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I'm working on a machine learning application and have to do transformation on large scale of data. I want to call the function like pywt.cwt((batch_size, signal_length)), but it seems only dim=1 supported. Is there any plan for supporting this feature?
The text was updated successfully, but these errors were encountered:
An implementation of this has been proposed in #509.
Any feedback there would be welcome. In the case of data with shape (batch_size, signal_length), you could leave the default axis=-1 argument since the signal is along the last axis of the input. The output would have shape (len(scales), batch_size, signal_length).
Also, another recent PR allows setting mode='fft' to do FFT-based convolutions for the CWT. This should have a performance benefit for larger data / scales.
I'm working on a machine learning application and have to do transformation on large scale of data. I want to call the function like
pywt.cwt((batch_size, signal_length))
, but it seems onlydim=1
supported. Is there any plan for supporting this feature?The text was updated successfully, but these errors were encountered: