No, but I'm not sure that would be more accurate in any sense.

The cell values I usually see represent some field values integrated over
the volume of the cell.  In this case, the smaller the cell volume, the
more representative the integrated value is likely to be for any point in
the cell.  Thus, if I was to introduce weighting, I would use the inverse
of the cell volume.

I'm sure you can quickly come up with a counterexample why scaling by the
cell volume is the right thing to do.  And that's kind of the point.  The
conversion from cell data to point data is ambiguously defined and the
best solution depends on your data semantics and problem domain.  Although
simple averaging is not always ideal, it is fast and can be used as a low
order approximation as well as anything else.

-Ken

On 10/18/11 8:45 AM, "Stephen Wornom" <[email protected]> wrote:

>Moreland, Kenneth wrote:
>> None of those.  The cell data to point data filter just finds all cells
>> neighboring each point and averages the cell values of those neighbors.
>Wow, not even a volume averaging? node value = sum (cell values * cell
>volume)/total volume
>Stephen
>>
>>
>> -Ken
>>
>> On 10/18/11 8:26 AM, "Stephen Wornom"<[email protected]>  wrote:
>>
>>> How does PV go from cell data to point data? Linear interpolation? or
>>> 2nd-order interpolation? on higher order than 2nd-order.
>>> Thanks in advance,
>>> Stephen
>>>
>>> -- 
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>>> 2004 route des lucioles - BP93
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>
>
>-- 
>[email protected]
>2004 route des lucioles - BP93
>Sophia Antipolis
>06902 CEDEX
>        
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