matlab command window

How To Call Functions In a MATLAB Generated .NET DLL From C#

Posted on Updated on

This Tutorial does not represent a practical use of  a MATLAB generated .NET DLL since it requires the installation and use of MATLAB and the MATLAB Compiler Runtime (MCR) for a scenario that could be easily handled by a more elegant algorithm such as the one discussed in my earlier post on RPN expression parsing. However, it does seek to demonstrate the principles behind developing an algorithm in MATLAB which could be then exported to a .NET component and reused in any managed language. MATLAB provides a fast prototyping environment which gives the programmer a vast array of tools which she can then use to design and test her algorithms. A subset of these functionalities are provided in the MCR which is basically an installable, free, headless version of MATLAB. Since the MCR is a MATLAB instance it requires the same amount of time for initial loading into memory and will also be as memory intensive as its GUI cousin.

That said,  MATLAB allows the packaging of its code into an encrypted Dll file which can then be executed by the MCR. In addition to .NET, MATLAB code can also be exported to C libraries , Java libraries or an executable file.

The first thing we will do is fire up MATLAB, we will access its computational engine through the use of  of  the eval  function which will return the result of a mathematical expression passed to it as a string.  There are the steps.

  1. Launch MATLAB
  2. Type edit in the MATLAB command window then press enter/return. 
    edit
  3. In the new window create the function as seen below then hit the save button.
    function result = calculator(input)
    result = eval(input);
    end
    
  4. Click File->New->Deployment Project then type calculator in the name box.
  5. Select a location to save the project and .NET Assembly from the type drop down box.
  6. In the .NET Assembly window, under the build tab change the default name of the class to “demo” then drag and drop the calculator.m file unto the class to add it as a method of the class, then hit the compile button. This should create the calculator.dll which can be referenced from your c# application.
  7. Fire up Visual Studio and create a new C# Windows Forms Application, to this application add a reference to the calculator.dll file, you will also need to add a reference to the MWArray.Dll which is located at “C:\Program Files\MATLAB\MATLAB Compiler Runtime\v716\toolbox\dotnetbuilder\bin\win64\v2.0\MWArray.dll” (version dependent path) in order to facilitate the conversion of .NET types to MATLAB types.
  8. GUI for expression parser application.
  9. C# Application code.
    using System;
    using System.Windows.Forms;
    using MathWorks.MATLAB.NET.Arrays;
    using calculator;
    
    namespace DemoCalculator
    {
        public partial class Form1 : Form
        {
            public Form1()
            {
                InitializeComponent();
            }
    
            private void button1_Click(object sender, EventArgs e)
            {
                var calc= new demo();            
                MessageBox.Show(calc.calculator((MWCharArray)textBox1.Text)[1].ToString());
            }
            
        }
    }
    
  10. Run the application then enter a mathematical expression and hit the Calculate button, this will send the string to be interpreted by the MCR and return a result to the user, the end.

Using The GATOOL in MATLAB

Posted on Updated on

The gatool in MATLAB provides researchers with the ability to quickly apply optimization techniques to problems that need a genetic algorithm. As with all toolboxes contained in MATLAB the gatool has a command line interface and a GUI interface. We will be using the GUI interface since it provides an easier means of modifying the parameters of the toolbox. The gatool implements a canonical genetic algorithm, with the ability to provide custom functions for mutation, crossover and selection operators. Before going any further lets review Introduction To MathWorks MATLAB. Now that you are back lets see how this can be done.

We will need to create two functions for use with the gatool (1)objective function, (2)creation function. The objective function will be minimized by the genetic algorithm to give an ideal solution for our problem definition. While the creation function will be used to create initial individuals for the genetic algorithm population.

Objective Function:

function rtn = objective(param)
seq = [1 2 3 4 5];
temp = 5;
for i = 1:length(param)
 if eq(seq(i),floor(param(i)))
 temp = temp - 1;
 end
end
rtn = temp;

Creation Function:

function rtn = creator(genomeLength, fitnessFn, options)
temp = floor(5.*rand(5,1));
rtn = temp';

Gocha’s: Arguements for the respective functions must be provided otherwise the toolbox will not be able to provide the necessary parameters to the functions.

Launch gatool-> Type gatool in the MATLAB command window

GATOOL Interface: Only parameters marked in red were modified.

Results: Click the start button on the gatool to start the optimization routine.

Results Plot:

Conclusion:
This post intends to use the gatool present in MATLAB to evolve a vector of integers from 1 to 5. If you take the floor of the final point listings you will see that this aim was achieved with 0.0 fitness.  As an exercise you could modify the other parameters present in the gatool and re-run the routine to observe any changes that may occur.