BasisTensionSplineSet.java

package org.drip.sample.spline;

import org.drip.function.r1tor1.*;
import org.drip.numerical.differentiation.WengertJacobian;
import org.drip.spline.basis.*;
import org.drip.spline.params.*;
import org.drip.spline.segment.*;
import org.drip.spline.tension.KochLycheKvasovFamily;

/*
 * -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
 */

/*!
 * Copyright (C) 2018 Lakshmi Krishnamurthy
 * Copyright (C) 2017 Lakshmi Krishnamurthy
 * Copyright (C) 2016 Lakshmi Krishnamurthy
 * Copyright (C) 2015 Lakshmi Krishnamurthy
 * Copyright (C) 2014 Lakshmi Krishnamurthy
 * Copyright (C) 2013 Lakshmi Krishnamurthy
 * 
 *  This file is part of DRIP, a free-software/open-source library for buy/side financial/trading model
 *      libraries targeting analysts and developers
 *      https://lakshmidrip.github.io/DRIP/
 *  
 *  DRIP is composed of four main libraries:
 *  
 *  - DRIP Fixed Income - https://lakshmidrip.github.io/DRIP-Fixed-Income/
 *  - DRIP Asset Allocation - https://lakshmidrip.github.io/DRIP-Asset-Allocation/
 *  - DRIP Numerical Optimizer - https://lakshmidrip.github.io/DRIP-Numerical-Optimizer/
 *  - DRIP Statistical Learning - https://lakshmidrip.github.io/DRIP-Statistical-Learning/
 * 
 *  - DRIP Fixed Income: Library for Instrument/Trading Conventions, Treasury Futures/Options,
 *      Funding/Forward/Overnight Curves, Multi-Curve Construction/Valuation, Collateral Valuation and XVA
 *      Metric Generation, Calibration and Hedge Attributions, Statistical Curve Construction, Bond RV
 *      Metrics, Stochastic Evolution and Option Pricing, Interest Rate Dynamics and Option Pricing, LMM
 *      Extensions/Calibrations/Greeks, Algorithmic Differentiation, and Asset Backed Models and Analytics.
 * 
 *  - DRIP Asset Allocation: Library for model libraries for MPT framework, Black Litterman Strategy
 *      Incorporator, Holdings Constraint, and Transaction Costs.
 * 
 *  - DRIP Numerical Optimizer: Library for Numerical Optimization and Spline Functionality.
 * 
 *  - DRIP Statistical Learning: Library for Statistical Evaluation and Machine Learning.
 * 
 *  Licensed under the Apache License, Version 2.0 (the "License");
 *      you may not use this file except in compliance with the License.
 *   
 *  You may obtain a copy of the License at
 *      http://www.apache.org/licenses/LICENSE-2.0
 *  
 *  Unless required by applicable law or agreed to in writing, software
 *      distributed under the License is distributed on an "AS IS" BASIS,
 *      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  
 *  See the License for the specific language governing permissions and
 *      limitations under the License.
 */

/**
 * BasisTensionSplineSet implements Samples for the Construction and the usage of various basis spline
 *  functions. It demonstrates the following:
 *  - Construction of Kocke-Lyche-Kvasov tension spline segment control parameters - using hyperbolic,
 *      exponential, rational linear, and rational quadratic primitives.
 *  - Control the segment using the rational shape controller, and the appropriate Ck.
 *  - Estimate the node value and the node value Jacobian with the segment, as well as at the boundaries.
 *  - Calculate the segment monotonicity.

