anchor.diff:                (logger-function nil)
                 (randomize-weights nil)
                 (annealing nil)
  -              (rerandomize-weights nil))
  -    (declare (float target-mse)
  +              (rerandomize-weights nil)
  +              (log-file "/tmp/training.log"))
  +    (declare (real target-mse)
                (integer max-iterations report-frequency)
                (function report-function status-function))
       (loop
          initially
            (when status-function
              (funcall status-function
  +                    :file log-file
                       :net net :status "learning" :elapsed 0 :iteration 0
                       :mse 1.0))
            (when randomize-weights
  
positive.code:             (height 100.0)
              (h-margin 20.0)
              (v-margin 20.0))
      (declare (float width height h-margin v-margin))
      (let* ((c-width (- width (* h-margin 2)))
             (v-delta (/ (- height (* v-margin 2))
                                (1- (length (layers net))))))
  
negative.code: (defclass t-cx ()
    ((target :reader target :initarg :target :initform (error ":neuron required")
             :type t-neuron)
     (weight :accessor weight :initarg :weight :initform 1.0 :type real)
     (delta :accessor delta :initform 0.0 :type real))
    (:documentation "Describes a neural connection to TARGET neuron.  WEIGHT represents the strength of the connection and DELTA contains the last change in WEIGHT.  TARGET is required."))
  
  
  