Hi Ross,

The easiest way I can think of to do this would be to create a ParaView
Python script to loop over the windows/chunks that you want. What I would
do is use the trace capability to load the files in your first chunk that
you want and create your full pipeline. Then save that state and edit it to
loop over the set chunks that you want with the given files corresponding
to that chunk. Note that I'm assuming here that the data time steps fall
nicely into your time chunks. If your data sets have multiple time steps in
a single file (e.g. time series ExodusII files) then you can use the
Extract Time Steps filter to get what time steps you want from your reader.

Cheers,
Andy

On Wed, Jun 28, 2017 at 7:56 AM, Ross Gardiner <
ross.gardi...@ultrahaptics.com> wrote:

> Hi all,
>
> I have a time series of scalar fields (imageData) and want to use ParaView
> to compute a moving average of the values in the field with respect to time.
>
> For example (just looking at a single point in the field for this example):
>
> Time -------------->
>
> 0    2    4    6    2
>
> |---------|
>      2
>      |---------|
>           4
>           |---------|
>                4
>
> In my research so far, I’ve found the Temporal Statistics filter, but this
> doesn’t appear to support ‘chunking’ the time series or using a sliding
> window.
>
> Is there any way to do something like this in ParaView? Would I have to
> write a custom filter? If so, where should I start?
>
> I’m trying to do this as part of a numerical approximation to an integral
> dt.
>
> Thanks,
>
> Ross
>
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