MATLAB's integration with C and C++ offers powerful capabilities for enhancing performance and extending functionality. This seamless integration allows developers to leverage the strengths of both environments, combining MATLAB's high-level programming and visualization with C/C++'s speed and low-level control.
MEX (MATLAB Executable) files are the primary method for integrating C/C++ code with MATLAB. These dynamically linked subroutines are called from MATLAB as if they were built-in functions.
To create a MEX file:
Here's a simple example of a C MEX file:
#include "mex.h"
void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])
{
double *input, *output;
size_t n;
/* Check inputs */
if (nrhs != 1 || !mxIsDouble(prhs[0]))
mexErrMsgTxt("Input must be a double array");
/* Get input */
input = mxGetPr(prhs[0]);
n = mxGetNumberOfElements(prhs[0]);
/* Create output */
plhs[0] = mxCreateDoubleMatrix(1, n, mxREAL);
output = mxGetPr(plhs[0]);
/* Compute square of each element */
for (size_t i = 0; i < n; i++)
output[i] = input[i] * input[i];
}
After compiling, you can call this function from MATLAB like any other function:
result = mex_square([1 2 3 4 5]);
MATLAB Code Generation allows you to automatically convert MATLAB code into C/C++. This is particularly useful for deploying MATLAB algorithms in embedded systems or integrating them into larger C/C++ projects.
Here's a simple example:
function y = myFunction(x)
y = x.^2 + 2*x + 1;
end
% Generate C code
codegen myFunction -args {zeros(1,100)}
When integrating MATLAB with C/C++, efficient data exchange is crucial. MATLAB provides several mechanisms for this purpose:
MATLAB's integration with C/C++ provides a powerful toolset for developers seeking to combine high-level scripting with low-level performance. By mastering MEX files, code generation, and efficient data exchange techniques, you can create robust, high-performance applications that leverage the strengths of both environments.
For more advanced topics, consider exploring MATLAB MEX Files and MATLAB Performance Optimization techniques to further enhance your integration skills.