Module GrowComposite

command line utility for growing composite models

**Usage**

  _GrowComposite [optional args] filename_

**Command Line Arguments**

  - -n *count*: number of new models to build

  - -C *pickle file name*:  name of file containing composite upon which to build.

  - --inNote *note*: note to be used in loading composite models from the database
      for growing

  - --balTable *table name*:  table from which to take the original data set
     (for balancing)

  - --balWeight *weight*: (between 0 and 1) weighting factor for the new data
     (for balancing). OR, *weight* can be a list of weights

  - --balCnt *count*: number of individual models in the balanced composite
     (for balancing)

  - --balH: use only the holdout set from the original data set in the balancing
     (for balancing)

  - --balT: use only the training set from the original data set in the balancing
     (for balancing)

  - -S: shuffle the original data set
     (for balancing)

  - -r: randomize the activities of the original data set
     (for balancing)

  - -N *note*: note to be attached to the grown composite when it's saved in the
     database

  - --outNote *note*: equivalent to -N

  - -o *filename*: name of an output file to hold the pickled composite after
     it has been grown.
     If multiple balance weights are used, the weights will be added to
     the filenames.

  - -L *limit*: provide an (integer) limit on individual model complexity
  
  - -d *database name*: instead of reading the data from a QDAT file,
     pull it from a database.  In this case, the _filename_ argument
     provides the name of the database table containing the data set.

  - -p *tablename*: store persistence data in the database
     in table *tablename*

  - -l: locks the random number generator to give consistent sets
     of training and hold-out data.  This is primarily intended
     for testing purposes.

  - -g: be less greedy when training the models.

  - -G *number*: force trees to be rooted at descriptor *number*.

  - -D: show a detailed breakdown of the composite model performance
     across the training and, when appropriate, hold-out sets.
     
  - -t *threshold value*: use high-confidence predictions for the final
     analysis of the hold-out data.

  - -q *list string*:  Add QuantTrees to the composite and use the list
     specified in *list string* as the number of target quantization
     bounds for each descriptor.  Don't forget to include 0's at the
     beginning and end of *list string* for the name and value fields.
     For example, if there are 4 descriptors and you want 2 quant bounds
     apiece, you would use _-q "[0,2,2,2,2,0]"_.
     Two special cases:
       1) If you would like to ignore a descriptor in the model building,
          use '-1' for its number of quant bounds.
       2) If you have integer valued data that should not be quantized
          further, enter 0 for that descriptor.

  - -V: print the version number and exit

emits messages to _sys.stdout_
override this in modules which import this one to redirect output

**Arguments**

  - msg: the string to be displayed

does the actual work of building a composite model

**Arguments**

  - details:  a _CompositeRun.CompositeRun_ object containing details
    (options, parameters, etc.) about the run

  - composite: the composite model to grow
  
  - progressCallback: (optional) a function which is called with a single
    argument (the number of models built so far) after each model is built.

  - saveIt: (optional) if this is nonzero, the resulting model will be pickled
    and dumped to the filename specified in _details.outName_

  - setDescNames: (optional) if nonzero, the composite's _SetInputOrder()_ method
    will be called using the results of the data set's _GetVarNames()_ method;
    it is assumed that the details object has a _descNames attribute which
    is passed to the composites _SetDescriptorNames()_ method.  Otherwise
    (the default), _SetDescriptorNames()_ gets the results of _GetVarNames()_.

  - data: (optional) the data set to be used.  If this is not provided, the
    data set described in details will be used.
    
**Returns**

  the enlarged composite model

balances the composite using the parameters provided in details

**Arguments**

  - details a _CompositeRun.RunDetails_ object

  - composite: the composite model to be balanced

  - data1: (optional) if provided, this should be the
    data set used to construct the original models

  - data2: (optional) if provided, this should be the
    data set used to construct the new individual models

prints the version number

  

provides a list of arguments for when this is used from the command line

  

initializes a details object with default values

**Arguments**

  - details:  (optional) a _CompositeRun.CompositeRun_ object.
    If this is not provided, the global _runDetails will be used.

**Returns**

  the initialized _CompositeRun_ object.