NuRadioReco.modules.channelGenericNoiseAdder module

NuRadioReco.modules.channelGenericNoiseAdder.load_scale_parameters(scale_parameter_path)

Returns interpolated scale parameters ifo frequency per channel

Parameters:

scale_parameter_pathstr

path to the scale parameter json file

Returns:

scale_parameterslist

list of interpolated scale parameters per channel

class NuRadioReco.modules.channelGenericNoiseAdder.channelGenericNoiseAdder

Bases: object

Module that generates noise in some generic fashion (not based on measured data), which can be added to data.

Methods

add_data_driven_noise(ampl, selection, ...)	Function to add data driven noise to a selection range of a given array of amplitudes
add_random_phases(amps, n_samples_time_domain)	Adding random phase information to given amplitude spectrum.
bandlimited_noise(min_freq, max_freq, ...[, ...])	Generating noise of n_samples in a bandwidth [min_freq,max_freq].
bandlimited_noise_from_precalculated_parameters([...])	Generating noise of n_samples in a bandwidth [min_freq,max_freq].
bandlimited_noise_from_spectrum(n_samples, ...)	Generating noise of n_samples in a bandwidth [min_freq,max_freq].
begin([debug, seed, scale_parameter_dir])
fftnoise_fullfft(f)	Adding random phase information to given amplitude spectrum.
precalculate_bandlimited_noise_parameters(...)	Generating noise of n_samples in a bandwidth [min_freq,max_freq].
run(event, station, detector[, amplitude, ...])	Add noise to given event.

end

add_random_phases(amps, n_samples_time_domain)

Adding random phase information to given amplitude spectrum.

Parameters:

amps: array of floats

Data that random phase is added to.

n_samples_time_domain: int

number of samples in the time domain to differentiate between odd and even number of samples

fftnoise_fullfft(f)

Adding random phase information to given amplitude spectrum.

Parameters:

f: array of floats

Data that random phase is added to.

add_data_driven_noise(ampl, selection, frequencies, station_id=None, channel_id=None)

Function to add data driven noise to a selection range of a given array of amplitudes

Parameters:

ampl: np.ndarray

array of amplitudes to which to add noise

selection: list

selection of amplitudes to which to add noise in the form of a list of the same length as ampl filled with booleans

frequencies: np.ndarray

list of frequencies to query data-driven parameters

station_id: int

station from which to query data to drive noise generation

channel_id: int

channel from which to query data to drive noise generation

Returns:

ampl: np.ndarray

array of amplitudes with data driven noise included

bandlimited_noise(min_freq, max_freq, n_samples, sampling_rate, amplitude, type='perfect_white', time_domain=True, bandwidth=None, station_id=None, channel_id=None)

Generating noise of n_samples in a bandwidth [min_freq,max_freq].

Parameters:

min_freq: float

Minimum frequency of passband for noise generation min_freq = None: Only the DC component is removed. If the DC component should be included, min_freq = 0 has to be specified

max_freq: float

Maximum frequency of passband for noise generation If the maximum frequency is above the Nquist frequencey (0.5 * sampling rate), the Nquist frequency is used max_freq = None: Frequencies up to Nyquist freq are used.

n_samples: int

number of samples in the time domain

sampling_rate: float

desired sampling rate of data

amplitude: float

desired voltage of noise as V_rms (only roughly, since bandpass limited)

type: string

perfect_white: flat frequency spectrum rayleigh: Amplitude of each frequency bin is drawn from a Rayleigh distribution data-driven: Amplitude of each frequency bin is drawn from a data informed Rayleigh distribution # white: flat frequency spectrum with random jitter

time_domain: bool (default True)

if True returns noise in the time domain, if False it returns the noise in the frequency domain. The latter might be more performant as the noise is generated internally in the frequency domain.

bandwidth: float or None (default)

if this parameter is specified, the amplitude is interpreted as the amplitude for the bandwidth specified here Otherwise the amplitude is interpreted for the bandwidth of min(max_freq, 0.5 * sampling rate) - min_freq If bandwidth is larger then (min(max_freq, 0.5 * sampling rate) - min_freq) it has the same effect as None

station_id: int or None (default)

Only necessary when selecting data-driven noise type to determine from which station/channel data to generate noise

channel_id: int or None (default)

Only necessary when selecting data-driven noise type to determine from which station/channel data to generate noise

Notes

• Note that by design the max frequency is the Nyquist frequency, even if a bigger max_freq is implemented (RL 17-Sept-2018)

• Add ‘multi_white’ noise option on 20-Sept-2018 (RL)

precalculate_bandlimited_noise_parameters(min_freq, max_freq, n_samples, sampling_rate, amplitude, type='perfect_white', bandwidth=None)

Generating noise of n_samples in a bandwidth [min_freq,max_freq].

