Examples of com.numb3r3.common.concurrent.executors.FoldingExecutor$RunnableAsCallable

Package com.numb3r3.common.concurrent.executors

Examples of com.numb3r3.common.concurrent.executors.FoldingExecutor$RunnableAsCallable

com.numb3r3.common.math.Matrix
An executor that folds duplicate task submissions.
If a task is submitted while an equivalent task is waiting in the queue, only one of those tasks will be run.
If the constructor parameter pThrowAway is set to true, submitted tasks that are equivalent to an already running or queued task will be thrown out.
If pThrowAway is false, submitted tasks that are equivalent to a currently queued task will replace that queued task.
Example:
FoldingExecutor with pThrowAway set to FALSE Running Tasks: A1 B1 C1 Queued Tasks: D1 E1 F1
New submission: task D2
since D2 is equivalent to D1 (determined via hashCode and equals) D1 will be removed from the queue and replace by D2.
The resulting queue will look like: Queued Tasks: D2 E1 F1
Note: running tasks can not be replaced. So submitting A2 while A1 is running will just add A2 to the queue.
FoldingExecutor with pThrowAway set to TRUE If pThrowAway is true, new tasks are thrown away if an equivalent task is queued OR running. @author Matt Crinklaw-Vogt

        return new InMemoryJBlasMatrix(DoubleMatrix.eye(n), null);
    }


    @Override
    public Pair getDims() {
        return new Pair(this.getRowsNum(), this.getColumnsNum());
    }

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    public InMemoryJBlasMatrix(final int rowNum, final int colNum,
                               final ErrorProcessor errorProcessor) {
        if (errorProcessor != null) {
            this.errorProcessor = errorProcessor;
        } else {
            this.errorProcessor = new SystemErrorProcessor();
        }


        if (rowNum == 0 && colNum == 0) {
            throw new UnsupportedOperationException(
                    "Matrix should have more than zero elements.");

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    public InMemoryJBlasMatrix(DoubleMatrix matrix,
                               final ErrorProcessor errorProcessor) {
        if (errorProcessor != null) {
            this.errorProcessor = errorProcessor;
        } else {
            this.errorProcessor = new SystemErrorProcessor();
        }
        this.doubleMatrix = matrix;
    }

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        double part1 = Math.exp(-0.5 * k * Math.log(2 * Math.PI));


        double part2 = Math.pow(det, -0.5);


        Matrix dev = value.sub(mu);


        double part3 = Math.exp(-0.5
                * (dev.transpose().product(cox.inverse())).dot(dev));
        return part1 * part2 * part3;


    }

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        double part1 = Math.exp(-0.5 * k * Math.log(2 * Math.PI));


        double part2 = Math.pow(det, -0.5);


        Matrix dev = value.sub(mu);


        double part3 = Math.exp(-0.5 * (dev.transpose().product(inv)).dot(dev));
        return part1 * part2 * part3;


    }

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        else
            return PhiInverse(y, delta, mid, hi);
    }


    public static Matrix oneCox(int k) {
        Matrix cox = InMemoryJBlasMatrix.eye(k);


        return null;
    }

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        return null;
    }


    public static Matrix sample(Matrix mu, Matrix Sigma) {
        Matrix values = InMemoryJBlasMatrix.randn(mu.getRowsNum());
        return mu.add(Sigma.product(values));
    }

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        return distance;
    }


    public static void main(String[] args) {
        // 2.1, 3.5, 8. , 9.5
        Matrix x = InMemoryJBlasMatrix.randn(4);
        x.put(0, 0, 2.1);
        x.put(1, 0, 3.5);
        x.put(2, 0, 8.0);
        x.put(3, 0, 9.5);


        Matrix mu = InMemoryJBlasMatrix.zeros(4);
        mu.put(0, 0, 2.0);
        mu.put(1, 0, 3.0);
        mu.put(2, 0, 8.0);
        mu.put(3, 0, 10.0);


        Matrix Sigma = InMemoryJBlasMatrix.eye(4);
        Sigma.put(0, 0, 2.3);
        Sigma.put(1, 1, 1.5);
        Sigma.put(2, 2, 1.7);
        Sigma.put(3, 3, 2.0);


        System.out.println("Det: " + Sigma.det());
        System.out.println("Normal density: " + Gaussian.mphi(x, mu, Sigma));
        // System.out.println("PDF: " + Gaussian.pdf());


        double y = 0.1;
        double mean = 1.5;

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    public InMemoryJBlasMatrix() {


    }


    public static Matrix arrayMatrix(double[] arrays) {
        Matrix m = InMemoryJBlasMatrix.zeros(arrays.length);
        for (int i = 0; i < arrays.length; i++) {
            m.put(i, 0, arrays[i]);
        }
        return m;
    }

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        else
            return -1;
    }


    private Matrix createSubMatrix(int excluding_row, int excluding_col) {
        Matrix mat = new InMemoryJBlasMatrix(this.getRowsNum() - 1,
                this.getColumnsNum() - 1, this.errorProcessor);
        int r = -1;
        for (int i = 0; i < this.getRowsNum(); i++) {
            if (i == excluding_row)
                continue;
            r++;
            int c = -1;
            for (int j = 0; j < this.getColumnsNum(); j++) {
                if (j == excluding_col)
                    continue;
                mat.put(r, ++c, this.get(i, j));
            }
        }
        return mat;
    }

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