numpy.choose 32 choice limitation
===

Low and behold, I ran into a regression in numpy.choose after upgrading to 1.5.1.  Past versions (and numeric) supported an, as far as I could tell, unlimited number of potential choices.  The "new" choose is limited to 32.  [Here is a post][1] where another user laments the regression.

I have a list with 100 choices (0-99) that I was using to modify an array.  As a work around, I am using the following code.  Understandably, it is 7 times slower than using choose.  I am not a C programmer, and while I would to get in an fix the numpy issue, I wonder what other potentially faster work arounds exist.  Thoughts?

    d={...} #A dictionary with my keys and their new mappings
    for key, value in d.iteritems():
        array[array==key]=value 


  [1]: http://mail.scipy.org/pipermail/numpy-discussion/2011-July/057831.html