public void testing_collection(System.Windows.Forms.TextBox textbox)
{
// Collection testing
if (textbox != null)
{
textbox.Text += "Collection testing" + System.Environment.NewLine;
}
cc = new nkcore.Types.Collection(2);
cc.set_VectorName(0, "test1");
cc.set_VectorName(1, "test2");
cc.set_VectorVisibility(1, false);
cc.Add(0, 1); cc.Add(1, 11);
cc.Add(0, 2); cc.Add(1, 22);
cc.Add(0, 3); cc.Add(1, 33);
cc.Add(0, 4); cc.Add(1, 44);
cc.Load_TextFile("E:\\.PersonalProjects\\CSharp\\.Library\\.Data\\01-0078_(810).exp(001)_s_pr1.txt", null);
cc.Save_TextFile("E:\\.PersonalProjects\\CSharp\\.Library\\.Data\\01-0078_(810).exp(002)_s_pr1__.txt", null);
Console.WriteLine("Collection - done");
if (textbox != null)
{
textbox.Text += "Collection - done" + System.Environment.NewLine;
}
}
public void testing_AllanVariance(System.Windows.Forms.TextBox textbox, ref bool isBreak)
{
// Regression testing
if ( textbox != null ) textbox.Text += "Regression testing";
nkcore.Types.Collection base_collection = new nkcore.Types.Collection("E:\\.PersonalProjects\\CSharp\\.Library\\.Data\\01-0078_(810).exp(001)_s_pr1.txt", null);
nkcore.Types.Collection dd = nkcore.Math.AllanVariance( base_collection, ref isBreak );
}
public void testing_regression( System.Windows.Forms.TextBox textbox, Chart chart)
{
// Regression testing
if ( textbox != null ) textbox.Text += "Regression testing";
nkcore.Types.Collection base_collection = new nkcore.Types.Collection("E:\\.PersonalProjects\\CSharp\\.Library\\.Data\\01-0078_(810).exp(001)_s_pr1.txt", null);
//nkcore.Types.Collection base_collection = new nkcore.Types.Collection(2);
//base_collection.Add(0,0); base_collection.Add(1,0);
//base_collection.Add(0,1); base_collection.Add(1,0.5);
//base_collection.Add(0,2); base_collection.Add(1,1);
nkcore.Types.Collection c1 = base_collection.get_SubCollection(new int[]{0});
nkcore.Types.Collection c2 = base_collection.get_SubCollection(new int[]{1, 2, 3, 4});
int []power_array = new int[]{0, 1, 2, 3, 4};
double [][]res = nkcore.Math.Regression(c1, c2, power_array);
for ( int i = 0 ; i < c2.VectorsCount; i++)
{
System.Console.WriteLine(" vector1 = ");
if ( textbox != null ) textbox.Text += System.Environment.NewLine + " vector" + i.ToString() + " = ";
for ( int k = 0; k < power_array.Length; k++ )
{
System.Console.Write(res[i][k].ToString("f9") + "\t");
if ( textbox != null ) textbox.Text += res[i][k].ToString("f9") + "\t";
}
}
System.Console.WriteLine("");
if ( textbox != null ) textbox.Text += System.Environment.NewLine;
if ( textbox != null ) textbox.Text += System.Environment.NewLine;
List<double> correctionResult = new List<double>();
List<double> correctionResult_error = new List<double>();
for ( int i = 0; i < c1[0].Count; i++)
{
double value = 0;
for ( int k = 0; k < c2.VectorsCount; k++)
{
for ( int z = 0; z < power_array.Length; z++ )
{
value += res[k][z] * Math.Pow( c2[k][i] , power_array[z]);
}
}
correctionResult.Add(value);
correctionResult_error.Add((c1[0][i] - value)/0.035*3600.0);
}
chart.Series[0].Points.DataBindY(c1[0]);
chart.Series[1].Points.DataBindY(correctionResult);
chart.Series[2].Points.DataBindY(correctionResult_error);
}
public void testing_AllanVariance(System.Windows.Forms.TextBox textbox, ref bool isBreak)
{
// Regression testing
if (textbox != null)
{
textbox.Text += "Regression testing";
}
nkcore.Types.Collection base_collection = new nkcore.Types.Collection("E:\\.PersonalProjects\\CSharp\\.Library\\.Data\\01-0078_(810).exp(001)_s_pr1.txt", null);
nkcore.Types.Collection dd = nkcore.Math.AllanVariance(base_collection, ref isBreak);
}
/// <summary>
/// Низкочастотный фильтр
/// </summary>
/// <param name="t0">Время дискретизации</param>
/// <param name="freq">Частота среза</param>
/// <param name="hMax">Максимальная высока подъема</param>
public filter_loPass(double t0, double freq, double hMax)
{
coefs = new Types.Collection(2);
double Alfa = System.Math.Pow(System.Math.Tan(freq * t0 / 2.0 * 2.0 * System.Math.PI), 2.0);
