Week 6 pre-work Anonymous and User-Defined Functions in MATLAB

Digital Fundamentals MATLAB Programming III: Anonymous Functions and User-Defined Functions

Overview of Functions in MATLAB

  • Functions are modular blocks of code that perform specific tasks in programming languages, including MATLAB.

  • Functions are invoked whenever specific tasks are required within the code.

  • Types of functions in MATLAB:

    • Inbuilt Functions: Predefined functions provided by MATLAB (e.g., sin(), cos(), plot()).

    • Anonymous Functions: Simple, short functions defined in a single line (e.g., h = @(x) x^2).

    • User-Defined Functions: Custom functions created by the user and saved as .m files.

Inbuilt Functions

  • Inbuilt functions are readily available in MATLAB and often used for common operations, such as:

    • Mathematical functions: sin(), cos(), exp(), sqrt(), log(), log10(), log2()

    • Specialized functions: downsample(), interp1(), fft(), fftshift()

  • Accessing documentation: Use the MATLAB Help Center or use the help FunctionName command in the Command Window for usage instructions. MATLAB HELP DOCUMENTS

Function Attributes: Inputs and Outputs

  • Functions can consist of:

    • Inputs: Defined within parentheses after the function name.

    • Outputs: Variables assigned to the left of the equal sign.

    • Example syntax:

    • Single output: output = functionName(input)

    • Multiple outputs: [out1, out2] = functionName(input)

    • Multiple inputs: output = functionName(in1, in2)

Function Attributes: Unique Names

  • Every function must have a unique name.

  • MATLAB is case-sensitive, distinguishing between functionName() and FUNCTIONname().

  • Avoid using names that might conflict with existing MATLAB functions or reserved keywords (e.g., while, if, function).

  • Use iskeyword() to check for reserved keywords, where the function returns true (1) for reserved words.

checking if it is a command alr or not

Anonymous Functions

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  • Definition: Anonymous functions allow defining simple functions in a concise way without a separate script file.

  • Syntax: h = @(arglist) anonymous_function

  • Example: To evaluate the quadratic equation x^2 + 2x - 3:

    • Define the function: myFunction = @(x) (x.^2) + (2*x) - 3

    • Use with an array: y = myFunction(0:100)

  • Limitations: Can only contain one executable statement and are single-line functions.

    @ symbol creates a function handle

  • Anonomous functions are limited

    • only 1 excutable statment

    • only one single line of script

    • difficult to allow multiple outputs

  • this means if you have more complex requirments it is beneficial to use to use user defined function

User-Defined Functions

  • User-defined functions have a structured format saved as separate .m files and are typically structured as:

    • Function declaration: function out1 = MyFunction(in1, in2)

    • Functionality code: [Functionality code for desired operation]

    • Output assignment: out1 = x

  • Example Function: To compute the hypotenuse using the Pythagorean theorem:

    • hypot = @(a, b) sqrt((a.^2)+(b.^2))

    • Call this function with inputs (e.g., c = hypot(3, 4) results in c = 5).

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Writing User-Defined Functions: Examples

  1. Graphing Function:

    • Input: Arrays for x and y values, labels for axes.

    • Output: None, as it plots a graph.

    • Example implementation:

   function MyGrapher(x, y, xlab, ylab)
       figure();
       plot(x, y, 'Linewidth', 2.0);
       xlabel(xlab, 'Fontsize', 14);
       ylabel(ylab, 'Fontsize', 14);
   end

  1. Spreadsheet Function:

    • Input: Filename of a spreadsheet.

    • Output: Number of columns and mean values of columns.

    • Example implementation:

   function [cols, mu] = myfunc(filename)
       num = readmatrix(filename);
       cols = size(num, 2);
       mu = mean(num);
   end


Flowcharts and Function Calls

  • In flowchart designs, user-defined function calls should be depicted using a distinct subprocess symbol, identifying the area where the function is invoked.

Handling Variable Number of Arguments

  • Use nargin and nargout to manage different numbers of input and output arguments effectively.

  • Keywords:

    • varargin: Allows flexible input arguments.

    • varargout: Allows flexible output arguments.

  • Example usage of varargin in a graphing function:

  function MyGrapher(x, y, varargin)
      figure();
      plot(x, y, 'Linewidth', 2.0);
      hold on;
      for k = 2:2:length(varargin)
          plot(varargin{k-1}, varargin{k}, 'Linewidth', 2.0);
      end
  end

Conclusion

  • The lecture covered fundamental concepts related to MATLAB functions, including inbuilt, anonymous, and user-defined functions, along with practical examples of implementation and flexible argument handling. The related keywords include nargin, nargout, varargin, and varargout to enhance the functionality of user-defined functions.