Commit fb3c4147 authored by Jeannie Backer's avatar Jeannie Backer
Browse files

Removed bugs, deleted dulicate code, and added documentation. 

git-svn-id: http://subversion.wr.usgs.gov/repos/prog/isis3/branches/ipce@6063 41f8697f-d340-4b68-9986-7bafba869bb8
parent 79135929

isis/src/control/objs/MaximumLikelihoodWFunctions/MaximumLikelihoodWFunctions.cpp

+18 −33
Original line number Diff line number Diff line
@@ -10,7 +10,10 @@ 
#include "IString.h"



namespace Isis {

  

  /** 

   * Sets up a maximumlikelihood estimation function with Huber model and default tweaking

   * constant

   */  

  MaximumLikelihoodWFunctions::MaximumLikelihoodWFunctions() {

    this->setModel(Huber);

  } // choose Model and define the tweaking constant
@@ -45,17 +48,13 @@ namespace Isis { 
  MaximumLikelihoodWFunctions::MaximumLikelihoodWFunctions(Model modelSelection, 

                                                           double tweakingConstant) {

    // choose Model and define the tweaking constant

    m_model = modelSelection;

    if (tweakingConstant <= 0.0) {

      IString msg = "Maximum likelihood estimation tweaking constants must be > 0.0";

      throw IException(IException::Programmer, msg, _FILEINFO_);

    }

    m_tweakingConstant = tweakingConstant;

    setModel(modelSelection, tweakingConstant);

  }



  MaximumLikelihoodWFunctions::MaximumLikelihoodWFunctions(

      const MaximumLikelihoodWFunctions &other)

      : m_model(other.m_model), m_tweakingConstant(other.m_tweakingConstant) {

      : m_model(other.m_model), 

        m_tweakingConstant(other.m_tweakingConstant) {

  }
@@ -77,11 +76,10 @@ namespace Isis { 
   * @Param[in] enum Model modelSelection,  the model to be used

   *                                        (see documentation for enum Model)

   */

  bool MaximumLikelihoodWFunctions::setModel(Model modelSelection) {

  void MaximumLikelihoodWFunctions::setModel(Model modelSelection) {

    // choose Model and use default tweaking constant

    m_model = modelSelection;

    this->setTweakingConstantDefault();

    return true;

  }
@@ -89,21 +87,21 @@ namespace Isis { 
  /** 

   * Sets default tweaking constants based on the maximum likelihood estimation model being used.

   */

  bool MaximumLikelihoodWFunctions::setTweakingConstantDefault() {

  void MaximumLikelihoodWFunctions::setTweakingConstantDefault() {

    // default tweaking constants for the various likelihood models

    switch (m_model) {

      case Huber:

        m_tweakingConstant = 1.345; // "95% asymptotice efficiecy on the standard normal distribution"

        m_tweakingConstant = 1.345; // "95% asymptotic efficiecy on the standard normal distribution"

                                    // is obtained with this constant, 

                                    // see Zhang's "Parameter Estimation"

        break;

      case HuberModified:

        m_tweakingConstant = 1.2107;// "95% asymptotice efficiecy on the standard normal distribution"

        m_tweakingConstant = 1.2107;// "95% asymptotic efficiecy on the standard normal distribution"

                                    // is obtained with this constant,

                                    // see Zhang's "Parameter Estimation"

        break;

      case Welsch:

        m_tweakingConstant = 2.9846;// "95% asymptotice efficiecy on the standard normal distribution"

        m_tweakingConstant = 2.9846;// "95% asymptotic efficiecy on the standard normal distribution"

                                    // is obtained with this constant,

                                    // see Zhang's "Parameter Estimation"

        break;
@@ -114,9 +112,7 @@ namespace Isis { 
      default:

        m_tweakingConstant = 1;     // default, though at the time of writing this class,

                                    // this value should never actually be used

        break;

    }

    return true;

  }
@@ -126,22 +122,16 @@ namespace Isis { 
 *

 * @param[in] enum Model modelSelection,  the model to be used

 *                                        (see documentation for enum Model)

 * @param[in] double tweaking constant,  exact meaning varies by model, but generally the

 * @param[in] tweakingConstant,  exact meaning varies by model, but generally the

 *                                       larger the value the more influence larger resiudals

 *                                       have on the solution. As well as possibly the more

 *                                       measures are included in the solution.