double A = System.Math.Sqrt(Alfa / (hMax * hMax - 0.5));
double B = hMax * hMax * A * A;
coefs.Add(0, B);
coefs.Add(0, 2 * B);
coefs.Add(0, B);
coefs.Add(1, 1 + A + B);
coefs.Add(1, -2 * (1 - B));
coefs.Add(1, 1 - A + B);
}
/// <summary>
/// Низкочастотный фильтр
/// </summary>
/// <param name="t0">Время дискретизации</param>
/// <param name="freq">Частота среза</param>
/// <param name="hMax">Максимальная высока подъема</param>
public filter_loPass(double t0, double freq, double hMax)
{
coefs = new Types.Collection(2);
double Alfa = System.Math.Pow(System.Math.Tan(freq* t0 / 2.0 * 2.0 * System.Math.PI), 2.0);
double A = System.Math.Sqrt(Alfa / (hMax*hMax - 0.5));
double B = hMax*hMax*A*A;
coefs.Add(0, B );
coefs.Add(0, 2*B);
coefs.Add(0, B );
coefs.Add(1, 1+A+B );
coefs.Add(1, -2*(1-B));
coefs.Add(1, 1-A+B );
}
public void testing_collection(System.Windows.Forms.TextBox textbox)
{
// Collection testing
if ( textbox != null ) textbox.Text += "Collection testing" + System.Environment.NewLine;
cc = new nkcore.Types.Collection(2);
cc.set_VectorName(0, "test1");
cc.set_VectorName(1, "test2");
cc.set_VectorVisibility(1, false);
cc.Add(0, 1); cc.Add(1, 11);
cc.Add(0, 2); cc.Add(1, 22);
cc.Add(0, 3); cc.Add(1, 33);
cc.Add(0, 4); cc.Add(1, 44);
cc.Load_TextFile("E:\\.PersonalProjects\\CSharp\\.Library\\.Data\\01-0078_(810).exp(001)_s_pr1.txt", null);
cc.Save_TextFile("E:\\.PersonalProjects\\CSharp\\.Library\\.Data\\01-0078_(810).exp(002)_s_pr1__.txt", null);
Console.WriteLine("Collection - done");
if ( textbox != null ) textbox.Text += "Collection - done" + System.Environment.NewLine;
}
public static Types.Collection AllanVariance(nkcore.Types.Collection input, ref bool isBreak)
{
Types.Collection Result_Array = new Types.Collection();
Types.Collection CurrData = new Types.Collection();
double invert_sqrt_2 = 1.0 / System.Math.Sqrt(2.0);
int input_ValsCount = input[0].Count;
int CountAlanPoint = input[0].Count / 10;
int SumCounter;
double CurrentSum;
//if ( pb != NULL )
//{
// pb->Position = 0;
// pb->Max = CountAlanPoint;
//}
for (int i = 0; i < CountAlanPoint; 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(SCO);
//if ( pb != NULL ) pb->Position = 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(nkcore.Types.Collection y, nkcore.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];
}
nkcore.Types.Matrix XMat = new nkcore.Types.Matrix(ValuesCount, PolinomLevel * xParamCount);
nkcore.Types.Matrix YMat = new nkcore.Types.Matrix(ValuesCount, 1);
nkcore.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 nkcore.Types.Collection Frequency_responce(double begin_freq, double end_freq, double t0, nkcore.Types.Collection in_num_denum)
{
if (in_num_denum == null)
{
return(null);
}
nkcore.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;
// ------ Frequency List ------------
for (int n = 0; n < count_decad; n++)
{
for (int k = 0; k < count_points_inOneDecad; 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] + 1e-6;
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);
}
return(result);
}
public void testing_regression(System.Windows.Forms.TextBox textbox, Chart chart)
{
// Regression testing
if (textbox != null)
{
textbox.Text += "Regression testing";
}
nkcore.Types.Collection base_collection = new nkcore.Types.Collection("E:\\.PersonalProjects\\CSharp\\.Library\\.Data\\01-0078_(810).exp(001)_s_pr1.txt", null);
//nkcore.Types.Collection base_collection = new nkcore.Types.Collection(2);
//base_collection.Add(0,0); base_collection.Add(1,0);
//base_collection.Add(0,1); base_collection.Add(1,0.5);
//base_collection.Add(0,2); base_collection.Add(1,1);
nkcore.Types.Collection c1 = base_collection.get_SubCollection(new int[] { 0 });
nkcore.Types.Collection c2 = base_collection.get_SubCollection(new int[] { 1, 2, 3, 4 });
int [] power_array = new int[] { 0, 1, 2, 3, 4 };
double [][] res = nkcore.Math.Regression(c1, c2, power_array);
for (int i = 0; i < c2.VectorsCount; i++)
