Module VoteImg

collects the votes from _composite_ for the examples in _data_

    **Arguments**

      - composite: a composite model

      - data: a list of examples to run through _composite_

      - badOnly: if set only bad (misclassified) examples will be kept

    **Returns**

      a 4-tuple containing:

        1) the expanded list of vote details (see below)

        2) the list of predicted results

        3) the list of true results

        4) the number of miscounted examples

    
    **Notes**

pp      - the expanded list of vote details consists of:

        '[ vote1, vote2, ... voteN, 0, res, trueRes]'

        where _res_ is the predicted results and _trueRes_ is the actual result.
        The extra zero is included to allow a line to be drawn between the votes
        and the results.
        
  

constructs the actual image

**Arguments**

  - nModels: the number of models in the composite

  - data: the results of voting

  - values: predicted values for each example

  - trueValues: true values for each example

  - sortTrueVals: if nonzero the votes will be sorted so
    that the _trueValues_ are in order, otherwise the sort
    is by _values_

  - xScale: number of pixels per vote in the x direction

  - yScale: number of pixels per example in the y direction

  - addLine: if nonzero, a purple line is drawn separating
     the votes from the examples

**Returns**

  a PIL image
  

collects votes on the examples and constructs an image

**Arguments**

  - composte: a composite model

  - data: the examples to be voted upon

  - badOnly: if nonzero only the incorrect votes will be shown

  - sortTrueVals: if nonzero the votes will be sorted so
    that the _trueValues_ are in order, otherwise the sort
    is by _values_

  - xScale: number of pixels per vote in the x direction

  - yScale: number of pixels per example in the y direction

  - addLine: if nonzero, a purple line is drawn separating
     the votes from the examples

**Returns**

  a PIL image