 * @throws IsisProgrammerError if tweakingConstant <= 0.0

 */

  bool MaximumLikelihoodWFunctions::setModel(Model modelSelection, double tweakingConstant) { 

  void MaximumLikelihoodWFunctions::setModel(Model modelSelection, double tweakingConstant) { 

    // choose Model and define the tweaking constant

    m_model = modelSelection;

    if (tweakingConstant <= 0.0) {

      IString msg = "Maximum likelihood estimation tweaking constants must be > 0.0";

      throw IException(IException::Programmer, msg, _FILEINFO_);

      return false;

    }

    m_tweakingConstant = tweakingConstant;

    return true;

    setTweakingConstant(tweakingConstant);

  }
@@ -149,24 +139,19 @@ namespace Isis { 
  /** 

   * Allows the tweaking constant to be changed without changing the maximum likelihood function

   *

   * @param[in] double tweaking constant,  exact meaning varies by model, but generally the larger

   * the value the more influence larger resiudals have on the solution. As well as possiblely the

   * @param[in] tweakingConstant,  exact meaning varies by model, but generally the larger

   * the value the more influence larger resiudals have on the solution. As well as possiblly the

   * more measures are included in the solution.

   * 

   * @throws IsisProgrammerError if tweakingConstant <= 0.0

   */

  bool MaximumLikelihoodWFunctions::setTweakingConstant(double tweakingConstant) { 

  void MaximumLikelihoodWFunctions::setTweakingConstant(double tweakingConstant) { 

    // leave model type unaltered and change tweaking constant

    if (tweakingConstant <= 0.0) {

      return false;  // the constant must be positive

    }

    if (tweakingConstant <= 0.0) {

      IString msg = "Maximum likelihood estimation tweaking constants must be > 0.0";

      throw IException(IException::Programmer, msg, _FILEINFO_);

      return false;

    }

    m_tweakingConstant = tweakingConstant;

    return true;

  }

isis/src/control/objs/MaximumLikelihoodWFunctions/MaximumLikelihoodWFunctions.h

+8 −5
Original line number Diff line number Diff line
@@ -43,6 +43,7 @@ namespace Isis { 
   *              Chen, "Robust Regression with Projection Based M-estimators"

   *

   * @ingroup ControlNetwork

   * @ingroup Math

   *

   * @author 2012-03-23 Orrin Thomas

   *
@@ -54,7 +55,9 @@ namespace Isis { 
   *   @history 2014-07-03 Jeannie Backer - Replace member variable m_PI with Isis constant

   *   @history 2014-07-16 Jeannie Backer - Added enum to QString method and its inverse.

   *   @history 2014-07-23 Jeannie Backer - Added QDataStream >> and << operators and read/write

   *                           methods. Created unitTest.

   *                           methods.

   *   @history 2014-09-19 Jeannie Backer - Removed bugs. Added documentation. Cleaned

   *                           duplicate code.

   */

  class MaximumLikelihoodWFunctions {

  public:
@@ -113,11 +116,11 @@ namespace Isis { 
    ~MaximumLikelihoodWFunctions();

    MaximumLikelihoodWFunctions &operator=(const MaximumLikelihoodWFunctions &other);



    bool setModel(Model modelSelection); // uses default tweaking constant

    bool setTweakingConstantDefault();

    void setModel(Model modelSelection); // uses default tweaking constant

    void setTweakingConstantDefault();



    bool setModel(Model modelSelection, double tweakingConstant);

    bool setTweakingConstant(double tweakingConstant);

    void setModel(Model modelSelection, double tweakingConstant);

    void setTweakingConstant(double tweakingConstant);



    Model model() const;

    double tweakingConstant() const;

isis/src/control/objs/MaximumLikelihoodWFunctions/MaximumLikelihoodWFunctions.truth

