<div dir="ltr">Hi Ross,<div><br></div><div>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.</div><div><br></div><div>Cheers,</div><div>Andy</div></div><div class="gmail_extra"><br><div class="gmail_quote">On Wed, Jun 28, 2017 at 7:56 AM, Ross Gardiner <span dir="ltr"><<a href="mailto:ross.gardiner@ultrahaptics.com" target="_blank">ross.gardiner@ultrahaptics.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Hi all,<br>
<br>
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.<br>
<br>
For example (just looking at a single point in the field for this example):<br>
<br>
Time --------------><br>
<br>
0 2 4 6 2<br>
<br>
|---------|<br>
2<br>
|---------|<br>
4<br>
|---------|<br>
4<br>
<br>
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.<br>
<br>
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?<br>
<br>
I’m trying to do this as part of a numerical approximation to an integral dt.<br>
<br>
Thanks,<br>
<br>
Ross<br>
<br>
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