pycbc.noise package¶
Submodules¶
pycbc.noise.gaussian module¶
This module contains functions to generate gaussian noise colored with a noise spectrum.
- pycbc.noise.gaussian.frequency_noise_from_psd(psd, seed=None)[source]¶
Create noise with a given psd.
Return noise coloured with the given psd. The returned noise FrequencySeries has the same length and frequency step as the given psd. Note that if unique noise is desired a unique seed should be provided.
- Parameters
psd (FrequencySeries) – The noise weighting to color the noise.
seed ({0, int} or None) – The seed to generate the noise. If None specified, the seed will not be reset.
- Returns
noise – A FrequencySeries containing gaussian noise colored by the given psd.
- Return type
FrequencySeriesSeries
- pycbc.noise.gaussian.noise_from_psd(length, delta_t, psd, seed=None)[source]¶
Create noise with a given psd.
Return noise with a given psd. Note that if unique noise is desired a unique seed should be provided.
- Parameters
length (int) – The length of noise to generate in samples.
delta_t (float) – The time step of the noise.
psd (FrequencySeries) – The noise weighting to color the noise.
seed ({0, int}) – The seed to generate the noise.
- Returns
noise – A TimeSeries containing gaussian noise colored by the given psd.
- Return type
- pycbc.noise.gaussian.noise_from_string(psd_name, length, delta_t, seed=None, low_frequency_cutoff=10.0)[source]¶
Create noise from an analytic PSD
Return noise from the chosen PSD. Note that if unique noise is desired a unique seed should be provided.
- Parameters
psd_name (str) – Name of the analytic PSD to use.
low_fr –
length (int) – The length of noise to generate in samples.
delta_t (float) – The time step of the noise.
seed ({None, int}) – The seed to generate the noise.
low_frequency_cutof ({10.0, float}) – The low frequency cutoff to pass to the PSD generation.
- Returns
noise – A TimeSeries containing gaussian noise colored by the given psd.
- Return type
pycbc.noise.reproduceable module¶
- pycbc.noise.reproduceable.block(seed, sample_rate)[source]¶
Return block of normal random numbers
- Parameters
seed ({None, int}) – The seed to generate the noise.sd
sample_rate (float) – Sets the variance of the white noise
- Returns
noise – Array of random numbers
- Return type
numpy.ndarray
- pycbc.noise.reproduceable.colored_noise(psd, start_time, end_time, seed=0, sample_rate=16384, low_frequency_cutoff=1.0, filter_duration=128, scale=1.0)[source]¶
Create noise from a PSD
Return noise from the chosen PSD. Note that if unique noise is desired a unique seed should be provided.
- Parameters
psd (pycbc.types.FrequencySeries) – PSD to color the noise
start_time (int) – Start time in GPS seconds to generate noise
end_time (int) – End time in GPS seconds to generate nosie
seed ({None, int}) – The seed to generate the noise.
sample_rate ({16384, float}) – The sample rate of the output data. Keep constant if you want to ensure continuity between disjoint time spans.
low_frequency_cutof ({1.0, float}) – The low frequency cutoff to pass to the PSD generation.
filter_duration ({128, float}) – The duration in seconds of the coloring filter
- Returns
noise – A TimeSeries containing gaussian noise colored by the given psd.
- Return type
- pycbc.noise.reproduceable.noise_from_string(psd_name, start_time, end_time, seed=0, sample_rate=16384, low_frequency_cutoff=1.0, filter_duration=128, scale=1.0)[source]¶
Create noise from an analytic PSD
Return noise from the chosen PSD. Note that if unique noise is desired a unique seed should be provided.
- Parameters
psd_name (str) – Name of the analytic PSD to use.
start_time (int) – Start time in GPS seconds to generate noise
end_time (int) – End time in GPS seconds to generate nosie
seed ({None, int}) – The seed to generate the noise.
sample_rate ({16384, float}) – The sample rate of the output data. Keep constant if you want to ensure continuity between disjoint time spans.
low_frequency_cutof ({10.0, float}) – The low frequency cutoff to pass to the PSD generation.
filter_duration ({128, float}) – The duration in seconds of the coloring filter
- Returns
noise – A TimeSeries containing gaussian noise colored by the given psd.
- Return type
- pycbc.noise.reproduceable.normal(start, end, sample_rate=16384, seed=0)[source]¶
Generate data with a white Gaussian (normal) distribution
- Parameters
start_time (int) – Start time in GPS seconds to generate noise
end_time (int) – End time in GPS seconds to generate noise
sample-rate (float) – Sample rate to generate the data at. Keep constant if you want to ensure continuity between disjoint time spans.
seed ({None, int}) – The seed to generate the noise.
- Returns
noise – A TimeSeries containing gaussian noise
- Return type