MAINT: Separate adding SNRs per IFO to a sample into a new function

Moves code snippet which adds IFO snrs to a sample into a separate function within the Likelihood. Thus different likelihoods may define this differently if they have different SNRs which must be computed.

bilby/gw/likelihood/base.py

@@ -13,6 +13,10 @@ from ..detector import InterferometerList, get_empty_interferometer, calibration
 from ..prior import BBHPriorDict, Cosmological
 from ..utils import noise_weighted_inner_product, zenith_azimuth_to_ra_dec, ln_i0
 
+from typing import TYPE_CHECKING, Any
+
+if TYPE_CHECKING:
+    from bilby.gw.detector.interferometer import Interferometer
 
 class GravitationalWaveTransient(Likelihood):
     """ A gravitational-wave transient likelihood object
@@ -1129,3 +1133,28 @@ class GravitationalWaveTransient(Likelihood):
             reference_frame=self._reference_frame_str,
             lal_version=self.lal_version,
             lalsimulation_version=self.lalsimulation_version)
+
+    def add_interferometer_snrs_to_sample(ifo : Interferometer, ifo_index : int, new_samples : list, sample : Any) -> None:
+        """For use in gw.conversion.compute_snrs(). Attaches method to likelihood so alternate likelihoods may implement their own method.
+        
+        Parameters
+        ==========
+        ifo : bilby.gw.interferometer.Interferometer
+            The interferometer object for which to compute SNRs
+        ifo_index : int
+            The index of the IFO within likelihood.interferometers, for indexing of new_samples
+        new_samples : list
+            The output of _compute_snrs which contains SNRs
+        sample : Any
+            The sample from the posterior for which SNRs are being computed
+        """
+        matched_filter_snrs = list()
+        optimal_snrs = list()
+        mf_key = '{}_matched_filter_snr'.format(ifo.name)
+        optimal_key = '{}_optimal_snr'.format(ifo.name)
+        for new_sample in new_samples:
+            matched_filter_snrs.append(new_sample[ifo_index].complex_matched_filter_snr)
+            optimal_snrs.append(new_sample[ifo_index].optimal_snr_squared.real ** 0.5)
+
+        sample[mf_key] = matched_filter_snrs
+        sample[optimal_key] = optimal_snrs
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