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Generate C Code by Using the MATLAB Coder App

In this tutorial, you use the MATLAB® Coder™ app to generate a static C library for a MATLAB function. You first generate C code that can accept only inputs that have fixed preassigned size. You then generate C code that can accept inputs of many different sizes.

You can also generate code at the MATLAB command line by using the codegen command. For a tutorial on this workflow, see Generate C Code at the Command Line.

The MATLAB Coder app is not supported in MATLAB Online™. To generate C/C++ code in MATLAB Online, use the codegen command.

Tutorial Files

Copy the tutorial files from the folder matlabroot\help\toolbox\coder\examples\euclidean to a local working folder. Here, matlabroot is the MATLAB installation folder, for example, C:\Program Files\MATLAB\R2019a. To copy these files to your current folder, run this MATLAB command:

copyfile(fullfile(matlabroot,'help','toolbox','coder','examples','euclidean'))
The local working folder cannot be a private folder or an @ folder. This tutorial uses the euclidean_data.mat, euclidean.m, and test.m files.

  • The MATLAB data file euclidean_data.mat contains two pieces of data: a single point in three-dimensional Euclidean space and a set of several other points in three-dimensional Euclidean space. More specifically:

    • x is a 3-by-1 column vector that represents a point in three-dimensional Euclidean space.

    • cb is a 3-by-216 array. Each column in cb represents a point in three-dimensional Euclidean space.

  • The MATLAB file euclidean.m contains the function euclidean that implements the core algorithm in this example. The function takes x and cb as inputs. It calculates the Euclidean distance between x and each point in cb and returns these quantities:

    • The column vector y_min, which is equal to the column in cb that represents the point that is closest to x.

    • The column vector y_max, which is equal to the column in cb that represents the point that is farthest from x.

    • The 2-dimensional vector idx that contains the column indices of the vectors y_min and y_max in cb.

    • The 2-dimensional vector distance that contains the calculated smallest and largest distances to x.

    function [y_min,y_max,idx,distance] = euclidean(x,cb)
    % Initialize minimum distance as distance to first element of cb
    % Initialize maximum distance as distance to first element of cb
    idx(1)=1;
    idx(2)=1;
    
    distance(1)=norm(x-cb(:,1));
    distance(2)=norm(x-cb(:,1));
    
    % Find the vector in cb with minimum distance to x
    % Find the vector in cb with maximum distance to x
    for index=2:size(cb,2)
        d=norm(x-cb(:,index));
        if d < distance(1)
            distance(1)=d;
            idx(1)=index;
        end
        if d > distance(2)
            distance(2)=d;
            idx(2)=index;
        end
    end
    
    % Output the minimum and maximum distance vectors
    y_min=cb(:,idx(1));
    y_max=cb(:,idx(2));
    
    end
  • The MATLAB script test.m loads the data file euclidean_data.mat into the workspace. It then calls the function euclidean to calculate y_min, y_max, idx, and distance. The script then displays the calculated quantities at the command line.

    Loading euclidean_data.mat is the preprocessing step that is executed before calling the core algorithm. Displaying the results is the post-processing step.

    % Load test data 
    load euclidean_data.mat
    
    % Determine closest and farthest points and corresponding distances
    [y_min,y_max,idx,distance] = euclidean(x,cb);
    
    % Display output for the closest point
    disp('Coordinates of the closest point are: ');
    disp(num2str(y_min'));
    disp(['Index of the closest point is ', num2str(idx(1))]);
    disp(['Distance to the closest point is ', num2str(distance(1))]);
    
    disp(newline);
    
    % Display output for the farthest point
    disp('Coordinates of the farthest point are: ');
    disp(num2str(y_max'));
    disp(['Index of the farthest point is ', num2str(idx(2))]);
    disp(['Distance to the farthest point is ', num2str(distance(2))]);

Tip

You can generate code from MATLAB functions by using MATLAB Coder. Code generation from MATLAB scripts is not supported.

