title: Positive random number generation with given mean and standard deviation
body: <p>I am working on a simulation project. Need help on random number generation. I need two sets of random numbers.</p>
  <p>Properties:</p>
  <ol>
  <li>Primary set (var_a) &gt; Normally distributed, greater than 0, with given mean and std.</li>
  <li>Secondary set (var_b) -&gt; Same as a primary set, with an addition, that second set cannot be greater than primary set. The reason being the output of a deterministic function will be in percentage between 0-1 only. For example:</li>
  </ol>
  <p><a href="https://i.stack.imgur.com/3Zzrh.png" rel="nofollow noreferrer">service level calculation</a></p>
  <pre><code>import numpy as np
  
  n = 100000
  
  # Calls Handled
  callshandled = np.random.normal(loc=65,  scale=97, size=n)
  print('Calls handled: ', callshandled)
  
  # Call handled within sl. Has to always be less or equal to Calls Handled
  ansinsl = np.random.normal(loc=60,  scale=82, size=n)
  print('Answered in SL', ansinsl)
  
  # Service Level - Has to be between 0-1. With normal distribution we get values in negative
  sl = np.array(ansinsl)/np.array(callshandled)
  print('Service level', sl)
  
  Calls handled:  [ 43.26825426 129.79198758  31.56460354 ...  37.45059791   1.71420416
   -94.87241356]
  Answered in SL [-12.72293091 204.28084996 232.25722235 ... 166.03208722 -53.69933624
   -36.71949656]
  Service level [ -0.29404771   1.57390956   7.35815427 ...   4.43336279 -31.32610312
     0.38704082]
  </code></pre>