title: Compare multiple columns in numpy array
body: <p>I have a 2D numpy array with about 12 columns and 1000+ rows and each cell contains a number from 1 to 5. I'm searching for the best sextuple of columns according to my point system where 1 and 2 generate -1 point and 4 and 5 gives +1.</p>
  
  <p>If a row in a certain sextuple contains, for example, [1, 4, 5, 3, 4, 3] the point for this row should be +2, because 3*1 + 1*(-1) = 2. Next row may be [1, 2, 2, 3, 3, 3] and should be -3 points.</p>
  
  <p>At first, I tried a strait forward loop solution but I realized there are 665 280 possible combinations of columns to compare and when I also need to search for the best quintuple, quadruple etc. the loop is taking forever.</p>
  
  <p>Is there perhaps a smarter numpy-way of solving my problem?</p>