FixedRdFinder.java
package org.drip.function.rdtor1solver;
/*
* -*- 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
*
* 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>FixedRdFinder</i> exports the Methods needed for the locating a Fixed R<sup>d</sup> Point.
*
* <br><br>
* <ul>
* <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/NumericalCore.md">Numerical Core Module</a></li>
* <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/NumericalOptimizerLibrary.md">Numerical Optimizer</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/feed/README.md">Function</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/feed/rdtor1solver/README.md">R<sup>d</sup> To R<sup>1</sup> Solver</a></li>
* </ul>
*
* @author Lakshmi Krishnamurthy
*/
public abstract class FixedRdFinder
{
/**
* Flag Indicating whether the Verifier Increment Metrics are to be Traced
*/
public static boolean s_verifierIncrementBlog = false;
private org.drip.function.definition.RdToR1 _objectiveFunction = null;
private org.drip.function.rdtor1solver.ConvergenceControl _convergenceControl = null;
private org.drip.function.rdtor1descent.LineStepEvolutionControl _lineStepEvolutionControl = null;
protected FixedRdFinder (
final org.drip.function.definition.RdToR1 objectiveFunction,
final org.drip.function.rdtor1descent.LineStepEvolutionControl lineStepEvolutionControl,
final org.drip.function.rdtor1solver.ConvergenceControl convergenceControl)
throws java.lang.Exception
{
if (null == (_objectiveFunction = objectiveFunction) ||
null == (_convergenceControl = convergenceControl))
{
throw new java.lang.Exception ("FixedRdFinder Constructor => Invalid Inputs");
}
_lineStepEvolutionControl = lineStepEvolutionControl;
}
/**
* Retrieve the Objective Function
*
* @return The Objective Function
*/
public org.drip.function.definition.RdToR1 objectiveFunction()
{
return _objectiveFunction;
}
/**
* Retrieve the Line Step Evolution Control
*
* @return The Line Step Evolution Control
*/
public org.drip.function.rdtor1descent.LineStepEvolutionControl lineStepEvolutionControl()
{
return _lineStepEvolutionControl;
}
/**
* Retrieve the Convergence Control Parameters
*
* @return The Convergence Control Parameters
*/
public org.drip.function.rdtor1solver.ConvergenceControl convergenceControl()
{
return _convergenceControl;
}
/**
* Solve for the Optimal Variate-Inequality Constraint Multiplier Tuple Using the Variate/Inequality
* Constraint Tuple Convergence
*
* @param startingVariateConstraint The Starting Variate/Inequality Constraint Tuple
*
* @return The Optimal Variate-Inequality Constraint Multiplier Tuple
*/
public org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier convergeVariate (
final org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier startingVariateConstraint)
{
if (null == startingVariateConstraint)
{
return null;
}
org.drip.function.definition.RdToR1 objectiveFunction = objectiveFunction();
boolean fixedPointFound = false;
org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier currentVariateConstraint =
startingVariateConstraint;
org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier previousVariateConstraint =
startingVariateConstraint;
int comparisonVariateCount = objectiveFunction instanceof
org.drip.function.rdtor1.LagrangianMultivariate ? (
(org.drip.function.rdtor1.LagrangianMultivariate) objectiveFunction).objectiveFunctionDimension() :
objectiveFunction.dimension();
double absoluteToleranceFallback = _convergenceControl.absoluteTolerance();
double relativeTolerance = _convergenceControl.relativeTolerance();
while (!fixedPointFound)
{
org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier variateConstraint =
increment (
currentVariateConstraint
);
if (null == variateConstraint ||
null == (
currentVariateConstraint = next (
previousVariateConstraint,
variateConstraint,
incrementFraction (
currentVariateConstraint,
variateConstraint
)
)
)
)
{
return null;
}
try
{
fixedPointFound =
org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier.Compare (
currentVariateConstraint,
previousVariateConstraint,
relativeTolerance,
absoluteToleranceFallback,
comparisonVariateCount
);
}
catch (java.lang.Exception e)
{
e.printStackTrace();
return null;
}
previousVariateConstraint = currentVariateConstraint;
}
return currentVariateConstraint;
}
/**
* Solve for the Optimal Variate-Inequality Constraint Multiplier Tuple Using the Objective Function
* Convergence
*
* @param startingVariateConstraint The Starting Variate/Inequality Constraint Tuple Set
*
* @return The Optimal Variate-Inequality Constraint Multiplier Tuple
*/
public org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier convergeObjectiveFunction (
final org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier startingVariateConstraint)
{
if (null == startingVariateConstraint)
{
return null;
}
boolean fixedPointFound = false;
double objectiveFunctionValuePrevious = java.lang.Double.NaN;
org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier variateConstraint =
startingVariateConstraint;
try
{
objectiveFunctionValuePrevious = _objectiveFunction.evaluate (
variateConstraint.variateArray()
);
}
catch (java.lang.Exception e)
{
e.printStackTrace();
return null;
}
double convergenceControlAbsoluteTolerance = _convergenceControl.absoluteTolerance();
double objectiveFunctionAbsoluteTolerance = java.lang.Math.abs (
objectiveFunctionValuePrevious * _convergenceControl.relativeTolerance()
);
double dblAbsoluteTolerance = convergenceControlAbsoluteTolerance <
objectiveFunctionAbsoluteTolerance ?