Use test scripts to separate the pre- and post-processing steps from the function implementing the core algorithm. This practice enables you to easily reuse your algorithm. You generate code for the MATLAB function that implements the core algorithm. You do not generate code for the test script.

Generate C Code for the MATLAB Function

Run the Original MATLAB Code

Run the test script test.m in MATLAB. The output displays y, idx, and distance.

Coordinates of the closest point are: 
0.8         0.8         0.4
Index of the closest point is 171
Distance to the closest point is 0.080374


Coordinates of the farthest point are: 
0  0  1
Index of the farthest point is 6
Distance to the farthest point is 1.2923

Make the MATLAB Code Suitable for Code Generation

The Code Analyzer in the MATLAB Editor continuously checks your code as you enter it. It reports issues and recommends modifications to maximize performance and maintainability.

  1. Open euclidean.m in the MATLAB Editor. The Code Analyzer message indicator in the top right corner of the MATLAB Editor is green. The analyzer did not detect errors, warnings, or opportunities for improvement in the code.

  2. After the function declaration, add the %#codegen directive:

    function [y,idx,distance] = euclidean(x,cb) %#codegen
    The %#codegen directive prompts the Code Analyzer to identify warnings and errors specific to code generation.

    The Code Analyzer message indicator becomes red, indicating that it has detected code generation issues.

  3. To view the warning messages, move your cursor to the underlined code fragments. The warnings indicate that code generation requires the variables idx and distance to be fully defined before subscripting them. These warnings appear because the code generator must determine the sizes of these variables at their first appearance in the code. To fix this issue, use the ones function to simultaneously allocate and initialize these arrays.

    % Initialize minimum distance as distance to first element of cb
    % Initialize maximum distance as distance to first element of cb
    idx = ones(1,2);
    
    distance = ones(1,2)*norm(x-cb(:,1));

    The Code Analyzer message indicator becomes green again, indicating that it does not detect any more code generation issues.

    For more information about using the Code Analyzer, see Check Code for Errors and Warnings.

  4. Save the file.

    You are now ready to compile your code by using the MATLAB Coder app. Here, compilation refers to the generation of C/C++ code from your MATLAB code.

Note

Compilation of MATLAB code refers to the generation of C/C++ code from the MATLAB code. In other contexts, the term compilation could refer to the action of a C/C++ compiler.

Open the MATLAB Coder App and Select Source Files

  1. On the MATLAB toolstrip Apps tab, under Code Generation, click the MATLAB Coder app icon. The app opens the Select Source Files page.

  2. In the Select Source Files page, enter or select the name of the entry-point function euclidean. An entry-point function is a top-level MATLAB function from which you generate code. The app creates a project with the default name euclidean.prj in the current folder.

  3. Click Next to go to the Define Input Types step. The app runs the Code Analyzer (that you already ran in the previous step) and the Code Generation Readiness Tool on the entry-point function. The Code Generation Readiness Tool screens the MATLAB code for features and functions that are not supported for code generation. If the app identifies issues, it opens the Review Code Generation Readiness page where you can review and fix issues. In this example, because the app does not detect issues, it opens the Define Input Types page. For more information, see Code Generation Readiness Tool.

    Note

    The Code Analyzer and the Code Generation Readiness Tool might not detect all code generation issues. After eliminating the errors or warnings that these two tools detect, generate code with MATLAB Coder to determine if your MATLAB code has other compliance issues.

Certain MATLAB built-in functions and toolbox functions, classes, and System objects that are supported for C/C++ code generation have specific code generation limitations. These limitations and related usage notes are listed in the Extended Capabilities sections of their corresponding reference pages. For more information, see Functions and Objects Supported for C/C++ Code Generation.

Define Input Types

Because C uses static typing, the code generator must determine the class, size, and complexity of all variables in the MATLAB files at code generation time, also known as compile time. Therefore, you must specify the properties of all entry-point function inputs. To specify input properties, you can:

  • Instruct the app to automatically determine input properties by providing a script that calls the entry-point functions with sample inputs.

