title: Numpy - use values of array that meet condition
body: <p>I have two numpy arrays, one of a boolean type, the other float type. I want to get the rows of XY_coord where one of the colums has a row with True (so all rows in XY_coord with False-False in BOOL are removed. How do I do this?</p>
  <pre><code>BOOL = np.array([[False,  True],
             [False,  True],
             [False,  True],
             [False,  True],
             [ True,  True],
             [ True, False],
             [False, False],
             [False, False],
             [ True, False]])
         
  XY_coord =    np.array([[-192.9594843 ,   78.17485294],
             [-182.2699483 ,   50.143909  ],
             [-171.5804122 ,   22.11296505],
             [ -51.11635646,  132.2664039 ],
             [ -40.42682039,  104.2354599 ],
             [ -29.73728432,   76.20451597],
             [  90.72677139,  186.3579548 ],
             [ 101.4163075 ,  158.3270108 ],
             [ 112.1058435 ,  130.2960669 ]])
  </code></pre>
  <p>I can do:</p>
  <pre><code>XY_coord[out[:,0]]
  XY_coord[out[:,1]]
  </code></pre>
  <p>and append the outcome, but my matrix is much larger, so this will be inefficient.</p>