Compute d2#83
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rcjackson
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May 4, 2026
| inp_data = xr.Dataset(inp_data) | ||
| #inp_data['Data_ch' + str(chn)] = xr.DataArray( | ||
| # spectra['Data_ch' + str(chn)].values[np.newaxis, :], | ||
| # dims=['time', 'bins']) |
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If you have code commented out I would remove it from your final version. This helps the code be more readable.
| L : np.ndarray or None | ||
| Cholesky factor of Sigma, if Sigma is positive definite. | ||
| d2 : float or None | ||
| Statistical distance squared [Eq. (A.11)]. |
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Could you add a references section to this docstring showing the citation for the Moteki & Kondo paper?
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I added a single reference and description at the top of the module. If you would rather keep the reference in the docstring for each function, I can move it there.
| ) -> xr.DataArray: | ||
| """ | ||
| Compute d^2(k) for one selected event using the Moteki & Kondo statistical distance. | ||
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I would also add the same reference to MK in this docstring as well.
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rcjackson
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Just a few small changes!
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Function to compute the statistical distance ($d^2$ ) for an associated value of $\tau$ . This PR contains:
plot_normalized_derivativefunction to plot the scattering signal on the same plot as the normalized derivative for comparison purposes.