R/stats_plot3d.R
In xia-lab/MetaboAnalystR: An R Package for Comprehensive Analysis of Metabolomics Data
Defines functions
PlotPLS3DScoreImg
PlotSPLS3DScoreImg
PlotSPLS3DScoreImg
PlotPCA3DScoreImg
Plot3D
Documented in
PlotPCA3DScoreImg
PlotPLS3DScoreImg
PlotSPLS3DScoreImg
### R script for MetaboAnalyst
### Description: 3D scatter plot for PDF report (not used for web display)
### Author: Jeff Xia, jeff.xia@mcgill.ca
### McGill University, Canada
### License: GNU GPL (>= 2)
Plot3D <- function(x, y, z, xlab= xlabel, ylab=ylabel, zlab=zlabel,
angle =angl, color=cols, pch=pchs){
if(.on.public.web){
# make this lazy load
if(!exists("my.plot.scatter3d")){ # public web on same user dir
.load.scripts.on.demand("util_plot3d.Rc");
}
return(my.plot.scatter3d(x, y, z, xlab=xlab, ylab=ylab,
zlab=zlab, angle =angle, color=color, pch=pch));
}else{
return(my.plot.scatter3d(x, y, z, xlab=xlab, ylab=ylab,
zlab=zlab, angle =angle, color=color, pch=pch));
}
}
#'Create 3D PCA score plot
#'@description This function creates both a static 3D PCA score plot as well as an interactive 3D PCA score plot
#'using the plotly R package. The 3D PCA score plot is stored in the mSetObj (mSetObj$imgSet$pca.3d). To view
#'the plot, if your mSetObj is named mSet, type "mSet$imgSet$pca.3d" inro your R console, and the 3D plot will appear.
#'@author Jeff Xia\email{jeff.xia@mcgill.ca}
#'McGill University, Canada
#'License: GNU GPL (>= 2)
#'@usage PlotPCA3DScoreImg(mSetObj=NA, imgName,
#'format="png", dpi=72, width=NA, inx1, inx2, inx3, angl)
#'@param mSetObj Input name of the created mSet Object.
#'@param imgName Input a name for the plot.
#'@param format Select the image format, "png", or "pdf".
#'@param dpi Input the dpi. If the image format is "pdf", users need not define the dpi. For "png" images,
#'the default dpi is 72. It is suggested that for high-resolution images, select a dpi of 300.
#'@param width Input the width, there are 2 default widths, the first, width = NULL, is 10.5.
#'The second default is width = 0, where the width is 7.2. Otherwise users can input their own width.
#'@param inx1 Numeric, indicate the number of the principal component for the x-axis of the loading plot.
#'@param inx2 Numeric, indicate the number of the principal component for the y-axis of the loading plot.
#'@param inx3 Numeric, indicate the number of the principal component for the z-axis of the loading plot.
#'@param angl Input the angle
#'@export
#'@importFrom plotly plot_ly add_markers layout
PlotPCA3DScoreImg <- function(mSetObj=NA, imgName, format="png",
dpi=72, width=NA, inx1, inx2, inx3, angl){
mSetObj <- .get.mSet(mSetObj);
xlabel = paste("PC",inx1, "(", round(100*mSetObj$analSet$pca$variance[inx1],1), "%)");
ylabel = paste("PC",inx2, "(", round(100*mSetObj$analSet$pca$variance[inx2],1), "%)");
zlabel = paste("PC",inx3, "(", round(100*mSetObj$analSet$pca$variance[inx3],1), "%)");
imgName = paste(imgName, "dpi", dpi, ".", format, sep="");
if(is.na(width)){
w <- 9;
}else if(width == 0){
w <- 7.2;
}else{
w <- width;
}
h <- w;
mSetObj$imgSet$pca.score3d <- imgName;
Cairo::Cairo(file = imgName, unit="in", dpi=dpi, width=w, height=h, type=format, bg="white");
cls <- mSetObj$dataSet$cls;
pchs <- as.numeric(cls)+1;
uniq.pchs <- unique(pchs);
if(mSetObj$dataSet$cls.type == "disc"){
col.def <- GetColorSchema(cls);
all.cols <- ExpandSchema(cls, col.def);
Plot3D(mSetObj$analSet$pca$x[, inx1], mSetObj$analSet$pca$x[, inx2], mSetObj$analSet$pca$x[, inx3], xlab= xlabel, ylab=ylabel,
zlab=zlabel, angle =angl, color=cols, pch=pchs);
legend("topleft", legend = names(col.def), pch=uniq.pchs, col=col.def);
dev.off();
}else{
