matlab - What's the "right" way to organize GUI code?

Question

I'm working on a fairly sophisticated GUI program to be deployed with MATLAB Compiler. (There are good reasons MATLAB is being used to build this GUI, that is not the point of this question. I realize GUI-building is not a strong suit for this language.)

There are quite a few ways to share data between functions in a GUI, or even pass data between GUIs within an application:

• setappdata/getappdata/_____appdata - associate arbitrary data to a handle
• guidata - typically used with GUIDE; "store[s] or retrieve[s] GUI data" to a structure of handles
• Apply a set/get operation to the UserData property of a handle object
• Use nested functions within a main function; basically emulates "globally" scoping variables.
• Pass the data back and forth among subfunctions

The structure for my code is not the prettiest. Right now I have the engine segregated from the front-end (good!) but the GUI code is pretty spaghetti-like. Here's a skeleton of an "activity", to borrow Android-speak:

function myGui

    fig = figure(...); 

    % h is a struct that contains handles to all the ui objects to be instantiated. My convention is to have the first field be the uicontrol type I'm instantiating. See draw_gui nested function

    h = struct([]);


    draw_gui;
    set_callbacks; % Basically a bunch of set(h.(...), 'Callback', @(src, event) callback) calls would occur here

    %% DRAW FUNCTIONS

    function draw_gui
        h.Panel.Panel1 = uipanel(...
            'Parent', fig, ...
            ...);

        h.Panel.Panel2 = uipanel(...
            'Parent', fig, ...
            ...);


        draw_panel1;
        draw_panel2;

        function draw_panel1
             h.Edit.Panel1.thing1 = uicontrol('Parent', h.Panel.Panel1, ...);
        end
        function draw_panel2
             h.Edit.Panel2.thing1 = uicontrol('Parent', h.Panel.Panel2, ...);
        end


    end

    %% CALLBACK FUNCTIONS
    % Setting/getting application data is done by set/getappdata(fig, 'Foo').
end

I have previously-written code where nothing is nested, so I ended up passing h back and forth everywhere (since stuff needed to be redrawn, updated, etc) and setappdata(fig) to store actual data. In any case, I've been keeping one "activity" in a single file, and I'm sure this is going to be a maintenance nightmare in the future. Callbacks are interacting with both application data and graphical handle objects, which I suppose is necessary, but that's preventing a complete segregation of the two "halves" of the code base.

So I'm looking for some organizational/GUI design help here. Namely:

• Is there a directory structure I ought to be using to organize? (Callbacks vs drawing functions?)
• What's the "right way" to interact with GUI data and keep it segregated from application data? (When I refer to GUI data I mean set/getting properties of handle objects).
• How do I avoid putting all these drawing functions into one giant file of thousands of lines and still efficiently pass both application and GUI data back and forth? Is that possible?
• Is there any performance penalty associated with constantly using set/getappdata?
• Is there any structure my back-end code (3 object classes and a bunch of helper functions) should take to make it easier to maintain from a GUI perspective?

I'm not a software engineer by trade, I just know enough to be dangerous, so I'm sure these are fairly basic questions for seasoned GUI developers (in any language). I almost feel like the lack of a GUI design standard in MATLAB (does one exist?) is seriously interfering with my ability to complete this project. This is a MATLAB project that is much more massive than any I've ever undertaken, and I've never had to give much thought to complicated UIs with multiple figure windows, etc., before.

Answer 1

As @SamRoberts explained, the Model–view–controller (MVC) pattern is well-suited as an architecture to design GUIs. I agree that there are not a lot of MATLAB examples out there to show such design...

Below is a complete yet simple example I wrote to demonstrate an MVC-based GUI in MATLAB.

• The model represents a 1D function of some signal y(t) = sin(..t..). It is a handle-class object, that way we can pass the data around without creating unnecessary copies. It exposes observable properties, which allows other components to listen for change notifications.

• The view presents the model as a line graphics object. The view also contains a slider to control one of the signal properties, and listens to model change notifications. I also included an interactive property which is specific to the view (not the model), where the line color can be controlled using the right-click context menu.

