florisvb
commented
2 years ago This is with the total_variation_regularization.iterative_velocity method? Does the kernel crash with a smaller number of time points? 52,000 is a lot of data. If it works with smaller datasets you can run several smaller timeseries through and then blend. See jerk_sliding for an example on how to implement the blending.
On Tue, May 3, 2022 at 2:33 AM Sameer Kesava @.***> wrote:
Hello,
I am trying to use different methods to smoothen time series data (about ~52000 time points). When using options cg_maxiter: 1 or None with 'scale': large, the kernel crashes. Tried multiple times but same issue occurs. Other parameters are iterations = 1 and gamma = 0.001, whilst dt = 1.
When I don't specify the options argument, it runs fine but I believe here it uses 'scale: small'. Wanted to test when scale = large.
Thank you
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sameervk
Hello,
I am trying to use different methods to smoothen time series data (about ~52000 time points). When using options cg_maxiter: 1 or None with 'scale': large, the kernel crashes. Tried multiple times but same issue occurs. Other parameters are iterations = 1 and gamma = 0.001, whilst dt = 1.
When I don't specify the options argument, it runs fine but I believe here it uses 'scale: small'. Wanted to test when scale = large.
Thank you