Example #1
0
double cMathUtil::EvalGaussianLogp(const Eigen::VectorXd& mean, const Eigen::VectorXd& covar, const Eigen::VectorXd& sample)
{
	int data_size = static_cast<int>(covar.size());

	Eigen::VectorXd diff = sample - mean;
	double logp = -0.5 * diff.dot(diff.cwiseQuotient(covar));
	double det = covar.prod();
	logp += -0.5 * (data_size * std::log(2 * M_PI) + std::log(det));

	return logp;
}
Example #2
0
double cMathUtil::EvalGaussian(const Eigen::VectorXd& mean, const Eigen::VectorXd& covar, const Eigen::VectorXd& sample)
{
	assert(mean.size() == covar.size());
	assert(sample.size() == covar.size());

	Eigen::VectorXd diff = sample - mean;
	double exp_val = diff.dot(diff.cwiseQuotient(covar));
	double likelihood = std::exp(-0.5 * exp_val);

	double partition = CalcGaussianPartition(covar);
	likelihood /= partition;
	return likelihood;
}