Source code for cr.nimble._src.dsp.scaling

# Copyright 2021 CR.Sparse Development Team
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#     https://www.apache.org/licenses/LICENSE-2.0
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import jax
import jax.numpy as jnp
from jax import jit


[docs]def scale_0_mean_1_var(data, axis=-1): """Normalizes a data vector (data - mu) / sigma Args: data (jax.numpy.ndarray): A data vector or array axis (int): For nd arrays, the axis along which the data normalization will be done Returns: (jax.numpy.ndarray, jax.numpy.ndarray, jax.numpy.ndarray): A tuple comprising of: * Normalized data vector/array * Mean value(s) * Standard deviation value(s) """ mu = jnp.mean(data, axis) data = data - mu variance = jnp.var(data, axis) sigma = jnp.sqrt(variance) data = data / sigma return data, mu, sigma
scale_0_mean_1_var_jit = jit(scale_0_mean_1_var, static_argnums=(1,))
[docs]def scale_to_0_1(x): """Scales a signal to the range of 0 and 1 Args: x (jax.numpy.ndarray): A signal to be scaled Returns: (jax.numpy.ndarray, float, float): A tuple comprising of: * Scaled signal * The amount of shift * The scale factor """ shift = jnp.min(x) x = x - shift scale = jnp.max(x) x = x / scale return x, shift, scale
def descale_from_0_1(x, shift, scale): """Reverses the scaling of a signal from the range of 0 and 1 Args: x (jax.numpy.ndarray): A signal to be scaled shift (float): The amount of shift scale (float): The scale factor Returns: jax.numpy.ndarray: Descaled signal """ x = x * scale x = x + shift return x