Parameters:

min_freq: float

Minimum frequency of passband for noise generation min_freq = None: Only the DC component is removed. If the DC component should be included, min_freq = 0 has to be specified

max_freq: float

Maximum frequency of passband for noise generation If the maximum frequency is above the Nquist frequencey (0.5 * sampling rate), the Nquist frequency is used max_freq = None: Frequencies up to Nyquist freq are used.

n_samples: int

number of samples in the time domain

sampling_rate: float

desired sampling rate of data

amplitude: float

desired voltage of noise as V_rms (only roughly, since bandpass limited)

type: string

perfect_white: flat frequency spectrum rayleigh: Amplitude of each frequency bin is drawn from a Rayleigh distribution # white: flat frequency spectrum with random jitter

time_domain: bool (default True)

if True returns noise in the time domain, if False it returns the noise in the frequency domain. The latter might be more performant as the noise is generated internally in the frequency domain.

bandwidth: float or None (default)

if this parameter is specified, the amplitude is interpreted as the amplitude for the bandwidth specified here Otherwise the amplitude is interpreted for the bandwidth of min(max_freq, 0.5 * sampling rate) - min_freq If bandwidth is larger then (min(max_freq, 0.5 * sampling rate) - min_freq) it has the same effect as None

Notes

• Note that by design the max frequency is the Nyquist frequency, even if a bigger max_freq is implemented (RL 17-Sept-2018)

• Add ‘multi_white’ noise option on 20-Sept-2018 (RL)

bandlimited_noise_from_precalculated_parameters(type='perfect_white', time_domain=True)

Generating noise of n_samples in a bandwidth [min_freq,max_freq].

Parameters:

min_freq: float

Minimum frequency of passband for noise generation min_freq = None: Only the DC component is removed. If the DC component should be included, min_freq = 0 has to be specified

max_freq: float

Maximum frequency of passband for noise generation If the maximum frequency is above the Nquist frequencey (0.5 * sampling rate), the Nquist frequency is used max_freq = None: Frequencies up to Nyquist freq are used.

n_samples: int

number of samples in the time domain

sampling_rate: float

desired sampling rate of data

amplitude: float

desired voltage of noise as V_rms (only roughly, since bandpass limited)

type: string

perfect_white: flat frequency spectrum rayleigh: Amplitude of each frequency bin is drawn from a Rayleigh distribution # white: flat frequency spectrum with random jitter

time_domain: bool (default True)

if True returns noise in the time domain, if False it returns the noise in the frequency domain. The latter might be more performant as the noise is generated internally in the frequency domain.

bandwidth: float or None (default)

if this parameter is specified, the amplitude is interpreted as the amplitude for the bandwidth specified here Otherwise the amplitude is interpreted for the bandwidth of min(max_freq, 0.5 * sampling rate) - min_freq If bandwidth is larger then (min(max_freq, 0.5 * sampling rate) - min_freq) it has the same effect as None

Notes

• Note that by design the max frequency is the Nyquist frequency, even if a bigger max_freq is implemented (RL 17-Sept-2018)

• Add ‘multi_white’ noise option on 20-Sept-2018 (RL)

bandlimited_noise_from_spectrum(n_samples, sampling_rate, spectrum, amplitude=None, type='perfect_white', time_domain=True, station_id=None, channel_id=None)

Generating noise of n_samples in a bandwidth [min_freq,max_freq].

Parameters:

n_samples: int

number of samples in the time domain

sampling_rate: float

desired sampling rate of data

spectrum: numpy.ndarray, function

desired spectrum of the noise, either as a numpy.ndarray of length n_frequencies or a function that takes the frequencies as an argument and returns the amplitudes. The overall normalization of the spectrum is ignored if the paramter “amplitude” is set.

amplitude: float, optional

desired voltage of noise as V_rms. If set to None the power of the noise will be equal to the power of the spectrum.

type: string

perfect_white: flat frequency spectrum rayleigh: Amplitude of each frequency bin is drawn from a Rayleigh distribution data-driven : Amplitude of each frequency bin is drawn from a data informed Rayleigh distribution # white: flat frequency spectrum with random jitter

time_domain: bool (default True)

if True returns noise in the time domain, if False it returns the noise in the frequency domain. The latter might be more performant as the noise is generated internally in the frequency domain.

station_id: int or None (default)

Only necessary when selecting data-driven noise type to determine from which station/channel data to generate noise

channel_id: int or None (default)

Only necessary when selecting data-driven noise type to determine from which station/channel data to generate noise

begin(debug=False, seed=None, scale_parameter_dir=None)

Parameters:

scale_parameter_dirstring

Parameter for noise type “data-driven” Path to the directory that contains the scale parameter files. One file contains one station. The module expects the files to be named thermal_noise_scale_parameters_sXX_seasonXX.json

run(event, station, detector, amplitude=0.001, min_freq=0.05, max_freq=2.0, type='perfect_white', excluded_channels=None, bandwidth=None)

Add noise to given event.

Parameters:

event

station

detector

amplitude: float or dict of floats

desired voltage of noise as V_rms for the specified bandwidth a dict can be used to specify a different amplitude per channel, the key is the channel_id

min_freq: float

Minimum frequency of passband for noise generation

max_freq: float

Maximum frequency of passband for noise generation If the maximum frequency is above the Nquist frequencey (0.5 * sampling rate), the Nquist frequency is used

type: string

perfect_white: flat frequency spectrum rayleigh: Amplitude of each frequency bin is drawn from a Rayleigh distribution data-driven: Amplitude of each frequency bin is drawn from a data-informed Rayleigh distribution

excluded_channels: list of ints

the channels ids of channels where no noise will be added, default is that no channel is excluded

bandwidth: float or None (default)

if this parameter is specified, the amplitude is interpreted as the amplitude for the bandwidth specified here Otherwise the amplitude is interpreted for the bandwidth of min(max_freq, 0.5 * sampling rate) - min_freq If bandwidth is larger then (min(max_freq, 0.5 * sampling rate) - min_freq) it has the same effect as None

end()