title: numpy arange: how to make "precise" array of floats?
body: <p>In short, the problem I encounter is this:</p>
  
  <pre><code>aa = np.arange(-1., 0.001, 0.01)
  aa[-1]
  Out[16]: 8.8817841970012523e-16
  </code></pre>
  
  <p>In reality, this cause a series problem since my simulations doesn't allow positive value inputs.</p>
  
  <p>I can sort of get around by doing:</p>
  
  <pre><code>aa = np.arange(-100, 1, 1)/100.
  aa[-1]
  Out[21]: 0.0
  </code></pre>
  
  <p>But this is a pain. Practically you can't do this every time. </p>
  
  <p>This seems like such a basic problem. There's gotta be something I am missing here.
  By the way, I am using Python 2.7.13. </p>