PLS_Toolbox Documentation: plotscores	< plotloads	pls >

plotscores

Purpose

Extract and display scores information from model.

Synopsis

a = scoresplot(modl,options)

a = scoresplot(modl,pred,options)

a = plotscores(scores,labels,classes)

options = plotscores('options')

Description

Given a standard model structure, relevant scores information (e.g. labels) is collected and passed to PLOTGUI for plotting. The input is the model containing scores to plot modl. (e.g. see MODELSTRUCT). A second input pred contains a test or validation structrure (see PCA) that can be plotted with scores in modl. Optional input options is discussed below.

Input scores is a M by K scores matrix (class “double”). Optional input labels is a character or cell array with M rows containing sample labels, and optional input classes is a vector with M integer elements of class identifiers.

If no output is requested then PLOTSCORES initiates an interactive plotting utility to make scores plots. If an output is requested, no plots are made, and the output a is a dataset object containing the scores and labels, etc.

Options

             options =   a structure array with the following fields:

              display:   [ {'on'} | 'off' ], governs level of display,

                  plots:   ['none' | 'final' | {'auto'} |], governs plotting behavior, 'auto' makes plots if no output is requested {default},

                figure:  [],governs where plots are made, when figure = [] plots are made in a new figure window {default}, this can also be a valid figure number (i.e. figure handle), and

                      sct:  [ 0 | {1} ], tells whether to plot cal (modl scores) with test (pred scores), sct = 1 plots original calibration data with prediction set {default}.

The default options can be retreived using: options = plotscores('options');.

See Also

analysis, mcr, modelstruct, modelviewer, mpca, pca, pcr, plotgui, plotloads, pls