title: numpy interpolation to increase a vector size
body: <p>Hi I have to enlarge the number of points inside of vector to enlarge the vector to fixed size. for example:</p>
  
  <p><strong>for this simple vector</strong> </p>
  
  <pre><code>&gt;&gt;&gt; a = np.array([0, 1, 2, 3, 4, 5])
  &gt;&gt;&gt; len(a)
  # 6
  </code></pre>
  
  <p>now, I want to get a vector with size of 11 taken the <code>a</code> vector as base the results will be</p>
  
  <pre><code># array([ 0. ,  0.5,  1. ,  1.5,  2. ,  2.5,  3. ,  3.5,  4. ,  4.5,  5. ])
  </code></pre>
  
  <p><strong>EDIT 1</strong></p>
  
  <p>what I need is a function that will enter the base vector and the number of values that must be the resultant vector, and I return a new vector with size equal to the parameter. something like</p>
  
  <pre><code>def enlargeVector(vector, size):
      .....
      return newVector
  </code></pre>
  
  <p>to use like:</p>
  
  <pre><code>&gt;&gt;&gt; a = np.array([0, 1, 2, 3, 4, 5])
  &gt;&gt;&gt; b = enlargeVector(a, 200):
  &gt;&gt;&gt; len(b)
  # 200
  </code></pre>
  
  <p>and b contains data results of linear, cubic, or whatever interpolation methods </p>