title: How to efficiently check if an ordered numpy array contains a value?
body: <p>I have a 2-d numpy array that I know is sorted across axis=1. Example:</p>
  
  <pre><code>[[0,0,1],
  [0,7,1],
  [1,1,0]]
  </code></pre>
  
  <p>I want to check with complexity of log(n) if the array contains a certain row, example: [0,7,1].</p>
  
  <p>I thought about using search-sorted
  to get the index in which the row would have to go in, and if the row is indeed in the array, it would have to be before or after this index, but can I be sure it would be one way or the other?</p>