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

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.

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.

The UserData property is a useful, but legacy, property of MATLAB objects. The "AppData" suite of methods (i.e. setappdata, getappdata, rmappdata, isappdata, etc.) provide a great alternative to the comparatively more clumsy get/set(hFig,'UserData',dataStruct) approach, IMO. In fact, to manage GUI data, GUIDE employs the guidata function, which is just a wrapper for the setappdata/getappdata functions.
A couple of advantages of the AppData approach over the 'UserData' property that come to mind:
More natural interface for multiple heterogeneous properties.
UserData is limited to a single variable, requiring you to devise another layer of data oranization (i.e. a struct). Say you want to store a string str = 'foo' and a numeric array v=[1 2]. With UserData, you would need to adopt a struct scheme such as s = struct('str','foo','v',[1 2]); and set/get the whole thing whenever you want either property (e.g. s.str = 'bar'; set(h,'UserData',s);). With setappdata, the process is more direct (and efficient): setappdata(h,'str','bar');.
Protected interface to the underlying storage space.
While 'UserData' is just a regular handle graphics property, the property containing the application data is not visible, although it can be accessed by name ('ApplicationData', but don't do it!). You have to use setappdata to change any existing AppData properties, which prevents you from accidentally clobbering the entire contents of 'UserData' while trying to update a single field. Also, before setting or getting an AppData property, you can verify the existence of a named property with isappdata, which can help with exception handling (e.g. run a process callback before setting input values) and managing the state of the GUI or the tasks which it governs (e.g. infer state of a process by existence of certain properties and update GUI appropriately).
An important difference between the 'UserData' and 'ApplicationData' properties is that 'UserData' is by default [] (an empty array), while 'ApplicationData' is natively a struct. This difference, together with the fact that setappdata and getappdata have no M-file implementation (they are built-in), suggests that setting a named property with setappdata does not require rewriting the entire contents of the data struct. (Imagine a MEX function that performs a in-place modification of a struct field - an operation MATLAB is able to implement by maintaining a struct as the underlying data representation of the 'ApplicationData' handle graphics property.)
The guidata function is a wrapper to the AppData functions, but it is limited to a single variable, like 'UserData'. That means you have to overwrite the entire data structure containing all of your data fields to update a single field. A stated advantage is that you can access the data from a callback without needing the actual figure handle, but as far as I am concerned, this is not a big advantage if you are comfortable with the following statement:
hFig = ancestor(hObj,'Figure')
Also, as stated by MathWorks, there are efficiency issues:
Saving large amounts of data in the 'handles' structure can sometimes cause a considerable slowdown, especially if GUIDATA is often called within the various sub-functions of the GUI. For this reason, it is recommended to use the 'handles' structure only to store handles to graphics objects. For other kinds of data, SETAPPDATA and GETAPPDATA should be used to store it as application data.
This statement supports my assertion that the entire 'ApplicationData' is not rewritten when using setappdata to modify a single named property. (On the other hand, guidata crams the handles structure into a field of 'ApplicationData' called 'UsedByGUIData_m', so it is clear why guidata would need to rewrite all of the GUI data when one property is changed).
Nested functions require very little effort (no auxiliary structures or functions needed), but they obviously limit the scope of data to the GUI, making it impossible for other GUIs or functions to access that data without returning values to the base workspace or a common calling function. Obviously this prevents you from splitting sub-functions out into separate files, something that you can easily do with 'UserData' or AppData as long as you pass the figure handle.
In summary, if you choose to use handle properties to store and pass data, it is possible to use both guidata to manage graphics handles (not large data) and setappdata/getappdata for actual program data. They will not overwrite each other since guidata makes a special 'UsedByGUIData_m' field in ApplicationData for the handles structure (unless you make the mistake of using that property yourself!). Just to reiterate, do not directly access ApplicationData.
However, if you are comfortable with OOP, it may be cleaner to implement GUI functionality via a class, with handles and other data stored in member variables rather than handle properties, and callbacks in methods that can exist in separate files under the class or package folder. There is a nice example on MATLAB Central File Exchange. This submission demonstrates how passing data is simplified with a class since it is no longer necessary to constantly get and update guidata (members variables are always up to date). However there is the additional task of managing cleanup on exit, which the submission accomplishes by setting the figure's closerequestfcn, which then calls the delete function of the class. The submission nicely parallels the GUIDE example.
Those are the highlights as I see them, but many more details and different ideas are discussed by MathWorks. See also this official answer to UserData vs. guidata vs. setappdata/getappdata.

