private Node[] Epoch(int t, Drink inputDrink, Node[] nodesArray)
        {
            BestMatchingNodeMultiThreadedSearcher bestMatchingNodeMultiThreadedSearcher = new BestMatchingNodeMultiThreadedSearcher(nodesArray, processorsCount, inputDrink.FeaturesArray);
            int winningNodeIndex = bestMatchingNodeMultiThreadedSearcher.GetBestMatchingNodeIndex();

            double neighbourhoodRadius = Radius(t);
            double learningRate = LearningRate(t);

            potentialsArray[winningNodeIndex] -= (_minNeuronPotential + maxNeuronRestTimeInv);
            UpdatePotentialsArray(maxNeuronRestTimeInv);

            System.Threading.Tasks.Parallel.ForEach(nodesArray, node =>
                {
                    double theta = Theta(t, nodesArray[winningNodeIndex], node, neighbourhoodRadius);

                    if (theta > 0)
                    {
                        node.AdjustWeights(theta, learningRate, inputDrink.FeaturesArray);
                        node.DrinkID = inputDrink.ID;
                    }
                });

            return nodesArray;
        }
Exemple #2
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        private void RefreshListViewSimilarDrinks(Drink[] similarDrinksArray)
        {
            lv_SimilarDrinks.BeginUpdate();

            lv_SimilarDrinks.Items.Clear();
            lv_SimilarDrinks.LargeImageList.Images.Clear();

            System.Collections.Concurrent.ConcurrentDictionary<int, Image> dictImages = new System.Collections.Concurrent.ConcurrentDictionary<int, Image>();

            System.Threading.Tasks.Parallel.ForEach( similarDrinksArray, drink =>
            {
                dictImages.TryAdd(drink.ID,GetDrinkImage(drink).ResizeImage(SIMILAR_DRINK_IMAGE_SIZE));
            });

            foreach(Drink drink in similarDrinksArray)
            {
                lv_SimilarDrinks.LargeImageList.Images.Add(drink.ID.ToString(),dictImages[drink.ID]);
                ListViewItem lvi = new ListViewItem(drink.Name);
                lvi.Tag = drink.Url;
                lvi.ImageKey = drink.ID.ToString();
                lv_SimilarDrinks.Items.Add(lvi);
            }

            /*
            for (int i = 0; i < similarDrinksArray.Length; i++)
            {
                lv_SimilarDrinks.LargeImageList.Images.Add(GetDrinkImage(similarDrinksArray[i]).ResizeImage(SIMILAR_DRINK_IMAGE_SIZE));
                ListViewItem lvi = new ListViewItem(similarDrinksArray[i].Name);
                lvi.Tag = similarDrinksArray[i].Url;
                lvi.ImageIndex = i;

                lv_SimilarDrinks.Items.Add(lvi);
            }
            */

            lv_SimilarDrinks.EndUpdate();
        }
        private Node[] InitializeNodes(Drink[] trainingDataBaseArray)
        {
            List<Drink> trainingData = trainingDataBaseArray.ToList();
            int nodesNumber = neuralMapWidth * neuralMapHeight;
            Node[] nodesArray = new Node[nodesNumber];

            for (int i = 0; i < nodesNumber; i++)
            {
                if( trainingData.Count == 0)
                    trainingData = trainingDataBaseArray.ToList();

                    int index = randomizer.Next(trainingData.Count);
                    Drink drink = trainingData[index];

                    nodesArray[i] = new Node(trainingData[index].FeaturesArray,(i % neuralMapWidth) * distanceBetweenNeurons, (i / neuralMapWidth) * distanceBetweenNeurons, drink.ID);
                    trainingData.RemoveAt(index);
            }

            return nodesArray;
        }
Exemple #4
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 private Image GetDrinkImage(Drink drink)
 {
     if (drinksImagesDictionary.ContainsKey(drink.ID))
     {
         return drinksImagesDictionary[drink.ID];
     }
     else
     {
         Image drinkImage = GetImageFromUrl(drink.ImageUrl);
         drinksImagesDictionary.Add(drink.ID, drinkImage);
         return drinkImage;
     }
 }