cutcutcodec.core.signal.window.alpha_to_band

cutcutcodec.core.signal.window.alpha_to_band(alpha: float) → float

Empirical estimation based on regression.

The fitted model is \(band = a*\alpha + b + c*tanh(d*\alpha)\).

This function is close to the identity function.

Examples

>>> import torch
>>> from cutcutcodec.core.signal.window import alpha_to_band, find_dpss_law
>>> alphas, _, bands = find_dpss_law()
>>> pred = [alpha_to_band(a) for a in alphas.tolist()]
>>> # import matplotlib.pyplot as plt
>>> # _ = plt.plot(alphas.numpy(force=True), bands.numpy(force=True))
>>> # _ = plt.plot(alphas.numpy(force=True), pred)
>>> # plt.show()
>>>