get smoothed_x from differentiation

[DongweiYe]

Hi all,

I am new to the SINDy and I am trying to use the smoothing functions in SINDy to deal with the noise data for parameter inference. I am currently using Kalman filter or Spline, e.g.
sfd = ps.SINDyDerivative(kind="kalman", alpha=0.1)
d_hat = sfd._differentiate(X, t)

It offers me the derivative of state data directly. I want to also get access to the smoothed_x for other use. I do found there is a self.smoothed_x_. in sindy_derivative.py, but I have no clue how to call it properly. Could you help me out?

Thank you!
Dongwei

[Jacob-Stevens-Haas]

BaseDifferentiation.smoothed_x_ is an attribute set to the smoothed x values from the last derivative calculation. It isn't itself callable. That weird API was introduced in order to maintain backwards compatibility, but I admit it's a hack.

Hopefully we provide a better differentiation API soon

[DongweiYe]

Thanks for the reply! I see. Do you have any alternative way to get smoothed x value?