I disagree that MATLAB is not good for implementing (even complex) GUIs - it's perfectly fine.
However, what is true is that:
There are no examples in the MATLAB documentation of how to implement or organize a complex GUI application
All the documentation examples of simple GUIs use patterns that do not scale well at all to complex GUIs
In particular, GUIDE (the built-in tool for auto-generating GUI code) generates terrible code that is a dreadful example to follow if you're implementing something yourself.
Because of these things, most people are only exposed to either very simple or really horrible MATLAB GUIs, and they end up thinking MATLAB is not suitable for making GUIs.
In my experience the best way to implement a complex GUI in MATLAB is the same way as you would in another language - follow a well-used pattern such as MVC (model-view-controller).
However, this is an object-oriented pattern, so first you'll have to get comfortable with object-oriented programming in MATLAB, and particularly with the use of events. Using an object-oriented organization for your application should mean that all the nasty techniques you mention (setappdata, guidata, UserData, nested function scoping, and passing back and forth multiple data copies) are not necessary, as all the relevant things are available as class properties.
The best example I know of that MathWorks has published is in this article from MATLAB Digest. Even that example is very simple, but it gives you an idea of how to start off, and if you look into the MVC pattern it should become clear how to extend it.
In addition, I typically make heavy use of package folders to organize large codebases in MATLAB, to ensure there are no name clashes.
One final tip - use the GUI Layout Toolbox, from MATLAB Central. It makes many aspects of GUI development much easier, particularly implementing automatic resize behaviour, and gives you several additional UI elements to use.
Hope that helps!
Edit: In MATLAB R2016a MathWorks introduced AppDesigner, a new GUI-building framework intended to gradually replace GUIDE.
AppDesigner represents a major break with previous GUI-building approaches in MATLAB in several ways (most deeply, the underlying figure windows generated are based on an HTML canvas and JavaScript, rather than Java). It is another step along a road initiated by the introduction of Handle Graphics 2 in R2014b, and will doubtless evolve further over future releases.
But one impact of AppDesigner on the question asked is that it generates much better code than GUIDE did - it's pretty clean, object-oriented, and suitable to form the basis of an MVC pattern.

I am very uncomfortable with the way GUIDE produces functions. (think about cases where you'd like to call one gui from another)
I would strongly suggest you write your code object oriented using handle classes. That way you can do fancy stuffs (e.g. this) and not get lost. For organizing code you have the + and # directories.

I don't think structuring GUI-code is fundamentally different from non-GUI code.
Put things that belong together, together at some location.
Like helper-functions that might go into a util or helpers directory. Depending on the content, maybe make it a package.
Personally I don't like the "one function one m-file" philosophy some MATLAB people have.
Putting a function like:
function pushbutton17_callback(hObject,evt, handles)
some_text = someOtherFunction();
set(handles.text45, 'String', some_text);
end
into a seperate file simply makes no sense, when there's no scenario whatsoever you'd call this from somewhere else then from your own GUI.
You can however build the GUI itself in a modular way, by e.g. creating certain components by simply passing the parent container:
handles.panel17 = uipanel(...);
createTable(handles.panel17); % creates a table in the specified panel
This also simplifies testing of certain sub-components - you could simply call createTable on an empty figure and test certain functionalities of the table without loading the full application.
Just two additional items I started using when my application became increasingly larger:
Use listeners over callbacks, they can simplify GUI programming significantly.
If you have really large data (such as from a database, etc.) it might be worthwhile implementing a handle-class holding this data.
Storing this handle somewhere in the guidata/appdata significantly improves get/setappdata performance.
Edit:
Listeners over callbacks:
A pushbutton is bad example. Pushing a button usually only triggers on certain action, here callbacks are fine imho.
A main advantage in my case e.g. was that programmatically changing text/popup lists does not trigger callbacks, while listeners on their String or Value property are triggered.
Another example:
If there's some central property (e.g. like some source of inputdata) that multiple components in the application depend on, then using listeners is very convenient to assure that all components are notified if the property changes.
Every new component "interested" in this property can simply add it's own listener, so there's no need to centrally modify the callback.
This allows for a much more modular design of the GUI components and makes adding/removing of such components easier.

