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    <p>I like to use objects. You don't need to call clear classes on every change. It is enough to delete all instances of the "old" object. </p> <p>Two very powerful additions I inherit often are handle and dynamicprops. </p> <ol> <li>Handle makes the object behave as handle. Very nice to come around matlabs copy-on-change behavior. </li> <li>Dynamic props - to do some meta programming. </li> </ol> <p>About the consistency checks - why no do them when you use set.property?</p> <hr> <p>Edit 1:</p> <p>a simplified class that uses the database:</p> <pre><code>classdef measurement class id properties (SetAccess = private) end methods function obj = measurement(varargin) obj.id = varargin{1}; end function cs = get.class(obj) if isempty(obj.id) cs = ''; return end mc = mydb.local; % use some tricks here to keep the connection open tmp = mym(mc,... 'SELECT class FROM measurements WHERE id = {Si}'... ,obj.id); cs = tmp{1}; end end </code></pre> <hr> <p>Edit 2: Example for Event - Observer</p> <pre><code>classdef ObservableClass &lt; handle properties ListObservers=[] data end methods function obj = ObservableClass(varargin) obj.data = rand(100,2); end function addObserver(obj,observer) obj.ListObservers = [obj.ListObservers,observer]; end function fireUpdate(obj) for i=1:numel(obj.ListObservers) obj.ListObservers(i).update(); end end function set.data(obj,newData) obj.data = newData; obj.fireUpdate; end end end </code></pre> <p>and a listener:</p> <pre><code> classdef ObservingPlot properties fig observedClass end methods function obj = ObservingPlot(varargin) obj.observedClass = varargin{1}; obj.createPlot; obj.observedClass.addObserver(obj); end function createPlot(obj) obj.fig=figure; plot(obj.observedClass.data); end function update(obj) gcf(obj.fig) clf plot(obj.observedClass.data); end end end </code></pre> <p>The example:</p> <pre><code>a = ObservableClass() b = ObservingPlot(a) </code></pre> <p>you can then observe when you do a: <code>a.data=rand(100,3)</code> - the plot will change immediatly.</p> <hr> <p>Edit 3: a simple saving class</p> <pre><code>classdef SavingClass &lt; handle properties saveName data end methods function set.data(obj,input) if isempty(obj.saveName) obj.saveName = [tempname '.mat']; end save(obj.saveName,'input') end function out = get.data(obj) out = []; if exist(obj.saveName,'file') tmp = load(obj.saveName); out = tmp.input; end end end end </code></pre> <p>Example:</p> <pre><code>a = SavingClass; b=rand(1000,1000); a.data = b; </code></pre> <p>look at `whos':</p> <pre><code>Name Size Bytes Class Attributes a 1x1 60 SavingClass ans 1x5 10 char b 1000x1000 8000000 double </code></pre> <p>although you can do calculations like <code>d = a.data-b</code> - <code>a</code> takes just 60 bytes in memory - as opposed to the ~8 MB of <code>b</code>.</p> <hr> <p>Edit 4: trick for often changing functions. When you put the logic in external commands matlab will not complain when you change the function definition there.</p> <pre><code>classdef MyOftenEditedClass &lt; handle properties a end methods function set.a(obj,val) mySetFunctionA(obj,val) end function out=get.a(obj) out = myGetFunctionA(obj); end end end </code></pre>
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    1. POis it possible to do 'stateless' programming in matlab / how to avoid checking data integrity?
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    1. COdo your objects reside in the base workspace? Since my objects are handled by a generic GUI, I need to keep them with the GUI (otherwise I need to always use `evalin` & `assignin`)
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    2. COhow big (memory wise) are your objects? mine grow up to 3GB, and re-instantiating them is therefore very annoying ...
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    3. COThe case with GUI I use the handle class - using this I can manipulate the objects in base workspace and in the figure the changes will be available. Together with listener-observer pattern very nice.
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