Class DataFusionMergeStage

    UserDict.UserDict --+        
                        |        
UserDict.IterableUserDict --+    
                            |    
                  stage.Stage --+
                                |
                               DataFusionMergeStage

This stage takes in results from a Glide docking job, Phase Shape job,
and a Canvas 2D fingerprint job and combines them based on the Z-score
for each method.

This stage is used by Data Fusion workflow (data_fusion_backend.py).

Z-score = the number of standard deviations above or below the mean of the
          distribution of scores for that method.
Final score = For each compound, the sum of z-scores for the 3 methods.
              Compounds will be sorted by the final score in the output.

STAGE Merge Results
    Input 1: Docking PV file
    Input 2: Phase Shape output file
    Input 3: Canvas 2D Fingerprints output file
    Output: Merged Maestro file of compounds sorted by the final score.

Properties included in the output:
1. Glide score
2. Phase Shape score
3. Similarity score
4. Consensus/final score (average of z-scores)

WARNING: This stage assumes that only one ligand with the same UNIQUEFIELD
exists in each input set.

Takes in a dictionary where keys are compound IDs, and values are
scores, and returns a dict of z-scores (keys are compound IDs also).
Z-score is calculated by:
    z-score = (score-average) / std-deviations

If the number of compounds is 1, then the z-score will be <None>.

@param scores_by_compound: Dictionary of scores (e.g. Glide score)
    keyed by compound ID.
@type scores_by_compound: dict

@param more_negative_is_better: If set to True, more negavtive scores
    are considered to be better, and will result in higher Z-scores.
@type more_negative_is_better: bool

@return: Z-Scores, in a dictionary keyed by compound ID.
@rtype: dict