title: Generating smoothed randoms that follow a distribution
body: <p>I have two variables, lets call them <code>x</code> and <code>y</code>, which when plotted are the scattered blue points in the graph. <strong>I have fitted them using curve_fit from Scipy</strong>. </p>
  
  <p>I want to generate (lets say 500000) <strong>"smoothed"</strong> random numbers replicating the distribution followed by <code>x</code> and <code>y</code>. </p>
  
  <p><img src="https://i.stack.imgur.com/3gzh3.png" alt="enter image description here"></p>
  
  <p>By <strong>"smoothed"</strong> I mean, I don't want randoms that exactly replicate my data (<code>x</code> and <code>y</code>) like in the figure <strong>below</strong>, with the <strong><code>red diamonds being my data distribution and the histogram being my generated randoms.</code></strong> (<strong>even the fluctuations of the data are replicated here!!!!</strong>). I want a "smoothed" histogram.</p>
  
  <p><img src="https://i.stack.imgur.com/pGXBo.png" alt="enter image description here"> </p>
  
  <p>What I have tried so far is to fit the points <code>x</code> and <code>y</code> using <code>curve_fit</code> from scipy. So now I know what the data distribution is. Now I need to create random numbers that follow the above <strong>fit</strong>/distribution. </p>
  
  <p>P.S I have also tried creating uniform randoms from 0 to 1 and trying to get the points below the fitted curve, but I don't know how! </p>