How to Write and Optimize MATLAB Functions

Writing MATLAB Functions

1. Basic Structure:
   • Function Keyword: Every MATLAB function starts with the function keyword.
   • Output Arguments: Specify the output arguments in square brackets. If there are no outputs, you can omit them or use empty square brackets.
   • Function Name: The function name must start with a letter and can contain letters, digits, or underscores. It is recommended to use the same name for both the function file and the first function within the file.
   • Input Arguments: Input arguments are specified in parentheses after the function name. If there are no inputs, you can omit the parentheses.
   Example:
   matlabCopy

   function [output1, output2] = functionName(input1, input2)
       % Function body
   end

2. Function Body:
   • The body of a function can include MATLAB expressions, control flow statements, comments, blank lines, and nested functions.
   • Variables created within a function are stored in a workspace specific to that function, separate from the base workspace.
3. Calling a Function:
   • To call a function, simply use its name followed by the input arguments in parentheses.
   • For example, to call the addNumbers function:
     matlabCopy

     result = addNumbers(3, 5);

Optimizing MATLAB Functions

1. Vectorization:
   • Vectorization involves performing operations on entire arrays rather than individual elements. This can significantly speed up your code.
   • For example, instead of using a loop to square each element of an array, you can use vectorized operations:
     matlabCopy

     A = [1, 2, 3, 4];
     B = A.^2; % Vectorized operation

2. Preallocation:
   • Preallocating memory for arrays can improve performance by reducing the overhead of resizing arrays during execution.
   • Use functions like zeros, ones, or prealloc to preallocate memory.
3. Efficient Use of Built-in Functions:
   • MATLAB has a vast library of built-in functions optimized for performance. Use these functions whenever possible instead of writing your own.
   • For example, use sum, mean, std, etc., instead of implementing these operations manually.
4. Minimizing Function Calls:
   • Reducing the number of function calls can improve performance. For example, if a function is called multiple times with the same inputs, consider storing the result in a variable.
5. Using Inline Functions:
   • For simple functions, consider using inline functions to avoid the overhead of function calls.
   • Example:
     matlabCopy

     f = @(x) x^2;
     result = f(5);

6. Profiling and Debugging:
   • Use MATLAB’s profiler (profile viewer) to identify bottlenecks in your code.
   • Debugging tools can help you find and fix errors efficiently.

Practical Example

function sumSquares = calculateSumSquares(matrix)
    sumSquares = 0;
    [rows, cols] = size(matrix);
    for i = 1:rows
        for j = 1:cols
            sumSquares = sumSquares + matrix(i, j)^2;
        end
    end
end

function sumSquares = calculateSumSquares(matrix)
    sumSquares = sum(matrix(:).^2);
end

Conclusion