anchor.diff:  (defgeneric randomize-weights (object &key)
     (:method ((neuron t-neuron) &key max min)
       (declare (float max min))
  -    (loop for cx in (cxs neuron) do
  -         (setf (weight cx) (+ (random (- max min)) min))
  -         (setf (delta cx) 0))
  +    (if (= max min)
  +        (loop for cx in (cxs neuron) do
  +             (setf (weight cx) max)
  +             (setf (delta cx) 0))
  +        (loop for cx in (cxs neuron) do
  +             (setf (weight cx) (+ (random (- max min)) min))
  +             (setf (delta cx) 0)))
       neuron)
     (:method ((layer t-layer) &key max min)
       (declare (float max min))
  
positive.code:                    (randomize-weights net))
                 (when logger-function
                   (funcall logger-function "randomized weights")))
               (when (> (- i last-anneal-iteration) 20)
                 (anneal net 1.0)
                 (setf last-anneal-iteration i)
                 (when logger-function
  
negative.code:   (setf (output neuron)
          (if (eq (layer-type (layer neuron)) :input)
              (input neuron)
              (funcall (transfer-function (net neuron)) neuron)))
    (setf (input neuron) (if (biased neuron) 1.0 0.0))
    neuron)
  
  