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

#' @title plot curves
#'
#' @description Plot a range of curves in data
#'
#' @param data Object of class Data
#' @param indices Range of indices (integers or dates)
#'
#' @export
plotCurves <- function(data, indices)
{
	yrange = quantile( range( sapply( indices, function(i) {
		serie = c(data$getCenteredSerie(i))
		if (!all(is.na(serie)))
			range(serie, na.rm=TRUE)
		c()
	}) ), probs=c(0.05,0.95) )
	par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
	for (i in seq_along(indices))
	{
		plot(data$getSerie(indices[i]), type="l", ylim=yrange,
			xlab=ifelse(i==1,"Temps (en heures)",""), ylab=ifelse(i==1,"PM10",""))
		if (ii < length(indices))
			par(new=TRUE)
	}
}

#' @title plot measured / predicted
#'
#' @description Plot measured curve (in black) and predicted curve (in red)
#'
#' @param data Object return by \code{getData}
#' @param pred Object as returned by \code{getForecast}
#' @param index Index in forecasts
#'
#' @export
plotPredReal <- function(data, pred, index)
{
	horizon = length(pred$getSerie(1))
	par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=3)
	measure = data$getSerie(pred$getIndexInData(index)+1)[1:horizon]
	yrange = range( pred$getSerie(index), measure )
	plot(measure, type="l", ylim=yrange, xlab="Temps (en heures)", ylab="PM10")
	par(new=TRUE)
	plot(pred$getSerie(index), type="l", col="#0000FF", ylim=yrange, xlab="", ylab="")
}

#' @title Compute filaments
#'
#' @description Get similar days in the past + "past tomorrow", as black as distances are small
#'
#' @param data Object as returned by \code{getData}
#' @param index Index in data
#' @param limit Number of neighbors to consider
#' @param plot Should the result be plotted?
#'
#' @export
computeFilaments <- function(data, index, limit=60, plot=TRUE)
{
	index = dateIndexToInteger(index, data)
	ref_serie = data$getCenteredSerie(index)
	if (any(is.na(ref_serie)))
		stop("computeFilaments requires a serie without NAs")
	L = length(ref_serie)
	first_day = ifelse(length(data$getCenteredSerie(1)<L), 2, 1)
	distances = sapply(first_day:(index-1), function(i) {
		sqrt( sum( (ref_serie - data$getCenteredSerie(i))^2 ) / L )
	})
	# HACK to suppress NA effect while keeping indexation
	distances[is.na(distances)] = max(distances,na.rm=TRUE) + 1
	indices = sort(distances, index.return=TRUE)$ix[1:min(limit,index-first_day)]
	yrange = quantile( range( ref_serie, sapply( indices, function(i) {
		index = i - first_day + 1
		serie = c(data$getCenteredSerie(index), data$getCenteredSerie(index+1))
		if (!all(is.na(serie)))
			return (range(serie, na.rm=TRUE))
		c()
	}) ), probs=c(0.1,0.9) )
	grays = gray.colors(20, 0.1, 0.9) #TODO: 20 == magic number
	color_values = floor( 20.5 * distances[indices] / (1+max(distances[indices])) )
	plot_order = sort(color_values, index.return=TRUE)$ix
	colors = c(grays[ color_values[plot_order] ], "#FF0000")
	if (plot)
	{
		par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=2)
		for ( i in c(plot_order,length(indices)+1) )
		{
			ind = ifelse(i<=length(indices), indices[i] - first_day + 1, index)
			plot(c(data$getCenteredSerie(ind),data$getCenteredSerie(ind+1)),
				ylim=yrange, type="l", col=colors[i],
				xlab=ifelse(i==1,"Temps (en heures)",""), ylab=ifelse(i==1,"PM10 centré",""))
			if (i <= length(indices))
				par(new=TRUE)
		}
	}
	list("indices"=c(indices[plot_order]-first_day+1,index), "colors"=colors)
}

