MATLAB: How to compare two models in Simulink 6.6 (R2007a)

simulink

I would like to compare two models in Simulink. For example, I would like to list or highlight the blocks that exist in one of the models but not the other.

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The ability to compare two models in Simulink 6.6 (R2007a) is not available.

In Simulink 7.3 (R2009a) it is possible to compare models with the addition of the Simulink Report Generator 3.6 (R2009a). This is accomplished by using Simulink Report Generator to compare XML text files exported from Simulink models. For more information on this, please see our documentation located here:

 <http://www.mathworks.com/help/rptgenext/model-comparison.html>

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MATLAB: How to compare differences between two Simulink models

Since MATLAB R2017b, base Simulink comes with a Model Comparison feature, which will allow you to see a comparison of differences between two Simulink models. With the Comparison Tool, you can review as well as merge differences. You can use models from any version of Simulink. Use the Comparison Tool to explore the differences, view the changes highlighted in the original models, and merge differences. See the following documentation page for further information, as well as multiple examples on how to use Simulink Model Comparison:

https://www.mathworks.com/help/releases/R2017b/simulink/ug/about-simulink-model-xml-comparison.html

There are three basic ways to initiate the comparison:

Select two Simulink models at once (e.g. by holding down the CTRL key while selecting one file after another in the “Current Folder” pane of MATLAB) and right click on the selection. In the appeared menu, select “Compare Selected Files/Folders”.
Alternatively, you may select one of the Simulink models, right click and select “Compare Against” > “Choose…”, then select the second Simulink model from the file browser in the “Selecting Files or Folders for Comparison” dialog box.
Click on the “compare” button in the MATLAB tool-strip under the “File” section. In the “Selecting Files or Folders for Comparison” dialog box, use the file browser to select the two Simulink model files for comparison.

Note that for MATLAB R2017a and earlier, doing this kind of comparison requires to have "Simulink Report Generator" toolbox installed and licensed for. For more information about comparing Simulink Models using Simulink Report Generator, and navigating through the Comparison Report, please refer to the link below:

https://www.mathworks.com/help/releases/R2017a/rptgenext/ug/compare-simulink-model-xml-files.html

Unfortunately, there is no practical way to compare two Simulink models without using the Simulink Report Generator toolbox in R2017a and earlier. Without the toolbox, there is a workaround in which you may export the models first into XML files via the “save_system” function. The command to use has the following syntax:

>> save_system('model_name’, 'model_xml.xml','ExportToXML', true);

Then use any commercial software available to compare the two XML files. This is not recommended as small changes in your model could result in large changes in the XML file, and thus raw comparison could yield misleading results.

MATLAB: Matlab : how to get method ‘tonndata’ for input arguments for matlab

Your version is too old

function [x,wasMatrix,err] = tonndata(x,columnSamples,cellTime)

 %TONNDATA Convert data to standard neural network cell array form.
 %








 %  tonndata and fromnndata convert data from and to standard neural
 %  network form.
 %
 %  Standard neural network cell array data consists of a cell array which
 %  has as many rows as there are signals and as many columns as there are
 %  timesteps. Each i,jth element of the cell array is a matrix which has
 %  as many rows as the ith signal has elements and as many columns as
 %  there are samples.
 %
 %  [Y,wasMatrix] = tonndata(x,columnSamples,cellTime) takes matrix or cell
 %  array data X and converts it to standard neural network cell data Y. 
 %  
 %  If columnSamples is false, then matrix X or matrices in cell array X
 %  will be transposed, so row samples will now be stored as column vectors.
 %
 %  If cellTime is false, then matrix samples will be separated into columns
 %  of a cell array so time originally represented as vectors in a matrix
 %  will now be represented as columns of a cell array.
 %
 %  The returned value wasMatrix can be used by FROMNNDATA to reverse the
 %  transformation.
 %
 %  Here data consisting of six timesteps of 5-element vectors is originally
 %  represented as a matrix with six columns is converted to standard
 %  neural network representation and back.
 %
 %    x = rand(5,6)
 %    [y,wasMatrix] = tonndata(x,true,false)
 %    x2 = fromnndata(y,wasMatrix,columnSamples,cellTime)
 %
 %  Here data is defined in standard neural network data cell form.
 %  Converting this data does not change it.  The data consists of three
 %  time series samples of 2-element signals over 3 timesteps.
 %
 %  See also FROMNNDATA

Thank you for formally accepting my answer

P.S. You can convert data between matrix and cell formats without using this function

Greg

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MATLAB: How to compare differences between two Simulink models

MATLAB: Matlab : how to get method ‘tonndata’ for input arguments for matlab

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