Plot3D(mSetObj$analSet$pca$x[, inx1], mSetObj$analSet$pca$x[, inx2], mSetObj$analSet$pca$x[, inx3], xlab= xlabel, ylab=ylabel,
zlab=zlabel, angle =angl, pch=pchs);
dev.off();
if(!.on.public.web){
# 3D View using plotly
col <- c("#C61951", "#1972A4")
p <- plotly::plot_ly(x = mSetObj$analSet$pca$x[, inx1], y = mSetObj$analSet$pca$x[, inx2], z = mSetObj$analSet$pca$x[, inx3],
color = pchs, colors = col, marker = list(colorbar = list(len = 1, tickmode = array, tickvals = range(unique(pchs)),
ticktext = levels(mSetObj$dataSet$cls))));
p <- plotly::add_markers(p, sizes = 1000);
p <- plotly::layout(p, scene = list(xaxis = list(title = xlabel),
yaxis = list(title = ylabel),
zaxis = list(title = zlabel)));
mSetObj$imgSet$pca.3d <- p;
print("The Interactive 3D PCA plot has been created, please find it in mSet$imgSet$pca.3d.")
}
}
return(.set.mSet(mSetObj));
}
#'Plot sPLS-DA 3D score plot
#'@description This function creates two 3D sPLS-DA score plots, the first is static for Analysis Report purposes, as well as
#'an interactive 3D plot using the plotly R package. The 3D score plot is saved in the created mSetObj (mSetObj$imgSet$splsda.3d).
#'To view the score plot, if the name of your mSetObj is mSet, enter "mSet$imgSet$splsda.3d" to view the interactive score plot.
#'@param mSetObj Input name of the created mSet Object
#'@param imgName Input a name for the plot
#'@param format Select the image format, "png", or "pdf".
#'@param dpi Input the dpi. If the image format is "pdf", users need not define the dpi. For "png" images,
#'the default dpi is 72. It is suggested that for high-resolution images, select a dpi of 300.
#'@param width Input the width, there are 2 default widths, the first, width = NULL, is 10.5.
#'The second default is width = 0, where the width is 7.2. Otherwise users can input their own width.
#'@param inx1 Numeric, indicate the number of the principal component for the x-axis of the loading plot.
#'@param inx2 Numeric, indicate the number of the principal component for the y-axis of the loading plot.
#'@param inx3 Numeric, indicate the number of the principal component for the z-axis of the loading plot.
#'@param angl Input the angle
#'@author Jeff Xia\email{jeff.xia@mcgill.ca}
#'McGill University, Canada
#'License: GNU GPL (>= 2)
#'@export
#'@importFrom plotly plot_ly add_markers layout
PlotSPLS3DScoreImg<-function(mSetObj=NA, imgName, format="png", dpi=72, width=NA, inx1, inx2, inx3, angl){
mSetObj <- .get.mSet(mSetObj);
imgName = paste(imgName, "dpi", dpi, ".", format, sep="");
if(is.na(width)){
w <- 9;
}else if(width == 0){
w <- 7.2;
}else{
w <- width;
}
h <- w;
mSetObj$imgSet$spls.score3d <- imgName;
Cairo::Cairo(file = imgName, unit="in", dpi=dpi, width=w, height=h, type=format, bg="white");
par(mar=c(5,5,3,3));
spls3d <- list();
## need to check if only 2 or 3 components generated
if(length(mSetObj$analSet$splsr$explained_variance$X)==2){
spls3d$score$axis <- paste("Component", c(inx1, inx2), " (", round(100*mSetObj$analSet$splsr$explained_variance$X[c(inx1, inx2)], 1), "%)", sep="");
coords <- data.frame(signif(mSetObj$analSet$splsr$variates$X[,c(inx1, inx2)], 5));
spls3d$score$axis <- c(spls3d$score$axis, "Component3 (NA)");
coords <- rbind(coords, "comp 3"=rep (0, ncol(coords)));
}else{
spls3d$score$axis <- paste("Component", c(inx1, inx2, inx3), " (", round(100*mSetObj$analSet$splsr$explained_variance$X[c(inx1, inx2, inx3)], 1), "%)", sep="");
coords <- data.frame(signif(mSetObj$analSet$splsr$variates$X[,c(inx1, inx2, inx3)], 5));
}
xlabel <- spls3d$score$axis[1]
ylabel <- spls3d$score$axis[2]
zlabel <- spls3d$score$axis[3]
# static
cls <- mSetObj$dataSet$cls;
col.def <- GetColorSchema(cls);
cols <- ExpandSchema(cls, col.def);
pchs <- as.numeric(cls)+1;
