Package java.io

Examples of java.io.DataInput.readDouble()


            Vector<Double> doubleV = new Vector<Double>();

            try {
                while (true) {
                    double f = dis.readDouble();
                    doubleV.add(new Double(f));
                }
            } catch (EOFException eof) {
                stream.close();
            }
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            double[] array = new double[n2 - n1];

            dis.skipBytes(n1 * 4);
            for (int i = 0; i < array.length; i++) {
                array[i] = dis.readDouble();
            }

            return array;
        } catch (IOException e) {
            throw new IllegalArgumentException("InputStream is unreadable : "
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            Vector<Double> doubleV = new Vector<Double>();

            try {
                while (true) {
                    double f = dis.readDouble();
                    doubleV.add(new Double(f));
                }
            } catch (EOFException eof) {
                stream.close();
            }
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            double[] array = new double[n2 - n1];

            dis.skipBytes(n1 * 4);
            for (int i = 0; i < array.length; i++) {
                array[i] = dis.readDouble();
            }

            return array;
        } catch (IOException e) {
            throw new IllegalArgumentException("InputStream is unreadable : "
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        this.distribution = (RealDistribution) ois.readObject();

//        this.inputTrainingData = MatrixWritable.readMatrix( di ); 
//        this.outputTrainingLabels = MatrixWritable.readMatrix( di );

        this.learningRateUpdate = di.readDouble();
        this.useRegularization = di.readBoolean();
        this.l2 = di.readDouble();
       
        this.setMomentum( di.readDouble() );
        this.setSparsity( di.readDouble() );
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//        this.inputTrainingData = MatrixWritable.readMatrix( di ); 
//        this.outputTrainingLabels = MatrixWritable.readMatrix( di );

        this.learningRateUpdate = di.readDouble();
        this.useRegularization = di.readBoolean();
        this.l2 = di.readDouble();
       
        this.setMomentum( di.readDouble() );
        this.setSparsity( di.readDouble() );
       
       
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        this.learningRateUpdate = di.readDouble();
        this.useRegularization = di.readBoolean();
        this.l2 = di.readDouble();
       
        this.setMomentum( di.readDouble() );
        this.setSparsity( di.readDouble() );
       
       
    } catch (Exception e) {
      throw new RuntimeException(e);
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        this.learningRateUpdate = di.readDouble();
        this.useRegularization = di.readBoolean();
        this.l2 = di.readDouble();
       
        this.setMomentum( di.readDouble() );
        this.setSparsity( di.readDouble() );
       
       
    } catch (Exception e) {
      throw new RuntimeException(e);
    }
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        this.connectionWeights = MatrixWritable.readMatrix( di );
//        this.trainingDataset = MatrixWritable.readMatrix( di ); 
               
        this.randNumGenerator = (RandomGenerator) ois.readObject();

      this.sparsity = di.readDouble();
      this.momentum = di.readDouble();
      this.l2 = di.readDouble();
      this.renderWeightsEveryNumEpochs = di.readInt();
      this.fanIn = di.readDouble();
      this.useRegularization = di.readBoolean();
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//        this.trainingDataset = MatrixWritable.readMatrix( di ); 
               
        this.randNumGenerator = (RandomGenerator) ois.readObject();

      this.sparsity = di.readDouble();
      this.momentum = di.readDouble();
      this.l2 = di.readDouble();
      this.renderWeightsEveryNumEpochs = di.readInt();
      this.fanIn = di.readDouble();
      this.useRegularization = di.readBoolean();
     
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