• The controller is responsible of initializing everything and responding to events from the view and correctly updating the model accordingly.

Note that the view and controller are written as regular functions, but you could write classes if you prefer fully object-oriented code.

It is a little extra work compared to the usual way of designing GUIs, but one of the advantages of such architecture is the separation of the data from presentation layer. This makes for a cleaner and more readable code especially when working with complex GUIs, where code maintenance becomes more difficult.

This design is very flexible as it allows you to build multiple views of the same data. Even more you can have multiple simultaneous views, just instantiate more views instances in the controller and see how changes in one view are propagated to the other! This is especially interesting if your model can be visually presented in different ways.

In addition, if you prefer you can use the GUIDE editor to build interfaces instead of programmatically adding controls. In such a design we would only use GUIDE to build the GUI components using drag-and-drop, but we would not write any callback functions. So we'll only be interested in the .fig file produced, and just ignore the accompanying .m file. We would setup the callbacks in the view function/class. This is basically what I did in the View_FrequencyDomain view component, which loads the existing FIG-file built using GUIDE.

---

Model.m

classdef Model < handle
    %MODEL  represents a signal composed of two components + white noise
    % with sampling frequency FS defined over t=[0,1] as:
    %   y(t) = a * sin(2pi * f*t) + sin(2pi * 2*f*t) + white_noise

    % observable properties, listeners are notified on change
    properties (SetObservable = true)
        f       % frequency components in Hz
        a       % amplitude
    end

    % read-only properties
    properties (SetAccess = private)
        fs      % sampling frequency (Hz)
        t       % time vector (seconds)
        noise   % noise component
    end

    % computable dependent property
    properties (Dependent = true, SetAccess = private)
        data    % signal values
    end

    methods
        function obj = Model(fs, f, a)
            % constructor
            if nargin < 3, a = 1.2; end
            if nargin < 2, f = 5; end
            if nargin < 1, fs = 100; end
            obj.fs = fs;
            obj.f = f;
            obj.a = a;

            % 1 time unit with 'fs' samples
            obj.t = 0 : 1/obj.fs : 1-(1/obj.fs);
            obj.noise = 0.2 * obj.a * rand(size(obj.t));
        end

        function y = get.data(obj)
            % signal data
            y = obj.a * sin(2*pi * obj.f*obj.t) + ...
                sin(2*pi * 2*obj.f*obj.t) + obj.noise;
        end
    end

    % business logic
    methods
        function [mx,freq] = computePowerSpectrum(obj)
            num = numel(obj.t);
            nfft = 2^(nextpow2(num));

            % frequencies vector (symmetric one-sided)
            numUniquePts = ceil((nfft+1)/2);
            freq = (0:numUniquePts-1)*obj.fs/nfft;

            % compute FFT
            fftx = fft(obj.data, nfft);

            % calculate magnitude
            mx = abs(fftx(1:numUniquePts)).^2 / num;
            if rem(nfft, 2)
                mx(2:end) = mx(2:end)*2;
            else
                mx(2:end -1) = mx(2:end -1)*2;
            end
        end
    end
end

View_TimeDomain.m

function handles = View_TimeDomain(m)
    %VIEW  a GUI representation of the signal model

    % build the GUI
    handles = initGUI();
    onChangedF(handles, m);    % populate with initial values

    % observe on model changes and update view accordingly
    % (tie listener to model object lifecycle)
    addlistener(m, 'f', 'PostSet', ...
        @(o,e) onChangedF(handles,e.AffectedObject));
end

function handles = initGUI()
    % initialize GUI controls
    hFig = figure('Menubar','none');
    hAx = axes('Parent',hFig, 'XLim',[0 1], 'YLim',[-2.5 2.5]);
    hSlid = uicontrol('Parent',hFig, 'Style','slider', ...
        'Min',1, 'Max',10, 'Value',5, 'Position',[20 20 200 20]);
    hLine = line('XData',NaN, 'YData',NaN, 'Parent',hAx, ...
        'Color','r', 'LineWidth',2);

