[NumPy-Tickets] [NumPy] #1673: first nonzero element

[NumPy Trac]

#1673: first nonzero element
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 Reporter:  tom3118      |       Owner:  somebody
     Type:  enhancement  |      Status:  new     
 Priority:  normal       |   Milestone:  2.0.0   
Component:  Other        |     Version:  1.5.0   
 Keywords:               |  
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Changes (by lcampagn):

 * cc: lcampagn@… (added)


Comment:

 I have seen many requests for a find_first in numpy, but most of these
 requests have subtly different (and incompatible) requirements such as
 "find first value less than x" or "find first nonzero value". I suggest
 the following function specification:
 {{{
   ind = array.find(x, testOp='eq', arrayOp='all', axis=0, test=None)
   arguments:
     x       -> value to search for
     testOp  -> condition to test for ('eq', 'ne', 'gt', 'lt', 'ge', 'le')
     arrayOp -> method for joining multiple comparisons ('any' or 'all')
     axis    -> the axis over which to search
     test    -> for convenience, this may specify a function to call to
 perform
                the test. This is not expected to be efficient.
   returns:
     first index where condition is true (or test returns true, if given)
     or None if the condition was never met
 }}}

 If the array has ndim > 1, then tests are performed using normal
 broadcasting rules.
 So for example, if I have an array with shape (2,3), the following would
 be valid:

 {{{
   ## find first row with all values=0
   array.find(0, testOp='eq', arrayOp='all', axis=0)
   ## equivalent to:
   for i in range(array.shape[axis]):
     if (array[i] == 0).all():
       return i

   ## find first column with any element greater than its corresponding
 element in col
   col = array([1,2])
   array.find(col, testOp='gt', arrayOp='any', axis=1)
   ## equivalent to:
   for i in range(array.shape[axis]):
     if (array[:,i] == col.any():
       return i
 }}}

-- 
Ticket URL: <http://projects.scipy.org/numpy/ticket/1673#comment:4>
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