convergenceControlAbsoluteTolerance : objectiveFunctionAbsoluteTolerance;
while (!fixedPointFound)
{
org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier incrementalVariateConstraint
= increment (
variateConstraint
);
if (null == incrementalVariateConstraint ||
null == (
variateConstraint = next (
variateConstraint,
incrementalVariateConstraint,
incrementFraction (
variateConstraint,
incrementalVariateConstraint
)
)
)
)
{
return null;
}
try
{
double objectiveFunctionValue = _objectiveFunction.evaluate (
variateConstraint.variateArray()
);
if (java.lang.Math.abs (
objectiveFunctionValuePrevious - objectiveFunctionValue
) < dblAbsoluteTolerance
)
{
fixedPointFound = true;
}
objectiveFunctionValuePrevious = objectiveFunctionValue;
}
catch (java.lang.Exception e)
{
e.printStackTrace();
return null;
}
}
return variateConstraint;
}
/**
* Find the Optimal Variate-Inequality Constraint Multiplier Tuple using the Iteration Parameters
* provided by the Convergence Control Instance
*
* @param startingVariateConstraint The Starting Variate-Inequality Constraint Multiplier Tuple
*
* @return The Optimal Variate-Inequality Constraint Multiplier Tuple
*/
public org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier find (
final org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier startingVariateConstraint)
{
int convergenceType = _convergenceControl.convergenceType();
if (org.drip.function.rdtor1solver.InteriorPointBarrierControl.OBJECTIVE_FUNCTION_SEQUENCE_CONVERGENCE
== convergenceType)
{
return convergeObjectiveFunction (startingVariateConstraint);
}
if (org.drip.function.rdtor1solver.InteriorPointBarrierControl.VARIATE_CONSTRAINT_SEQUENCE_CONVERGENCE
== convergenceType)
{
return convergeVariate (startingVariateConstraint);
}
return null;
}
/**
* Retrieve the Incremental Step Length Fraction
*
* @param variateConstraint The VariateInequalityConstraintMultiplier Base Instance
* @param variateConstraintIncrement The Full VariateInequalityConstraintMultiplier Instance Increment
*
* @return The VariateInequalityConstraintMultiplier Incremental Step Length Fraction
*/
public double incrementFraction (
final org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier variateConstraint,
final org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier
variateConstraintIncrement)
{
if (null == _lineStepEvolutionControl ||
null == variateConstraint || variateConstraint.incremental() ||
null == variateConstraintIncrement || !variateConstraintIncrement.incremental())
{
return 1.;
}
org.drip.function.rdtor1descent.LineEvolutionVerifier lineEvolutionVerifier =
_lineStepEvolutionControl.lineEvolutionVerifier();
org.drip.function.definition.UnitVector variateIncrementDirectionVector =
variateConstraintIncrement.variateIncrementVector().direction();
int reductionStepCount = _lineStepEvolutionControl.reductionStepCount();
double reductionFactor = _lineStepEvolutionControl.reductionFactor();
double[] variateArray = variateConstraint.variateArray();
double stepLength = 1.;
while (0 <= --reductionStepCount)
{
org.drip.function.rdtor1descent.LineEvolutionVerifierMetrics lineEvolutionVerifierMetrics =
lineEvolutionVerifier.metrics (
variateIncrementDirectionVector,
variateArray,
_objectiveFunction,
stepLength
);
if (null == lineEvolutionVerifierMetrics)
{
return 1.;
}
if (s_verifierIncrementBlog)
{
System.out.println (lineEvolutionVerifierMetrics);
}
if (lineEvolutionVerifierMetrics.verify())
{
return stepLength;
}
stepLength *= reductionFactor;
}
return 1.;
}
/**
* Produce the Incremental Variate-Constraint Multiplier
*
* @param currentVariateConstraint The Current Variate-Constraint Multiplier Tuple
*
* @return The Incremental Variate-Constraint Multiplier
*/
abstract public org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier increment (
final org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier currentVariateConstraint);
/**
* Iterate Over to the Next Variate-Constraint Multiplier Tuple
*
* @param currentVariateConstraint The Current Variate-Constraint Multiplier Tuple
* @param incrementalVariateConstraint The Incremental Variate-Constraint Multiplier Tuple
* @param incrementFraction The Incremental Fraction to be applied
*
* @return The Next Variate-Constraint Multiplier Set
*/
abstract public org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier next (
final org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier currentVariateConstraint,
final org.drip.function.rdtor1solver.VariateInequalityConstraintMultiplier incrementalVariateConstraint,
final double incrementFraction);
}