title: Comparing and Quantifying similarity in a set of non linear data
body: <p>I have 2 lists of data which are basically a batch of SEQUENTIAL data(thus, data cannot be sorted) from a larger database which are as follows</p>
  <pre><code>a = [0.8, 0.9, 0.4, -0.4, 1.12, 1.16, 1.08, 1.22]
  b = [0.85, 0.96, 0.4, -0.4, 1.15, 1.18, 1.1, 1.92]
  </code></pre>
  <p>The data provided may not be linear in nature and thus typical correlation wont serve the purpose.</p>
  <p>I wish to compare a and b (as a line graph) and assign a similarity score to them.</p>
  <p>Ive tried implementing linear co-relation from the stats library but the results are not convincing.</p>
  <p>Any way to do this using any other statistical function,  which emphasizes on the importance of non linear data?</p>
  <p>Also, is any supporting function available in scikit learn?</p>