Plotloads

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Purpose

Extract and display loadings information from a model structure.

Synopsis

a = plotloads(modl,options)
a = plotloads(loads,labels,classes)

Description

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

If no output is requested, then plotloads initiates an interactive plotting utility to make loadings plots. If an output is requested, no plots are made.

Input

  • modl = a standard model structure, containing loadings to plot; plotloads will extract the loadings, labels and other information for plotting.
  • loads = a N by K loadings matrix (class "double")

Optional Input

  • labels = a character or cell array with N rows containing sample labels
  • classes = a vector with N integer elements of class identifiers.

Output

  • a = a dataset object containing the loadings, labels and other information required for subsequent plotting

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)
  • mode: [2] specifies which mode of loadings to plot. Default is 2 (columns of the original data). This only has significance for multi-way data.
  • block: [1] specifies which block to plot loadings for. 1 = x-block, 2 = y-block. If specified block does not exist, an error will be thrown.
  • undopre: [ {'no'} | 'yes' ] undo preprocessing on loadings (to the extent possible). Corrects loadings for scaling and some other preprocessing effects. Note that this produces loadings which are not the same as what the data will be projected onto but unpreprocessed loadings may be more interpretable.


The default options can be retrieved using: options = plotloads('options');.

See Also

analysis, mcr, modelstruct, modelviewer, mpca, pca, pcr, ploteigen, plotgui, ploteigen, plotscores, pls, sratio, vip