uniq.pchs <- unique(pchs);
Plot3D(coords[,inx1], coords[,inx2], coords[,inx3], xlab= xlabel, ylab=ylabel,
zlab=zlabel, angle = angl, color=cols, pch=pchs);
legend("topleft", legend = names(col.def), pch=uniq.pchs, col=col.def);
dev.off();
return(.set.mSet(mSetObj));
}
#'Plot sPLS-DA 3D score plot
#'@description This function creates two 3D sPLS-DA score plots, the first is static for Analysis Report purposes, as well as
#'an interactive 3D plot using the plotly R package. The 3D score plot is saved in the created mSetObj (mSetObj$imgSet$splsda.3d).
#'To view the score plot, if the name of your mSetObj is mSet, enter "mSet$imgSet$splsda.3d" to view the interactive score plot.
#'@param mSetObj Input name of the created mSet Object
#'@param imgName Input a name for the plot
#'@param format Select the image format, "png", or "pdf".
#'@param dpi Input the dpi. If the image format is "pdf", users need not define the dpi. For "png" images,
#'the default dpi is 72. It is suggested that for high-resolution images, select a dpi of 300.
#'@param width Input the width, there are 2 default widths, the first, width = NULL, is 10.5.
#'The second default is width = 0, where the width is 7.2. Otherwise users can input their own width.
#'@param inx1 Numeric, indicate the number of the principal component for the x-axis of the loading plot.
#'@param inx2 Numeric, indicate the number of the principal component for the y-axis of the loading plot.
#'@param inx3 Numeric, indicate the number of the principal component for the z-axis of the loading plot.
#'@param angl Input the angle
#'@author Jeff Xia\email{jeff.xia@mcgill.ca}
#'McGill University, Canada
#'License: GNU GPL (>= 2)
#'@export
#'@importFrom plotly plot_ly add_markers layout
PlotSPLS3DScoreImg<-function(mSetObj=NA, imgName, format="png", dpi=72, width=NA, inx1, inx2, inx3, angl){
mSetObj <- .get.mSet(mSetObj);
imgName = paste(imgName, "dpi", dpi, ".", format, sep="");
if(is.na(width)){
w <- 9;
}else if(width == 0){
w <- 7.2;
}else{
w <- width;
}
h <- w;
mSetObj$imgSet$spls.score3d <- imgName;
Cairo::Cairo(file = imgName, unit="in", dpi=dpi, width=w, height=h, type=format, bg="white");
par(mar=c(5,5,3,3));
spls3d <- list();
## need to check if only 2 or 3 components generated
if(length(mSetObj$analSet$splsr$explained_variance$X)==2){
spls3d$score$axis <- paste("Component", c(inx1, inx2), " (", round(100*mSetObj$analSet$splsr$explained_variance$X[c(inx1, inx2)], 1), "%)", sep="");
coords <- data.frame(signif(mSetObj$analSet$splsr$variates$X[,c(inx1, inx2)], 5));
spls3d$score$axis <- c(spls3d$score$axis, "Component3 (NA)");
coords <- rbind(coords, "comp 3"=rep (0, ncol(coords)));
}else{
spls3d$score$axis <- paste("Component", c(inx1, inx2, inx3), " (", round(100*mSetObj$analSet$splsr$explained_variance$X[c(inx1, inx2, inx3)], 1), "%)", sep="");
coords <- data.frame(signif(mSetObj$analSet$splsr$variates$X[,c(inx1, inx2, inx3)], 5));
}
xlabel <- spls3d$score$axis[1]
ylabel <- spls3d$score$axis[2]
zlabel <- spls3d$score$axis[3]
# static
cls <- mSetObj$dataSet$cls;
col.def <- GetColorSchema(cls);
cols <- ExpandSchema(cls, col.def);
pchs <- as.numeric(cls)+1;
uniq.pchs <- unique(pchs);
Plot3D(coords[,inx1], coords[,inx2], coords[,inx3], xlab= xlabel, ylab=ylabel,
zlab=zlabel, angle = angl, color=cols, pch=pchs);
legend("topleft", legend = names(col.def), pch=uniq.pchs, col=col.def);
dev.off();
return(.set.mSet(mSetObj));
}
#'Plot PLS 3D score plot
#'@description This function creates two 3D PLS-DA score plots, the first is static for Analysis Report purposes, as well as
#'an interactive 3D plot using the plotly R package. The 3D score plot is saved in the created mSetObj (mSetObj$imgSet$plsda.3d).
