Plotscores: Difference between revisions

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===Description===
===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.
Given a standard model structure, relevant scores information (e.g. labels) is collected and passed to [[plotgui]] for plotting.


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, labels, and other information that is needed for subsequent plotting.


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.
====Inputs====


===Options===
* '''modl''' = a standard model structure. '''plotscores''' will extract the scores, labels, and and other information that is needed for plotting.
* '''pred''' = a standard prediction structure (e.g. output from PCA call: pred  = pca(x,modl,options);)
* '''scores''' = a ''M'' by ''K'' scores matrix (class "double").
 
====Optional Inputs====


''options'' a structure array with the following fields:
* '''labels''' is a character or cell array with ''M'' rows containing sample labels
* '''classes''' a vector with ''M'' integer elements of class identifiers.
* Optional input '''options''' is discussed below.


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


* '''plots''': ['none' | 'final' | {'auto'} |], governs plotting behavior, 'auto' makes plots if no output is requested {default},
* '''a''' = a dataset containing scores and label information that can be passed to [[plotgui]].


* '''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
===Options===


* '''sct''': [ 0 | {1} ], tells whether to plot cal (modl scores) with test (pred scores), sct = 1 plots original calibration data with prediction set {default}.
'''options''' =  a structure array with the following fields:
* '''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)
* '''sct''': [ 0 | {1} ], tells whether to plot cal (modl scores) with test (pred scores), sct = 1 plots original calibration data with prediction set {default = 1}.


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


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

Revision as of 16:51, 8 October 2008

Purpose

Extract and display scores information from model.

Synopsis

a = plotscores(modl,options)
a = plotscores(modl,pred,options)
a = plotscores(scores,labels,classes)

Description

Given a standard model structure, relevant scores information (e.g. labels) is collected and passed to plotgui for plotting.

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, labels, and other information that is needed for subsequent plotting.

Inputs

  • modl = a standard model structure. plotscores will extract the scores, labels, and and other information that is needed for plotting.
  • pred = a standard prediction structure (e.g. output from PCA call: pred = pca(x,modl,options);)
  • scores = a M by K scores matrix (class "double").

Optional Inputs

  • labels is a character or cell array with M rows containing sample labels
  • classes a vector with M integer elements of class identifiers.
  • Optional input options is discussed below.

Outputs

  • a = a dataset containing scores and label information that can be passed to plotgui.

Options

options = a structure array with the following fields:

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

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

See Also

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