+224 −27
Original line number Diff line number Diff line 
Test Huber

Model set in Constructor with defualt TC: wFunc->sqrtWeightScaler(-0.5): 1.000000 wFunc->sqrtWeightScaler(0.75): 1.000000 wFunc->sqrtWeightScaler(-2): 0.820061 wFunc->sqrtWeightScaler(2.5): 0.733485

TC constant re-set to 2.0:              : wFunc->sqrtWeightScaler(-0.5): 1.000000 wFunc->sqrtWeightScaler(0.75): 1.000000 wFunc->sqrtWeightScaler(-2): 1.000000 wFunc->sqrtWeightScaler(2.5): 0.894427

TC constant re-est to default:          : wFunc->sqrtWeightScaler(-0.5): 1.000000 wFunc->sqrtWeightScaler(0.75): 1.000000 wFunc->sqrtWeightScaler(-2): 0.820061 wFunc->sqrtWeightScaler(2.5): 0.733485

Model Manually set with default TC:     : wFunc->sqrtWeightScaler(-0.5): 1.000000 wFunc->sqrtWeightScaler(0.75): 1.000000 wFunc->sqrtWeightScaler(-2): 0.820061 wFunc->sqrtWeightScaler(2.5): 0.733485

Model Manually set with TC =2.0:        : wFunc->sqrtWeightScaler(-0.5): 1.000000 wFunc->sqrtWeightScaler(0.75): 1.000000 wFunc->sqrtWeightScaler(-2): 1.000000 wFunc->sqrtWeightScaler(2.5): 0.894427



Test HuberModified

Model set in Constructor with defualt TC: wFunc->sqrtWeightScaler(-0.5): 0.985807 wFunc->sqrtWeightScaler(0.75): 0.968121 wFunc->sqrtWeightScaler(-2): 0.778042 wFunc->sqrtWeightScaler(2.5): 0.695902

TC constant re-set to 2.0:              : wFunc->sqrtWeightScaler(-0.5): 0.994794 wFunc->sqrtWeightScaler(0.75): 0.988295 wFunc->sqrtWeightScaler(-2): 0.917317 wFunc->sqrtWeightScaler(2.5): 0.871314

TC constant re-est to default:          : wFunc->sqrtWeightScaler(-0.5): 0.985807 wFunc->sqrtWeightScaler(0.75): 0.968121 wFunc->sqrtWeightScaler(-2): 0.778042 wFunc->sqrtWeightScaler(2.5): 0.695902

Model Manually set with default TC:     : wFunc->sqrtWeightScaler(-0.5): 0.985807 wFunc->sqrtWeightScaler(0.75): 0.968121 wFunc->sqrtWeightScaler(-2): 0.778042 wFunc->sqrtWeightScaler(2.5): 0.695902

Model Manually set with TC =2.0:        : wFunc->sqrtWeightScaler(-0.5): 0.994794 wFunc->sqrtWeightScaler(0.75): 0.988295 wFunc->sqrtWeightScaler(-2): 0.917317 wFunc->sqrtWeightScaler(2.5): 0.871314



Test Welsch

Model set in Constructor with defualt TC: wFunc->sqrtWeightScaler(-0.5): 0.986065 wFunc->sqrtWeightScaler(0.75): 0.968920 wFunc->sqrtWeightScaler(-2): 0.798898 wFunc->sqrtWeightScaler(2.5): 0.704114

TC constant re-set to 2.0:              : wFunc->sqrtWeightScaler(-0.5): 0.969233 wFunc->sqrtWeightScaler(0.75): 0.932102 wFunc->sqrtWeightScaler(-2): 0.606531 wFunc->sqrtWeightScaler(2.5): 0.457833

TC constant re-est to default:          : wFunc->sqrtWeightScaler(-0.5): 0.986065 wFunc->sqrtWeightScaler(0.75): 0.968920 wFunc->sqrtWeightScaler(-2): 0.798898 wFunc->sqrtWeightScaler(2.5): 0.704114

Model Manually set with default TC:     : wFunc->sqrtWeightScaler(-0.5): 0.986065 wFunc->sqrtWeightScaler(0.75): 0.968920 wFunc->sqrtWeightScaler(-2): 0.798898 wFunc->sqrtWeightScaler(2.5): 0.704114