#'To view the score plot, if the name of your mSetObj is mSet, enter "mSet$imgSet$plsda.3d" to view the interactive score plot.
#'@param mSetObj Input name of the created mSet Object
#'@param imgName Input a name for the plot
#'@param format Select the image format, "png", or "pdf".
#'@param dpi Input the dpi. If the image format is "pdf", users need not define the dpi. For "png" images,
#'the default dpi is 72. It is suggested that for high-resolution images, select a dpi of 300.
#'@param width Input the width, there are 2 default widths, the first, width = NULL, is 10.5.
#'The second default is width = 0, where the width is 7.2. Otherwise users can input their own width.
#'@param inx1 Numeric, indicate the number of the principal component for the x-axis of the loading plot.
#'@param inx2 Numeric, indicate the number of the principal component for the y-axis of the loading plot.
#'@param inx3 Numeric, indicate the number of the principal component for the z-axis of the loading plot.
#'@param angl Input the angle
#'@author Jeff Xia\email{jeff.xia@mcgill.ca}
#'McGill University, Canada
#'License: GNU GPL (>= 2)
#'@export
#'@importFrom plotly plot_ly add_markers layout
PlotPLS3DScoreImg<-function(mSetObj=NA, imgName, format="png", dpi=72, width=NA, inx1, inx2, inx3, angl){
mSetObj <- .get.mSet(mSetObj);
imgName = paste(imgName, "dpi", dpi, ".", format, sep="");
if(is.na(width)){
w <- 9;
}else if(width == 0){
w <- 7.2;
}else{
w <- width;
}
h <- w;
mSetObj$imgSet$pls.score3d <- imgName;
Cairo::Cairo(file = imgName, unit="in", dpi=dpi, width=w, height=h, type=format, bg="white");
par(mar=c(5,5,3,3));
xlabel <- paste("Component", inx1, "(", round(100*mSetObj$analSet$plsr$Xvar[inx1]/mSetObj$analSet$plsr$Xtotvar,1), "%)");
ylabel <- paste("Component", inx2, "(", round(100*mSetObj$analSet$plsr$Xvar[inx2]/mSetObj$analSet$plsr$Xtotvar,1), "%)");
zlabel <- paste("Component", inx3, "(", round(100*mSetObj$analSet$plsr$Xvar[inx3]/mSetObj$analSet$plsr$Xtotvar,1), "%)");
cls <- mSetObj$dataSet$cls;
col.def <- GetColorSchema(cls);
cols <- ExpandSchema(cls, col.def);
pchs <- as.numeric(mSetObj$dataSet$cls)+1;
uniq.pchs <- unique(pchs);
Plot3D(mSetObj$analSet$plsr$score[,inx1], mSetObj$analSet$plsr$score[,inx2], mSetObj$analSet$plsr$score[,inx3], xlab= xlabel, ylab=ylabel,
zlab=zlabel, angle =angl, color=cols, pch=pchs);
legend("topleft", legend = names(col.def), pch=uniq.pchs, col=col.def);
dev.off();
return(.set.mSet(mSetObj));
}
xia-lab/MetaboAnalystR documentation built on April 20, 2024, 8:13 p.m.