Related

MATLAB Class Efficiency

I try making it short. I got a problem involving numerical simulation of a flow withing a gas pipe. I simulate using different models for the air flow (transport equations) travelling from one boundary to the other (i.e. from right to left).
The question is, since I am using different models to represent said gas flow and boundary conditions I got a lot of functions like:
boundary_left_model_1
boundary_right_model_1
boundary_left_model_2
boundary_right_model_2
boundary_left_model_2b
boundary_right_model_2b
....
flux_model_1
flux_model_2
....
source_model_1
source_model_2
.....
I allocate the needed function before the numerical scheme via (e.g.):
boundary_left = #[needed function];
boundary_right=# [needed function];
flux = #[needed function];
source=# [needed function];
What follows is something like:
Solution = numerical_scheme_#1(boundary_left,boundary_right,flux,source,parameters);
you get the point.
Now, what is the most efficient way (while being structured) to build the program? As far as I can tell I have three options:
1) I define every function in a matlab function file (will result in a lot of files)
2) I define every function in the script for the numerical scheme (will result in long file, which is less clear to adjust/read)
3) I create a class for boundary conditions with methods containing all the models, one class for fluxes and sources containing corresponding functions. In my function allocation for the numerical scheme I then call the methods I need. (seems complicated and inefficient, not sure about the time needed calling methods in matlab, but is for me the most structured way)
I should probably note that I am relatively new to matlab and numerical simulation (student) and I am also asking on how this kind of problem is generally solved. Thanks in advance!
Also as a bonus: if someone is fond of practical simulation of PDE systems with matlab - I got questions like "How do I decide on a numerical scheme - which criteria should I consider?"
Thanks again, I wish all of you a pleasent day!
Assuming that the methods associated to model 1 are always used together, and not mixed with those for model 2 or 3, then you could set up your code with all functions for one model in one file:
% MODEL1 Methods that implement model 1
function [boundary_left,boundary_right,flux,source] = model1
boundary_left = #boundary_left_method;
boundary_right = #boundary_right_method;
flux = #flux_method;
source = #source_method;
function [out, args] = boundary_left_method(input, args)
% [implementation]
end
function [out, args] = boundary_right_method(input, args)
% [implementation]
end
function [out, args] = flux_method(input, args)
% [implementation]
end
function [out, args] = source_method(input, args)
% [implementation]
end
end
Basically, here you have a function that returns the handles to a set of functions that implement one method. boundary_left_method is a private function, so cannot be accessed directly, but model1 can return handles to these functions, which makes them accessible.
You can now do:
[boundary_left,boundary_right,flux,source] = model1;
Solution = numerical_scheme_1(boundary_left,boundary_right,flux,source,parameters);
This solution is fairly similar to the custom class solution suggested by OP, but somewhat simpler. I don't think there would be a big difference in performance, but the only way to know for sure is implementing and timing the various options. What is most efficient changes over time as MATLAB's JIT improves.
Note that the scheme proposed here also allows for data (parameters) to be included in these functions:
% MODEL1 Methods that implement model 1
function [boundary_left,boundary_right,flux,source] = model1(parameters)
boundary_left = #boundary_left_method;
boundary_right = #boundary_right_method;
flux = #flux_method;
source = #source_method;
function [out, args] = boundary_left_method(input, args)
out = input * parameters; % You can use PARAMETERS here, note that it is not
% an input argument to this nested function, it is
% found in the parent scope.
end
% ...
end % This end here is important now, this way `boundary_left_method` is an
% nested function, not simply a separate function within the same file.
Now the function handle boundary_left returned has the data of parameters embedded in it. See the relevant documentation.
If you control also the code to the numerical scheme functions that take these function handles, you could write method1 et al. to return a cell array of handles instead, and the numerical_scheme_1 et al. functions to take a cell array of handles. Then you can simply do:
numerical_scheme_1(method1,parameters);
numerical_scheme_1(method2,parameters);
numerical_scheme_1(method3,parameters);
numerical_scheme_2(method1,parameters);
numerical_scheme_2(method2,parameters);
numerical_scheme_2(method3,parameters);
% etc.
You could then use a loop to go through all combinations:
schemes = {#numerical_scheme_1, #numerical_scheme_2, ... };
methods = {method1, method2, method3, ... };
for ii=1:numel(schemes)
for jj=1:numel(methods)
schemes{ii}(methods{jj},parameters);
end
end
[Disclaimer: this code not tested, but I don't see why it wouldn't work...]

