/// <summary>
/// 初期化
/// </summary>
#else
/// <summary>
/// Default constructor
/// </summary>
#endif
public CvEMParams()
{
_data = new WCvEMParams()
{
nclusters = 10,
cov_mat_type = 1,
start_step = 0,
probs = null,
weights = null,
means = null,
//covs = null
};
Covs = null;
}
/// <summary>
/// 初期化
/// </summary>
/// <param name="_nclusters">混合数</param>
/// <param name="_cov_mat_type">混合分布共変動行列のタイプ</param>
/// <param name="_start_step">アルゴリズムをスタートする最初のステップ</param>
/// <param name="_term_crit">処理の終了条件</param>
/// <param name="_probs">確率p_i,kの初期値． start_step=EMStartStep.Eのときのみ使用する（その場合はnullであってはならない）.</param>
/// <param name="_weights">混合分布の重みπ_kの初期値． start_step=EMStartStep.Eのときのみ（nullでない場合は）使用する. </param>
/// <param name="_means">混合分布の平均 a_kの初期値． start_step=EMStartStep.Eのときのみ使用する（その場合はnullであってはならない）.</param>
/// <param name="_covs">混合分布の共変動行列Skの初期値． start_step=EMStartStep.Eのときのみ（nullでない場合は）使用する．</param>
#else
/// <summary>
/// Constructor
/// </summary>
/// <param name="_nclusters">The number of mixtures. Some of EM implementation could determine the optimal number of mixtures within a specified value range, but that is not the case in ML yet. </param>
/// <param name="_cov_mat_type">The type of the mixture covariation matrices</param>
/// <param name="_start_step">The initial step the algorithm starts from</param>
/// <param name="_term_crit">Termination criteria of the procedure. </param>
/// <param name="_probs">Initial probabilities p_i,k; are used (and must be not null) only when start_step=EMStartStep.E. </param>
/// <param name="_weights">Initial mixture weights π_k; are used (if not null) only when start_step=EMStartStep.E. </param>
/// <param name="_means">Initial mixture means a_k; are used (and must be not null) only when start_step=EMStartStep.E. </param>
/// <param name="_covs">Initial mixture covariation matrices S_k; are used (if not null) only when start_step=EMStartStep.E. </param>
#endif
public CvEMParams(int _nclusters, EMCovMatType _cov_mat_type, EMStartStep _start_step, CvTermCriteria _term_crit,
CvMat _probs, CvMat _weights, CvMat _means, CvMat[] _covs )
{
unsafe
{
_data = new WCvEMParams()
{
nclusters = _nclusters,
cov_mat_type = (int)_cov_mat_type,
start_step = (int)_start_step,
term_crit = _term_crit,
probs = (_probs == null) ? null : _probs.CvPtr.ToPointer(),
weights = (_weights == null) ? null : _weights.CvPtr.ToPointer(),
means = (_means == null) ? null : _means.CvPtr.ToPointer(),
//covs = (_means == null) ? null : (void**)_means.CvPtr,
};
}
Covs = _covs;
}