Conduct DBSCAN on radian distance matrix with sklearn?
<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>