ad7292d5ce9dd3f713f4c091e188615a5ac95f97,librosa/core/time_frequency.py,,A_weighting,#Any#Any#,842

Before Change

    const = np.array([12200, 20.6, 107.7, 737.9])**2.0

    r_a = const[0] * f_sq**2
    r_a /= (f_sq + const[0]) * (f_sq + const[1])
    r_a /= np.sqrt((f_sq + const[2]) * (f_sq + const[3]))

    weights = 2.0 + 20 * np.log10(r_a)

    if min_db is not None:
        weights = np.maximum(min_db, weights)

After Change

    const = np.array([12200, 20.6, 107.7, 737.9])**2.0

    weights = 2.0 + 20.0 * (np.log10(const[0]) + 4 * np.log10(frequencies)
                            - np.log10(f_sq + const[0])
                            - np.log10(f_sq + const[1])
                            - 0.5 * np.log10(f_sq + const[2])
                            - 0.5 * np.log10(f_sq + const[3]))

    if min_db is not None:
        weights = np.maximum(min_db, weights)

Instances