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Defines functions PlotPLS3DScoreImg PlotSPLS3DScoreImg PlotSPLS3DScoreImg PlotPCA3DScoreImg Plot3D
Documented in PlotPCA3DScoreImg PlotPLS3DScoreImg PlotSPLS3DScoreImg
### R script for MetaboAnalyst
### Description: 3D scatter plot for PDF report (not used for web display)
### Author: Jeff Xia, jeff.xia@mcgill.ca
### McGill University, Canada
### License: GNU GPL (>= 2)
Plot3D <- function(x, y, z, xlab= xlabel, ylab=ylabel, zlab=zlabel,
angle =angl, color=cols, pch=pchs){
if(.on.public.web){
# make this lazy load
if(!exists("my.plot.scatter3d")){ # public web on same user dir
.load.scripts.on.demand("util_plot3d.Rc");
}
return(my.plot.scatter3d(x, y, z, xlab=xlab, ylab=ylab,
zlab=zlab, angle =angle, color=color, pch=pch));
}else{
return(my.plot.scatter3d(x, y, z, xlab=xlab, ylab=ylab,
zlab=zlab, angle =angle, color=color, pch=pch));
}
}
#'Create 3D PCA score plot
#'@description This function creates both a static 3D PCA score plot as well as an interactive 3D PCA score plot
#'using the plotly R package. The 3D PCA score plot is stored in the mSetObj (mSetObj$imgSet$pca.3d). To view
#'the plot, if your mSetObj is named mSet, type "mSet$imgSet$pca.3d" inro your R console, and the 3D plot will appear.
#'@author Jeff Xia\email{jeff.xia@mcgill.ca}
#'McGill University, Canada
#'License: GNU GPL (>= 2)
#'@usage PlotPCA3DScoreImg(mSetObj=NA, imgName,
#'format="png", dpi=72, width=NA, inx1, inx2, inx3, angl)
#'@param mSetObj Input name of the created mSet Object.
#'@param imgName Input a name for the plot.
#'@param format Select the image format, "png", or "pdf".
#'@param dpi Input the dpi. If the image format is "pdf", users need not define the dpi. For "png" images,
#'the default dpi is 72. It is suggested that for high-resolution images, select a dpi of 300.
#'@param width Input the width, there are 2 default widths, the first, width = NULL, is 10.5.
#'The second default is width = 0, where the width is 7.2. Otherwise users can input their own width.
#'@param inx1 Numeric, indicate the number of the principal component for the x-axis of the loading plot.
#'@param inx2 Numeric, indicate the number of the principal component for the y-axis of the loading plot.
#'@param inx3 Numeric, indicate the number of the principal component for the z-axis of the loading plot.
#'@param angl Input the angle
#'@export
#'@importFrom plotly plot_ly add_markers layout
PlotPCA3DScoreImg <- function(mSetObj=NA, imgName, format="png",
dpi=72, width=NA, inx1, inx2, inx3, angl){
mSetObj <- .get.mSet(mSetObj);
xlabel = paste("PC",inx1, "(", round(100*mSetObj$analSet$pca$variance[inx1],1), "%)");
ylabel = paste("PC",inx2, "(", round(100*mSetObj$analSet$pca$variance[inx2],1), "%)");
zlabel = paste("PC",inx3, "(", round(100*mSetObj$analSet$pca$variance[inx3],1), "%)");
imgName = paste(imgName, "dpi", dpi, ".", format, sep="");
if(is.na(width)){
w <- 9;
}else if(width == 0){
w <- 7.2;
}else{
w <- width;
}
h <- w;
mSetObj$imgSet$pca.score3d <- imgName;
Cairo::Cairo(file = imgName, unit="in", dpi=dpi, width=w, height=h, type=format, bg="white");
cls <- mSetObj$dataSet$cls;
pchs <- as.numeric(cls)+1;
uniq.pchs <- unique(pchs);
if(mSetObj$dataSet$cls.type == "disc"){
col.def <- GetColorSchema(cls);
all.cols <- ExpandSchema(cls, col.def);
Plot3D(mSetObj$analSet$pca$x[, inx1], mSetObj$analSet$pca$x[, inx2], mSetObj$analSet$pca$x[, inx3], xlab= xlabel, ylab=ylabel,
zlab=zlabel, angle =angl, color=cols, pch=pchs);
legend("topleft", legend = names(col.def), pch=uniq.pchs, col=col.def);
dev.off();
}else{
Plot3D(mSetObj$analSet$pca$x[, inx1], mSetObj$analSet$pca$x[, inx2], mSetObj$analSet$pca$x[, inx3], xlab= xlabel, ylab=ylabel,