Model Manually set with TC =2.0:        : wFunc->sqrtWeightScaler(-0.5): 0.969233 wFunc->sqrtWeightScaler(0.75): 0.932102 wFunc->sqrtWeightScaler(-2): 0.606531 wFunc->sqrtWeightScaler(2.5): 0.457833



Test Chen

Model set in Constructor with defualt TC: wFunc->sqrtWeightScaler(-0.5): 1.837117 wFunc->sqrtWeightScaler(0.75): 1.071652 wFunc->sqrtWeightScaler(-2): 0.000000 wFunc->sqrtWeightScaler(2.5): 0.000000

TC constant re-set to 2.0:              : wFunc->sqrtWeightScaler(-0.5): 9.185587 wFunc->sqrtWeightScaler(0.75): 8.420121 wFunc->sqrtWeightScaler(-2): 0.000000 wFunc->sqrtWeightScaler(2.5): 0.000000

TC constant re-est to default:          : wFunc->sqrtWeightScaler(-0.5): 1.837117 wFunc->sqrtWeightScaler(0.75): 1.071652 wFunc->sqrtWeightScaler(-2): 0.000000 wFunc->sqrtWeightScaler(2.5): 0.000000

Model Manually set with default TC:     : wFunc->sqrtWeightScaler(-0.5): 1.837117 wFunc->sqrtWeightScaler(0.75): 1.071652 wFunc->sqrtWeightScaler(-2): 0.000000 wFunc->sqrtWeightScaler(2.5): 0.000000

Model Manually set with TC =2.0:        : wFunc->sqrtWeightScaler(-0.5): 9.185587 wFunc->sqrtWeightScaler(0.75): 8.420121 wFunc->sqrtWeightScaler(-2): 0.000000 wFunc->sqrtWeightScaler(2.5): 0.000000

Test for MaximumLikelihoodWFunctions 



Default constructor sets model to Huber and corresponding default TC: 

Model                    =  "Huber" 

TweakingConstant         =  "1.345" 

WeightedResidualCutoff   =  "N/A" 

TweakingConstantQuantile =  "0.5" 

wFunc->sqrtWeightScaler(-0.5):  1 

wFunc->sqrtWeightScaler(0.75):  1 

wFunc->sqrtWeightScaler(-2):    0.820061 

wFunc->sqrtWeightScaler(2.5):   0.733485 



TC constant re-set to 2.0: 

Model                    =  "Huber" 

TweakingConstant         =  "2.0" 

WeightedResidualCutoff   =  "N/A" 

TweakingConstantQuantile =  "0.5" 

wFunc->sqrtWeightScaler(-0.5):  1 

wFunc->sqrtWeightScaler(0.75):  1 

wFunc->sqrtWeightScaler(-2):    1 

wFunc->sqrtWeightScaler(2.5):   0.894427 



TC constant re-set to default: 

Model                    =  "Huber" 

TweakingConstant         =  "1.345" 

WeightedResidualCutoff   =  "N/A" 

TweakingConstantQuantile =  "0.5" 

wFunc->sqrtWeightScaler(-0.5):  1 

wFunc->sqrtWeightScaler(0.75):  1 

wFunc->sqrtWeightScaler(-2):    0.820061 

wFunc->sqrtWeightScaler(2.5):   0.733485 



Model manually set with default TC: 

Model                    =  "Huber" 

TweakingConstant         =  "1.345" 

WeightedResidualCutoff   =  "N/A" 

TweakingConstantQuantile =  "0.5" 

wFunc->sqrtWeightScaler(-0.5):  1 

wFunc->sqrtWeightScaler(0.75):  1 

wFunc->sqrtWeightScaler(-2):    0.820061 

wFunc->sqrtWeightScaler(2.5):   0.733485 



Model manually set with TC = 2.0: 

Model                    =  "Huber" 

TweakingConstant         =  "2.0" 

WeightedResidualCutoff   =  "N/A" 

TweakingConstantQuantile =  "0.5" 

wFunc->sqrtWeightScaler(-0.5):  1 

wFunc->sqrtWeightScaler(0.75):  1 

wFunc->sqrtWeightScaler(-2):    1 

wFunc->sqrtWeightScaler(2.5):   0.894427 



Testing Copy constructor: 

