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()
Metadata
Release files for burst-waveform 0.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| burst_waveform-0.3.1.tar.gz | 1.6 MB | Details |
Release files / burst_waveform-0.3.1.tar.gz
| Download URL | burst_waveform-0.3.1.tar.gz |
|---|---|
| Size | 1.6 MB |
| Tags | Source |
|
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904b621e07088f0fc402cb88ac060a395f902014933372f4ee887a01484e7aa0
|
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twine/7.0.0 CPython/3.10.21
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