How to access variables from base workspace within function?

I am a nested function inside a function and I am calling variables from base workspace. Note that guiel is in base workspace.
function callback(~,~)
vars.dropheight = str2num(get(edit(2),'String'));
vars.armradius = str2num(get(edit(1),'String'));
kiddies = get(guiel.hAX(3),'Children');
delete(kiddies);
clear kiddies;
set(guiel.tfPanel,'Visible','off','Position',cnst.tfPanelpos);
set(guiel.hAX(1),'Position',cnst.axpos1);
if ishandle(guiel.hAX(2))
set(guiel.hAX(2),'Position',cnst.axpos2);
end
eval(get(guiel.hPB(4),'Callback'));
end
The best way, in my opinion, is to store guiel into guidata.
guidata(hFig, guiel); % hFig can be gcf for top figure
and access it in callback by
guiel = guidata(hFig);
One of the alternatives is to pass the variable as input to callback by defining it as
{#callback, guiel}
The callback function definition will be
function callback(~, ~, guiel)
If you really hate these methods, a simple way is to define it as global in base and your callback. But this is something one tries to avoid for both performance and code maintainability consideration.
Best practices for GUI design are that you encapsulate your GUI and its operations in such a way that it never has to depend on the base workspace to function correctly. The reason? The user and other programs can modify anything in the base workspace, and can thus easily break your GUI.
I give an example of a basic GUI setup using nested functions in this post. Here's a general skeleton for designing a GUI:
function create_GUI()
% Initialize data:
data1 = ...;
data2 = ...;
% Create GUI:
hFigure = figure;
hObject1 = uicontrol(..., 'Callback', #callback1);
hObject2 = uicontrol(..., 'Callback', #callback2);
....
function callback1(~, ~)
% Access any data or handles from above
...
end
function callback1(~, ~)
% Access any data or handles from above
...
end
end
The idea is that the main function creates all the GUI components, initializing all the needed data and object handles. The callbacks nested within the main function will have access to the data and handles as needed. I suggest designing your GUI like this, or using one of the other options listed here. This should alleviate some of your data access issues and make your GUI more robust.

Graphic object handle array in embedded matlab function in Simulink in R2014a or newer