Model                    =  "Huber" 

TweakingConstant         =  "2.0" 

WeightedResidualCutoff   =  "N/A" 

TweakingConstantQuantile =  "0.5" 

copyWFunc->sqrtWeightScaler(-0.5):  1 

copyWFunc->sqrtWeightScaler(0.75):  1 

copyWFunc->sqrtWeightScaler(-2):    1 

copyWFunc->sqrtWeightScaler(2.5):   0.894427 





Reassign object using operator= and passing HuberModified to constructor with default TC: 

Model                    =  "HuberModified" 

TweakingConstant         =  "1.2107" 

WeightedResidualCutoff   =  "N/A" 

TweakingConstantQuantile =  "0.4" 

wFunc->sqrtWeightScaler(-0.5):  0.985807 

wFunc->sqrtWeightScaler(0.75):  0.968121 

wFunc->sqrtWeightScaler(-2):    0.778042 

wFunc->sqrtWeightScaler(2.5):   0.695902 



TC constant re-set to 2.0: 

Model                    =  "HuberModified" 

TweakingConstant         =  "2.0" 

WeightedResidualCutoff   =  "N/A" 

TweakingConstantQuantile =  "0.4" 

wFunc->sqrtWeightScaler(-0.5):  0.994794 

wFunc->sqrtWeightScaler(0.75):  0.988295 

wFunc->sqrtWeightScaler(-2):    0.917317 

wFunc->sqrtWeightScaler(2.5):   0.871314 



TC constant re-set to default: 

Model                    =  "HuberModified" 

TweakingConstant         =  "1.2107" 

WeightedResidualCutoff   =  "N/A" 

TweakingConstantQuantile =  "0.4" 

wFunc->sqrtWeightScaler(-0.5):  0.985807 

wFunc->sqrtWeightScaler(0.75):  0.968121 

wFunc->sqrtWeightScaler(-2):    0.778042 

wFunc->sqrtWeightScaler(2.5):   0.695902 



Model manually set to Huber_Modified with default TC: 

Model                    =  "HuberModified" 

TweakingConstant         =  "1.2107" 

WeightedResidualCutoff   =  "N/A" 

TweakingConstantQuantile =  "0.4" 

wFunc->sqrtWeightScaler(-0.5):  0.985807 

wFunc->sqrtWeightScaler(0.75):  0.968121 

wFunc->sqrtWeightScaler(-2):    0.778042 

wFunc->sqrtWeightScaler(2.5):   0.695902 



Model manually set with TC = 2.0: 

Model                    =  "HuberModified" 

TweakingConstant         =  "2.0" 

WeightedResidualCutoff   =  "N/A" 

TweakingConstantQuantile =  "0.4" 

wFunc->sqrtWeightScaler(-0.5):  0.994794 

wFunc->sqrtWeightScaler(0.75):  0.988295 

wFunc->sqrtWeightScaler(-2):    0.917317 

wFunc->sqrtWeightScaler(2.5):   0.871314 





Reassign object using operator= and passing Welsch with TC = 2.0: 

Model                    =  "Welsch" 

TweakingConstant         =  "2.0" 

WeightedResidualCutoff   =  "3.0" 

TweakingConstantQuantile =  "0.7" 

wFunc->sqrtWeightScaler(-0.5):  0.969233 

wFunc->sqrtWeightScaler(0.75):  0.932102 

wFunc->sqrtWeightScaler(-2):    0.606531 

wFunc->sqrtWeightScaler(2.5):   0.457833 



TC constant set to default: 

Model                    =  "Welsch" 

TweakingConstant         =  "2.9846" 

WeightedResidualCutoff   =  "4.4769" 

TweakingConstantQuantile =  "0.7" 

wFunc->sqrtWeightScaler(-0.5):  0.986065 

wFunc->sqrtWeightScaler(0.75):  0.96892 

wFunc->sqrtWeightScaler(-2):    0.798898 

wFunc->sqrtWeightScaler(2.5):   0.704114 



Model manually set with default TC: 

Model                    =  "Welsch" 

TweakingConstant         =  "2.9846" 

WeightedResidualCutoff   =  "4.4769" 

