Generate Single-Precision C Code at the Command Line

This example shows how to generate single-precision C code from double-precision MATLAB^® code at the command line.

Prerequisites

To complete this example, install the following products:

MATLAB
MATLAB Coder™
Fixed-Point Designer™
C compiler
See Supported Compilers.
You can use mex -setup to change the default compiler. See Change Default Compiler.

Create Code Files

In a local, writable folder, create a function ex_2ndOrder_filter.m.

function y = ex_2ndOrder_filter(x) %#codegen
  persistent z
  if isempty(z)
      z = zeros(2,1);
  end
  % [b,a] = butter(2, 0.25)
  b = [0.0976310729378175,  0.195262145875635,  0.0976310729378175];
  a = [1, -0.942809041582063,  0.3333333333333333];

 
  y = zeros(size(x));
  for i = 1:length(x)
      y(i) = b(1)*x(i) + z(1);
      z(1) = b(2)*x(i) + z(2) - a(2) * y(i);
      z(2) = b(3)*x(i)        - a(3) * y(i);
  end
end

Create a test file, ex_2ndOrder_filter_test.m, to exercise the ex_2ndOrder_filter algorithm.

It is a best practice to create a separate test script for preprocessing and postprocessing such as:

Setting up input values.
Calling the function under test.
Outputting the test results.

To cover the full intended operating range of the system, the test script runs the ex_2ndOrder_filter function with three input signals: chirp, step, and impulse. The script then plots the outputs.

% ex_2ndOrder_filter_test
%
% Define representative inputs
N = 256;                   % Number of points
t = linspace(0,1,N);       % Time vector from 0 to 1 second
f1 = N/2;                  % Target frequency of chirp set to Nyquist
x_chirp = sin(pi*f1*t.^2); % Linear chirp from 0 to Fs/2 Hz in 1 second
x_step = ones(1,N);        % Step
x_impulse = zeros(1,N);    % Impulse
x_impulse(1) = 1;

% Run the function under test
x = [x_chirp;x_step;x_impulse];
y = zeros(size(x));
for i = 1:size(x,1)
  y(i,:) = ex_2ndOrder_filter(x(i,:));
end

% Plot the results
titles = {'Chirp','Step','Impulse'}
clf
for i = 1:size(x,1)
  subplot(size(x,1),1,i)
  plot(t,x(i,:),t,y(i,:))
  title(titles{i})
  legend('Input','Output')
end
xlabel('Time (s)')
figure(gcf)

disp('Test complete.')

Determine the Type of the Input Argument

To determine the type of the input argument x, use coder.getArgTypes to run the test file ex_2ndOrder_filter_test.m

types = coder.getArgTypes('ex_2ndOrder_filter_test', 'ex_2ndOrder_filter');

The test file runs and displays the outputs of the filter for each of the input signals. coder.getArgTypes determines that the input type of x is 1x256 double.

Generate and Run Single-Precision MEX to Verify Numerical Behavior

Before you generate single-precision C code, generate a single-precision MEX function that you can use to verify the behavior of the generated single-precision code. To indicate that you want the single-precision MEX code, use the -singleC option.
```
codegen -singleC ex_2ndOrder_filter -args types -report
```
During MEX generation, the code generator detects single-precision conversion issues. Before you generate C/C++ code, fix these issues. This example does not have single-precision conversion issues.
The generated MEX accepts single-precision and double-precision input. You can use the same test file to run the double-precision MATLAB function and the single-precision MEX function. You do not have to modify the test file to call the single-precision MEX function.
Run the test file ex_2ndOrder_filter_test.m. This file calls the double-precision MATLAB function ex_2ndOrder_filter.m.
```
ex_2ndOrder_filter_test
```
The test file runs and displays the outputs of the filter for each of the input signals.
Run the test file ex_2ndOrder_filter_test, replacing calls to the double-precision ex_2ndOrder_filter function with calls to the single-precision ex_2ndOrder_filter_mex function.
```
coder.runTest('ex_2ndOrder_filter_test', 'ex_2ndOrder_filter')
```
The test file runs and displays the outputs of the filter for each of the input signals. The single-precision MEX function produces the same results as the double-precision MATLAB function.