title: Numpy - How to fill 2D array with random discrete numbers sampled from various distributions?
body: <p>I've written Dijkstra's path finding algorithm, which takes in a Numpy 2D array of integers (cost) and finds the shortest path.</p>
  <p>However, I want to play around with how I create that 2D array with random numbers. Right now, I'm just using <em>np.random.default_rng().integers()</em> to create a 2d array with numbers from the uniform distribution.</p>
  <p>However, how would I go about creating a 2D array with random discrete numbers sampled from, for example, the Gaussian distribution? Or the Rayleigh distribution? Or Poisson? etc. etc.</p>
  <p>The requirements for the generated numbers is as follows:</p>
  <ul>
  <li>Has to be in the range 0,10 inclusive.</li>
  <li>Has to be an integer.</li>
  </ul>
  <p>I'm using Python 3.10.0</p>
  <p>If anyone can help I would very much appreciate it!</p>