2008/5/31 Pauli Virtanen <pav <at> iki.fi>:

> The reason for the strange behavior of slice assignment is that when the
> left and right sides in a slice assignment are overlapping views of the
> same array, the result is currently effectively undefined. Same is true
> for ndarrays:
>
>>>> import numpy
>>>> a = numpy.array([1, 2, 3, 4, 5])
>>>> a[::-1]
> array([5, 4, 3, 2, 1])
>>>> a[:] = a[::-1]
>>>> a
> array([5, 4, 3, 4, 5])

I think that the current rule is, slices are walked from low index to
high index. This doesn't help with multidimensional arrays, where the
order of the axes is (and should be) determined by efficiency
considerations.

Unfortunately there's really no good way to warn about overlapping
copies. Remember that this is a frequent operation, so it has to be
fast for small arrays.

I think changing base so that it points to the real base and not the
parent would help (and clear up a memory leak: try "while True: A =
A[::-1]" some time) eliminate some cases where overlap cannot occur,
but what about the following cases?

A[:5] = A[-5:]
A[::2] = A[1::2]
A[1:] = A[-1:]

The last is actually fairly common (I've needed it), and relies on
numpy's ordering of copies. The middle one is very common, and the
first one would be a royal pain to code around if the slices were not
allowed to overlap.

I think I at one point wrote an algorithm that would detect many cases
where overlap could not occur (maybe in the smarter reshape code?) but
I came to the conclusion that detecting all the cases was infeasible.
It's a number-theoretic problem - "can you write the same number as
the sum of multiples of these two lists of numbers with nonnegative
integer coefficients less than these other two lists of numbers?" -
and I suspect it's NP-complete. (Ah, yes, you can make a knapsack out
of it - take an array with strides a_1, ... a_n and shape (2,...,2),
and a single-element array starting at position N.) In any case it's
infeasible to solve it every time somebody tries to do a slice
assignment.

Bala,

One thing I can think of is that you might have multiple versions of
Python installed.  For example, I have Python 2.4 and 2.5 on my
machine, but numpy is only installed for 2.5.   Since just running
"python" brings up 2.4, sometimes I find myself in the wrong
interpreter typing "import numpy", which fails in the way you
described.

Cheers,
Alan

On Sat, May 31, 2008 at 10:52 AM, Bala subramanian
<bala.biophysics <at> gmail.com> wrote:
> Dear friends,
>
> I installed numpy in a 32-bit machines running with RHEL3. The installation
> was successful. I tested the installtion by importint numpy inside python
> interpreter.
> By once i shutdown the system and restart, and try the same, it says
> ImportError: No module named numpy.
>
> What could be the problem i dnt get. Kindly someone write me on the same.
>
> Thanks,
> Bala
>
>

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