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📄 gaus_06.cc

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// file: $isip/class/stat/GaussianModel/gaus_06.cc// version: $Id: gaus_06.cc,v 1.6 2001/12/26 22:32:34 alphonso Exp $//// system include files//#include <typeinfo>// isip include files//#include "GaussianModel.h"// method: eq//// arguments://  const GaussianModel& arg: (input) dat ato copy//// return: a boolean value - true if objects are equivalent, false otherwise//// check whether the gaussian models are equal. this is a pure equality// method so the means and covariances must be exactly equal.//boolean GaussianModel::eq(const GaussianModel& arg_a) const {  // check the mean vectors  //  if (!mean_d.eq(arg_a.mean_d)) {    return false;  }  // if the objects are in the same initialization state,  // we can compare them directly  //  if ((mode_d == NONE) && (arg_a.mode_d == NONE)) {    return covariance_d.eq(arg_a.covariance_d);  }  if ((mode_d == PRECOMPUTE) && (arg_a.mode_d == PRECOMPUTE) &&      (is_valid_d == arg_a.is_valid_d)) {    return covariance_d.eq(arg_a.covariance_d);  }  // if the covariance matrices have not been inverted, invert them.  // it is better to compare inverted matrices in this case,  // since restoring an inverted matrix is prone to numerical error.  //  MatrixFloat tmp_0(covariance_d);  if ((mode_d == NONE) || (!is_valid_d)) {    tmp_0.inverse();  }  MatrixFloat tmp_1(arg_a.covariance_d);  if ((arg_a.mode_d == NONE) || (!arg_a.is_valid_d)) {    tmp_1.inverse();  }  // now we can check the matrices  //  return tmp_0.eq(tmp_1);}// method: eq//// arguments://  const StatisticalModelBase& arg: (input) object to test//// return: a boolean value indicating equality//// this method is part of the StatisticalModelBase interface contract// which compares two virtual model types//boolean GaussianModel::eq(const StatisticalModelBase& arg_a) const {  if (typeid(arg_a) == typeid(GaussianModel)) {    return eq((GaussianModel&)arg_a);  }  else {    return Error::handle(name(), L"eq", Error::ARG, __FILE__, __LINE__);  }}

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