    % define a color property specific to the view
    hMenu = uicontextmenu;
    hMenuItem = zeros(3,1);
    hMenuItem(1) = uimenu(hMenu, 'Label','r', 'Checked','on');
    hMenuItem(2) = uimenu(hMenu, 'Label','g');
    hMenuItem(3) = uimenu(hMenu, 'Label','b');
    set(hLine, 'uicontextmenu',hMenu);

    % customize
    xlabel(hAx, 'Time (sec)')
    ylabel(hAx, 'Amplitude')
    title(hAx, 'Signal in time-domain')

    % return a structure of GUI handles
    handles = struct('fig',hFig, 'ax',hAx, 'line',hLine, ...
        'slider',hSlid, 'menu',hMenuItem);
end

function onChangedF(handles,model)
    % respond to model changes by updating view
    if ~ishghandle(handles.fig), return, end
    set(handles.line, 'XData',model.t, 'YData',model.data)
    set(handles.slider, 'Value',model.f);
end

View_FrequencyDomain.m

function handles = View_FrequencyDomain(m)    
    handles = initGUI();
    onChangedF(handles, m);

    hl = event.proplistener(m, findprop(m,'f'), 'PostSet', ...
        @(o,e) onChangedF(handles,e.AffectedObject));
    setappdata(handles.fig, 'proplistener',hl);
end

function handles = initGUI()
    % load FIG file (its really a MAT-file)
    hFig = hgload('ViewGUIDE.fig');
    %S = load('ViewGUIDE.fig', '-mat');

    % extract handles to GUI components
    hAx = findobj(hFig, 'tag','axes1');
    hSlid = findobj(hFig, 'tag','slider1');
    hTxt = findobj(hFig, 'tag','fLabel');
    hMenu = findobj(hFig, 'tag','cmenu1');
    hMenuItem = findobj(hFig, 'type','uimenu');

    % initialize line and hook up context menu
    hLine = line('XData',NaN, 'YData',NaN, 'Parent',hAx, ...
        'Color','r', 'LineWidth',2);
    set(hLine, 'uicontextmenu',hMenu);

    % customize
    xlabel(hAx, 'Frequency (Hz)')
    ylabel(hAx, 'Power')
    title(hAx, 'Power spectrum in frequency-domain')

    % return a structure of GUI handles
    handles = struct('fig',hFig, 'ax',hAx, 'line',hLine, ...
        'slider',hSlid, 'menu',hMenuItem, 'txt',hTxt);
end

function onChangedF(handles,model)
    [mx,freq] = model.computePowerSpectrum();
    set(handles.line, 'XData',freq, 'YData',mx)
    set(handles.slider, 'Value',model.f)
    set(handles.txt, 'String',sprintf('%.1f Hz',model.f))
end

Controller.m

function [m,v1,v2] = Controller
    %CONTROLLER  main program

    % controller knows about model and view
    m = Model(100);           % model is independent
    v1 = View_TimeDomain(m);  % view has a reference of model

    % we can have multiple simultaneous views of the same data
    v2 = View_FrequencyDomain(m);

    % hook up and respond to views events
    set(v1.slider, 'Callback',{@onSlide,m})
    set(v2.slider, 'Callback',{@onSlide,m})
    set(v1.menu, 'Callback',{@onChangeColor,v1})
    set(v2.menu, 'Callback',{@onChangeColor,v2})

    % simulate some change
    pause(3)
    m.f = 10;
end

function onSlide(o,~,model)
    % update model (which in turn trigger event that updates view)
    model.f = get(o,'Value');
end

function onChangeColor(o,~,handles)
    % update view
    clr = get(o,'Label');
    set(handles.line, 'Color',clr)
    set(handles.menu, 'Checked','off')
    set(o, 'Checked','on')
end

In the controller above, I instantiate two separate but synchronized views, both representing and responding to changes in the same underlying model. One view shows the time-domain of the signal, and another shows the frequency-domain representation using FFT.