import numpy as np


def a_weight(fs, n_fft, min_db=-80.0):
    freq = np.linspace(0, fs // 2, n_fft // 2 + 1)
    freq_sq = np.power(freq, 2)
    freq_sq[0] = 1.0
    weight = 2.0 + 20.0 * (2 * np.log10(12194) + 2 * np.log10(freq_sq)
                           - np.log10(freq_sq + 12194 ** 2)
                           - np.log10(freq_sq + 20.6 ** 2)
                           - 0.5 * np.log10(freq_sq + 107.7 ** 2)
                           - 0.5 * np.log10(freq_sq + 737.9 ** 2))
    weight = np.maximum(weight, min_db)

    return weight


def compute_gain(sound, fs, min_db=-80.0, mode="A_weighting"):
    if fs == 16000:
        n_fft = 2048
    elif fs == 24000:
        n_fft = 4096
    elif fs == 32000:
        n_fft = 2048
    elif fs == 44100:
        n_fft = 2048
    elif fs == 48000:
        n_fft = 4096
    else:
        raise Exception("Invalid fs {}".format(fs))
    stride = n_fft // 2

    gain = []
    for i in range(0, len(sound) - n_fft + 1, stride):
        if mode == "RMSE":
            g = np.mean(sound[i: i + n_fft] ** 2)
        elif mode == "A_weighting":
            spec = np.fft.rfft(np.hanning(n_fft + 1)[:-1] * sound[i: i + n_fft])
            power_spec = np.abs(spec) ** 2
            a_weighted_spec = power_spec * np.power(10, a_weight(fs, n_fft) / 10)
            g = np.sum(a_weighted_spec)
        else:
            raise Exception("Invalid mode {}".format(mode))
        gain.append(g)

    gain = np.array(gain)
    gain = np.maximum(gain, np.power(10, min_db / 10))
    gain_db = 10 * np.log10(gain)
    return gain_db


def mix(sound1, sound2, r, fs):
    gain1 = np.max(compute_gain(sound1, fs))  # Decibel
    gain2 = np.max(compute_gain(sound2, fs))
    t = 1.0 / (1 + np.power(10, (gain1 - gain2) / 20.) * (1 - r) / r)
    sound = ((sound1 * t + sound2 * (1 - t)) / np.sqrt(t ** 2 + (1 - t) ** 2))
    return sound