code: def classifySPoutput(targetOutputColumns, outputColumns):
    
    numTargets, numDims = targetOutputColumns.shape
    overlap = np.zeros((numTargets,))
    for i in range(numTargets):
      overlap[i] = percentOverlap(outputColumns, targetOutputColumns[i, :])
    classLabel = np.argmax(overlap)
    return classLabel
docs: Classify the SP output
    @param targetOutputColumns (list) The target outputs, corresponding to
                                      different classes
    @param outputColumns (array) The current output
    @return classLabel (int) classification outcome