set_io_data

SET_IO_DATA sets GUI parameters that change with dataset choices

Description:
Function to set the GUI parameters that change when a new dataset is
choosen.  For example, the choices of plots in the extra plot must be
updated as well the number of neurons in each layer.

Syntax:
SET_IO_DATA(Handles,ThNN,TrainingParams);

Input Parameters:
o Handles: A structure containing the handles to all the GUI objects,
    as generated in ThNN_GUI.
o LoadFile: Path and file containing the dataset information.
o DataName: String containing the name of the dataset.

Output Parameters:
o Status: A Boolean flag indicating the success of execution.

Example:
>> GUIHandle=start_ThNN;
>> Temp=get(GUIHandle,'UserData');
>> Handles=Temp{2};
>> TrainingParams=get_training_params(Handles);
>> set_io_data(Handles,[pwd, C, 'Datasets', C, 'Regression', C, TrainingParams.DataName],...
        TrainingParams.DataName);

See also theta_neuron_network

0001 function status=set_io_data(Handles,LoadFile,DataName)
0002 %SET_IO_DATA sets GUI parameters that change with dataset choices
0003 %
0004 %Description:
0005 %Function to set the GUI parameters that change when a new dataset is
0006 %choosen.  For example, the choices of plots in the extra plot must be
0007 %updated as well the number of neurons in each layer.
0008 %
0009 %Syntax:
0010 %SET_IO_DATA(Handles,ThNN,TrainingParams);
0011 %
0012 %Input Parameters:
0013 %o Handles: A structure containing the handles to all the GUI objects,
0014 %    as generated in ThNN_GUI.
0015 %o LoadFile: Path and file containing the dataset information.
0016 %o DataName: String containing the name of the dataset.
0017 %
0018 %Output Parameters:
0019 %o Status: A Boolean flag indicating the success of execution.
0020 %
0021 %Example:
0022 %>> GUIHandle=start_ThNN;
0023 %>> Temp=get(GUIHandle,'UserData');
0024 %>> Handles=Temp{2};
0025 %>> TrainingParams=get_training_params(Handles);
0026 %>> set_io_data(Handles,[pwd, C, 'Datasets', C, 'Regression', C, TrainingParams.DataName],...
0027 %        TrainingParams.DataName);
0028 %
0029 %See also theta_neuron_network
0030 
0031 %Copyright (C) 2008 Sam McKennoch <Samuel.McKennoch@loria.fr>
0032 
0033 
0034 status=1;
0035 try
0036     load(LoadFile);
0037     NumTests=0;
0038     if strcmp(EncodeMethod,'Spikes')
0039         %Assume each synapse has at least one input spikes.
0040         NumInputs=length(unique(InputSpikeTimes{1}(:,1)));
0041         NumOutputs=length(unique(DesiredSpikeTimes{1}(:,1)));        
0042         NumPatterns=length(InputSpikeTimes);  
0043         if TestFlag
0044             NumTests=length(TestingInputSpikeTimes);
0045         end
0046     else
0047         NumInputs=size(Inputs,2);
0048         NumOutputs=size(Outputs,2);        
0049         NumPatterns=size(Inputs,1);      
0050         if TestFlag
0051             NumTests=size(TestingInputs,1);
0052         end
0053     end
0054     
0055     TrainingMethods=get(Handles.Training_Method,'String');
0056     PlotNames={};
0057     PlotNames{1}='Choose From Below';
0058     set(Handles.Training_Method,'Enable','on');
0059     DataType=get(Handles.Training_Data,'UserData');
0060     if strfind(DataType,'Classification')
0061         PlotNames{2}='Classification Error';
0062     elseif strfind(DataType,'Regression')
0063         PlotNames{2}='Function Approximation';
0064     end
0065     set(Handles.AvailablePlots,'String',PlotNames);
0066     if strfind(DataType,'SpikeTimes')
0067         set(Handles.AvailablePlots,'Value',1);
0068     else
0069         set(Handles.AvailablePlots,'Value',2);
0070     end
0071     set(Handles.Input_Data,'String',DataName);
0072     set(Handles.Num_Inputs,'String',NumInputs);
0073     set(Handles.Num_Outputs,'String',NumOutputs);
0074     set(Handles.Num_Patterns,'String',NumPatterns);
0075     set(Handles.Num_Tests,'String',NumTests);
0076 catch
0077     disp('Error in set_io_data!');
0078     status=-1;
0079 end
0080 
0081 return;