SMALLbox

h1. 2012HackSessionNotes

h2. SMALLbox Add-ons

h3. Installing an add on 

This section refers to the incoherentdl algorithm code tagged as ver_1.1 in the project’s Mercurial repository. To download this version please go to the project’s homepage in http://code.soundsoftware.ac.uk/projects/incoherentdl.

The incoherent dictionary learning add-on includes algorithms for learning dictionaries that are both adapted to the training data and that exhibit a low mutual coherence (defined as the maximum absolute inner product between any two different atoms) [27]. It extends

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SMALLbox v2.0 User Documentation 27

the functionalities of the SMALL_two_step_DL toolbox which is included in the SMALLBox distribution, and is an example showing the capabilities of SMALLbox add–ons.

These are the steps needed to interface SMALLbox add-ons to the core SMALLbox dis- tribution:

* Download the add-on distribution from: http://code.soundsoftware.ac.uk/projects/incoherentdl/files

** The version you wish to download is *version 1.1*

* Place the add-on code in any convenient location of your file system, and add this to your MATLAB path

** addpath(genpath('/Users/luisf/incoherentdl-v1_1'))

* Modify the relevant files in the folder {SMALLBox Root}/config/

** modify/create SMBOX/config/SMALL_learn_config_local.m

*** cp SMBOX/config/SMALL_learn_local.m SMBOX/config/SMALL_learn_config_local.m

**** the local file is not tracked

**** if you need to revert to the 'default' SMALLbox setting, you just need to delete/rename your local file

*** add the following code to the local config file: 

<pre>

elseif strcmpi(DL.toolbox , 'SMALL_incoherentDL')

  DL=SMALL_incoherentDL ( Problem , DL ) ;

   % we need to make sure that columns are normalised to % unit lenght .

  for i = 1: size(DL.D,2)

    DL.D(: ,i)=DL.D(: ,i)/norm(DL.D(: ,i));

  end

  D = DL.D;

</pre>

* Run the SMALLboxInit.m script to set environmental variables.

* Run any function or script contained in the add-on.

** example: 

*** load test_mocod.mat (incoherentdl-v1_1/results/test_mocod.mat)

*** open SMALL_test_mocod.m

*** run the code from the block that starts on line 110 (with the comment Plot Results)

**** this will display two coherence/signal to noise ratio plots based on results previously computed

h3. Creating a new add on