endolith

"""
Train a neural network to implement the discrete Fourier transform
"""
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
import numpy as np
import matplotlib.pyplot as plt

N = 32
batch = 10000

alimanfoo

import numpy as np


def find_runs(x):
    """Find runs of consecutive items in an array."""

    # ensure array
    x = np.asanyarray(x)
    if x.ndim != 1:
        raise ValueError('only 1D array supported')

endolith

Adaptation of Sethares' dissonance measurement function to Python

Example is meant to match the curve in Figure 3:

Original model used products of the two amplitudes a1⋅a2, but this was changed to minimum of the two amplitudes min(a1, a2), as explained in G: Analysis of the Time Domain Model appendix of Tuning, Timbre, Spectrum, Scale.

This weighting is incorporated into the dissonance model (E.2) by assuming that the roughness is proportional to the loudness of the beating. ... Thus, the amplitude of the beating is given by the minimum of the two amplitudes.