UnitRegressionExecutor.java

package org.drip.regression.core;

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

/*!
 * Copyright (C) 2020 Lakshmi Krishnamurthy
 * Copyright (C) 2019 Lakshmi Krishnamurthy
 * 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
 * Copyright (C) 2012 Lakshmi Krishnamurthy
 * 
 *  This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
 *      asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
 *      analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
 *      equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
 *      numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
 *      and computational support.
 *  
 *      https://lakshmidrip.github.io/DROP/
 *  
 *  DROP is composed of three modules:
 *  
 *  - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
 *  - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
 *  - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
 * 
 *  DROP Product Core implements libraries for the following:
 *  - Fixed Income Analytics
 *  - Loan Analytics
 *  - Transaction Cost Analytics
 * 
 *  DROP Portfolio Core implements libraries for the following:
 *  - Asset Allocation Analytics
 *  - Asset Liability Management Analytics
 *  - Capital Estimation Analytics
 *  - Exposure Analytics
 *  - Margin Analytics
 *  - XVA Analytics
 * 
 *  DROP Computational Core implements libraries for the following:
 *  - Algorithm Support
 *  - Computation Support
 *  - Function Analysis
 *  - Model Validation
 *  - Numerical Analysis
 *  - Numerical Optimizer
 *  - Spline Builder
 *  - Statistical Learning
 * 
 *  Documentation for DROP is Spread Over:
 * 
 *  - Main                     => https://lakshmidrip.github.io/DROP/
 *  - Wiki                     => https://github.com/lakshmiDRIP/DROP/wiki
 *  - GitHub                   => https://github.com/lakshmiDRIP/DROP
 *  - Repo Layout Taxonomy     => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
 *  - Javadoc                  => https://lakshmidrip.github.io/DROP/Javadoc/index.html
 *  - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
 *  - Release Versions         => https://lakshmidrip.github.io/DROP/version.html
 *  - Community Credits        => https://lakshmidrip.github.io/DROP/credits.html
 *  - Issues Catalog           => https://github.com/lakshmiDRIP/DROP/issues
 *  - JUnit                    => https://lakshmidrip.github.io/DROP/junit/index.html
 *  - Jacoco                   => https://lakshmidrip.github.io/DROP/jacoco/index.html
 * 
 *  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.
 */

/**
 * <i>UnitRegressionExecutor</i> implements the UnitRegressor, and splits the regression execution into pre-,
 * execute, and post-regression. It provides default implementations for pre-regression and post-regression.
 * Most typical regressors only need to over-ride the execRegression method.
 * 
 * <br><br>
 *  <ul>
 *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ComputationalCore.md">Computational Core Module</a></li>
 *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ComputationSupportLibrary.md">Computation Support</a></li>
 *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/regression/README.md">Regression Engine Core and the Unit Regressors</a></li>
 *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/regression/core/README.md">Regression Engine Core - Unit Regressors</a></li>
 *  </ul>
 * <br><br>
 *
 * @author Lakshmi Krishnamurthy
 */

public abstract class UnitRegressionExecutor implements org.drip.regression.core.UnitRegressor {
    private static final boolean _bDisplayStatus = false;

    private java.lang.String _strRegressorSet = "";
    private java.lang.String _strRegressorName = "";

    /**
     * Constructor for the unit regression executor
     * 
     * @param strRegressorName Name of the unit regressor
     * @param strRegressorSet Name of the regressor set
     * 
     * @throws java.lang.Exception Thrown if inputs are invalid
     */

    protected UnitRegressionExecutor (
        final java.lang.String strRegressorName,
        final java.lang.String strRegressorSet)
        throws java.lang.Exception
    {
        if (null == (_strRegressorName = strRegressorName) || strRegressorName.isEmpty() || null ==
            (_strRegressorSet = strRegressorSet) || _strRegressorSet.isEmpty())
            throw new java.lang.Exception ("UnitRegressionExecutor ctr: Invalid inputs");
    }

    /**
     * One-time initialization to set up the objects needed for the regression
     * 
     * @return TRUE - Initialization successful
     */

    public boolean preRegression()
    {
        return true;
    }

    /**
     * Execute the regression call within this function
     * 
     * @return The result of the regression
     */

    public abstract boolean execRegression();

    /**
     * Clean-up of the objects set-up for the regression
     * 
     * @param rnvd Regression Run Detail object to capture the regression details
     * 
     * @return TRUE - Clean-up successful
     */

    public boolean postRegression (
        final org.drip.regression.core.RegressionRunDetail rnvd)
    {
        return true;
    }

    @Override public org.drip.regression.core.RegressionRunOutput regress()
    {
        org.drip.regression.core.RegressionRunOutput ro = null;

        try {
            ro = new org.drip.regression.core.RegressionRunOutput (_strRegressorSet + "." +
                _strRegressorName);
        } catch (java.lang.Exception e) {
            e.printStackTrace();

            return null;
        }

        if (!preRegression()) {
            if (_bDisplayStatus)
                System.out.println (_strRegressorSet + "." + _strRegressorName +
                    ": Cannot set-up the regressor!");

            return null;
        }

        long lStartTime = System.nanoTime();

        if (!execRegression()) {
            if (_bDisplayStatus)
                System.out.println (_strRegressorSet + "." + _strRegressorName + ": failed");

            ro.setTerminationStatus (false);

            return ro;
        }

        ro._lExecTime = (long) (1.e-03 * (System.nanoTime() - lStartTime));

        if (!postRegression (ro.getRegressionDetail())) {
            if (_bDisplayStatus)
                System.out.println (_strRegressorSet + "." + _strRegressorName +
                    ": Regressor clean-up unsuccessful!");

            return null;
        }

        if (_bDisplayStatus) System.out.println (_strRegressorSet + "." + _strRegressorName + ": succeeded");

        ro.setTerminationStatus (true);

        return ro;
    }

    @Override public java.lang.String getName()
    {
        return _strRegressorName;
    }
}