title: Conduct DBSCAN on radian distance matrix with sklearn?
body: <p>I wish to conduct clustering on several timestamps(in minutes).
  So what i've done so far is:</p>
  
  <p>1) Convert points to radian</p>
  
  <pre><code>#points containing time value in minutes
  points = [100, 200, 600, 659, 700]
  
  def convert_to_radian(x):
      return((x / (24 * 60)) * 2 * pi)
  
  rad_function = np.vectorize(convert_to_radian)
  points_rad = rad_function(points)
  </code></pre>
  
  <p>2) Generate distance matrix</p>
  
  <pre><code>#generate distance matrix from each point
  dist = points_rad[None,:] - points_rad[:, None]
  </code></pre>
  
  <p>3) Assign shortest distances from each point</p>
  
  <pre><code>dist[((dist &gt; pi) &amp; (dist &lt;= (2*pi)))] = dist[((dist &gt; pi) &amp; (dist &lt;= (2*pi)))] -(2*pi)
  dist[((dist &gt; (-2*pi)) &amp; (dist &lt;= (-1*pi)))] = dist[((dist &gt; (-2*pi)) &amp; (dist &lt;= (-1*pi)))] + (2*pi) 
  dist = abs(dist)
  </code></pre>
  
  <p>And now i want to use DBSCAN on the distance matrix, how do i go about clustering it to radian distance?</p>
  
  <p>Thank you!</p>