Burst waveform

This package hosts the python version of the burst waveform used in coherentWaveBurst(cWB) search.

Installation

Using pip

pip install burst-waveform

from source

make install

Usage

The Burst-Waveform package provides four burst waveform models: SineGaussian, SineGaussianQ, WhiteNoiseBurst, and Ringdown.

The waveforms can be generated by calling the instance of the waveform model after initializing it with the desired parameters.

For example, to generate a SineGaussianQ waveform,

from burst_waveform.models import SineGaussianQ
from matplotlib import pyplot as plt

params = {
    "amplitude": 1.0,
    "frequency": 300.0,
    "Q": 9
}

model = SineGaussianQ(params)
strain = model()

plt.plot(strain)
plt.show()

For WhiteNoiseBurst waveform,

from burst_waveform.models import WhiteNoiseBurst
import matplotlib.pyplot as plt

params = {
    'frequency': 300,
    'bandwidth': 50,
    'duration': 0.005,
    'inj_length': 1,
    'mode': 1
}

WNB = WhiteNoiseBurst(params)
wnb_strain = WNB()

plt.plot(wnb_strain)
plt.xlim(0.5 - 10 * params['duration'], 0.5 + 10 * params['duration'])
plt.show()

For Ringdown waveform,

import numpy as np
from burst_waveform.models import Ringdown
from matplotlib import pyplot as plt

params = {
    "tau": 0.3,
    "frequency": 10.0,
    "iota": np.pi / 2,  # inclination angle in radians (90 deg)
}

model = Ringdown(params)
hp, hc = model()

plt.plot(hp)
plt.plot(hc)
plt.show()

cWB analytic burst conventions

burst_waveform.interface.generate_waveform_pycwb.get_td_waveform owns the cWB-compatible SG, SGE, GA, and WNB implementations. PycWB no longer provides a separate burst_population generator. The public interface returns GWpy hp and hc series and accepts delta_t or sample_rate (16384 Hz by default); supplying inconsistent values raises an error. The default buffer is one second centered at epoch -0.5, configurable with inj_length.

• SGE uses sine for hp, cosine for hc, and cWB's positive-half component normalization. Source hrss is applied before inclination factors (1 + cos(iota)**2)/2 and cos(iota). iota is in radians; ellipticity remains an alias. This corrects the previous swapped phases and post-inclination normalization. SG has only the sine polarization.
• WNB has two independent, equally normalized polarizations, without inclination weighting (cWB MDC_WNB). frequency is the lower band edge; duration is the Gaussian amplitude standard deviation, correcting the former envelope's missing factor of 1/2. mode=0 (the cWB default) selects a noise band; mode=1 constructs the symmetric heterodyned band, including the corrected conjugation and cWB packed-FFT DC/Nyquist handling. To migrate the removed PycWB generator's WNBs, specify mode=1 explicitly.
• GA uses cWB's exp(-(t/duration)**2) convention and has zero cross component.
• The interface defaults source hrss to 5e-23; specify it explicitly for scientific runs. SG/CG direct classes share the same numerical kernels and now return the full padded buffer. The explicitly elliptical WNB class remains available as a separate model, but is not used for cWB WNB.

NumPy's RNG differs from ROOT's: equal integer seeds do not produce identical WNB realizations. Tests against saved original cWB samples use the same Gaussian inputs and require relative L2 error below 1e-12. Reference fixtures and their provenance live in test/data/.