title: Creating normal noise array with different dispersions(sigma)
body: <p>I have a problem where I need to create a numpy array 1920x1080 filled with a normally distributed noise and for each element I use different sigma (gradually incremented with step).
  But I ran into a time problem: I creating around 1500 arrays(not at the same time but, writing first in file then creating second and writing it and so on) and time it cost is nearly 1.5 ours. I used folowing code</p>
  
  <pre class="lang-py prettyprint-override"><code>np.fromiter((random.normalvariate(0, sigma_step * x) for x in range(0, 1080 * 1920)), dtype = np.float64).reshape(1080, 1920)
  </code></pre>
  
  <p>I'm thinking about creating 1500 values at once because they have same sigma value but calling np.random.normal 1080*1920 times dont give me &lt;5 min mark and creates multiple storage problems(I need to write binary each frame consistently and dont have so much memory to keep them all)
  Thanks for any help</p>