#' @title Plot similarities
#'
#' @description Plot histogram of similarities (weights)
#'
#' @param pred Object as returned by \code{getForecast}
#' @param index Index in forecasts (not in data)
#'
#' @export
plotSimils <- function(pred, index)
{
	weights = pred$getParams(index)$weights
	if (is.null(weights))
		stop("plotSimils only works on 'Neighbors' forecasts")
	par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
	hist(pred$getParams(index)$weights, nclass=20, xlab="Poids", ylab="Effectif")
}

#' @title Plot error
#'
#' @description Draw error graphs, potentially from several runs of \code{getForecast}
#'
#' @param err Error as returned by \code{getError}
#' @param cols Colors for each error (default: 1,2,3,...)
#'
#' @seealso \code{\link{plotPredReal}}, \code{\link{plotFilaments}}, \code{\link{plotSimils}}
#'   \code{\link{plotFbox}}
#'
#' @export
plotError <- function(err, cols=seq_along(err))
{
	if (!is.null(err$abs))
		err = list(err)
	par(mfrow=c(2,2), mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=2)
	L = length(err)
	yrange = range( sapply(1:L, function(index) ( err[[index]]$abs$day ) ), na.rm=TRUE )
	for (i in seq_len(L))
	{
		plot(err[[i]]$abs$day, type="l", xlab=ifelse(i==1,"Temps (heures)",""),
			ylab=ifelse(i==1,"Moyenne |y - y_hat|",""), ylim=yrange, col=cols[i])
		if (i < L)
			par(new=TRUE)
	}
	yrange = range( sapply(1:L, function(index) ( err[[index]]$abs$indices ) ), na.rm=TRUE )
	for (i in seq_len(L))
	{
		plot(err[[i]]$abs$indices, type="l", xlab=ifelse(i==1,"Temps (jours)",""),
			ylab=ifelse(i==1,"Moyenne |y - y_hat|",""), ylim=yrange, col=cols[i])
		if (i < L)
			par(new=TRUE)
	}
	yrange = range( sapply(1:L, function(index) ( err[[index]]$MAPE$day ) ), na.rm=TRUE )
	for (i in seq_len(L))
	{
		plot(err[[i]]$MAPE$day, type="l", xlab=ifelse(i==1,"Temps (heures)",""),
			ylab=ifelse(i==1,"MAPE moyen",""), ylim=yrange, col=cols[i])
		if (i < L)
			par(new=TRUE)
	}
	yrange = range( sapply(1:L, function(index) ( err[[index]]$MAPE$indices ) ), na.rm=TRUE )
	for (i in seq_len(L))
	{
		plot(err[[i]]$MAPE$indices, type="l", xlab=ifelse(i==1,"Temps (jours)",""),
			ylab=ifelse(i==1,"MAPE moyen",""), ylim=yrange, col=cols[i])
		if (i < L)
			par(new=TRUE)
	}
}

#' @title Functional boxplot
#'
#' @description Draw the functional boxplot on the left, and bivariate plot on the right
#'
#' @param data Object return by \code{getData}
#' @param fiter Optional filter: return TRUE on indices to process
#' @param plot_bivariate Should the bivariate plot appear?
#'
#' @export
plotFbox <- function(data, filter=function(index) TRUE, plot_bivariate=TRUE)
{
	if (!requireNamespace("rainbow", quietly=TRUE))
		stop("Functional boxplot requires the rainbow package")

	start_index = 1
	end_index = data$getSize()
	if (length(data$getCenteredSerie(1)) < length(data$getCenteredSerie(2)))
	{
		# Shifted start (7am, or 1pm, or...)
		start_index = 2
		end_index = data$getSize() - 1
	}

	series_matrix = sapply(start_index:end_index, function(index) {
		as.matrix(data$getSerie(index))
	})
	# Remove NAs. + filter TODO: merge with previous step: only one pass required...
	nas_indices = seq_len(ncol(series_matrix))[ sapply( 1:ncol(series_matrix),
		function(index) ( !filter(index) || any(is.na(series_matrix[,index])) ) ) ]
	series_matrix = series_matrix[,-nas_indices]

	series_fds = rainbow::fds(seq_len(nrow(series_matrix)), series_matrix)
	if (plot_bivariate)
		par(mfrow=c(1,2))
	par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
	rainbow::fboxplot(series_fds, "functional", "hdr", xlab="Temps (heures)", ylab="PM10",
		plotlegend=FALSE, lwd=2)
	if (plot_bivariate)
		rainbow::fboxplot(series_fds, "bivariate", "hdr", plotlegend=FALSE)
}

