title: Scipy Minimization
body: <p>I have an inequality constrained optimization problem and am a bit unclear about the syntax of the input. The documentation did not prove all that clarifying.  I want to know if the function below is doing what I hope it is: Initialize the optimization with (Pguess, Qguess) and use SLSQP to find the minimum constrained such that 0&lt; Qguess &lt; QMax(Pguess) &amp;&amp; Pguess > 0.</p>
  
  <pre><code>def optimalSurface(self):
          Pguess=  float(1.1) if (self.type[0] == 'A' or self.type[0] =='a') else float(2.0)
          Qguess = .9* self.QMax(Pguess)
  
          ##(Qguess should always be less than QMax(Pguess))
  
          cons = ({'type': 'ineq', 'fun': lambda x : self.QMax(x[1]) - x[0]}) 
          bnds = ((0, None),(0 , None))  
          f = self.endObjective
          result = optimize.minimize(f, [Pguess,Qguess] ,method ='SLSQP', constraints = cons, bounds = bnds, options = {'disp':True})
  </code></pre>