2
$\begingroup$

I am working on scientific visualizations involving huge arrays of 3d vectors, sometimes 100k or sometimes even millions of vectors. I quickly ran into performance related issues, mostly when needing to iterate over arrays of vectors, or even values, using Loop Inputs. Case in point, the attached blend file, that "spiralizes" a linear segment. I generate an 1D array of numpy values between a and b using:

interpolated_values = np.linspace(value_a,value_b,number_of_elements)

and I invoke that in a 3d vector combine node in x and rotate every vector in the array around it's Z-axis using a multiplied value of it's own index. In order to do that I have to iterate over the array using a Loop Input node. So far so good, it works, but the performance is a killer. Already by 1k iterations the scene lags like crazy on a quite powerful machine. Comparatively, if I do exactly the same in XSI's ICE, I can generate over 100k vectors before the scene starts lagging. Is there a better way to achieve this than using Loop Input, which is the culprit here? Using a for loop in Python doesn't work of course, as the for loop is first executed in the script and then called in AN... Here is the attached blend file https://we.tl/t-L8snsm1VOE

$\endgroup$
4
  • $\begingroup$ I am not sure how familiar you are with AN and autoexecution? Do you know what autoexecution does? If not, you should think about using triggers...docs.animation-nodes.com/documentation/introduction/execution $\endgroup$
    – Chris
    May 5 at 2:41
  • $\begingroup$ Thank you for your answer Chris, but that doesn't really solve the lag, it just delays it until the code gets executed. I mean, it doesn't bring anything to improve the performance, if I have to wait 20 minutes for the code to iterate over a 100k by any change of value or some kind of other trigger. $\endgroup$
    – radoo
    May 5 at 8:10
  • $\begingroup$ well...this wan't an answer - it was a comment ;) $\endgroup$
    – Chris
    May 5 at 8:16
  • $\begingroup$ thank you for your comment :) $\endgroup$
    – radoo
    May 5 at 8:19
1
$\begingroup$

I think it is executing the script node every iteration so I added a float list parameter to the loop and put your script node outside of the loop. On my machine instead of about 350ms execution time I got about 50ms execution time with it outside. about 7 times improvement. enter image description here

$\endgroup$
5
  • $\begingroup$ Something like this I had in my mind - but radoo „knew“ better ;) well done! $\endgroup$
    – Chris
    May 6 at 2:33
  • $\begingroup$ Hi Richard, thank you! That's awesome! $\endgroup$
    – radoo
    May 6 at 13:27
  • $\begingroup$ Jesus, Chris, :D How is your comment about autoexec and triggers having anything to do with Richard's solution? $\endgroup$
    – radoo
    May 6 at 13:30
  • $\begingroup$ Hi radoo, would you be able to mark the question as answered, please? Also there is a you tube channel called "Thinking Penguin" who does stuff on animation nodes. He has a video called "Speed Up Performance in Animation Nodes by Caching" which I think you will find useful for your sort projects with large arrays. $\endgroup$ May 6 at 18:04
  • $\begingroup$ Hi Richard, I know that YT channel, as well as the caching mechanism. Right now I am trying to speed things up with Numba + Cuda for large arrays. Another idea would be to maybe port most of the code externally and let it run in a parallel instance + IO on a Ramdisk idk yet $\endgroup$
    – radoo
    May 6 at 18:24
1
$\begingroup$

Animation nodes have fromNumpyArray() function which can be used to convert numpy arrays without much overhead. For example a 1d array can be converted to float list by DoubleList.fromNumpyArray(myArray.astype('float64')).

Here you can see conversion speed for 1million numbers: enter image description here

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.