On Thu, Aug 29, 2013 at 3:41 PM, Jonathan T. Niehof <jniehof@lanl.gov> wrote:

On 08/29/2013 09:33 AM, Anubhab Baksi wrote:
> Hi,
> I need to know about the relative speed (i.e., which one is faster) of
> the followings:
> 1. list and numpy array, tuples and numpy array
> 2. list of tuples and numpy matrix (first one is rectangular)
> 3. random.randint() and numpy.random.random_integers()

Hi Anubhab, if you have a reasonably large amount of data (say O(100)), always try to use numpy arrays and not lists or tuples - it'll be faster. I'd recommend not to use numpy.matrix, it's speed will be similar to numpy arrays but it has some peculiarities that you'd rather not deal with. For the random numbers I'm not sure without checking, just timing it in ipython with %timeit is indeed the way to go.

Cheers,
Ralf

African or European?

Why on earth would you ask that?

It really depends on what you're doing with it. The ipython %timeit
magic is pretty useful for answering that question. Note that the answer
may change dramatically based on the size of the data set.

--
Jonathan Niehof
ISR-3 Space Data Systems
Los Alamos National Laboratory
MS-D466
Los Alamos, NM 87545

Phone: 505-667-9595
email: jniehof@lanl.gov

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