Calculate SNR and some bug fixes

• Calculate SNR from power spectrum density additionally.
• Check if resolution fit fails and add nans in those cases to avoid a crash.
• Regularize H calculation to avoid fit failure by setting numerator to zero when it is too small.
• Pay attention to deactivated channels when estimating pedestal to avoid crashing as a result of nonsensical channels.
• Added long notebooks with paper analysis for bookkeeping.

pes_to_spec/model.py

@@ -109,7 +109,9 @@ def deconv(y: np.ndarray, yhat: np.ndarray) -> Dict[str, Any]:
     sigma_s = np.real(np.sqrt(np.sum(H2*Syy)/n_bins))
     snr = sigma_s/sigma_n
 
-    return dict(h=np.fft.fftshift(np.fft.ifft(H)),
+    h = np.real(np.absolute(np.fft.fftshift(np.fft.ifft(H))))
+
+    return dict(h=h,
                 H=H,
                 H2=H2,
                 Syy=Syy,
@@ -152,8 +154,8 @@ def get_resolution(y: np.ndarray, y_hat: np.ndarray, e: np.ndarray,
         y_hat_sel = y_hat_sel*f
     results = deconv(y_sel, y_hat_sel)
     results["e_axis"] = e_axis
-    results["fit"] = fit_gaussian(e_axis, np.absolute(h))
-    results["fit_success"] = results["fit"].covar_ is not None
+    results["fit"] = fit_gaussian(e_axis, results["h"])
+    results["fit_success"] = results["fit"].covar is not None
     return results
 
 class PromptNotFoundError(Exception):