On Wed, Mar 10, 2010 at 18:19, Neal Becker <ndbecker2@gmail.com> wrote:

This is a bit confusing to me:

import numpy as np

u = np.ones ((3,3))

for u_row in u:    u_row = u_row * 2  << doesn't work

print u [[ 1.  1.  1.]  [ 1.  1.  1.]  [ 1.  1.  1.]]

for u_row in u:    u_row *= 2  << does work [[ 2.  2.  2.]  [ 2.  2.  2.]  [ 2.  2.  2.]]

Naively, I'm thinking a *= b === a = a * b.

http://docs.python.org/reference/simple_stmts.html#augmented-assignment-stat... """An augmented assignment expression like x += 1 can be rewritten as x = x + 1 to achieve a similar, but not exactly equal effect. In the augmented version, x is only evaluated once. Also, when possible, the actual operation is performed in-place, meaning that rather than creating a new object and assigning that to the target, the old object is modified instead."""

Is this behavior expected?  I'm asking because I really want:

u_row = my_func (u_row)

Iterate over indices instead: for i in range(len(u)): u[i] = my_func(u[i]) -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco