Using pyseobnr

Standard interface

pyseobnr provides an interface that closely follows the conventions used in the gwsignal waveform interface.

In this interface, one first constructs a GenerateWaveform class which serves as a container for waveform information. This class then allows one to:

• compute the time-domain waveform modes via generate_td_modes

• compute the time-domain polarizations via generate_td_polarizations

• compute the frequency-domain polarizations via generate_fd_polarizations

The input parameters to GenerateWaveform are expected to be in the so-called cosmo units. The most salient point is that masses are expected in solar masses and distance in Mpc. For details see GenerateWaveform docstring.

Tip

See also the relevant documentation in gwsignal.

Here is a simple example to get the modes:

import numpy as np
from pyseobnr.generate_waveform import GenerateWaveform

# Start with the usual parameter definitions
# Masses in solar masses
m1 = 50.0
m2 = 30.0
s1x, s1y, s1z = 0.0, 0.0, 0.5
s2x, s2y, s2z = 0.0, 0.0, 0.8

deltaT = 1.0 / 2048.0
f_min = 20.0
f_max = 1024.0

distance = 1000.0  # Mpc
inclination = np.pi / 3.0
phiRef = 0.0
approximant = "SEOBNRv5HM"

params_dict = {
    "mass1": m1,
    "mass2": m2,
    "spin1x": s1x,
    "spin1y": s1y,
    "spin1z": s1z,
    "spin2x": s2x,
    "spin2y": s2y,
    "spin2z": s2z,
    "deltaT": deltaT,
    "f22_start": f_min,
    "phi_ref": phiRef,
    "distance": distance,
    "inclination": inclination,
    "f_max": f_max,
    "approximant": approximant,
}

# We call the generator with the parameters
wfm_gen = GenerateWaveform(params_dict)
# Generate mode dictionary
times, hlm = wfm_gen.generate_td_modes()

To get the polarizations in the frequency domain:

# Generate Fourier-domain polarizations - As LAL COMPLEX16FrequencySeries

hpf, hcf = wfm_gen.generate_fd_polarizations()
freqs = hpf.deltaF*np.arange(hpf.data.length)

The notebooks below give several examples on how to use pyseobnr with different models:

PySEOBNR introduction

SEOBNRv5PHM: spin-precessing model example

SEOBNRv5EHM: aligned spin eccentric model example

EOB internal interface

Internally, pyseobnr computes the waveforms in geometric units and follows slightly different conventions (that agree with previous models in the SEOBNR family). The output is a numpy array of times and a dictionary of modes. Note that for aligned-spin, the internal EOB generator only outputs modes with \(m>0\).

>>> from pyseobnr.generate_waveform import generate_modes_opt
>>> q = 5.3
>>> chi_1 = 0.9
>>> chi_2 = 0.3
>>> omega0 = 0.0137 # This is the orbital frequency in geometric units with M=1
>>> t,modes = generate_modes_opt(q,chi_1,chi_2,omega0)
>>> modes.keys()
dict_keys(['2,2', '2,1', '3,3', '3,2', '4,4', '4,3', '5,5'])

Usage through pyCBC

Added in version 0.2.13.

It is possible to use the approximants implemented in pyseobnr from pyCBC directly thanks to the pyCBC plugin infrastructure.

Installing pyseobnr will automatically create the required pyCBC plugins, which will translate the pyCBC parameters into pyseobnr compatible ones. Note that installing pyseobnr will not install pyCBC.

pyCBC example

See also

pyCBC plugin infrastructure pycbc plugin.