Article <mailman.38.1720846018.2981.python-list@python.org>

Deutsch English Français Italiano
<mailman.38.1720846018.2981.python-list@python.org>

View for Bookmarking (what is this?)
Look up another Usenet article
Path: ...!fu-berlin.de!uni-berlin.de!not-for-mail
From: <avi.e.gross@gmail.com>
Newsgroups: comp.lang.python
Subject: RE: Relatively prime integers in NumPy
Date: Sat, 13 Jul 2024 00:46:55 -0400
Lines: 598
Message-ID: <mailman.38.1720846018.2981.python-list@python.org>
References: <SA0PR09MB6363F3E6B493202E73869DF4DBDA2@SA0PR09MB6363.namprd09.prod.outlook.com>
 <00e801dad3bf$473daed0$d5b90c70$@gmail.com>
 <DM8PR09MB63603191F5509E5013D1BEDCDBA52@DM8PR09MB6360.namprd09.prod.outlook.com>
 <DM8PR09MB636055F61171899BF14B01D3DBA62@DM8PR09MB6360.namprd09.prod.outlook.com>
 <011801dad4b7$44a07100$cde15300$@gmail.com>
 <DM8PR09MB6360AD8A1C512FAC31F32F70DBA72@DM8PR09MB6360.namprd09.prod.outlook.com>
 <01ef01dad4df$aff92ff0$0feb8fd0$@gmail.com>
Mime-Version: 1.0
Content-Type: text/plain;
	charset="UTF-8"
Content-Transfer-Encoding: quoted-printable
Cancel-Lock: sha1:rvhelq++Kq/GiLLePpaK8YhQuJc= sha256:3TFJef1SxKGkmFg20c2Ub/13RD1v6l+zB6FROvMFxvY=
In-Reply-To: <DM8PR09MB6360AD8A1C512FAC31F32F70DBA72@DM8PR09MB6360.namprd09.prod.outlook.com>
Content-Language: en-us
Thread-Index: AQHaqdYQj6Isi+wDzs9EemRqPkPTEQJmM6ydAUtEEooBr5vKQQKMAsT/Aml9nvCxoa0LoA==
Precedence: list
Bytes: 27655

Dmitry,

=20

Efficiency of several kinds is hotly debated and sometimes it depends a =
lot on what is done within loops.

=20

Many suggest a mild speed up of some comprehensions over loops but the =
loops are not gone but somewhat hidden and perhaps some aspects are =
faster for having been written in C carefully and not interpreted.

=20

Comprehensions (and there are other versions that generate dictionaries =
and tuples and sets) may also be sped up a bit for other reasons like =
your fairly expensive APPPEND that has to keep finding the end o f a =
growing list and is not done the same way in a comprehension.

=20

If you do a search, you find many opinions including on using functional =
programming techniques such as map/reduce. There are also=20

=20

Your particular case is interesting because it just makes all =
combination of three variables. Some languages, like R, have functions =
that do this for you, like expand.grd. Python has many modules, like =
itertools that do things including combinations but perhaps not designed =
for your case.=20

=20

Here is a version of your scenario:

=20

import itertools

a =3D range(3)

b =3D range(4)

c =3D range(5)

=20

list(itertools.product(a,b,c))

=20

The result comes as tuples but as you are moving the result into numpy, =
does it matter:

=20

>>> list(itertools.product(a,b,c))

[(0, 0, 0), (0, 0, 1), (0, 0, 2), (0, 0, 3), (0, 0, 4), (0, 1, 0), (0, =
1, 1), (0, 1, 2), (0, 1, 3), (0, 1, 4), (0, 2, 0), (0, 2, 1), (0, 2, 2), =
(0, 2, 3), (0, 2, 4), (0, 3, 0), (0, 3, 1), (0, 3, 2), (0, 3, 3), (0, 3, =
4), (1, 0, 0), (1, 0, 1), (1, 0, 2), (1, 0, 3), (1, 0, 4), (1, 1, 0), =
(1, 1, 1), (1, 1, 2), (1, 1, 3), (1, 1, 4), (1, 2, 0), (1, 2, 1), (1, 2, =
2), (1, 2, 3), (1, 2, 4), (1, 3, 0), (1, 3, 1), (1, 3, 2), (1, 3, 3), =
(1, 3, 4), (2, 0, 0), (2, 0, 1), (2, 0, 2), (2, 0, 3), (2, 0, 4), (2, 1, =
0), (2, 1, 1), (2, 1, 2), (2, 1, 3), (2, 1, 4), (2, 2, 0), (2, 2, 1), =
(2, 2, 2), (2, 2, 3), (2, 2, 4), (2, 3, 0), (2, 3, 1), (2, 3, 2), (2, 3, =
3), (2, 3, 4)]

========== REMAINDER OF ARTICLE TRUNCATED ==========