ToneToNoiseRatio#

class ansys.sound.core.psychoacoustics.ToneToNoiseRatio(psd=None, frequency_list=None)#

Computes the ECMA 418-1/ISO 7779 tone-to-noise ratio (TNR).

This class computes the TNR from a power spectral density (PSD), according to the ECMA 418-1 and ISO 7779 standards.

Examples

Compute and display the tone-to-noise ratio of all identified peaks in a given power spectral density.

>>> from ansys.sound.core.psychoacoustics import ToneToNoiseRatio
>>> tone_to_noise_ratio = ToneToNoiseRatio(psd=my_psd)
>>> tone_to_noise_ratio.process()
>>> tnr_values = tone_to_noise_ratio.get_TNR_values()
>>> frequencies = tone_to_noise_ratio.get_peaks_frequencies()
>>> max_tnr = tone_to_noise_ratio.get_max_TNR_value()
>>> tone_to_noise_ratio.plot()

Compute the tone-to-noise ratio at specific frequencies.

>>> from ansys.sound.core.psychoacoustics import ToneToNoiseRatio
>>> tone_to_noise_ratio = ToneToNoiseRatio(psd=my_psd, frequency_list=[500, 1000, 2000])
>>> tone_to_noise_ratio.process()
>>> tnr_values = tone_to_noise_ratio.get_TNR_values()

See also

Calculate TNR and PR: Example demonstrating how to compute tone-to-noise ratio and prominence ratio.

Class instantiation takes the following parameters.

Parameters:

psdField

PSD of the signal on which to compute TNR. The PSD field has the following characteristics:

num_entities = 1
location = “TimeFreq_sets”
data: Vector of amplitude values in unit^2/Hz
time_freq_support: Vector of regularly spaced frequencies in Hz associated with amplitude values (from 0 Hz to the maximum frequency)
unit = “<unit>^2/Hz” (where <unit> is Pa for example).

You can use the function create_scalar_field() to create the field.

frequency_listlist, default: None

List of the frequencies in Hz of the tones (peaks in the spectrum) for which to calculate the TNR. The default is None, in which case a peak detection method is applied to automatically find the tones in the input spectrum. Then, the TNR is calculated for each detected tone.

Methods

`ToneToNoiseRatio.get_TNR_values`()	Get the vector of the peaks' TNR values in dB.
`ToneToNoiseRatio.get_max_TNR_value`()	Get the maximum TNR value in dB.
`ToneToNoiseRatio.get_nb_tones`()	Get the number of tones.
`ToneToNoiseRatio.get_output`()	Get TNR data as a generic data container.
`ToneToNoiseRatio.get_output_as_nparray`()	Get TNR data in a tuple as a NumPy array.
`ToneToNoiseRatio.get_peaks_frequencies`()	Get the vector of the peaks' frequencies in Hz.
`ToneToNoiseRatio.get_peaks_high_frequencies`()	Get the vector of the peaks' higher-frequency limits in Hz.
`ToneToNoiseRatio.get_peaks_levels`()	Get the vector of the peaks' level values in dB SPL.
`ToneToNoiseRatio.get_peaks_low_frequencies`()	Get the vector of the peaks' lower-frequency limits in Hz.
`ToneToNoiseRatio.get_reference_curve`()	Get the reference threshold curve, above which a tone is considered as prominent.
`ToneToNoiseRatio.get_single_tone_info`(tone_index)	Get the TNR information for a tone.
`ToneToNoiseRatio.plot`()	Plot the TNR for all identified peaks, along with the threshold curve.
`ToneToNoiseRatio.process`()	Compute the TNR.

Attributes

`ToneToNoiseRatio.frequency_list`	Tone frequency list in Hz.
`ToneToNoiseRatio.psd`	Input power spectral density (PSD).