#' @title Functional boxplot on filaments
#'
#' @description Draw the functional boxplot on filaments obtained by \code{computeFilaments}
#'
#' @param data Object return by \code{getData}
#' @param indices Indices as output by \code{computeFilaments}
#'
#' @export
plotFilamentsBox = function(data, indices, ...)
{
	past_neighbs_indices = head(indices,-1)
	plotFbox(data, function(i) i %in% past_neighbs_indices, plot_bivariate=FALSE)
	par(new=TRUE)
	# "Magic" found at http://stackoverflow.com/questions/13842560/get-xlim-from-a-plot-in-r
	usr <- par("usr")
	yr <- (usr[4] - usr[3]) / 27
	plot(data$getSerie(tail(indices,1)), type="l", lwd=2, lty=2,
		ylim=c(usr[3] + yr, usr[4] - yr), xlab="", ylab="")
}
Commit	Line	Data
e030a6e3 BA	1	#' @title plot curves
	2	#'
	3	#' @description Plot a range of curves in data
	4	#'
	5	#' @param data Object of class Data
	6	#' @param indices Range of indices (integers or dates)
	7	#'
	8	#' @export
	9	plotCurves <- function(data, indices)
	10	{
fa8078f9	11	yrange = quantile( range( sapply( indices, function(i) {
e030a6e3 BA	12	serie = c(data$getCenteredSerie(i))
	13	if (!all(is.na(serie)))
	14	range(serie, na.rm=TRUE)
	15	c()
fa8078f9	16	}) ), probs=c(0.05,0.95) )
e030a6e3 BA	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$getSerie(indices[i]), type="l", ylim=yrange,
	21	xlab=ifelse(i==1,"Temps (en heures)",""), ylab=ifelse(i==1,"PM10",""))
	22	if (ii < length(indices))
	23	par(new=TRUE)
	24	}
	25	}
	26
3d69ff21 BA	27	#' @title plot measured / predicted
	28	#'
	29	#' @description Plot measured curve (in black) and predicted curve (in red)
	30	#'
	31	#' @param data Object return by \code{getData}
	32	#' @param pred Object as returned by \code{getForecast}
	33	#' @param index Index in forecasts
	34	#'
	35	#' @export
	36	plotPredReal <- function(data, pred, index)
	37	{
	38	horizon = length(pred$getSerie(1))
4e95ec8f	39	par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=3)
3d69ff21 BA	40	measure = data$getSerie(pred$getIndexInData(index)+1)[1:horizon]
3d69ff21 BA	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="")
3d69ff21 BA	45	}
3d69ff21 BA	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
3d69ff21 BA	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?
3d69ff21 BA	55	#'
3d69ff21 BA	56	#' @export
fa8078f9	57	computeFilaments <- function(data, index, limit=60, plot=TRUE)
3d69ff21 BA	58	{
	59	index = dateIndexToInteger(index, data)
	60	ref_serie = data$getCenteredSerie(index)
	61	if (any(is.na(ref_serie)))
fa8078f9	62	stop("computeFilaments requires a serie without NAs")
3d69ff21 BA	63	L = length(ref_serie)
	64	first_day = ifelse(length(data$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) {
3d69ff21 BA	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
fa8078f9 BA	79	color_values = floor( 20.5 * distances[indices] / (1+max(distances[indices])) )
	80	plot_order = sort(color_values, index.return=TRUE)$ix
	81	colors = c(grays[ color_values[plot_order] ], "#FF0000")
	82	if (plot)
3d69ff21	83	{
fa8078f9 BA	84	par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=2)
	85	for ( i in c(plot_order,length(indices)+1) )
	86	{
	87	ind = ifelse(i<=length(indices), indices[i] - first_day + 1, index)
	88	plot(c(data$getCenteredSerie(ind),data$getCenteredSerie(ind+1)),
	89	ylim=yrange, type="l", col=colors[i],
	90	xlab=ifelse(i==1,"Temps (en heures)",""), ylab=ifelse(i==1,"PM10 centré",""))
	91	if (i <= length(indices))
	92	par(new=TRUE)
	93	}
3d69ff21	94	}