  • Specify properties directly.

In this example, to define the properties of the inputs x and cb, specify the test file test.m that the code generator can use to define types automatically:

  1. Enter or select the test file test.m.

  2. Click Autodefine Input Types.

    The test file, test.m, calls the entry-point function, euclidean, with the expected input types. The app determines that the input x is double(3x1) and the input cb is double(3x216).

  3. Click Next to go to the Check for Run-Time Issues step.

Check for Run-Time Issues

The Check for Run-Time Issues step generates a MEX file from your entry-point functions, runs the MEX function, and reports issues. A MEX function is generated code that can be called from inside MATLAB. It is a best practice to perform this step because you can detect and fix run-time errors that are harder to diagnose in the generated C code. By default, the MEX function includes memory integrity checks. These checks perform array bounds and dimension checking. The checks detect violations of memory integrity in code generated for MATLAB functions. For more information, see Control Run-Time Checks.

To convert MATLAB code to efficient C/C++ source code, the code generator introduces optimizations that, in certain situations, cause the generated code to behave differently than the original source code. See Differences Between Generated Code and MATLAB Code.

  1. To open the Check for Run-Time Issues dialog box, click the Check for Issues arrow .

  2. In the Check for Run-Time Issues dialog box, specify a test file or enter code that calls the entry-point function with example inputs. For this example, use the test file test that you used to define the input types.

  3. Click Check for Issues.

    The app generates a MEX function. It runs the test script test replacing calls to euclidean with calls to the generated MEX. If the app detects issues during the MEX function generation or execution, it provides warning and error messages. Click these messages to navigate to the problematic code and fix the issue. In this example, the app does not detect issues.

  4. By default, the app collects line execution counts. These counts help you to see how well the test file test.m exercised the euclidean function. To view line execution counts, click View MATLAB line execution counts. The app editor displays a color-coded bar to the left of the code. To extend the color highlighting over the code and to see line execution counts, place your cursor over the bar.

    A particular shade of green indicates that the line execution count for this code falls in a certain range. In this case, the for-loop executes 215 times. For information about how to interpret line execution counts and turn off collection of the counts, see Collect and View Line Execution Counts for Your MATLAB Code.

  5. Click Next to go to the Generate Code step.

Note

Before generating standalone C/C++ code from your MATLAB code, generate a MEX function. Run the generated MEX function and make sure it has the same run-time behavior as your MATLAB function. If the generated MEX function produces answers that are different from MATLAB, or produces an error, you must fix these issues before proceeding to standalone code generation. Otherwise, the standalone code that you generate might be unreliable and have undefined behavior.

Generate C Code

  1. To open the Generate dialog box, click the Generate arrow .

  2. In the Generate dialog box, set Build type to Static Library (.lib) and Language to C. Use the default values for the other project build configuration settings.

    Instead of generating a C static library, you can choose to generate a MEX function or other C/C++ build types. Different project settings are available for the MEX and C/C++ build types. When you switch between MEX and C/C++ code generation, verify the settings that you choose.

  3. Click Generate.

    MATLAB Coder generates a standalone C static library euclidean in the work\codegen\lib\euclidean. work is the folder that contains your tutorial files. The MATLAB Coder app indicates that code generation succeeded. It displays the source MATLAB files and generated output files on the left side of the page. On the Variables tab, it displays information about the MATLAB source variables. On the Target Build Log tab, it displays the build log, including C/C++ compiler warnings and errors. By default, in the code window, the app displays the C source code file, euclidean.c. To view a different file, in the Source Code or Output Files pane, click the file name.

  4. Click View Report to view the report in the Report Viewer. If the code generator detects errors or warnings during code generation, the report describes the issues and provides links to the problematic MATLAB code. For more information, see Code Generation Reports.