zlab=zlabel, angle =angl, pch=pchs);
dev.off();
if(!.on.public.web){
# 3D View using plotly
col <- c("#C61951", "#1972A4")
p <- plotly::plot_ly(x = mSetObj$analSet$pca$x[, inx1], y = mSetObj$analSet$pca$x[, inx2], z = mSetObj$analSet$pca$x[, inx3],
color = pchs, colors = col, marker = list(colorbar = list(len = 1, tickmode = array, tickvals = range(unique(pchs)),
ticktext = levels(mSetObj$dataSet$cls))));
p <- plotly::add_markers(p, sizes = 1000);
p <- plotly::layout(p, scene = list(xaxis = list(title = xlabel),
yaxis = list(title = ylabel),
zaxis = list(title = zlabel)));
mSetObj$imgSet$pca.3d <- p;
print("The Interactive 3D PCA plot has been created, please find it in mSet$imgSet$pca.3d.")
}
}
return(.set.mSet(mSetObj));
}
#'Plot sPLS-DA 3D score plot
#'@description This function creates two 3D sPLS-DA score plots, the first is static for Analysis Report purposes, as well as
#'an interactive 3D plot using the plotly R package. The 3D score plot is saved in the created mSetObj (mSetObj$imgSet$splsda.3d).
#'To view the score plot, if the name of your mSetObj is mSet, enter "mSet$imgSet$splsda.3d" to view the interactive score plot.
#'@param mSetObj Input name of the created mSet Object
#'@param imgName Input a name for the plot
#'@param format Select the image format, "png", or "pdf".
#'@param dpi Input the dpi. If the image format is "pdf", users need not define the dpi. For "png" images,
#'the default dpi is 72. It is suggested that for high-resolution images, select a dpi of 300.
#'@param width Input the width, there are 2 default widths, the first, width = NULL, is 10.5.
#'The second default is width = 0, where the width is 7.2. Otherwise users can input their own width.
#'@param inx1 Numeric, indicate the number of the principal component for the x-axis of the loading plot.
#'@param inx2 Numeric, indicate the number of the principal component for the y-axis of the loading plot.
#'@param inx3 Numeric, indicate the number of the principal component for the z-axis of the loading plot.
#'@param angl Input the angle
#'@author Jeff Xia\email{jeff.xia@mcgill.ca}
#'McGill University, Canada
#'License: GNU GPL (>= 2)
#'@export
#'@importFrom plotly plot_ly add_markers layout
PlotSPLS3DScoreImg<-function(mSetObj=NA, imgName, format="png", dpi=72, width=NA, inx1, inx2, inx3, angl){
mSetObj <- .get.mSet(mSetObj);
imgName = paste(imgName, "dpi", dpi, ".", format, sep="");
if(is.na(width)){
w <- 9;
}else if(width == 0){
w <- 7.2;
}else{
w <- width;
}
h <- w;
mSetObj$imgSet$spls.score3d <- imgName;
Cairo::Cairo(file = imgName, unit="in", dpi=dpi, width=w, height=h, type=format, bg="white");
par(mar=c(5,5,3,3));
spls3d <- list();
## need to check if only 2 or 3 components generated
if(length(mSetObj$analSet$splsr$explained_variance$X)==2){
spls3d$score$axis <- paste("Component", c(inx1, inx2), " (", round(100*mSetObj$analSet$splsr$explained_variance$X[c(inx1, inx2)], 1), "%)", sep="");
coords <- data.frame(signif(mSetObj$analSet$splsr$variates$X[,c(inx1, inx2)], 5));
spls3d$score$axis <- c(spls3d$score$axis, "Component3 (NA)");
coords <- rbind(coords, "comp 3"=rep (0, ncol(coords)));
}else{
spls3d$score$axis <- paste("Component", c(inx1, inx2, inx3), " (", round(100*mSetObj$analSet$splsr$explained_variance$X[c(inx1, inx2, inx3)], 1), "%)", sep="");
coords <- data.frame(signif(mSetObj$analSet$splsr$variates$X[,c(inx1, inx2, inx3)], 5));
}
xlabel <- spls3d$score$axis[1]
ylabel <- spls3d$score$axis[2]
zlabel <- spls3d$score$axis[3]
# static
cls <- mSetObj$dataSet$cls;
col.def <- GetColorSchema(cls);
cols <- ExpandSchema(cls, col.def);
pchs <- as.numeric(cls)+1;
uniq.pchs <- unique(pchs);
