In a directly related problem, I am able to compute the wavelet likelihood given the model_prediction and data in
np.array format, to later subtract as the residuals.
The function call is
dwt_chisq(model_prediction, data, [gamma, sigma_r, sigma_w])
To run this with
PyMC it places
model_prediction as a tensor (i.e.
sigma_w are each of type
In order to run the
dwt_chisq as is, I would need to output a numpy array from each of those tensors. What is the appropriate method to do so?
.eval(); but that had very little useful outputs. Please let me know if I'm off base, such as "it's not possible to output a
np.array type" or "that's now how you use