#############################################################################################################
# Author :
# Kim-Anh Le Cao, The University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD
# Benoit Gautier, The University of Queensland, The University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD
# Florian Rohart, The University of Queensland, The University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD
#
# created: 19-04-2016
# last modified: 24-05-2016
#
# Copyright (C) 2016
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
#############################################################################################################
#----------------------------------------------------------------------------------------------------------#
#-- Includes plotIndiv for PLS-DA, SPLS-DA, sGCCDA --#
#----------------------------------------------------------------------------------------------------------#
plotLoadings.mixo_plsda =
#plotLoadings.mlplsda = # because plsda too
plotLoadings.mixo_splsda =
#plotLoadings.mlsplsda = # because splsda too
plotLoadings.sgccda =
function(object,
contrib = NULL, # choose between 'max" or "min", NULL does not color the barplot
method = "mean", # choose between 'mean" or "median"
block, #single value, for sgccda object
comp = 1,
plot = TRUE,
show.ties = TRUE,
col.ties = "white",
ndisplay = NULL,
size.name = 0.7,
size.legend = 0.8,
name.var = NULL,
name.var.complete = FALSE,
title = NULL,
subtitle,
size.title = rel(1.8),
size.subtitle = rel(1.4),
legend = TRUE,
legend.color = NULL,
legend.title = 'Outcome',
layout = NULL,
border = NA,
xlim = NULL,
...
) {
# -- input checks
check = check.input.plotLoadings(object = object, block = block, subtitle = subtitle, size.name = size.name, size.legend = size.legend,
title = title, col = NULL, contrib = contrib, name.var = name.var, xlim = xlim)
size.name = check$size.name
size.legend = check$size.legend
block = check$block
xlim = check$xlim
# contrib
# --
# if contrib is NULL, then we switch to the classical plotLoadings (without contribution/colors)
if(is.null(contrib))
{
if(plot)
{
plotLoadings.mixo_pls(object = object, block = block, comp = comp, ndisplay = ndisplay,
size.name = size.name,
name.var = name.var,
name.var.complete = name.var.complete,
title = title,
subtitle = subtitle,
xlim = xlim,
layout = layout,
size.title = size.title,
size.subtitle = size.subtitle,
border = TRUE,
col = "white")
} else {
stop("'contrib' is NULL and 'plot' is FALSE => no results to show", call. = FALSE)
}
# stop the script without error message
# blankMsg <- sprintf("\r%s\r", paste(rep(" ", getOption("width")-1L), collapse=" "))
# stop(simpleError(blankMsg))
} else {
# -- layout
res = layout.plotLoadings(layout = layout, plot = plot, legend = legend, block = block)
reset.mfrow = res$reset.mfrow
opar = res$opar
omar = par("mar") #reset mar at the end
# method
# ----
if (length(method) !=1 || !method %in% c("mean","median"))
{
method = "median"
warning("'method' should be either 'mean' or 'median', set to 'median' by default")
}
if (length(block) == 1 & !is.null(name.var))
name.var = list(name.var = name.var)
for (i in 1 : length(block))
{
res = get.loadings.ndisplay(object = object, comp = comp, block = block[i], name.var = name.var[[i]], name.var.complete = name.var.complete, ndisplay = ndisplay)
X = res$X
names.block = res$names.block
colnames.X = res$colnames.X
name.selected.var = res$name.selected.var
value.selected.var = res$value.selected.var
Y = object$Y #v6: all $Y are factors for DA methods
#legend.color
#-----
if (!is.null(legend.color) & (length(legend.color) != nlevels(Y)))
{
warning('legend.color must be the same length than the number of group, by default set to default colors')
legend.color = color.mixo(1:10) # by default set to the colors in color.mixo (10 colors)
}
if (is.null(legend.color))
legend.color = color.mixo(1:10)[1:nlevels(Y)] # by default set to the colors in color.mixo (10 colors)
if (col.ties%in%legend.color[1:nlevels(Y)])
stop("'col.ties' should not be in 'legend.color'")
# determine the colors/groups matching max contribution
df = get.contrib.df(Y = Y, X = X, method = method, contrib = contrib, value.selected.var = value.selected.var, colnames.X = colnames.X, name.selected.var = name.selected.var, legend.color = legend.color, col.ties = col.ties)
# when working with sparse counts in particular and using the median to measure contribution
# ties to determine the contribution of a variable may happen, in that case remove them, otherwise they are showns as blank
if (show.ties == FALSE)
{
df = df[!df$color %in% col.ties, ]
colnames.X = rownames(df)
}
# display barplot with names of variables
if (plot) # condition if all we need is the contribution stats
{
if (!is.null(title) & length(block) > 1)
{
par(mar = c(4, max(7, max(sapply(colnames.X, nchar),na.rm = TRUE)/3), 6, 2))
} else {
par(mar = c(4, max(7, max(sapply(colnames.X, nchar), na.rm = TRUE)/3), 4, 2))
}
mp = barplot(df$importance, horiz = TRUE, las = 1, col = df$color, axisnames = TRUE, names.arg = colnames.X, #names.arg = row.names(df),
cex.names = size.name, cex.axis = 0.7, beside = TRUE, border = border, xlim = xlim[i, ])
if ( length(block) == 1 & is.null(title) )
{
title(paste0('Contribution on comp ', comp), line=0, cex.main = size.title)
} else if (length(block) == 1) {
title(paste(title), line=1, cex.main = size.title)
} else if ((length(block) > 1 & missing(subtitle))) {
title(paste0('Contribution on comp ', comp, "\nBlock '", names.block,"'"), line=0, cex.main = size.subtitle)
} else if (length(block) > 1 & !missing(subtitle)) {
title(paste(subtitle[i]), line=1, cex.main = size.subtitle)
}
if (legend)
{
par(mar = c(5, 0, 4, 3) + 0.1)
plot(1,1, type = "n", axes = FALSE, ann = FALSE)
legend(0.8, 1, col = legend.color[1:nlevels(Y)], legend = levels(Y), pch = 19,
title = paste(legend.title),
cex = size.legend)
}
} # end if plot
}
if(plot) # overall title and reset par if needed
{
# legend
if (length(block) > 1 & !is.null(title))
title(title, outer=TRUE, line = -2, cex.main = size.title)
if (reset.mfrow)
par(opar)#par(mfrow = omfrow)
par(mar = omar) #reset mar
}
# return the contribution matrix
return(invisible(df))
}# end contrib missing
}
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