code: 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))
docs: 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.