f4fc3bfac02a7f703c493aa29c16bab51c2dc6a1
[talweg.git] / pkg / R / plot.R
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
9 plotCurves <- function(data, indices=seq_len(data$getSize()))
10 {
11 yrange = quantile( range( sapply( indices, function(i) {
12 serie = c(data$getCenteredSerie(i))
13 if (!all(is.na(serie)))
14 range(serie, na.rm=TRUE)
15 c()
16 }) ), probs=c(0.05,0.95) )
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$getSerie(indices[i]), type="l", ylim=yrange,
21 xlab=ifelse(i==1,"Temps (en heures)",""), ylab=ifelse(i==1,"PM10",""))
22 if (i < length(indices))
23 par(new=TRUE)
24 }
25 }
26
27 #' @title plot measured / predicted
28 #'
29 #' @description Plot measured curve (in black) and predicted curve (in red)
30 #'
31 #' @param data Object return by \code{getData}
32 #' @param pred Object as returned by \code{getForecast}
33 #' @param index Index in forecasts
34 #'
35 #' @export
36 plotPredReal <- function(data, pred, index)
37 {
38 horizon = length(pred$getSerie(1))
39 measure = data$getSerie(pred$getIndexInData(index)+1)[1:horizon]
40 yrange = range( pred$getSerie(index), measure )
41 par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=3)
42 plot(measure, type="l", ylim=yrange, xlab="Temps (en heures)", ylab="PM10")
43 par(new=TRUE)
44 plot(pred$getSerie(index), type="l", col="#0000FF", ylim=yrange, xlab="", ylab="")
45 }
46
47 #' @title Compute filaments
48 #'
49 #' @description Get similar days in the past + "past tomorrow", as black as distances are small
50 #'
51 #' @param data Object as returned by \code{getData}
52 #' @param index Index in data
53 #' @param limit Number of neighbors to consider
54 #' @param plot Should the result be plotted?
55 #'
56 #' @export
57 computeFilaments <- function(data, index, limit=60, plot=TRUE)
58 {
59 index = dateIndexToInteger(index, data)
60 ref_serie = data$getCenteredSerie(index)
61 if (any(is.na(ref_serie)))
62 stop("computeFilaments requires a serie without NAs")
63 L = length(ref_serie)
64 first_day = ifelse(length(data$getCenteredSerie(1)<L), 2, 1)
65 distances = sapply(first_day:(index-1), function(i) {
66 sqrt( sum( (ref_serie - data$getCenteredSerie(i))^2 ) / L )
67 })
68 # HACK to suppress NA effect while keeping indexation
69
70
71
72
73
74 ##TOCONTINUE
75
76
77
78
79 distances[is.na(distances)] = max(distances,na.rm=TRUE) + 1
80 indices = sort(distances, index.return=TRUE)$ix[1:min(limit,length(distances))]
81 yrange = quantile( range( ref_serie, sapply( indices, function(i) {
82 ii = i - 1 + first_day
83 serie = c(data$getCenteredSerie(ii), data$getCenteredSerie(ii+1))
84 if (!all(is.na(serie)))
85 return (range(serie, na.rm=TRUE))
86 c()
87 }) ), probs=c(0.05,0.95) )
88 grays = gray.colors(20, 0.1, 0.9) #TODO: 20 == magic number
89 color_values = floor( 20.5 * distances[indices] / (1+max(distances[indices])) )
90 plot_order = sort(color_values, index.return=TRUE)$ix
91 colors = c(grays[ color_values[plot_order] ], "#FF0000")
92 if (plot)
93 {
94 par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=2)
95 for ( i in c(plot_order,length(indices)+1) )
96 {
97 ind = ifelse(i<=length(indices), indices[i] - first_day + 1, index)
98 plot(c(data$getCenteredSerie(ind),data$getCenteredSerie(ind+1)),
99 ylim=yrange, type="l", col=colors[i],
100 xlab=ifelse(i==1,"Temps (en heures)",""), ylab=ifelse(i==1,"PM10 centré",""))
101 if (i <= length(indices))
102 par(new=TRUE)
103 }
104 }
105 list("indices"=c(indices[plot_order]-first_day+1,index), "colors"=colors)
106 }
107
108 #' @title Plot similarities
109 #'
110 #' @description Plot histogram of similarities (weights)
111 #'
112 #' @param pred Object as returned by \code{getForecast}
113 #' @param index Index in forecasts (not in data)
114 #'
115 #' @export
116 plotSimils <- function(pred, index)
117 {
118 weights = pred$getParams(index)$weights
119 if (is.null(weights))
120 stop("plotSimils only works on 'Neighbors' forecasts")
121 par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
122 hist(pred$getParams(index)$weights, nclass=20, xlab="Poids", ylab="Effectif")
123 }
124
125 #' @title Plot error
126 #'
127 #' @description Draw error graphs, potentially from several runs of \code{getForecast}
128 #'
129 #' @param err Error as returned by \code{getError}
130 #' @param cols Colors for each error (default: 1,2,3,...)
