title: How to normalise plotted points and get a circle?
body: <p>Given 2000 random points in a unit circle (using numpy.random.normal(0,1)), I want to normalize them such that the output is a circle, how do I do that?</p>
  
  <p>I was requested to show my efforts. This is part of a larger question: Write a program that samples 2000 points uniformly from the circumference of a unit circle. Plot and show it is indeed picked from the circumference. To generate a point (x,y) from the circumference, sample (x,y) from std normal distribution and normalise them.</p>
  
  <p>I'm almost certain my code isn't correct, but this is where I am up to. Any advice would be helpful.</p>
  
  <p>This is the new updated code, but it still doesn't seem to be working.</p>
  
  <pre><code>import numpy as np
  import matplotlib.pyplot as plot
  
  def plot():
  
      xy = np.random.normal(0,1,(2000,2))
  
      for i in range(2000):
          s=np.linalg.norm(xy[i,])
          xy[i,]=xy[i,]/s
  
      plot.plot(xy)
      plot.show()
  </code></pre>
  
  <p>I think the problem is in </p>
  
  <pre><code> plot.plot(xy)
  </code></pre>
  
  <p>even if I use </p>
  
  <pre><code> plot.plot(xy[:,0],xy[:,1])
  </code></pre>
  
  <p>it doesn't work.</p>