From ee03b0d5a712bbbd417c9803d4348a5c72b67a37 Mon Sep 17 00:00:00 2001
From: Cecilio Garcia-Quiros <cecilio.garcia-quiros@ligo.org>
Date: Sun, 1 Dec 2019 18:25:42 -0600
Subject: [PATCH] Include options to call FD waveform model with a custom mode
array and to call IMRPhenomXHM with multibanding
---
bilby/gw/source.py | 70 ++++++++++++++++++++++++++++++++++++++++++++++
1 file changed, 70 insertions(+)
diff --git a/bilby/gw/source.py b/bilby/gw/source.py
index 66ace0968..811346846 100644
--- a/bilby/gw/source.py
+++ b/bilby/gw/source.py
@@ -54,6 +54,27 @@ def lal_binary_black_hole(
The phase at coalescence
kwargs: dict
Optional keyword arguments
+ Supported arguments:
+ waveform_approximant
+ reference_frequency
+ minimum_frequency
+ maximum_frequency
+ pn_spin_order
+ pn_tidal_order
+ pn_phase_order
+ pn_amplitude_order
+ mode_array: Activate a specific mode array and evaluate the model using those modes only.
+ e.g. waveform_arguments = dict(waveform_approximant='IMRPhenomHM', modearray=[[2,2],[2,-2])
+ returns the 22 and 2-2 modes only of IMRPhenomHM.
+ You can only specify modes that are included in that particular model.
+ e.g. waveform_arguments = dict(waveform_approximant='IMRPhenomHM', modearray=[[2,2],[2,-2],[5,5],[5,-5]])
+ is not allowed because the 55 modes are not included in this model.
+ Be aware that some models only take positive modes and return the positive and the negative mode together,
+ while others need to call both.
+ e.g. waveform_arguments = dict(waveform_approximant='IMRPhenomHM', modearray=[[2,2],[4,-4]])
+ returns the 22 and 2-2 of IMRPhenomHM.
+ However, waveform_arguments = dict(waveform_approximant='IMRPhenomXHM', modearray=[[2,2],[4,-4]])
+ returns the 22 and 4-4 of IMRPhenomXHM.
Returns
-------
@@ -110,6 +131,27 @@ def lal_binary_neutron_star(
Dimensionless tidal deformability of mass_2
kwargs: dict
Optional keyword arguments
+ Supported arguments:
+ waveform_approximant
+ reference_frequency
+ minimum_frequency
+ maximum_frequency
+ pn_spin_order
+ pn_tidal_order
+ pn_phase_order
+ pn_amplitude_order
+ mode_array: Activate a specific mode array and evaluate the model using those modes only.
+ e.g. waveform_arguments = dict(waveform_approximant='IMRPhenomHM', modearray=[[2,2],[2,-2])
+ returns the 22 and 2-2 modes only of IMRPhenomHM.
+ You can only specify modes that are included in that particular model.
+ e.g. waveform_arguments = dict(waveform_approximant='IMRPhenomHM', modearray=[[2,2],[2,-2],[5,5],[5,-5]])
+ is not allowed because the 55 modes are not included in this model.
+ Be aware that some models only take positive modes and return the positive and the negative mode together,
+ while others need to call both.
+ e.g. waveform_arguments = dict(waveform_approximant='IMRPhenomHM', modearray=[[2,2],[4,-4]])
+ returns the 22 a\nd 2-2 of IMRPhenomHM.
+ However, waveform_arguments = dict(waveform_approximant='IMRPhenomXHM', modearray=[[2,2],[4,-4]])
+ returns the 22 and 4-4 of IMRPhenomXHM.
Returns
-------
@@ -151,6 +193,27 @@ def lal_eccentric_binary_black_hole_no_spins(
The phase at coalescence
kwargs: dict
Optional keyword arguments
+ Supported arguments:
+ waveform_approximant
+ reference_frequency
+ minimum_frequency
+ maximum_frequency
+ pn_spin_order
+ pn_tidal_order
+ pn_phase_order
+ pn_amplitude_order
+ mode_array: Activate a specific mode array and evaluate the model using those modes only.
+ e.g. waveform_arguments = dict(waveform_approximant='IMRPhenomHM', modearray=[[2,2],[2,-2])
+ returns the 22 and 2-2 modes only of IMRPhenomHM.
+ You can only specify modes that are included in that particular model.
+ e.g. waveform_arguments = dict(waveform_approximant='IMRPhenomHM', modearray=[[2,2],[2,-2],[5,5],[5,-5]])
+ is not allowed because the 55 modes are not included in this model.
+ Be aware that some models only take positive modes and return the positive and the negative mode together,
+ while others need to call both.
+ e.g. waveform_arguments = dict(waveform_approximant='IMRPhenomHM', modearray=[[2,2],[4,-4]])
+ returns the 22 and 2-2 of IMRPhenomHM.
+ However, waveform_arguments = dict(waveform_approximant='IMRPhenomXHM', modearray=[[2,2],[4,-4]])
+ returns the 22 and 4-4 of IMRPhenomXHM.
Returns
-------
@@ -260,6 +323,13 @@ def _base_lal_cbc_fd_waveform(
lalsim_SimInspiralWaveformParamsInsertTidalLambda2(
waveform_dictionary, lambda_2)
+ if 'modearray' in waveform_kwargs:
+ modearray = waveform_kwargs['modearray']
+ mode_array = lalsim.SimInspiralCreateModeArray()
+ for mode in modearray:
+ lalsim.SimInspiralModeArrayActivateMode(mode_array, mode[0], mode[1])
+ lalsim.SimInspiralWaveformParamsInsertModeArray(waveform_dictionary, mode_array)
+
if lalsim.SimInspiralImplementedFDApproximants(approximant):
wf_func = lalsim_SimInspiralChooseFDWaveform
else:
--
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