[Insight-developers] Re: Statistics Refactoring : Engineering:SandBox - NAMIC Wiki

[Karthik Krishnan]

Raghu Venkatram wrote:

> Hi Karthik,
>
> Yes I noticed that with the new DistanceMetric. But right now, we are 
> planning
> to check in the BackPropagation related code during the first week of 
> August.
> When do you plan to incorporate the sandbox enhancements into the 
> Statistics
> package?

I don't know. That would be a question for the Tzars of the Insight 
Consortium.

I don't see why it can't introduce it right away. It doesn't break any 
API as is evident from the fact that I didn't have to change a single 
test or Example to have them running.

I will update the wiki as I make changes.
Maybe this will be brought up this coming Tcon.

>
>
> Thanks
> Warm regards
> Raghu
>
>
> Quoting Karthik Krishnan <Karthik.Krishnan at kitware.com>
>
>> Hello Raghu,
>>
>> Are you using an SVN checkout of the Statistics classes from
>> NAMICSandBox/RefactoringITKStatisticsClasses/
>>
>> You should be able to use the Distance metrics etc absolutely fine 
>> with itk::Array (or for that matter any other container in 
>> itkMeasuremetVectorTraits.h)
>>
>> I still have some API issues to resolve with the Histogram classes, 
>> but most of it is ironed out. Templating your code over the 
>> measurement vector is fine. However make sure you use 
>> MeasurementVectorTraits to work with the measurement vector.
>> For an example, take a look at the GaussianDensityFunction and the 
>> DensityFunction in the NAMIC repository
>>
>> You will find a detailed description on the wiki.
>>
>> http://www.itk.org/Wiki/Proposals:Statistics_Framework_Runtime_Vector_Size 
>>
>>
>>
>> The current SVN checkout builds fine with ITK and the tests pass. 
>> There may still be bugs.
>>
>> Thanks
>> Regards
>> Karthik
>>
>> Raghu Venkatram wrote:
>>
>>> Hi Everybody,
>>>
>>> With regard to DistanceMetric:
>>>
>>> The NeuralNetwork TransferFunctionBase class derives from 
>>> FunctionBase and
>>> templated over Input/Output ScalarType.
>>> The GaussianRadialBasisFunction derives from TransferFunctionBase, 
>>> trying to
>>> use the EulideanDistance in here is not possible as DistanceMetric is
>>> templated over FixedArray.
>>> At this point, I have moved things around, so that the 
>>> EuclideanDistance is
>>> applied in the RBFLayer, LayerBase is templated over the input and 
>>> output
>>> MeasurementVectorTypes, which s itk::Vector. It might just be that 
>>> my initial
>>> design was flawed :).
>>> Each layer has a transferfunction plugged in.
>>>
>>> Looking at  the new Statistics classes, if anything I would have to 
>>> change
>>> things around to take advantage of the new features, but I dont 
>>> think it will
>>> break the existing NeuralNetwork classes.
>>>
>>> Warm regards,
>>> Raghu
>>>
>>>
>>> Quoting "Stephen R. Aylward" <aylward at unc.edu>:
>>>
>>>> Everyone...meet Raghu.   Raghu...meet everyone. :)
>>>>
>>>> Raghu has also run into difficulty using the statistics framework 
>>>> to have measurement vectors whos lengths (lenghts) are set at 
>>>> run-time. This is needed for the neural networks library that he is 
>>>> adding to ITK.
>>>>
>>>> Raghu, Luis and Karthik and Jim have created a version of the 
>>>> statistics library that removes the requirement that the 
>>>> measurement vector length be set at compile time (e.g., that length 
>>>> in itkSample is now stored as an ivar instead of as a value 
>>>> determined from the measurement vector template argument).
>>>>
>>>> Raghu - maybe you can checkout their version of the library (as 
>>>> detailed below) and see if it is compatible with your solution.  Or 
>>>> perhaps you can offer an alternative solution.   Also, I tried to 
>>>> explain the difficulties you were having with the distance 
>>>> functions, but I didn't explain it very well.  Perhaps you can 
>>>> clarify to the group.
>>>>
>>>> Thanks!
>>>> Stephen
>>>>
>>>> Luis Ibanez wrote:
>>>>
>>>>>
>>>>> Hi Stephen,
>>>>>
>>>>> Following on the discusion of the tcon on refactoring the
>>>>> ITK Statistics Framework, here is the link to the NAMIC
>>>>> Sandbox where Karthik has been reworking the Statistics
>>>>> library:
>>>>>
>>>>> <http://www.na-mic.org/Wiki/index.php/Engineering:SandBox>
>>>>>
>>>>>
>>>>> Subversion allows direct HTML access to the repository too:
>>>>>
>>>>>      http://www.na-mic.org:8000/svn/NAMICSandBox/
>>>>>
>>>>>
>>>>> The directory of interest is:
>>>>>
>>>>> http://www.na-mic.org:8000/svn/NAMICSandBox/RefactoringITKStatisticsClasses/ 
>>>>> Clients for Subversion (CVS) are available in standard
>>>>> Linux distrbutions and Cygwin.  Windows versions can be
>>>>> found at:
>>>>>
>>>>>
>>>>>         http://subversion.tigris.org/
>>>>>
>>>>>
>>>>> -- 
>>>>>
>>>>>
>>>>>
>>>>>    Luis
>>>>>
>>>>>
>>>>>
>>>>
>>>>
>>>
>>>
>>>
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>
>
>