[Numpy-discussion] Characteristic of a Matrix.

Colin J. Williams cjw at ncf.ca
Wed Feb 4 15:07:23 EST 2015


On 08/01/2015 1:19 PM, Ryan Nelson wrote:
> Colin,
>
> I'll second the endorsement of Sage; however, for teaching purposes, I 
> would suggest Sage Math Cloud. It is a free, web-based version of 
> Sage, and it does not require you or the students to install any 
> software (besides a new-ish web browser). It also make 
> sharing/collaborative work quite easy as well. I've used this a bit 
> for demos, and it's great. The author William Stein is good at 
> correcting bugs/issues very quickly.
>
> Sage implements it's own Matrix and Vector classes, and the Vector 
> class has a "column" method that returns a column vector (transpose).
> http://www.sagemath.org/doc/tutorial/tour_linalg.html
>
> For what it's worth, I agree with others about the benefits of 
> avoiding a Matrix class in Numpy. In my experience, it certainly makes 
> things cleaner in larger projects when I always use NDArray and just 
> call the appropriate linear algebra functions (e.g. np.dot, etc) when 
> that is context I need.
>
> Anyway, just my two cents.
>
> Ryan
Ryan,

Thanks.  I agree that Sage Math Cloud seems the better way to go for 
students. However your preference for the dot() world may be because the 
Numpy Matrix Class is inadequately developed.

I'm not suggesting that development, at this time, but proposing that 
the errors I referenced be considered as bugs.

Colin W.
>
> On Wed, Jan 7, 2015 at 2:44 PM, cjw <cjw at ncf.ca <mailto:cjw at ncf.ca>> 
> wrote:
>
>     Thanks Alexander,
>
>     I'll look at Sage.
>
>     Colin W.
>
>
>     On 06-Jan-15 8:38 PM, Alexander Belopolsky wrote:
>>     On Tue, Jan 6, 2015 at 8:20 PM, Nathaniel Smith<njs at pobox.com>  <mailto:njs at pobox.com>  wrote:
>>
>>>>     Since matrices are now part of some high school curricula, I urge that
>>>     they
>>>>     be treated appropriately in Numpy.  Further, I suggest that
>>>     consideration be
>>>>     given to establishing V and VT sub-classes, to cover vectors and
>>>     transposed
>>>>     vectors.
>>>     The numpy devs don't really have the interest or the skills to create
>>>     a great library for pedagogical use in high schools. If you're
>>>     interested in an interface like this, then I'd suggest creating a new
>>>     package focused specifically on that (which might use numpy
>>>     internally). There's really no advantage in glomming this into numpy
>>>     proper.
>>     Sorry for taking this further off-topic, but I recently discovered an
>>     excellent SAGE package,<http://www.sagemath.org/>  <http://www.sagemath.org/>.  While it's targeted
>>     audience includes math graduate students and research mathematicians, parts
>>     of it are accessible to schoolchildren.  SAGE is written in Python and
>>     integrates a number of packages including numpy.
>>
>>     I would highly recommend to anyone interested in using Python for education
>>     to take a look at SAGE.
>>
>>
>>
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