anchor.diff:                     (randomize-weights net))
                  (when logger-function
                    (funcall logger-function "randomized weights")))
  -             (when (> (- i last-anneal-iteration) 20)
  +             (when (and annealing (> (- i last-anneal-iteration) annealing))
                  (anneal net 1.0)
                  (setf last-anneal-iteration i)
                  (when logger-function
  
positive.code:                          :net (net layer))
            (neuron-array layer)))))
  
  (defun transfer-function-1 (input)
    (declare (single-float input))
    (cond
      ((> input 50.0) 1.0)
      ((< input -50.0) 0.0)
      (t (/ 1.0 (1+ (exp (- input)))))))
  
  (defun transfer-derivative-1 (neuron)
    (declare (t-neuron neuron))
    (* (output neuron) (- 1 (output neuron))))
  
  (defclass t-net ()
    ((topology :reader topology :initarg :topology
  
negative.code: (defgeneric randomize-weights (object &key)
    (:method ((neuron t-neuron) &key max min)
      (declare (float max min))
      (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))
  