fa8078f9	95	list("indices"=c(indices[plot_order]-first_day+1,index), "colors"=colors)
3d69ff21 BA	96	}
	97
	98	#' @title Plot similarities
	99	#'
	100	#' @description Plot histogram of similarities (weights)
	101	#'
	102	#' @param pred Object as returned by \code{getForecast}
	103	#' @param index Index in forecasts (not in data)
	104	#'
	105	#' @export
	106	plotSimils <- function(pred, index)
	107	{
	108	weights = pred$getParams(index)$weights
	109	if (is.null(weights))
	110	stop("plotSimils only works on 'Neighbors' forecasts")
4e95ec8f BA	111	par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
4e95ec8f BA	112	hist(pred$getParams(index)$weights, nclass=20, xlab="Poids", ylab="Effectif")
3d69ff21 BA	113	}
	114
	115	#' @title Plot error
	116	#'
	117	#' @description Draw error graphs, potentially from several runs of \code{getForecast}
	118	#'
	119	#' @param err Error as returned by \code{getError}
09cf9c19	120	#' @param cols Colors for each error (default: 1,2,3,...)
3d69ff21 BA	121	#'
	122	#' @seealso \code{\link{plotPredReal}}, \code{\link{plotFilaments}}, \code{\link{plotSimils}}
	123	#' \code{\link{plotFbox}}
	124	#'
	125	#' @export
09cf9c19	126	plotError <- function(err, cols=seq_along(err))
3d69ff21	127	{
09cf9c19 BA	128	if (!is.null(err$abs))
09cf9c19 BA	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)
3d69ff21 BA	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])
3d69ff21 BA	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])
3d69ff21 BA	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])
3d69ff21 BA	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])
3d69ff21 BA	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?
3d69ff21 BA	173	#'
3d69ff21 BA	174	#' @export
fa8078f9	175	plotFbox <- function(data, filter=function(index) TRUE, plot_bivariate=TRUE)
3d69ff21 BA	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$getSerie(index))
	191	})
	192	# Remove NAs. + filter TODO: merge with previous step: only one pass required...
	193	nas_indices = seq_len(ncol(series_matrix))[ sapply( 1:ncol(series_matrix),
	194	function(index) ( !filter(index) \|\| any(is.na(series_matrix[,index])) ) ) ]
	195	series_matrix = series_matrix[,-nas_indices]
	196
	197	series_fds = rainbow::fds(seq_len(nrow(series_matrix)), series_matrix)
fa8078f9 BA	198	if (plot_bivariate)
	199	par(mfrow=c(1,2))
	200	par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
3d69ff21 BA	201	rainbow::fboxplot(series_fds, "functional", "hdr", xlab="Temps (heures)", ylab="PM10",
3d69ff21 BA	202	plotlegend=FALSE, lwd=2)
fa8078f9 BA	203	if (plot_bivariate)
	204	rainbow::fboxplot(series_fds, "bivariate", "hdr", plotlegend=FALSE)
	205	}
	206
	207	#' @title Functional boxplot on filaments
	208	#'
	209	#' @description Draw the functional boxplot on filaments obtained by \code{computeFilaments}
	210	#'
	211	#' @param data Object return by \code{getData}
	212	#' @param indices Indices as output by \code{computeFilaments}
	213	#'
	214	#' @export
	215	plotFilamentsBox = function(data, indices, ...)
	216	{
	217	past_neighbs_indices = head(indices,-1)
	218	plotFbox(data, function(i) i %in% past_neighbs_indices, plot_bivariate=FALSE)
	219	par(new=TRUE)
	220	# "Magic" found at http://stackoverflow.com/questions/13842560/get-xlim-from-a-plot-in-r
	221	usr <- par("usr")
	222	yr <- (usr[4] - usr[3]) / 27
	223	plot(data$getSerie(tail(indices,1)), type="l", lwd=2, lty=2,
	224	ylim=c(usr[3] + yr, usr[4] - yr), xlab="", ylab="")
3d69ff21	225	}