How to find maximal entry in a Numpy array?

[alex]

Hi.  Is there a fast way to find the location of a maximal entry in a
Numeric array?  I realize I could do something along the lines of
flattening it, finding the maximum value, and then searching for that
value, but that means going over the array twice.  I could also use
argmax to find the position of the largest value in each column, make a
new array with dimension one less containing those maximal values, and
repeat, but I can't see how to make that new array without doing a
slow-looking python loop.  

The best I've been able to come up with is to search in a python loop
over the entries specified by argmax.  Is there a way to push more of
this down into C loops?  And can someone please show me something better
than this horrendous "else: break" trick for iterating over the tuples
with entries less than some specific tuple?

import copy, Numeric

def find_max (array):
    maximal_indices = argmax (array)
    ashape = maximal_indices.shape
    index = len (ashape) * [0]
    maximal_value = 0
    while 1:
        if array [index + [maximal_indices [index]]] > \
           maximal_value:
            maximal_value = array [ \
                index + [maximal_indices [index]]]
            maximal_index = copy.copy (index)
        for i in range (len (index)):
            index [i] = index [i] + 1
            if index [i] < ashape [i]: break
            index [i] = 0
        else: break
    return maximal_index + [maximal_indices [index]]

In the end, I'm probably not going to be happy with just the maximal
value, either.  If there's a fast way to get all the indices, sorted by
their values, that would be even better.

No-harm-in-asking'ly Alex.