for (i in seq_len(L))
134 {
135 plot(err[[i]]$abs$day, type="l", xlab=ifelse(i==1,"Temps (heures)",""),
09cf9c19 136 ylab=ifelse(i==1,"Moyenne |y - y_hat|",""), ylim=yrange, col=cols[i])
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137 if (i < L)
138 par(new=TRUE)
139 }
140 yrange = range( sapply(1:L, function(index) ( err[[index]]$abs$indices ) ), na.rm=TRUE )
141 for (i in seq_len(L))
142 {
143 plot(err[[i]]$abs$indices, type="l", xlab=ifelse(i==1,"Temps (jours)",""),
09cf9c19 144 ylab=ifelse(i==1,"Moyenne |y - y_hat|",""), ylim=yrange, col=cols[i])
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145 if (i < L)
146 par(new=TRUE)
147 }
148 yrange = range( sapply(1:L, function(index) ( err[[index]]$MAPE$day ) ), na.rm=TRUE )
149 for (i in seq_len(L))
150 {
151 plot(err[[i]]$MAPE$day, type="l", xlab=ifelse(i==1,"Temps (heures)",""),
09cf9c19 152 ylab=ifelse(i==1,"MAPE moyen",""), ylim=yrange, col=cols[i])
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153 if (i < L)
154 par(new=TRUE)
155 }
156 yrange = range( sapply(1:L, function(index) ( err[[index]]$MAPE$indices ) ), na.rm=TRUE )
157 for (i in seq_len(L))
158 {
159 plot(err[[i]]$MAPE$indices, type="l", xlab=ifelse(i==1,"Temps (jours)",""),
09cf9c19 160 ylab=ifelse(i==1,"MAPE moyen",""), ylim=yrange, col=cols[i])
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161 if (i < L)
162 par(new=TRUE)
163 }
164}
165
166#' @title Functional boxplot
167#'
168#' @description Draw the functional boxplot on the left, and bivariate plot on the right
169#'
170#' @param data Object return by \code{getData}
171#' @param fiter Optional filter: return TRUE on indices to process
fa8078f9 172#' @param plot_bivariate Should the bivariate plot appear?
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173#'
174#' @export
fa8078f9 175plotFbox <- function(data, filter=function(index) TRUE, plot_bivariate=TRUE)
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176{
177 if (!requireNamespace("rainbow", quietly=TRUE))
178 stop("Functional boxplot requires the rainbow package")
179
180 start_index = 1
181 end_index = data$getSize()
182 if (length(data$getCenteredSerie(1)) < length(data$getCenteredSerie(2)))
183 {
184 # Shifted start (7am, or 1pm, or...)
185 start_index = 2
186 end_index = data$getSize() - 1
187 }
188
189 series_matrix = sapply(start_index:end_index, function(index) {
190 as.matrix(data$getSerie(index))
191 })
192 # Remove NAs. + filter TODO: merge with previous step: only one pass required...
193 nas_indices = seq_len(ncol(series_matrix))[ sapply( 1:ncol(series_matrix),
194 function(index) ( !filter(index) || any(is.na(series_matrix[,index])) ) ) ]
195 series_matrix = series_matrix[,-nas_indices]
196
197 series_fds = rainbow::fds(seq_len(nrow(series_matrix)), series_matrix)
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198 if (plot_bivariate)
199 par(mfrow=c(1,2))
200 par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
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201 rainbow::fboxplot(series_fds, "functional", "hdr", xlab="Temps (heures)", ylab="PM10",
202 plotlegend=FALSE, lwd=2)
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203 if (plot_bivariate)
204 rainbow::fboxplot(series_fds, "bivariate", "hdr", plotlegend=FALSE)
205}
206
207#' @title Functional boxplot on filaments
208#'
209#' @description Draw the functional boxplot on filaments obtained by \code{computeFilaments}
210#'
211#' @param data Object return by \code{getData}
212#' @param indices Indices as output by \code{computeFilaments}
213#'
214#' @export
215plotFilamentsBox = function(data, indices, ...)
216{
217 past_neighbs_indices = head(indices,-1)
218 plotFbox(data, function(i) i %in% past_neighbs_indices, plot_bivariate=FALSE)
219 par(new=TRUE)
220 # "Magic" found at http://stackoverflow.com/questions/13842560/get-xlim-from-a-plot-in-r
221 usr <- par("usr")
222 yr <- (usr[4] - usr[3]) / 27
223 plot(data$getSerie(tail(indices,1)), type="l", lwd=2, lty=2,
224 ylim=c(usr[3] + yr, usr[4] - yr), xlab="", ylab="")
3d69ff21 225}