001/* ---------------------------------------------------------------------------- 002 * This file was automatically generated by SWIG (https://www.swig.org). 003 * Version 4.1.1 004 * 005 * Do not make changes to this file unless you know what you are doing - modify 006 * the SWIG interface file instead. 007 * ----------------------------------------------------------------------------- */ 008 009package org.quantlib; 010 011public class MarkovFunctionalSettings implements org.quantlib.helpers.QuantLibJNIHelpers.AutoCloseable { 012 private transient long swigCPtr; 013 protected transient boolean swigCMemOwn; 014 015 protected MarkovFunctionalSettings(long cPtr, boolean cMemoryOwn) { 016 swigCMemOwn = cMemoryOwn; 017 swigCPtr = cPtr; 018 } 019 020 protected static long getCPtr(MarkovFunctionalSettings obj) { 021 return (obj == null) ? 0 : obj.swigCPtr; 022 } 023 024 protected static long swigRelease(MarkovFunctionalSettings obj) { 025 long ptr = 0; 026 if (obj != null) { 027 if (!obj.swigCMemOwn) 028 throw new RuntimeException("Cannot release ownership as memory is not owned"); 029 ptr = obj.swigCPtr; 030 obj.swigCMemOwn = false; 031 obj.delete(); 032 } 033 return ptr; 034 } 035 036 @SuppressWarnings("deprecation") 037 protected void finalize() { 038 delete(); 039 } 040 041 public synchronized void delete() { 042 if (swigCPtr != 0) { 043 if (swigCMemOwn) { 044 swigCMemOwn = false; 045 QuantLibJNI.delete_MarkovFunctionalSettings(swigCPtr); 046 } 047 swigCPtr = 0; 048 } 049 } 050 051 public MarkovFunctionalSettings() { 052 this(QuantLibJNI.new_MarkovFunctionalSettings__SWIG_0(), true); 053 } 054 055 public MarkovFunctionalSettings(long yGridPoints, double yStdDevs, long gaussHermitePoints, double digitalGap, double marketRateAccuracy, double lowerRateBound, double upperRateBound, int adjustments, DoubleVector smileMoneyCheckpoints) { 056 this(QuantLibJNI.new_MarkovFunctionalSettings__SWIG_1(yGridPoints, yStdDevs, gaussHermitePoints, digitalGap, marketRateAccuracy, lowerRateBound, upperRateBound, adjustments, DoubleVector.getCPtr(smileMoneyCheckpoints), smileMoneyCheckpoints), true); 057 } 058 059 public MarkovFunctionalSettings(long yGridPoints, double yStdDevs, long gaussHermitePoints, double digitalGap, double marketRateAccuracy, double lowerRateBound, double upperRateBound, int adjustments) { 060 this(QuantLibJNI.new_MarkovFunctionalSettings__SWIG_2(yGridPoints, yStdDevs, gaussHermitePoints, digitalGap, marketRateAccuracy, lowerRateBound, upperRateBound, adjustments), true); 061 } 062 063 public void validate() { 064 QuantLibJNI.MarkovFunctionalSettings_validate(swigCPtr, this); 065 } 066 067 public final static class Adjustments { 068 public final static MarkovFunctionalSettings.Adjustments AdjustNone = new MarkovFunctionalSettings.Adjustments("AdjustNone", QuantLibJNI.MarkovFunctionalSettings_AdjustNone_get()); 069 public final static MarkovFunctionalSettings.Adjustments AdjustDigitals = new MarkovFunctionalSettings.Adjustments("AdjustDigitals", QuantLibJNI.MarkovFunctionalSettings_AdjustDigitals_get()); 070 public final static MarkovFunctionalSettings.Adjustments AdjustYts = new MarkovFunctionalSettings.Adjustments("AdjustYts", QuantLibJNI.MarkovFunctionalSettings_AdjustYts_get()); 071 public final static MarkovFunctionalSettings.Adjustments ExtrapolatePayoffFlat = new MarkovFunctionalSettings.Adjustments("ExtrapolatePayoffFlat", QuantLibJNI.MarkovFunctionalSettings_ExtrapolatePayoffFlat_get()); 072 public final static MarkovFunctionalSettings.Adjustments NoPayoffExtrapolation = new MarkovFunctionalSettings.Adjustments("NoPayoffExtrapolation", QuantLibJNI.MarkovFunctionalSettings_NoPayoffExtrapolation_get()); 073 public final static MarkovFunctionalSettings.Adjustments KahaleSmile = new MarkovFunctionalSettings.Adjustments("KahaleSmile", QuantLibJNI.MarkovFunctionalSettings_KahaleSmile_get()); 074 public final static MarkovFunctionalSettings.Adjustments SmileExponentialExtrapolation = new MarkovFunctionalSettings.Adjustments("SmileExponentialExtrapolation", QuantLibJNI.MarkovFunctionalSettings_SmileExponentialExtrapolation_get()); 075 public final static MarkovFunctionalSettings.Adjustments KahaleInterpolation = new MarkovFunctionalSettings.Adjustments("KahaleInterpolation", QuantLibJNI.MarkovFunctionalSettings_KahaleInterpolation_get()); 076 public final static MarkovFunctionalSettings.Adjustments SmileDeleteArbitragePoints = new MarkovFunctionalSettings.Adjustments("SmileDeleteArbitragePoints", QuantLibJNI.MarkovFunctionalSettings_SmileDeleteArbitragePoints_get()); 077 public final static MarkovFunctionalSettings.Adjustments SabrSmile = new MarkovFunctionalSettings.Adjustments("SabrSmile", QuantLibJNI.MarkovFunctionalSettings_SabrSmile_get()); 078 079 public final int swigValue() { 080 return swigValue; 081 } 082 083 public String toString() { 084 return swigName; 085 } 086 087 public static Adjustments swigToEnum(int swigValue) { 088 if (swigValue < swigValues.length && swigValue >= 0 && swigValues[swigValue].swigValue == swigValue) 089 return swigValues[swigValue]; 090 for (int i = 0; i < swigValues.length; i++) 091 if (swigValues[i].swigValue == swigValue) 092 return swigValues[i]; 093 throw new IllegalArgumentException("No enum " + Adjustments.class + " with value " + swigValue); 094 } 095 096 private Adjustments(String swigName) { 097 this.swigName = swigName; 098 this.swigValue = swigNext++; 099 } 100 101 private Adjustments(String swigName, int swigValue) { 102 this.swigName = swigName; 103 this.swigValue = swigValue; 104 swigNext = swigValue+1; 105 } 106 107 private Adjustments(String swigName, Adjustments swigEnum) { 108 this.swigName = swigName; 109 this.swigValue = swigEnum.swigValue; 110 swigNext = this.swigValue+1; 111 } 112 113 private static Adjustments[] swigValues = { AdjustNone, AdjustDigitals, AdjustYts, ExtrapolatePayoffFlat, NoPayoffExtrapolation, KahaleSmile, SmileExponentialExtrapolation, KahaleInterpolation, SmileDeleteArbitragePoints, SabrSmile }; 114 private static int swigNext = 0; 115 private final int swigValue; 116 private final String swigName; 117 } 118 119}