For debugging, I have some plots of vectors in an embedded matlab function in Simulink. Up to Matlab R2013b, everything works just fine with the following minimum example code:
function fcn
%#minimum example for plot within for-loop of embedded matlab function
coder.extrinsic('delete');
coder.extrinsic('quiver');
coder.extrinsic('gobjects');
numSteps=4;
persistent hFig;
persistent hVector;
if isempty(hFig)
hFig = figure;
hold on;
hVector=zeros(numSteps,1);
hVector=gobjects(numSteps,1);
for i=1:numSteps
hVector(i) = quiver(0,0,0,0);
end
end
set(0, 'CurrentFigure', hFig);
delete(hVector);
for i=1:numSteps
startInc=[1 1;1 1].*i;
endInc=[2 3;2 -3].*i;
hVector(i) = quiver(startInc(1,:),startInc(2,:),endInc(1,:),endInc(2,:));
end
For the handle array hVector, an initialization is necessary due to its use in the for-loop. However, for an Initialization of a graphics handle object, the function gobjects is needed and in turn the initialization as double with zeros(numSteps,1) becomes necessary, since matlab cannot correctly determine the data type of an output of an extrinsic function.
As I said, this code snippet works just fine if copied to an embedded matlab function block in simulink without anything else in the model.
My problem: Mathworks changed a lot of the plotting functions in R2014a, one of the changes being the datatype of the graphics handles which are no of type quiver for my quiver plot. Thus, the initialization with zeros(numSteps,1) initializes the wrong data type for the handle array. However leaving it out still does not work, because of the problem mentioned above. Neither does a init loop or anything similar compile without errors.
I'd greatly appreciate any help on that issue.
You can try to remove the gobject initialisation and use double() to wrap your call to any matlab graphic object. Ex:
hVector(i) = double( quiver(startInc(1,:),startInc(2,:),endInc(1,:),endInc(2,:)) ) ;
I suggest reading Loren's article about the compatibility issues which can arise when switching to HG2 versions of Matlab.
A quick quote from it which apply more to your issue:
Graphics Functions Return Objects, not Numeric Handles
Prior to R2014b, you could store a set of handles to graphics objects
in an array and then add some numeric data to that array. In R2014b,
that will cause an error.
[...]
If you find yourself really stuck, it is possible to cast object
handles to numeric handles using the double function. You can then
cast the number back to an object handle using the handle function. We
don't recommend this as a long term solution. Be aware that we may
choose to remove this feature in a future version of MATLAB. If we do,
we'll let you know in advance.
Now if you really have to use this solution, note that both functions works on single elements but also on arrays. So
hVector_HG = handle( hVector_Num ) ; %// works if "hVector_Num" is an array of numeric handles
%// and ...
hVector_Num = double( hVector_HG ) ; %// works if "hVector_HG" is an array of HG2 graphic handles
That may simplify the round trips between a format or another if they often become necessary.
Edit:
I put this at the bottom of the post for the moment because the beginning is already accepted answer but please try the following and let me know if it works. It may solve your problem in a better (more future-proof) way.
Another way to initialise an array of handle of a given graphic object is to create one (empty is good enough) and replicate it. For example:
hqNaN = quiver(NaN,NaN) ; %// create an empty quiver
hVector = repmat( hqNaN , numSteps , 1 ) ; %// replicate it in an array
will give you an array hVector containing numSteps HG2 graphic object handles. At this point they all point to the very same object but it is perfectly legal to overwrite each element with a handle of the same type. So a later :
hVector(i) = quiver( ... , etc ... ) ; %// overwrite handle "i" with a new quiver plot handle
will (should) work without problem.
A few things to take care with this approach:
where will the empty quiver be created ?
you may already have a "current" figure and you don't want it to be messed up. If not a new empty plot will be created. So to make sure the empty quiver do not cause problem (just a flicker on the screen), you could wrap it this way:
figure ; hqNaN = quiver(NaN,NaN) ; close(gcf) ;
or you can also park it in a figure (it will be invisible anyway) in case you need to re-use a handle of this type for other array initialisation. Just don't forget that once you close the figure it is on, or you delete the graphic object, the hqNaN variable is still there but it is not the same type of handle any more (so not useful to replicate if you want this type exactly).
What if you do not overwrite all you initial handle array ?
Remember all the initial handles of the array point to the same graphic object. So in case your array contains 12 elements but let's say by mistake you only overwrite 10 of them, then 2 elements will be handles pointing to the same object (which you may already have deleted)). This means that calling:
delete(hVector)
will throw you the annoying:
Error using handle.handle/delete. Invalid or deleted object.
gna gna gna ... luckily you can easily prepare for that by programming defensively and using instead:
delete( hVector(ishandle(hVector)) )
Matlab will do the check automatically and only delete the right handles.

