Variable arguments (varargin, varargout) in MATLAB - Time & Space Complexity
When using variable input or output arguments in MATLAB functions, it is important to understand how the number of inputs or outputs affects the time the function takes to run.
We want to know how the function's running time changes as we pass more or fewer arguments.
Analyze the time complexity of the following MATLAB function using varargin and varargout.
function varargout = exampleFunc(varargin)
n = length(varargin);
for k = 1:n
varargout{k} = varargin{k} * 2;
end
end
This function takes any number of inputs, doubles each one, and returns the results as outputs.
Look for loops or repeated steps that depend on input size.
- Primary operation: The for-loop that doubles each input argument.
- How many times: The loop runs once for each input argument, so n times.
As you add more input arguments, the function does more work by doubling each one.
| Input Size (n) | Approx. Operations |
|---|---|
| 10 | 10 doubling steps |
| 100 | 100 doubling steps |
| 1000 | 1000 doubling steps |
Pattern observation: The work grows directly with the number of inputs. Double the inputs, double the work.
Time Complexity: O(n)
This means the time to run the function grows in a straight line with the number of input arguments.
[X] Wrong: "Using varargin or varargout makes the function slower in a way that grows faster than the number of inputs."
[OK] Correct: The function only processes each input once, so the time grows linearly, not faster. The variable arguments themselves don't add hidden loops.
Understanding how variable arguments affect time helps you write flexible functions without surprises about speed. This skill shows you can think about how code scales with input size.
"What if the function called another function inside the loop that itself loops over the input? How would the time complexity change?"