metrax.SNR

class metrax.SNR(total: Array, count: Array)

Bases: Average

SNR (Signal-to-Noise Ratio) Metric for audio.

This class calculates the Signal-to-Noise Ratio (SNR) in decibels (dB) between a predicted audio signal and a ground truth audio signal, and averages it over a dataset.

The SNR is defined as:

\[SNR_{dB} = 10 \cdot \log_{10} \left( \frac{P_{signal}}{P_{noise}} \right)\]

Where:

• \(P_{signal}\) is the power of the ground truth signal (target). By default (zero_mean=False), this is the mean of the squared target values. If zero_mean=True, it’s the variance of the target values.

• \(P_{noise}\) is the power of the noise component, which is defined as the difference between the target and preds (target - preds). By default (zero_mean=False), this is the mean of the squared noise values. If zero_mean=True, it’s the variance of the noise values.

__init__(total: Array, count: Array) → None

Methods

__init__(total, count)
compute()	Computes final metrics from intermediate values.
compute_value()	Wraps compute() and returns a values.Value.
empty()	Returns an empty instance (i.e. .merge(Metric.empty()) is a no-op).
from_fun(fun)	Calls cls.from_model_output with the return value from fun.
from_model_output(predictions, targets[, ...])	Computes SNR for a batch of audio signals and creates an SNR metric instance.
from_output(name)	Calls cls.from_model_output with model output named name.
merge(other)	Returns Metric that is the accumulation of self and other.
reduce()	Reduces the metric along it first axis by calling _reduce_merge().
replace(**updates)	Returns a new object replacing the specified fields with new values.

Attributes

total
count

classmethod from_model_output(predictions: Array, targets: Array, zero_mean: bool = False) → SNR

Computes SNR for a batch of audio signals and creates an SNR metric instance.

Parameters:

• predictions – A JAX array of predicted audio signals.

• targets – A JAX array of ground truth audio signals.

• zero_mean – If True, subtracts the mean from the signal and noise before calculating their respective powers.

Returns:

An SNR instance containing the SNR value for the current batch, ready for averaging.

__init__(total: Array, count: Array) → None

replace(**updates)

Returns a new object replacing the specified fields with new values.