Документация

using System;

using MathWorks.MATLAB.NET.Utility;
using MathWorks.MATLAB.NET.Arrays;

using SpectraComp;

namespace MathWorks.Examples.SpectraApp
{
  /// <summary>
  /// This application computes and plots the power spectral density of an input signal. 
  /// </summary>
  class SpectraCSApp
    {
      #region MAIN

      /// <summary>
      /// The main entry point for the application.
      /// </summary>
      [STAThread]
      static void Main(string[] args)
        {
          try
            {
              const double interval= 0.01;  // The sampling interval
              const int numSamples= 1001;   // The number of samples

              // Construct input data as sin(2*PI*15*t) + (sin(2*PI*40*t)) plus a
              // random signal.  Duration= 10; Sampling interval= 0.01
              MWNumericArray data= new MWNumericArray(MWArrayComplexity.Real, 
                     MWNumericType.Double, numSamples);

              Random random= new Random();

              // Initialize data 
              for (int idx= 1; idx <= numSamples; idx++)
                {
                  double t= (idx-1)* interval;

                  data[idx]= Math.Sin(2.0*Math.PI*15.0*t) + Math.Sin(2.0*Math.PI*40.0*t) +
                       random.NextDouble();
                }

              // Create a new signal analyzer object
              SignalAnalyzer signalAnalyzer= new SignalAnalyzer();

              // Compute the fft and power spectral density for the data array
              MWArray[] argsOut= signalAnalyzer.computefft(3, data, interval);

              // Print the first twenty elements of each result array
              int numElements= 20;
			        
              MWNumericArray resultArray= new MWNumericArray(MWArrayComplexity.Complex, 
                    MWNumericType.Double, numElements);

			        for (int idx= 1; idx <= numElements; idx++)
			          {
				          resultArray[idx]= ((MWNumericArray)argsOut[0])[idx];
			          }

			        Console.WriteLine("FFT:\n{0}\n", resultArray);

              for (int idx= 1; idx <= numElements; idx++)
                {
                  resultArray[idx]= ((MWNumericArray)argsOut[1])[idx];
                }

              Console.WriteLine("Frequency:\n{0}\n", resultArray);

              for (int idx= 1; idx <= numElements; idx++)
                {
                  resultArray[idx]= ((MWNumericArray)argsOut[2])[idx];
                }

              Console.WriteLine("Power Spectral Density:\n{0}", resultArray);

              // Create a new plotter object
              Plotter plotter= new Plotter();

              // Plot the fft and power spectral density for the data array
              plotter.plotfft(argsOut[0], argsOut[1], argsOut[2]);

              Console.ReadLine();  // Wait for user to exit application
            }

          catch(Exception exception)
            {
              Console.WriteLine("Error: {0}", exception);
            }
          }

        #endregion
    }
}

Imports System

Imports MathWorks.MATLAB.NET.Utility
Imports MathWorks.MATLAB.NET.Arrays

Imports SpectraComp


Namespace MathWorks.Examples.SpectraApp

    ' <summary>
    ' This application computes and plots the power spectral density of an input signal. 
    ' </summary>
    Class SpectraDemoApp

#Region " MAIN "

        ' <summary>
        ' The main entry point for the application.
        ' </summary>
        Shared Sub Main(ByVal args() As String)
            Try
                Const interval As Double = 0.01   ' The sampling interval
                Const numSamples As Integer = 1001   ' The number of samples

                ' Construct input data as sin(2*PI*15*t) + (sin(2*PI*40*t) plus a
                ' random signal.  Duration= 10; Sampling interval= 0.01
                Dim data As MWNumericArray = New MWNumericArray(MWArrayComplexity.Real, 
                                             MWNumericType.Double, numSamples)

                Dim random As Random = New Random

                ' Initialize data 
                Dim t As Double
                Dim idx As Integer
                For idx = 1 To numSamples
                    t = (idx - 1) * interval
                    data(idx) = New MWNumericArray(Math.Sin(2.0 * Math.PI * 15.0 * t) + 
                                    Math.Sin(2.0 * Math.PI * 40.0 * t) + 
                                    random.NextDouble())
                Next idx

                ' Create a new signal analyzer object
                Dim signalAnalyzer As SignalAnalyzer = New SignalAnalyzer

                ' Compute the fft and power spectral density for the data array
                Dim argsOut() As MWArray = signalAnalyzer.computefft(3, data, 
                                                 MWArray.op_Implicit(interval))

                ' Print the first twenty elements of each result array
                Dim numElements As Integer = 20
                Dim resultArray As MWNumericArray = 
                         New MWNumericArray(MWArrayComplexity.Complex, 
                                    MWNumericType.Double, numElements)

                For idx = 1 To numElements
                    resultArray(idx) = (CType(argsOut(0), MWNumericArray))(idx)
                Next idx

                Console.WriteLine("FFT:{0}{1}{2}", Chr(10), resultArray, Chr(10))

                For idx = 1 To numElements
                    resultArray(idx) = (CType(argsOut(1), MWNumericArray))(idx)
                Next idx

                Console.WriteLine("Frequency:{0}{1}{2}", Chr(10), resultArray, Chr(10))

                For idx = 1 To numElements
                    resultArray(idx) = (CType(argsOut(2), MWNumericArray))(idx)
                Next idx

                Console.WriteLine("Power Spectral Density:{0}{1}{2}", 
                  Chr(10), resultArray, Chr(10))

                ' Create a new plotter object
                Dim plotter As Plotter = New Plotter

                ' Plot the fft and power spectral density for the data array
                plotter.plotfft(argsOut(0), argsOut(1), argsOut(2))

                Console.ReadLine()  ' Wait for user to exit application

            Catch exception As Exception
                Console.WriteLine("Error: {0}", exception)

            End Try
        End Sub
#End Region

    End Class
End Namespace