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Anonymous Functions and Function Handles

Understand MATLAB's @ syntax for anonymous functions and function handles, closures over workspace variables, and passing handles to arrayfun, cellfun, ode45, and fplot.

Control Flow & FunctionsIntermediate11 min readJul 10, 2026
Analogies

Defining Anonymous Functions and Handles

An anonymous function is created inline with the @ symbol: f = @(x) x^2 + 1 defines a function without a separate .m file, useful for short throwaway expressions. You can also create a function handle to an existing named function with @functionName (no parentheses), which lets you pass that function around as a value — store it in a variable, pass it as an argument, or call it later via feval or by invoking the handle directly like f(3).

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Cricket analogy: strikeRate = @(runs, balls) (runs/balls)*100 creates an anonymous function on the fly, just like a commentator instantly computing a batsman's strike rate without writing a whole scorecard program

Closures: Capturing Workspace Variables

When you define an anonymous function, MATLAB captures a snapshot of the values of any workspace variables it references at the moment of creation — this is a closure. If you later change the original variable in the workspace, the already-created handle keeps using the old captured value, not the updated one. Creating a new handle after the change would capture the new value instead.

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Cricket analogy: addBonus = @(runs) runs + bonusRuns captures the value of bonusRuns at creation time, so later changing bonusRuns in the workspace does not affect the handle, like a scorecard entry locked in at the moment it was recorded

matlab
exchangeRate = 83.2;
convertToINR = @(usd) usd * exchangeRate;   % captures 83.2 now

fprintf('%.2f\n', convertToINR(100));  % 8320.00

exchangeRate = 90.0;                        % changing the variable later...
fprintf('%.2f\n', convertToINR(100));  % still 8320.00 - handle kept the old rate

convertToINR_new = @(usd) usd * exchangeRate;  % recreated handle captures 90.0
fprintf('%.2f\n', convertToINR_new(100));  % 9000.00

Because closures capture values, not references, an anonymous function created inside a loop that refers to the loop variable will each capture that iteration's value correctly in MATLAB — but if you intend a handle to always reflect the CURRENT value of a variable, you must recreate the handle after the variable changes; it will never auto-update.

Passing Handles to arrayfun, cellfun, and feval

Function handles become powerful when passed to higher-order functions. arrayfun applies a handle to each element of a numeric array, cellfun applies a handle to each cell of a cell array, and feval calls a handle stored in a variable dynamically — useful when the function to call is determined at runtime rather than hard-coded. Both arrayfun and cellfun accept 'UniformOutput', false when the handle's outputs aren't uniform scalars.

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Cricket analogy: strikeRates = arrayfun(@(r,b) r/b*100, runsArray, ballsArray) applies the strike-rate formula across every player's stats in one vectorized call instead of looping

Handles with fplot, ode45, and Optimization

Many MATLAB toolbox functions accept a function handle as their core argument: fplot(@(x) expr, xrange) plots a mathematical expression directly, ode45(@(t,y) expr, tspan, y0) numerically integrates a differential equation defined inline, and optimization routines like fminbnd(@(x) expr, lower, upper) search for the input minimizing an anonymous objective function. This pattern avoids writing a separate named function file for a one-off mathematical model.

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Cricket analogy: fplot(@(x) 100*(1-exp(-0.1*x)), [0 50]) plots a strike-rate acceleration curve against balls faced, feeding the anonymous handle directly into fplot

You can check whether a variable is a function handle with isa(f, 'function_handle'), and inspect its definition text with func2str(f) — handy for debugging pipelines that build anonymous functions dynamically.

  • Anonymous functions use @(args) expression syntax; @functionName creates a handle to a named function.
  • Anonymous functions form closures, capturing referenced workspace variable values at creation time, not by reference.
  • A handle's captured values never update automatically when the source variable later changes.
  • arrayfun and cellfun apply a handle across every element of an array or cell array without an explicit loop.
  • feval calls a handle stored in a variable, useful for runtime-selected functions.
  • Toolbox functions like fplot, ode45, and fminbnd accept handles directly as their core argument.
  • func2str() and isa(f,'function_handle') help inspect and validate handles at runtime.

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