def brown(num_points=1024, b2=1.0, fs=1.0):
    """ Brownian or random walk (diffusion) noise with 1/f^2 PSD
        (not really a color... rather Brownian or random-walk)

        N = number of samples
        b2 = desired PSD is b2*f^-2
        fs = sampling frequency

        we integrate white-noise to get Brownian noise.

    """
    return (1.0/float(fs))*numpy.cumsum(white(num_points, b0=b2*(4.0*math.pi*math.pi), fs=fs))
def brown ( num_points = 1024 , b2 = 1.0 , fs = 1.0 ) : return ( 1.0 / float ( fs ) ) * numpy . cumsum ( white ( num_points , b0 = b2 * ( 4.0 * math . pi * math . pi ) , fs = fs ) )
Brownian or random walk (diffusion) noise with 1/f^2 PSD
        (not really a color... rather Brownian or random-walk)

        N = number of samples
        b2 = desired PSD is b2*f^-2
        fs = sampling frequency

        we integrate white-noise to get Brownian noise.