title: I'm having difficulty understanding the syntax of scipy.optimize
body: <p>I feel stupid asking this, but I'm having a really hard time understanding the synatx of scipy.optimize</p>
  
  <p>I have an mxm matrix M, and I simply like to find an m-dimensional vector x which </p>
  
  <pre><code>    minimizes M.dot(x)
  
      such that ||x||_2^2 = 1
  </code></pre>
  
  <p>Essentially I want to minimize Mx with x being l2-normalized. </p>
  
  <p>I can't seem to find a way to fit my idea of what is going on within the syntax of numpy. I'd greatly appreciate any help in remedying my stupid with understanding. </p>
  
  <hr>
  
  <p>The problem also has a special case where it can be solved by finding x such that</p>
  
  <pre><code>    M.dot(x) = zeros
  
      such that ||x||_2^2 = 1
  </code></pre>
  
  <p>Would the same optimization algorithm be appropriate for both problems? Or are there different ways to solve the minimization and finding zeros problem? </p>