Package org.encog.workbench.dialogs.common

Examples of org.encog.workbench.dialogs.common.IntegerField


    addProperty(this.perturbPercent = new DoubleField("perturb percent","Perturb Percent",true,0,-1));
    this.beginTab("Gaussian");
    addProperty(this.mean = new DoubleField("mean","Mean",true,0,-1));
    addProperty(this.deviation = new DoubleField("standard deviation","Standard Deviation",true,0,-1));
    this.beginTab("Consistent");
    addProperty(this.seedValue = new IntegerField("seed value","Seed Value",true,0,-1));
    addProperty(this.constHigh = new DoubleField("high","High Range",true,0,-1));
    addProperty(this.constLow = new DoubleField("low","Low Range",true,0,-1));   
    this.beginTab("Constant");
    addProperty(this.constantValue = new DoubleField("constant value","Constant Value",true,0,-1));
    render();
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  public InputAndIdealDialog(Frame owner) {
    super(owner);

    setTitle("Create Training");
    setSize(500,150);
    addProperty(this.inputCount = new IntegerField("input count","Input Count",true,1,10000));
    addProperty(this.idealCount = new IntegerField("ideal count","Ideal Count (0=unsupervised)",true,0,10000));
    render();   
  }
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  public NewPopulationDialog() {
    super(EncogWorkBench.getInstance().getMainWindow());
    this.setSize(400, 200);
    this.setTitle("Create NEAT Population");
   
    addProperty(this.populationSize = new IntegerField("population size","Population Size",true,1,-1));
    addProperty(this.inputNeurons = new IntegerField("input size","Input Neurons",true,1,-1));
    addProperty(this.outputNeurons = new IntegerField("output size","output Neurons",true,1,-1));
    addProperty(this.snapshot = new CheckField("snapshot","Snapshot"));
   
    addProperty(this.outputActivationField = new PopupField("output activation",
        "Output Activation Function", true));
    addProperty(this.neatActivationField = new PopupField("NEAT activation",
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    setTitle("Extract Top Genomes");
    setSize(400,200);
    setLocation(200,200);
   
    addProperty(this.genomesToExtract = new IntegerField("genomes to extract", "Genomes to Extract", true, 0 , populationSize));
    addProperty(this.prefix = new TextField("prefix","Neural Network Prefix",true));
   
    render();
    this.prefix.setValue("network-");
    this.genomesToExtract.setValue(1);
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    this.setSize(640, 200);
    this.setTitle("Export Image");
   
    addProperty(this.targetFile = new FileField("target file","Target File",true,true,null));
    addProperty(this.fileType = new ComboBoxField("type type", "Export File Type",true,list));
    addProperty(this.height = new IntegerField("height","Image Height (pixels)",true,32,Integer.MAX_VALUE));
    addProperty(this.width = new IntegerField("width","Image Width (pixels)",true,32,Integer.MAX_VALUE));
    render();
  }
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  public NeuronRangeDialog(Frame owner) {
    super(owner);
    setTitle("Hidden Layer Range");
    setSize(400,400);
    setLocation(200,200);
    addProperty(this.low = new IntegerField("low","Low Neuron Count",true,0,100000));
    addProperty(this.high = new IntegerField("high","High Neuron Count",true,1,100000));
    render();
  }
View Full Code Here

    kernelTypeList.add("Reciprocal");   
   
    setTitle("Create GRNN/PNN Network");
    setSize(400,400);
    setLocation(200,200);
    addProperty(this.inputCount = new IntegerField("input neurons","Input Neuron Count",true,1,100000));
    addProperty(this.outputCount = new IntegerField("input neurons","Output Neuron Count",true,1,100000));
    addProperty(this.kernelType = new ComboBoxField("kernel type","Kernel Type",true,kernelTypeList));
    addProperty(this.outputModel = new ComboBoxField("output model","Output Model",true,outputModelList));
   
    render();
  }
View Full Code Here

  public CreateElmanDialog(Frame owner) {
    super(owner);
    setTitle("Create Elman Network");
    setSize(400,400);
    setLocation(200,200);
    addProperty(this.inputCount = new IntegerField("input neurons","Input Neuron Count",true,1,100000));
    addProperty(this.hiddenCount = new IntegerField("input neurons","Hidden Neuron Count",true,1,100000));
    addProperty(this.outputCount = new IntegerField("input neurons","Output Neuron Count",true,1,100000));
    render();
  }
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  public CreateART1(Frame owner) {
    super(owner);
    setTitle("Create ART1 Network");
    setSize(400,400);
    setLocation(200,200);
    addProperty(this.f1 = new IntegerField("f1 neuron count","Layer F1 Neuron Count",true,1,100000));
    addProperty(this.f2 = new IntegerField("f2 neuron count","Layer F2 Neuron Count",true,1,100000));
    render();
  }
View Full Code Here

  public CreateBAMDialog(Frame owner) {
    super(owner);
    setTitle("Create BAM Network");
    setSize(400,400);
    setLocation(200,200);
    addProperty(this.layerACount = new IntegerField("neurons-f1","F1 Neuron Count",true,1,100000));
    addProperty(this.layerBCount = new IntegerField("neurons-f2","F2 Neuron Count",true,1,100000));
    render();
  }
View Full Code Here

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