Pass data between gui's matlab

I have two gui's one is main gui and other is sub gui. In opening function of main gui i used open('subgui.fig'); to open sub gui. Main consists of 5 edit box and one pushbutton. After pressing pushbutton the data in those 5 edit boxes should be passed to sub gui and main gui should close. Please any one help me to do this.
Let us take a simple case of one editbox and one pusbutton in main GUI and one editbox in sub GUI that will get value from the editbox in main GUI. One can easily extend this to as many editboxes as needed. The basic medium of data storage and retrieval would be a global structure data1.
For the sake of understanding the codes, let us take the following assumptions -
Main GUI is named as main_gui.m and thus has an associated
main_gui.fig from GUIDE. Main GUI's figure has the tag main_gui_figure.
Sub GUI is named as sub_gui.m and thus has an associated sub_gui.fig
from GUIDE.
Edits to be made in main_gui.m
Inside editbox's callback, add this -
global data1;
%%// Field in data1 to store the string in editbox from main GUI
data1.main_gui.edit1val = get(hObject,'String');
Inside the pushbutton's callback, add this right before it's return -
global data1;
sub_gui;
delete(handles.main_gui_figure);
Edits to be made in sub_gui.m
Inside sub_gui_OpeningFcn, add this -
global data1;
set(handles.edit1,'String',data1.main_gui.edit1val);%%// Tag of editbox in sub-gui is edit1
Hope this works out for you! Let us know!
There are probably more than one ways to achieve this. But one of the approaches is to define a function that takes two input arguments: 1) handles to the destination figure and 2) whatever data from the source figure.
The following psuedo code doesn't necessarily run in MATLAB, but it gives the basic idea:
function takeAction(uihdls, data)
set(0, 'CurrentFigure', uihdls.fig); % uihdls.fig is the handle of the destination figure.
set(gcf, 'CurrentAxes', uihdls.aexs1); % axes1 is inside fig
plot(data.x, data.y); % Do some plotting
set(uihdls.editBox, 'String', data.string); % Modify some property of a control inside fig.
key_Callback(uihdls.fig, data.keyData); % Call a callback function of the destination figure
return
This function can be called by the source figure whenever it is ready to do so.
A bit more work - but I think it's worth it.
I usually use the MVC pattern for that. Practically it means to write a controller object that will pass the messages through to the required fields.

How to store results from a callback function?

I have created a MATLAB gui in order to run a certain simulation.
In this gui is one button to start the simulation. This button callback function will then excecute the calculations. This will off course result in a dataset with the results.
Furthermore in the interface is a plot area, and a selectbox to switch between different graphs, in order to show different aspects of the simulation results. Therefore the results must be available for other functions in the gui as well. This is a problem, since the callback function has no output
Two solutions I can think of are storing the dataset in a MAT-file, or using global variables. The first solution seems not really correct to me, and furthermore I learned that global variabeles must be avoided if possible. So what is the best solution here?
you could create a user defined class inheriting from the handle class that defines your callbacks, your callbacks then execute from "inside" the handle class instance
classdef mySimulation < handle
properties
hFigure
mySimResults
end
methods
function this = mySimulation(varargin)
hFigure = figure;
...
<build figure components>
...
end
function myButtonCallback(this, src, evnt)
this.mySimResults = runMySimulation;
...
<update plot etc>
end
function mySelectBoxCallback(this, src, evnt)
...
<update plots>
end
end
end
MATLAB offers certain functions for this. There is the function guidata, which can store one variable. This can for instance be used to pass around your gui handles. Furthermore there are the functions setappdata and getappdata. These functions are the way to transfer data between functions, and couple variables to a figure handle.
More information on the different methods can be read here.
This is supposed to be semantically more correct then using global variables. However, I am still curious why. Any comments?