import matplotlib.pyplot as plt
import numpy as np

import scgenerator as sc


def main():
    nperseg = 513
    nseg = 240
    ntot = (nperseg - 1) * (nseg - 1)

    fs = 44100
    nf = 45611
    f = np.linspace(0, fs // 2, nf)

    spec = 1 / (f + 1)
    spec += np.exp(-(((f - (0.2 * fs)) / (0.5 * fs)) ** 2))
    plt.plot(f, spec)
    plt.xscale("log")
    plt.yscale("log")
    plt.show()

    noise = sc.noise.NoiseMeasurement(f, spec)
    t, y = noise.time_series(nf=nperseg, nseg=nseg)
    # tf, yf = noise.time_series(nperseg=(ntot // 2) + 1, nseg=1)
    plt.plot(t, y, ls="", marker=".")
    plt.show()

    newnoise = noise.from_time_series(y, t[1] - t[0], nperseg=(nperseg - 1) * 2)

    plt.plot(*noise.plottable())
    f, sxx = noise.sample_spectrum(nperseg)
    plt.plot(f, 10 * np.log10(sxx))
    plt.plot(*newnoise.plottable())
    plt.xscale("log")
    plt.show()


if __name__ == "__main__":
    main()