131 #'
132 #' @seealso \code{\link{plotPredReal}}, \code{\link{plotFilaments}}, \code{\link{plotSimils}}
133 #' \code{\link{plotFbox}}
134 #'
135 #' @export
136 plotError <- function(err, cols=seq_along(err))
137 {
138 if (!is.null(err$abs))
139 err = list(err)
140 par(mfrow=c(2,2), mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=2)
141 L = length(err)
142 yrange = range( sapply(1:L, function(index) ( err[[index]]$abs$day ) ), na.rm=TRUE )
143 for (i in seq_len(L))
144 {
145 plot(err[[i]]$abs$day, type="l", xlab=ifelse(i==1,"Temps (heures)",""),
146 ylab=ifelse(i==1,"Moyenne |y - y_hat|",""), ylim=yrange, col=cols[i])
147 if (i < L)
148 par(new=TRUE)
149 }
150 yrange = range( sapply(1:L, function(index) ( err[[index]]$abs$indices ) ), na.rm=TRUE )
151 for (i in seq_len(L))
152 {
153 plot(err[[i]]$abs$indices, type="l", xlab=ifelse(i==1,"Temps (jours)",""),
154 ylab=ifelse(i==1,"Moyenne |y - y_hat|",""), ylim=yrange, col=cols[i])
155 if (i < L)
156 par(new=TRUE)
157 }
158 yrange = range( sapply(1:L, function(index) ( err[[index]]$MAPE$day ) ), na.rm=TRUE )
159 for (i in seq_len(L))
160 {
161 plot(err[[i]]$MAPE$day, type="l", xlab=ifelse(i==1,"Temps (heures)",""),
162 ylab=ifelse(i==1,"MAPE moyen",""), ylim=yrange, col=cols[i])
163 if (i < L)
164 par(new=TRUE)
165 }
166 yrange = range( sapply(1:L, function(index) ( err[[index]]$MAPE$indices ) ), na.rm=TRUE )
167 for (i in seq_len(L))
168 {
169 plot(err[[i]]$MAPE$indices, type="l", xlab=ifelse(i==1,"Temps (jours)",""),
170 ylab=ifelse(i==1,"MAPE moyen",""), ylim=yrange, col=cols[i])
171 if (i < L)
172 par(new=TRUE)
173 }
174 }
175
176 #' @title Functional boxplot
177 #'
178 #' @description Draw the functional boxplot on the left, and bivariate plot on the right
179 #'
180 #' @param data Object return by \code{getData}
181 #' @param fiter Optional filter: return TRUE on indices to process
182 #' @param plot_bivariate Should the bivariate plot appear?
183 #'
184 #' @export
185 plotFbox <- function(data, filter=function(index) TRUE, plot_bivariate=TRUE)
186 {
187 if (!requireNamespace("rainbow", quietly=TRUE))
188 stop("Functional boxplot requires the rainbow package")
189
190 start_index = 1
191 end_index = data$getSize()
192 if (length(data$getCenteredSerie(1)) < length(data$getCenteredSerie(2)))
193 {
194 # Shifted start (7am, or 1pm, or...)
195 start_index = 2
196 end_index = data$getSize() - 1
197 }
198
199 series_matrix = sapply(start_index:end_index, function(index) {
200 as.matrix(data$getSerie(index))
201 })
202 # Remove NAs. + filter TODO: merge with previous step: only one pass required...
203 nas_indices = seq_len(ncol(series_matrix))[ sapply( 1:ncol(series_matrix),
204 function(index) ( !filter(index) || any(is.na(series_matrix[,index])) ) ) ]
205 series_matrix = series_matrix[,-nas_indices]
206
207 series_fds = rainbow::fds(seq_len(nrow(series_matrix)), series_matrix)
208 if (plot_bivariate)
209 par(mfrow=c(1,2))
210 par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
211 rainbow::fboxplot(series_fds, "functional", "hdr", xlab="Temps (heures)", ylab="PM10",
212 plotlegend=FALSE, lwd=2)
213 if (plot_bivariate)
214 rainbow::fboxplot(series_fds, "bivariate", "hdr", plotlegend=FALSE)
215 }
216
217 #' @title Functional boxplot on filaments
218 #'
219 #' @description Draw the functional boxplot on filaments obtained by \code{computeFilaments}
220 #'
221 #' @param data Object return by \code{getData}
222 #' @param indices Indices as output by \code{computeFilaments}
223 #'
224 #' @export
225 plotFilamentsBox = function(data, indices, ...)
226 {
227 past_neighbs_indices = head(indices,-1)
228 plotFbox(data, function(i) i %in% past_neighbs_indices, plot_bivariate=FALSE)
229 par(new=TRUE)
230 # "Magic" found at http://stackoverflow.com/questions/13842560/get-xlim-from-a-plot-in-r
231 usr <- par("usr")
232 yr <- (usr[4] - usr[3]) / 27
233 plot(data$getSerie(tail(indices,1)), type="l", lwd=2, lty=2,
234 ylim=c(usr[3] + yr, usr[4] - yr), xlab="", ylab="")
235 }