From aa53639d0a782a43b3cf10ba1e13cdaaf403e1d8 Mon Sep 17 00:00:00 2001
From: Colm Talbot <colm.talbot@ligo.org>
Date: Fri, 21 Oct 2022 11:30:06 -0700
Subject: [PATCH] make implementation a bit more generic
---
bilby/gw/conversion.py | 14 +------
bilby/gw/detector/interferometer.py | 63 +++++------------------------
2 files changed, 13 insertions(+), 64 deletions(-)
diff --git a/bilby/gw/conversion.py b/bilby/gw/conversion.py
index 92abe19da..6c3cfacf9 100644
--- a/bilby/gw/conversion.py
+++ b/bilby/gw/conversion.py
@@ -1394,22 +1394,12 @@ def compute_snrs(sample, likelihood, npool=1):
"""
if likelihood is not None:
- if likelihood.__class__.__name__ == "RelativeBinningGravitationalWaveTransient":
- logger.info("Relative Binning Likelihood; Calculating SNRs from Summary Data")
-
if isinstance(sample, dict):
- if likelihood.__class__.__name__ == "RelativeBinningGravitationalWaveTransient":
- waveform_ratio = likelihood.compute_waveform_ratio(sample)
- else:
- signal_polarizations = likelihood.waveform_generator.frequency_domain_strain(sample)
+ signal_polarizations = likelihood.waveform_generator.frequency_domain_strain(sample)
likelihood.parameters.update(sample)
for ifo in likelihood.interferometers:
- if likelihood.__class__.__name__ == "RelativeBinningGravitationalWaveTransient":
- per_detector_snr = likelihood.calculate_snrs_relative_binning(waveform_ratio[ifo.name], ifo)
- else:
- per_detector_snr = likelihood.calculate_snrs(
- signal_polarizations, ifo)
+ per_detector_snr = likelihood.calculate_snrs(signal_polarizations, ifo)
sample['{}_matched_filter_snr'.format(ifo.name)] =\
per_detector_snr.complex_matched_filter_snr
sample['{}_optimal_snr'.format(ifo.name)] = \
diff --git a/bilby/gw/detector/interferometer.py b/bilby/gw/detector/interferometer.py
index 10e965e35..93457aa32 100644
--- a/bilby/gw/detector/interferometer.py
+++ b/bilby/gw/detector/interferometer.py
@@ -279,7 +279,7 @@ class Interferometer(object):
polarization_tensor = get_polarization_tensor(ra, dec, time, psi, mode)
return three_by_three_matrix_contraction(self.geometry.detector_tensor, polarization_tensor)
- def get_detector_response(self, waveform_polarizations, parameters):
+ def get_detector_response(self, waveform_polarizations, parameters, frequencies=None):
""" Get the detector response for a particular waveform
Parameters
@@ -293,6 +293,12 @@ class Interferometer(object):
=======
array_like: A 3x3 array representation of the detector response (signal observed in the interferometer)
"""
+ if frequencies is None:
+ frequencies = self.frequency_array[self.frequency_mask]
+ mask = self.frequency_mask
+ else:
+ mask = np.ones(len(frequencies), dtype=bool)
+
signal = {}
for mode in waveform_polarizations.keys():
det_response = self.antenna_response(
@@ -314,58 +320,11 @@ class Interferometer(object):
dt_geocent = parameters['geocent_time'] - self.strain_data.start_time
dt = dt_geocent + time_shift
- signal_ifo[self.strain_data.frequency_mask] = signal_ifo[self.strain_data.frequency_mask] * np.exp(
- -1j * 2 * np.pi * dt * self.strain_data.frequency_array[self.strain_data.frequency_mask])
-
- signal_ifo[self.strain_data.frequency_mask] *= self.calibration_model.get_calibration_factor(
- self.strain_data.frequency_array[self.strain_data.frequency_mask],
- prefix='recalib_{}_'.format(self.name), **parameters)
-
- return signal_ifo
-
- def get_detector_response_relative_binning(self, waveform_polarizations,
- parameters, bin_frequencies):
- """Get the detector response for a particular waveform, where the frequencies
- of the waveform polarizations are only the binning frequencies and we
- assume that there is no frequency mask necessary for the data. Kind of
- a hacky workaround. Should do something better probably.
-
- Parameters
- -------
- waveform_polarizations: dict
- polarizations of the waveform
- parameters: dict
- parameters describing position and time of arrival of the signal
-
- Returns
- -------
- array_like: A 3x3 array representation of the detector response (signal observed in the interferometer)
- """
- signal = {}
- for mode in waveform_polarizations.keys():
- det_response = self.antenna_response(
- parameters['ra'],
- parameters['dec'],
- parameters['geocent_time'],
- parameters['psi'], mode)
-
- signal[mode] = waveform_polarizations[mode] * det_response
- signal_ifo = sum(signal.values())
-
- time_shift = self.time_delay_from_geocenter(
- parameters['ra'], parameters['dec'], parameters['geocent_time'])
-
- # Be careful to first subtract the two GPS times which are ~1e9 sec.
- # And then add the time_shift which varies at ~1e-5 sec
- dt_geocent = parameters['geocent_time'] - self.strain_data.start_time
- dt = dt_geocent + time_shift
-
- signal_ifo = signal_ifo * \
- np.exp(-1j * 2 * np.pi * dt * bin_frequencies)
+ signal_ifo[mask] = signal_ifo[mask] * np.exp(-1j * 2 * np.pi * dt * frequencies)
- signal_ifo *= self.calibration_model.get_calibration_factor(
- bin_frequencies, prefix='recalib_{}_'.format(self.name),
- **parameters)
+ signal_ifo[mask] *= self.calibration_model.get_calibration_factor(
+ frequencies, prefix='recalib_{}_'.format(self.name), **parameters
+ )
return signal_ifo
--
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