{
System.Console.WriteLine(" vector1 = ");
if (textbox != null)
{
textbox.Text += System.Environment.NewLine + " vector" + i.ToString() + " = ";
}
for (int k = 0; k < power_array.Length; k++)
{
System.Console.Write(res[i][k].ToString("f9") + "\t");
if (textbox != null)
{
textbox.Text += res[i][k].ToString("f9") + "\t";
}
}
}
System.Console.WriteLine("");
if (textbox != null)
{
textbox.Text += System.Environment.NewLine;
}
if (textbox != null)
{
textbox.Text += System.Environment.NewLine;
}
List <double> correctionResult = new List <double>();
List <double> correctionResult_error = new List <double>();
for (int i = 0; i < c1[0].Count; i++)
{
double value = 0;
for (int k = 0; k < c2.VectorsCount; k++)
{
for (int z = 0; z < power_array.Length; z++)
{
value += res[k][z] * Math.Pow(c2[k][i], power_array[z]);
}
}
correctionResult.Add(value);
correctionResult_error.Add((c1[0][i] - value) / 0.035 * 3600.0);
}
chart.Series[0].Points.DataBindY(c1[0]);
chart.Series[1].Points.DataBindY(correctionResult);
chart.Series[2].Points.DataBindY(correctionResult_error);
}
public Form1()
{
InitializeComponent();
int t1 = System.Environment.TickCount;
this.StartPosition = FormStartPosition.CenterScreen;
this.Text = (System.Environment.TickCount - t1).ToString();
chart1.ChartAreas.Clear();
chart1.Series.Clear();
chart1.ChartAreas.Add(new ChartArea("First"));
chart1.ChartAreas.Add(new ChartArea("Second"));
Series series1 = new Series();
Series series2 = new Series();
Series series3 = new Series();
series1.Color = Color.Blue;
series1.ChartArea = "First";
series1.ChartType = SeriesChartType.FastLine;
series2.Color = Color.Yellow;
series2.ChartArea = "First";
series2.ChartType = SeriesChartType.FastLine;
series3.Color = Color.Blue;
series3.ChartArea = "Second";
series3.ChartType = SeriesChartType.FastLine;
chart1.Series.Add(series1);
chart1.Series.Add(series2);
chart1.Series.Add(series3);
//////
for (int i = 0; i < chart1.ChartAreas.Count; i++)
{
chart1.ChartAreas[i].Visible = true;
chart1.ChartAreas[i].BorderWidth = 2;
chart1.ChartAreas[i].BorderDashStyle = ChartDashStyle.Solid;
//chart1.ChartAreas[i].AxisX.ArrowStyle = AxisArrowStyle.Triangle;
chart1.ChartAreas[i].AxisX.IsLogarithmic = false;
chart1.ChartAreas[i].AxisX.IsStartedFromZero = false;
chart1.ChartAreas[i].AxisX.LineColor = Color.Red;
chart1.ChartAreas[i].AxisX.LabelStyle.Enabled = false;
//chart1.ChartAreas[i].AxisY.ArrowStyle = AxisArrowStyle.Triangle;
chart1.ChartAreas[i].AxisY.IsLogarithmic = false;
chart1.ChartAreas[i].AxisY.IsStartedFromZero = false;
chart1.ChartAreas[i].AxisY.LineColor = Color.Red;
chart1.ChartAreas[i].AxisY.MajorGrid.Enabled = false;
chart1.ChartAreas[i].AxisX.MajorGrid.Enabled = false;
chart1.ChartAreas[i].AxisY.MajorGrid.LineWidth = 1;
chart1.ChartAreas[i].AxisX.MinorGrid.Enabled = true;
chart1.ChartAreas[i].AxisX.MinorGrid.LineColor = Color.Silver;
chart1.ChartAreas[i].AxisX.MinorGrid.LineDashStyle = ChartDashStyle.Dash;
chart1.ChartAreas[i].AxisY.MinorGrid.Enabled = true;
chart1.ChartAreas[i].AxisY.MinorGrid.LineColor = Color.Silver;
chart1.ChartAreas[i].AxisY.MinorGrid.LineDashStyle = ChartDashStyle.Dash;
//chart1.ChartAreas[i].Position.Width = 80;
//chart1.ChartAreas[i].Position.Height = 90;
//chart1.ChartAreas[i].Position.X = 30;
chart1.Dock = DockStyle.Right;
chart1.Anchor = AnchorStyles.Bottom | AnchorStyles.Left | AnchorStyles.Right | AnchorStyles.Top;
//chart1.Series[0].IsVisibleInLegend = false;
chart1.Legends.Clear();
chart1.Titles.Clear();
}
/////////////////////////
//testing.testing_regression(textBox1, chart1);
testing.testing_matix(textBox1);
nkcore.Digital.filter_loPass lo = new nkcore.Digital.filter_loPass(0.001, 100, 1);
nkcore.Types.Collection c = nkcore.Math.Frequency_responce(0.1, 1000, 0.001, lo.coefs);
//testing.testing_collection(textBox1);
/////////////////////////
series1.Points.DataBindXY(c[0], c[1]);
series3.Points.DataBindXY(c[0], c[2]);
//series2.Points.DataBindY(testing.cc[0]);
}