  5. Click Next to open the Finish Workflow page.

Review the Finish Workflow Page

The Finish Workflow page indicates that code generation succeeded. It provides a project summary and links to generated output.

Compare the Generated C Code to Original MATLAB Code

To compare your generated C code to the original MATLAB code, open the C file, euclidean.c, and the euclidean.m file in the MATLAB Editor.

Important information about the generated C code:

  • The function signature is:

    void euclidean(const double x[3], const double cb[648], double y_min[3], double
                   y_max[3], double idx[2], double distance[2])

    const double x[3] corresponds to the input x in your MATLAB code. The size of x is 3, which corresponds to the total size (3 x 1) of the example input that you used when you generated code from your MATLAB code.

    const double cb[648] corresponds to the input cb in your MATLAB code. The size of cb is 648, which corresponds to the total size (3 x 216) of the example input that you used when you generated code from your MATLAB code. In this case, the generated code uses a one-dimensional array to represent a two-dimensional array in the MATLAB code.

    The generated code has four additional input arguments: the arrays y_min, y_max, idx, and distance. These arrays are used to return the output values. They correspond to the output arguments y_min, y_max, idx, and distance in the original MATLAB code.

  • The code generator preserves your function name and comments. When possible, the code generator preserves your variable names.

    Note

    If a variable in your MATLAB code is set to a constant value, it does not appear as a variable in the generated C code. Instead, the generated C code contains the actual value of the variable.

With Embedded Coder®, you can interactively trace between MATLAB code and generated C/C++ code. See Interactively Trace Between MATLAB Code and Generated C/C++ Code (Embedded Coder).

Generate C Code for Variable-Size Inputs

The C function that you generated for euclidean.m can accept only inputs that have the same size as the sample inputs that you specified during code generation. However, the input arrays to the corresponding MATLAB function can be of any size. In this part of the tutorial, you generate C code from euclidean.m that accepts variable-size inputs.

Suppose that you want the dimensions of x and cb in the generated C code to have these properties:

  • The first dimension of both x and cb can vary in size up to 3.

  • The second dimension of x is fixed and has the value 1.

  • The second dimension of cb can vary in size up to 216.

To specify these input properties:

  1. In the Define Input Types step, enter the test file test.m and click Autodefine Input Types as before. The test file calls the entry-point function, euclidean.m, with the expected input types. The app determines that the input x is double(3x1) and the input cb is double(3x216). These types specify fixed-size inputs.

  2. Click the input type specifications and edit them. You can specify variable size, up to a specified limit, by using the : prefix. For example, :3 implies that the corresponding dimension can vary in size up to 3. Change the types to double(:3 x 1) for x and double(:3 x :216) for cb.

You can now generate code by following the same steps as before. The function signature for the generated C code in euclidean.c now reads:

void euclidean(const double x_data[], const int x_size[1], const double cb_data[],
               const int cb_size[2], double y_min_data[], int y_min_size[1],
               double y_max_data[], int y_max_size[1], double idx[2], double
               distance[2])
The arguments x_data, cb_data, y_min_data, and y_max_data correspond to the input arguments x and cb and the output arguments y_min and y_max in the original MATLAB function. The C function now accepts four additional input arguments x_size, cb_size, y_min_size, and y_max_size that specify the sizes of x_data, cb_data, y_min_data, and y_max_data at run time.

Next Steps

GoalMore Information

Learn about code generation support for MATLAB built-in functions and toolbox functions, classes, and System objects

Functions and Objects Supported for C/C++ Code Generation

Generate C++ code

C++ Code Generation

Generate and modify an example C main function and use it to build a C executable program

Use an Example C Main in an Application

Package generated files into a compressed file

Package Code for Other Development Environments

Optimize the execution speed or memory usage of generated code

Optimization Strategies

Integrate your custom C/C++ code into the generated code

Call C/C++ Code from MATLAB Code

Learn about the code generation report

Code Generation Reports

Interactively Trace Between MATLAB Code and Generated C/C++ Code (Embedded Coder)