 * @author Lakshmi Krishnamurthy
 */

public class BasisTensionSplineSet {

    /*
     * Sample demonstrating the creation of the KLK Hyperbolic tension basis spline set
     * 
     *      USE WITH CARE: This sample ignores errors and does not handle exceptions.
     */

    private static final FunctionSet KLKHyperbolicTensionSpline()
        throws Exception
    {
        double dblTension = .01;

        /*
         * Create the basis parameter set from the segment tension parameter, and construct the basis
         */

        ExponentialTensionSetParams etbsbp = new ExponentialTensionSetParams (dblTension);

        return KochLycheKvasovFamily.FromHyperbolicPrimitive (etbsbp);
    }

    /*
     * Sample demonstrating the creation of the KLK Rational Linear tension basis spline set
     * 
     *      USE WITH CARE: This sample ignores errors and does not handle exceptions.
     */

    private static final FunctionSet KLKRationalLinearTensionSpline()
        throws Exception
    {
        double dblTension = 1.;

        /*
         * Create the basis parameter set from the segment tension parameter, and construct the basis
         */

        ExponentialTensionSetParams etbsbp = new ExponentialTensionSetParams (dblTension);

        return KochLycheKvasovFamily.FromRationalLinearPrimitive (etbsbp);
    }

    /*
     * Sample demonstrating the creation of the KLK Rational Quadratic tension basis spline set
     * 
     *      USE WITH CARE: This sample ignores errors and does not handle exceptions.
     */

    private static final FunctionSet KLKRationalQuadraticTensionSpline()
        throws Exception
    {
        double dblTension = 1.;

        /*
         * Create the basis parameter set from the segment tension parameter, and construct the basis
         */

        ExponentialTensionSetParams etbsbp = new ExponentialTensionSetParams (dblTension);

        return KochLycheKvasovFamily.FromRationalQuadraticPrimitive (etbsbp);
    }

    /*
     * Sample demonstrating the creation of the KLK Exponential tension basis spline set
     * 
     *      USE WITH CARE: This sample ignores errors and does not handle exceptions.
     */

    private static final FunctionSet KLKExponentialTensionSpline()
        throws Exception
    {
        double dblTension = 1.;

        /*
         * Create the basis parameter set from the segment tension parameter, and construct the basis
         */

        ExponentialTensionSetParams etbsbp = new ExponentialTensionSetParams (dblTension);

        return KochLycheKvasovFamily.FromExponentialPrimitive (etbsbp);
    }

    /*
     * This sample demonstrates the following:
     * 
     *  - Construction of two segments, 1 and 2.
     *  - Calibration of the segments to the left and the right node values
     *  - Extraction of the segment Jacobians and segment monotonicity
     *  - Estimate point value and the Jacobian
     *  - Estimate the curvature penalty
     * 
     *      USE WITH CARE: This sample ignores errors and does not handle exceptions.
     */

    private static final void TestSpline (
        final FunctionSet fs,
        final ResponseScalingShapeControl rssc,
        final SegmentInelasticDesignControl segParams)
        throws Exception
    {
        /*
         * Construct the left and the right segments
         */

        LatentStateResponseModel seg1 = LatentStateResponseModel.Create (
            1.0,
            1.5,
            fs,
            rssc,
            segParams
        );

        LatentStateResponseModel seg2 = LatentStateResponseModel.Create (
            1.5,
            2.0,
            fs,
            rssc,
            segParams
        );

        /*
         * Calibrate the left segment using the node values, and compute the segment Jacobian, the monotonicity, and the curvature penalty
         */

        WengertJacobian wj1 = seg1.jackDCoeffDEdgeParams (
            25.,
            0.,
            20.25,
            null
        );

        System.out.println ("\tY[" + 1.0 + "]: " + seg1.responseValue (1.));

        System.out.println ("\tY[" + 1.5 + "]: " + seg1.responseValue (1.5));

        System.out.println ("Segment 1 Jacobian: " + wj1.displayString());

        System.out.println ("Segment 1 Head: " + seg1.jackDCoeffDEdgeInputs().displayString());

        System.out.println ("Segment 1 Monotone Type: " + seg1.monotoneType());

        System.out.println ("\tSegment 1 DPE: " + seg1.curvatureDPE());

        /*
         * Calibrate the right segment using the node values, and compute the segment Jacobian, the monotonicity, and the curvature penalty
         */

