public static Types.Collection AllanVariance( double t0, mcore.Types.Collection input, ref bool isBreak, System.Windows.Forms.ProgressBar pb )
{
Types.Collection Result_Array = new Types.Collection(2);
Types.Collection CurrData = new Types.Collection();
double invert_sqrt_2 = 1.0 / System.Math.Sqrt(2.0);
int input_ValsCount = input[0].Count;
int CountAllanPoint = input[0].Count / 10;
int SumCounter;
double CurrentSum;
if ( pb != null )
{
pb.Value = 0;
pb.Maximum = CountAllanPoint;
}
for ( int i = 0; i < CountAllanPoint; i++)
{
CurrData.Clear();
// ---------
double OldSum = 0;
for (int k = 0; k < input_ValsCount; k = k + (i+1))
{
SumCounter = 0;
CurrentSum = 0;
for ( int z = k; z < k + (i+1); z++)
if ( z <= input_ValsCount - 1)
{
CurrentSum = CurrentSum + input[0][z];
SumCounter++;
}
CurrentSum = CurrentSum / (float)SumCounter;
// ---------- Разность соседних сумм -----
if ( k > 0 ) CurrData.Add( CurrentSum - OldSum);
// ----------
OldSum = CurrentSum;
}
double Mean = CurrData.Vectors[0].get_Mean();
double SCO = CurrData.Vectors[0].get_SCO (0, CurrData[0].Count, Mean) * invert_sqrt_2;
Result_Array.Add(0, t0*(i+1));
Result_Array.Add(1, SCO);
if ( pb != null ) pb.Value = i;
System.Windows.Forms.Application.DoEvents();
if ( isBreak == true )
return Result_Array;
}
return Result_Array;
}
/// <summary>
/// Считает коэфициенты регрессии для "У" набором данных "Х"
/// </summary>
/// <param name="x">Набор данных Х</param>
/// <param name="y">К чему стремимся</param>
/// <param name="power">Степенной ряд, для которого делаем счет</param>
/// <returns></returns>
public static double[][] Regression( mcore.Types.Collection y, mcore.Types.Collection x, int[] powers)
{
if ( x == null ) throw new Exception("(x) is null");
if ( y == null ) throw new Exception("(y) is null");
if ( powers == null ) throw new Exception("(powers) is null");
if ( powers.Length >= y[0].Count ) throw new Exception("Length is small");
int ValuesCount = y[0].Count;
int xParamCount = x.VectorsCount;
int PolinomLevel = powers.Length;
double [][]result = new double[xParamCount][];
for ( int i = 0; i < xParamCount; i++) result[i] = new double[PolinomLevel];
mcore.Types.Matrix XMat = new mcore.Types.Matrix(ValuesCount, PolinomLevel * xParamCount);
mcore.Types.Matrix YMat = new mcore.Types.Matrix(ValuesCount, 1);
mcore.Types.Matrix K = new Types.Matrix();
for ( int i = 0; i < ValuesCount; i++ ) YMat[i][0] = y[0][i];
for ( int i = 0; i < ValuesCount; i++)
for ( int z = 0; z < xParamCount; z++)
for ( int k = 0; k < PolinomLevel; k++)
XMat[i][k + z*(PolinomLevel)] = System.Math.Pow(x[z][i], powers[k]);
K = (XMat.Transpose() * XMat).Inverse()*XMat.Transpose()*YMat;
// ---------- K.Rows
for ( int i = 0; i < xParamCount; i++)
for ( int k = 0; k < PolinomLevel; k++ )
result[i][k] = K[k + i*PolinomLevel][0];
return result;
}
/// <summary>
/// Расчет АЧХ/ФЧХ, по входному полиному (X/Y)
/// </summary>
/// <param name="begin_decad">Целое число - начальная декада</param>
/// <param name="end_decad">Целое число - конечная декада</param>
/// <param name="in_num_denum">Входной масив данных, вектор "0" - числитель полинома, вектор "1" - знаменатель полинома</param>
/// <returns>Результат вычилений, вектор "0" - частота, вектор "1" - АЧХ, вектор "2" - ФЧХ</returns>
public static mcore.Types.Collection Frequency_responce( double begin_freq, double end_freq, double t0, mcore.Types.Collection in_num_denum )
{
if ( in_num_denum == null ) return null;
mcore.Types.Collection result = new Types.Collection(3);
// preparing frequency list
double b_decad = System.Math.Floor( System.Math.Log(begin_freq + 0.0001) / System.Math.Log(10) );
double e_decad = System.Math.Floor( System.Math.Log(end_freq + 0.0001) / System.Math.Log(10) );
int count_decad = Convert.ToInt32( e_decad - b_decad );
int screen_width = System.Windows.Forms.Screen.PrimaryScreen.Bounds.Width;
double count_points_inOneDecad = screen_width / count_decad;
double freq_offset = 1e-6;
// ------ Frequency List ------------
for ( int n = 0; n < count_decad; n++)
for ( int k = 0; k < count_points_inOneDecad+1; k++)
result.Add(0, System.Math.Pow(10, (k / count_points_inOneDecad) + n + b_decad));
int vector_legth = result.Vectors[0].data.Count;
int num_length = in_num_denum.Vectors[0].data.Count;
int denum_length = in_num_denum.Vectors[1].data.Count;
for ( int i = 0; i < vector_legth; i++)
{
double freq = result[0][i] + freq_offset;
double Re1 = 0.0;
double Im1 = 0.0;
double Re2 = 0.0;
double Im2 = 0.0;
//double aOmega = 2 / T0 * Math::ArcTan2(T0 * aLambda, 2);
double aOmega = freq;
for ( int k = 0; k < num_length; k++ )
{
double value = in_num_denum[0][k];
Re1 += value * System.Math.Cos(k * aOmega * t0 * 2 * System.Math.PI);
Im1 -= value * System.Math.Sin(k * aOmega * t0 * 2 * System.Math.PI);
}
for ( int k = 0; k < denum_length; k++)
{
double value = in_num_denum[1][k];
Re2 += value * System.Math.Cos(k * aOmega * t0 * 2 * System.Math.PI);
Im2 -= value * System.Math.Sin(k * aOmega * t0 * 2 * System.Math.PI);
}
double val1;
double val2;
try {
val1 = 20.0 * System.Math.Log10( System.Math.Sqrt(Re1*Re1 + Im1*Im1) / System.Math.Sqrt(Re2*Re2 + Im2*Im2));
val2 = System.Math.Atan2(Im1,Re1) - System.Math.Atan2(Im2,Re2);
} catch {
val1 = 0.0;
val2 = 0.0;
}
result.Add(1, val1);
result.Add(2, val2 * 180.0 / System.Math.PI);
}
return result;
}
