PredictorResponseWeightConstraint.java
package org.drip.state.estimator;
/*
* -*- 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
*
* 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>PredictorResponseWeightConstraint</i> holds the Linearized Constraints (and, optionally, their quote
* sensitivities) necessary needed for the Linear Calibration. Linearized Constraints are expressed as
*
* Sum_i[Predictor Weight_i * Function (Response_i)] = Constraint Value
*
* where Function can either be univariate function, or weighted spline basis set. To this end, it
* implements the following functionality:
*
* <br><br>
* <ul>
* <li>
* Update/Retrieve Predictor/Response Weights and their Quote Sensitivities
* </li>
* <li>
* Update/Retrieve Predictor/Response Constraint Values and their Quote Sensitivities
* </li>
* <li>
* Display the contents of PredictorResponseWeightConstraint
* </li>
* </ul>
*
* <br><br>
* <ul>
* <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ProductCore.md">Product Core Module</a></li>
* <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/FixedIncomeAnalyticsLibrary.md">Fixed Income Analytics</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/state/README.md">Latent State Inference and Creation Utilities</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/state/estimator/README.md">Multi-Pass Customized Stretch Curve</a></li>
* </ul>
* <br><br>
*
* @author Lakshmi Krishnamurthy
*/
public class PredictorResponseWeightConstraint {
private java.util.HashSet<org.drip.state.identifier.LatentStateLabel> _setLSL = null;
private org.drip.state.estimator.PredictorResponseRelationSetup _prrsCalib = new
org.drip.state.estimator.PredictorResponseRelationSetup();
private org.drip.analytics.support.CaseInsensitiveHashMap<org.drip.state.estimator.PredictorResponseRelationSetup>
_mapPRRSSens = new
org.drip.analytics.support.CaseInsensitiveHashMap<org.drip.state.estimator.PredictorResponseRelationSetup>();
private org.drip.state.estimator.PredictorResponseRelationSetup getPRRS (
final java.lang.String strManifestMeasure)
{
if (null == strManifestMeasure || strManifestMeasure.isEmpty()) return null;
if (!_mapPRRSSens.containsKey (strManifestMeasure))
_mapPRRSSens.put (strManifestMeasure, new
org.drip.state.estimator.PredictorResponseRelationSetup());
return _mapPRRSSens.get (strManifestMeasure);
}
/**
* Empty PredictorResponseWeightConstraint constructor
*/
public PredictorResponseWeightConstraint()
{
}
/**
* Add a Predictor/Response Weight entry to the Linearized Constraint
*
* @param dblPredictor The Predictor Node
* @param dblResponseWeight The Response Weight at the Node
*
* @return TRUE - Successfully added
*/
public boolean addPredictorResponseWeight (
final double dblPredictor,
final double dblResponseWeight)
{
return _prrsCalib.addPredictorResponseWeight (dblPredictor, dblResponseWeight);
}
/**
* Add a Predictor/Response Weight entry to the Linearized Constraint
*
* @param strManifestMeasure The Manifest Measure
* @param dblPredictor The Predictor Node
* @param dblDResponseWeightDManifestMeasure The Response Weight-to-Manifest Measure Sensitivity at the
* Node
*
* @return TRUE - Successfully added
*/
public boolean addDResponseWeightDManifestMeasure (
final java.lang.String strManifestMeasure,
final double dblPredictor,
final double dblDResponseWeightDManifestMeasure)
{
return getPRRS (strManifestMeasure).addPredictorResponseWeight (dblPredictor,
dblDResponseWeightDManifestMeasure);
}
/**
* Update the Constraint Value
*
* @param dblValue The Constraint Value Update Increment
*
* @return TRUE - This Update Succeeded
*/
public boolean updateValue (
final double dblValue)
{
return _prrsCalib.updateValue (dblValue);
}
/**
* Update the Constraint Value Sensitivity
*
* @param strManifestMeasure The Manifest Measure
* @param dblDValueDManifestMeasure The Constraint Value Sensitivity Update Increment
*
* @return TRUE - This Sensitivity Update Succeeded
*/
public boolean updateDValueDManifestMeasure (
final java.lang.String strManifestMeasure,
final double dblDValueDManifestMeasure)
{
return getPRRS (strManifestMeasure).updateValue (dblDValueDManifestMeasure);
}
/**
* Retrieve the Constraint Value
*
* @return The Constraint Value
*/
public double getValue()
{
return _prrsCalib.getValue();