        WengertJacobian wj2 = seg2.jackDCoeffDEdgeParams (
            seg1,
            "Default",
            16.,
            null,
            Double.NaN,
            null
        );

        System.out.println ("\tY[" + 1.5 + "]: " + seg2.responseValue (1.5));

        System.out.println ("\tY[" + 2. + "]: " + seg2.responseValue (2.));

        System.out.println ("Segment 2 Jacobian: " + wj2.displayString());

        System.out.println ("Segment 2 Regular Jacobian: " + seg2.jackDCoeffDEdgeInputs().displayString());

        System.out.println ("Segment 2 Monotone Type: " + seg2.monotoneType());

        System.out.println ("\tSegment 2 DPE: " + seg2.curvatureDPE());

        /*
         * Re-calibrate Segment #2 with a different response value
         */

        seg2.calibrate (
            seg1,
            14.,
            null
        );

        /*
         * Estimate the segment value at the given variate, and compute the corresponding Jacobian and the curvature penalty
         */

        double dblX = 2.0;

        System.out.println ("\t\tValue[" + dblX + "]: " + seg2.responseValue (dblX));

        System.out.println ("\t\tValue Jacobian[" + dblX + "]: " + seg2.jackDResponseDEdgeInput (dblX, 1).displayString());

        System.out.println ("\t\tSegment 2 DPE: " + seg2.curvatureDPE());
    }

    /*
     * This sample illustrates the construction and the usage of basis splines (all types, really). It shows
     *  the following:
     *  - Construct a rational shape controller with the specified shape controller tension.
     *  - Construct the segment inelastic parameter that is C2 (iK = 2 sets it to C2), with second order
     *      curvature penalty, and without constraint.
     *  - Test the KLK Hyperbolic Tension basis tension spline.
     *  - Test the KLK Rational Linear basis tension spline.
     *  - Test the KLK Rational Quadratic basis tension spline.
     *  - Test the KLK Exponential Tension basis tension spline.
     * 
     *      USE WITH CARE: This sample ignores errors and does not handle exceptions.
     */

    private static final void BasisTensionSplineSetSample()
        throws Exception
    {
        /*
         * Construct a rational shape controller with the shape controller tension of 1.
         */

        double dblShapeControllerTension = 1.;

        ResponseScalingShapeControl rssc = new ResponseScalingShapeControl (
            true,
            new QuadraticRationalShapeControl (dblShapeControllerTension)
        );

        /*
         * Construct the segment inelastic parameter that is C2 (iK = 2 sets it to C2), with second order
         *  curvature penalty, and without constraint
         */

        int iK = 2;
        int iCurvaturePenaltyDerivativeOrder = 2;

        SegmentInelasticDesignControl segParams = SegmentInelasticDesignControl.Create (
            iK,
            iCurvaturePenaltyDerivativeOrder
        );

        /*
         * Test the KLK Hyperbolic tension spline
         */

        System.out.println ( " ----------- \n KLK HYPERBOLIC \n ----------- \n");

        TestSpline (
            KLKHyperbolicTensionSpline(),
            rssc,
            segParams
        );

        /*
         * Test the KLK Rational Linear tension spline
         */

        System.out.println ( " ----------- \n KLK RATIONAL LINEAR \n ----------- \n");

        TestSpline (
            KLKRationalLinearTensionSpline(),
            rssc,
            segParams
        );

        /*
         * Test the KLK Rational Quadratic tension spline
         */

        System.out.println ( " ----------- \n KLK RATIONAL QUADRATIC \n ----------- \n");

        TestSpline (
            KLKRationalQuadraticTensionSpline(),
            rssc,
            segParams
        );

        /*
         * Test the KLK Exponential tension spline
         */

        System.out.println ( " ----------- \n KLK EXPONENTIAL \n ----------- \n");

        TestSpline (
            KLKExponentialTensionSpline(),
            rssc,
            segParams
        );
    }

    public static final void main (
        final String[] astrArgs)
        throws Exception
    {
        BasisTensionSplineSetSample();
    }
}