TweakingConstantQuantile =  "0.7" 

wFunc->sqrtWeightScaler(-0.5):  0.986065 

wFunc->sqrtWeightScaler(0.75):  0.96892 

wFunc->sqrtWeightScaler(-2):    0.798898 

wFunc->sqrtWeightScaler(2.5):   0.704114 



Model manually set with TC = 2.0: 

Model                    =  "Welsch" 

TweakingConstant         =  "2.0" 

WeightedResidualCutoff   =  "3.0" 

TweakingConstantQuantile =  "0.7" 

wFunc->sqrtWeightScaler(-0.5):  0.969233 

wFunc->sqrtWeightScaler(0.75):  0.932102 

wFunc->sqrtWeightScaler(-2):    0.606531 

wFunc->sqrtWeightScaler(2.5):   0.457833 





Reassign object using operator= and passing Chen with default TC: 

Model                    =  "Chen" 

TweakingConstant         =  "1.0" 

WeightedResidualCutoff   =  "1.0" 

TweakingConstantQuantile =  "0.98" 

wFunc->sqrtWeightScaler(-0.5):  1.83712 

wFunc->sqrtWeightScaler(0.75):  1.07165 

wFunc->sqrtWeightScaler(-2):    0 

wFunc->sqrtWeightScaler(2.5):   0 



TC constant re-set to 2.0: 

Model                    =  "Chen" 

TweakingConstant         =  "2.0" 

WeightedResidualCutoff   =  "2.0" 

TweakingConstantQuantile =  "0.98" 

wFunc->sqrtWeightScaler(-0.5):  9.18559 

wFunc->sqrtWeightScaler(0.75):  8.42012 

wFunc->sqrtWeightScaler(-2):    0 

wFunc->sqrtWeightScaler(2.5):   0 



TC constant re-set to default: 

Model                    =  "Chen" 

TweakingConstant         =  "1.0" 

WeightedResidualCutoff   =  "1.0" 

TweakingConstantQuantile =  "0.98" 

wFunc->sqrtWeightScaler(-0.5):  1.83712 

wFunc->sqrtWeightScaler(0.75):  1.07165 

wFunc->sqrtWeightScaler(-2):    0 

wFunc->sqrtWeightScaler(2.5):   0 



Model manually set with default TC: 

Model                    =  "Chen" 

TweakingConstant         =  "1.0" 

WeightedResidualCutoff   =  "1.0" 

TweakingConstantQuantile =  "0.98" 

wFunc->sqrtWeightScaler(-0.5):  1.83712 

wFunc->sqrtWeightScaler(0.75):  1.07165 

wFunc->sqrtWeightScaler(-2):    0 

wFunc->sqrtWeightScaler(2.5):   0 



Model manually set with TC = 2.0: 

Model                    =  "Chen" 

TweakingConstant         =  "2.0" 

WeightedResidualCutoff   =  "2.0" 

TweakingConstantQuantile =  "0.98" 

wFunc->sqrtWeightScaler(-0.5):  9.18559 

wFunc->sqrtWeightScaler(0.75):  8.42012 

wFunc->sqrtWeightScaler(-2):    0 

wFunc->sqrtWeightScaler(2.5):   0 





Testing serialization... 

Previous class written and read from QByteArray: 

Model                    =  "Chen" 

TweakingConstant         =  "2.0" 

WeightedResidualCutoff   =  "2.0" 

TweakingConstantQuantile =  "0.98" 

wFunc->sqrtWeightScaler(-0.5):  9.18559 

wFunc->sqrtWeightScaler(0.75):  8.42012 

wFunc->sqrtWeightScaler(-2):    0 

wFunc->sqrtWeightScaler(2.5):   0 



Huber enum written to and read from QByteArray: 

Model                    =  "Huber" 





Testing error throws... 

**PROGRAMMER ERROR** Maximum likelihood estimation tweaking constants must be > 0.0.

**PROGRAMMER ERROR** Unknown estimation model enum [4].

**PROGRAMMER ERROR** Unknown maximum likelihood model name Nonsense.

isis/src/control/objs/MaximumLikelihoodWFunctions/unitTest.cpp

+326 −149

File changed.

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