}
/**
* Retrieve the Constraint Value Sensitivity
*
* @param strManifestMeasure The Manifest Measure
*
* @return The Constraint Value Sensitivity
*
* @throws java.lang.Exception Thrown if the Inputs are invalid
*/
public double getDValueDManifestMeasure (
final java.lang.String strManifestMeasure)
throws java.lang.Exception
{
if (!_mapPRRSSens.containsKey (strManifestMeasure))
throw new java.lang.Exception
("PredictorResponseWeightConstraint::getDValueDManifestMeasure => Cannot locate manifest measure "
+ strManifestMeasure);
return _mapPRRSSens.get (strManifestMeasure).getValue();
}
/**
* Add a Merging Latent State Label
*
* @param lslMerge The Merging Latent State Label
*
* @return TRUE - The Latent State Label Successfully Added
*/
public boolean addMergeLabel (
final org.drip.state.identifier.LatentStateLabel lslMerge)
{
if (null == lslMerge) return false;
if (null == _setLSL) _setLSL = new java.util.HashSet<org.drip.state.identifier.LatentStateLabel>();
_setLSL.add (lslMerge);
return true;
}
/**
* Return the Set of Merged Latent State Labels
*
* @return The Set of Merged Latent State Labels
*/
public java.util.Set<org.drip.state.identifier.LatentStateLabel> mergeLabelSet()
{
return _setLSL;
}
/**
* Retrieve the Predictor To-From Response Weight Map
*
* @return The Predictor To-From Response Weight Map
*/
public java.util.TreeMap<java.lang.Double, java.lang.Double> getPredictorResponseWeight()
{
return _prrsCalib.getPredictorResponseWeight();
}
/**
* Retrieve the Predictor To-From Response Weight Sensitivity Map
*
* @param strManifestMeasure The Manifest Measure
*
* @return The Predictor To-From Response Weight Sensitivity Map
*/
public java.util.TreeMap<java.lang.Double, java.lang.Double> getDResponseWeightDManifestMeasure (
final java.lang.String strManifestMeasure)
{
return !_mapPRRSSens.containsKey (strManifestMeasure) ? null : _mapPRRSSens.get
(strManifestMeasure).getPredictorResponseWeight();
}
/**
* "Absorb" the other PRWC Instance into the Current One
*
* @param prwcOther The "Other" PRWC Instance
*
* @return TRUE - At least one entry of the "Other" was absorbed
*/
public boolean absorb (
final PredictorResponseWeightConstraint prwcOther)
{
if (null == prwcOther || !_prrsCalib.absorb (prwcOther._prrsCalib)) return false;
if (0 == prwcOther._mapPRRSSens.size()) return true;
if (0 != _mapPRRSSens.size()) {
for (java.util.Map.Entry<java.lang.String, org.drip.state.estimator.PredictorResponseRelationSetup>
me : _mapPRRSSens.entrySet()) {
java.lang.String strKey = me.getKey();
if (prwcOther._mapPRRSSens.containsKey (strKey))
me.getValue().absorb (prwcOther._mapPRRSSens.get (strKey));
}
}
for (java.util.Map.Entry<java.lang.String, org.drip.state.estimator.PredictorResponseRelationSetup>
me : prwcOther._mapPRRSSens.entrySet()) {
java.lang.String strKey = me.getKey();
if (!_mapPRRSSens.containsKey (strKey)) _mapPRRSSens.put (strKey, me.getValue());
}
java.util.Set<org.drip.state.identifier.LatentStateLabel> lsLSL = prwcOther.mergeLabelSet();
if (null == lsLSL || 0 == lsLSL.size()) return true;
for (org.drip.state.identifier.LatentStateLabel lsl : lsLSL) {
if (!addMergeLabel (lsl)) return false;
}
return true;
}
/**
* Return the Set of Available Sensitivities (if any)
*
* @return The Set of Available Sensitivities
*/
public java.util.Set<java.lang.String> sensitivityKeys()
{
return _mapPRRSSens.keySet();
}
/**
* Display the Constraints and the corresponding Weights
*
* @param strComment The Prefix Comment
*/
public void displayString (
final java.lang.String strComment)
{
java.util.Map<java.lang.Double, java.lang.Double> mapPRW = _prrsCalib.getPredictorResponseWeight();
if (null != mapPRW && 0 != mapPRW.size()) {
for (java.util.Map.Entry<java.lang.Double, java.lang.Double> me : mapPRW.entrySet()) {
double dblDate = me.getKey();
System.out.println ("\t\t" + strComment + " - " + new org.drip.analytics.date.JulianDate
((int) dblDate) + " => " + me.getValue());
}
}
System.out.println ("\t" + strComment + " Constraint: " + _prrsCalib.getValue());
if (null != _setLSL) {
java.lang.String strLabels = "\t" + strComment + " Labels:";
for (org.drip.state.identifier.LatentStateLabel lsl : _setLSL)
strLabels += " " + lsl.fullyQualifiedName();
System.out.println (strLabels);
}
System.out.flush();
}
}