Plot3D(coords[,inx1], coords[,inx2], coords[,inx3], xlab= xlabel, ylab=ylabel,
zlab=zlabel, angle = angl, color=cols, pch=pchs);
legend("topleft", legend = names(col.def), pch=uniq.pchs, col=col.def);
dev.off();
return(.set.mSet(mSetObj));
}
#'Plot sPLS-DA 3D score plot
#'@description This function creates two 3D sPLS-DA score plots, the first is static for Analysis Report purposes, as well as
#'an interactive 3D plot using the plotly R package. The 3D score plot is saved in the created mSetObj (mSetObj$imgSet$splsda.3d).
#'To view the score plot, if the name of your mSetObj is mSet, enter "mSet$imgSet$splsda.3d" to view the interactive score plot.
#'@param mSetObj Input name of the created mSet Object
#'@param imgName Input a name for the plot
#'@param format Select the image format, "png", or "pdf".
#'@param dpi Input the dpi. If the image format is "pdf", users need not define the dpi. For "png" images,
#'the default dpi is 72. It is suggested that for high-resolution images, select a dpi of 300.
#'@param width Input the width, there are 2 default widths, the first, width = NULL, is 10.5.
#'The second default is width = 0, where the width is 7.2. Otherwise users can input their own width.
#'@param inx1 Numeric, indicate the number of the principal component for the x-axis of the loading plot.
#'@param inx2 Numeric, indicate the number of the principal component for the y-axis of the loading plot.
#'@param inx3 Numeric, indicate the number of the principal component for the z-axis of the loading plot.
#'@param angl Input the angle
#'@author Jeff Xia\email{jeff.xia@mcgill.ca}
#'McGill University, Canada
#'License: GNU GPL (>= 2)
#'@export
#'@importFrom plotly plot_ly add_markers layout
PlotSPLS3DScoreImg<-function(mSetObj=NA, imgName, format="png", dpi=72, width=NA, inx1, inx2, inx3, angl){
mSetObj <- .get.mSet(mSetObj);
imgName = paste(imgName, "dpi", dpi, ".", format, sep="");
if(is.na(width)){
w <- 9;
}else if(width == 0){
w <- 7.2;
}else{
w <- width;
}
h <- w;
mSetObj$imgSet$spls.score3d <- imgName;
Cairo::Cairo(file = imgName, unit="in", dpi=dpi, width=w, height=h, type=format, bg="white");
par(mar=c(5,5,3,3));
spls3d <- list();
## need to check if only 2 or 3 components generated
if(length(mSetObj$analSet$splsr$explained_variance$X)==2){
spls3d$score$axis <- paste("Component", c(inx1, inx2), " (", round(100*mSetObj$analSet$splsr$explained_variance$X[c(inx1, inx2)], 1), "%)", sep="");
coords <- data.frame(signif(mSetObj$analSet$splsr$variates$X[,c(inx1, inx2)], 5));
spls3d$score$axis <- c(spls3d$score$axis, "Component3 (NA)");
coords <- rbind(coords, "comp 3"=rep (0, ncol(coords)));
}else{
spls3d$score$axis <- paste("Component", c(inx1, inx2, inx3), " (", round(100*mSetObj$analSet$splsr$explained_variance$X[c(inx1, inx2, inx3)], 1), "%)", sep="");
coords <- data.frame(signif(mSetObj$analSet$splsr$variates$X[,c(inx1, inx2, inx3)], 5));
}
xlabel <- spls3d$score$axis[1]
ylabel <- spls3d$score$axis[2]
zlabel <- spls3d$score$axis[3]
# static
cls <- mSetObj$dataSet$cls;
col.def <- GetColorSchema(cls);
cols <- ExpandSchema(cls, col.def);
pchs <- as.numeric(cls)+1;
uniq.pchs <- unique(pchs);
Plot3D(coords[,inx1], coords[,inx2], coords[,inx3], xlab= xlabel, ylab=ylabel,
zlab=zlabel, angle = angl, color=cols, pch=pchs);
legend("topleft", legend = names(col.def), pch=uniq.pchs, col=col.def);
dev.off();
return(.set.mSet(mSetObj));
}
#'Plot PLS 3D score plot
#'@description This function creates two 3D PLS-DA score plots, the first is static for Analysis Report purposes, as well as
#'an interactive 3D plot using the plotly R package. The 3D score plot is saved in the created mSetObj (mSetObj$imgSet$plsda.3d).
#'To view the score plot, if the name of your mSetObj is mSet, enter "mSet$imgSet$plsda.3d" to view the interactive score plot.
#'@param mSetObj Input name of the created mSet Object
#'@param imgName Input a name for the plot
#'@param format Select the image format, "png", or "pdf".
#'@param dpi Input the dpi. If the image format is "pdf", users need not define the dpi. For "png" images,
#'the default dpi is 72. It is suggested that for high-resolution images, select a dpi of 300.
#'@param width Input the width, there are 2 default widths, the first, width = NULL, is 10.5.
#'The second default is width = 0, where the width is 7.2. Otherwise users can input their own width.
#'@param inx1 Numeric, indicate the number of the principal component for the x-axis of the loading plot.
#'@param inx2 Numeric, indicate the number of the principal component for the y-axis of the loading plot.
#'@param inx3 Numeric, indicate the number of the principal component for the z-axis of the loading plot.
#'@param angl Input the angle
#'@author Jeff Xia\email{jeff.xia@mcgill.ca}
#'McGill University, Canada
#'License: GNU GPL (>= 2)
#'@export
#'@importFrom plotly plot_ly add_markers layout
PlotPLS3DScoreImg<-function(mSetObj=NA, imgName, format="png", dpi=72, width=NA, inx1, inx2, inx3, angl){
mSetObj <- .get.mSet(mSetObj);
imgName = paste(imgName, "dpi", dpi, ".", format, sep="");
if(is.na(width)){
w <- 9;
}else if(width == 0){
w <- 7.2;
}else{
w <- width;
}
h <- w;
mSetObj$imgSet$pls.score3d <- imgName;
Cairo::Cairo(file = imgName, unit="in", dpi=dpi, width=w, height=h, type=format, bg="white");
par(mar=c(5,5,3,3));
xlabel <- paste("Component", inx1, "(", round(100*mSetObj$analSet$plsr$Xvar[inx1]/mSetObj$analSet$plsr$Xtotvar,1), "%)");
ylabel <- paste("Component", inx2, "(", round(100*mSetObj$analSet$plsr$Xvar[inx2]/mSetObj$analSet$plsr$Xtotvar,1), "%)");
zlabel <- paste("Component", inx3, "(", round(100*mSetObj$analSet$plsr$Xvar[inx3]/mSetObj$analSet$plsr$Xtotvar,1), "%)");
cls <- mSetObj$dataSet$cls;
col.def <- GetColorSchema(cls);
cols <- ExpandSchema(cls, col.def);
pchs <- as.numeric(mSetObj$dataSet$cls)+1;
uniq.pchs <- unique(pchs);
Plot3D(mSetObj$analSet$plsr$score[,inx1], mSetObj$analSet$plsr$score[,inx2], mSetObj$analSet$plsr$score[,inx3], xlab= xlabel, ylab=ylabel,
zlab=zlabel, angle =angl, color=cols, pch=pchs);
legend("topleft", legend = names(col.def), pch=uniq.pchs, col=col.def);
dev.off();
return(.set.mSet(mSetObj));
}
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