[Numpy-discussion] basearray & dimarray : you have dead URL; + some questions

dmitrey openopt@ukr....
Mon Mar 19 07:57:42 CDT 2007


Hallo!
Excuse my bad English.

In the web page
http://www.scipy.org/BaseArray/Application
in the section


      Project details and tentative schedule

you refer to the dead link with name
http://numeric.scipy.org/array_interface.html
which leads to
http://numpy.scipy.org//array_interface.html
which is dead (with singular '/' before array_interface.html - too)
I'm using Mozilla browser if it's important.

Now I'm writing some code and want to know, what will dotwise and matrix 
operations look like?
Is there any discussion where these and related questions are concerned?
So, will they be MATLAB/Octave/omatrix/SciLab/etc look-like:
dot is present => dotwise operation
dot is absend => matrix operation
or you'll continue numpy array operations, which seems to be very 
unclear for newbies?
As for me I'm sure that in long-term period 1st approach is much more 
better, because  users will not have to  dig in  numpy documentation for 
to chose appropriate operator, and translating code from those languages 
will be much more easier. Of course, many people can say that 2nd way 
simplifies translating code from already-written py-files, but it will 
be done only once, while migrating MATLAB, Octave, etc users will 
continue for years or dozens of years or even more.
Maybe you'll organize a voting or separate discussion thread or 
something else to gather users opinions?
And 2nd question is - is it so important to have own class? Maybe 
something from c/c++ boost (www.boost.org), or collaboration with Octave 
developers will be more fast & require less workers and money? And it 
will be possible to fork any time when something will be going wrong. As 
far as I understood from my discussions in octave mailing lists with 
David Bateman, they still have many problems with for example sparse 
matrices. Even Mathworks still have some troubles, and sparse witn 
dimension > 2 isn't implemented at all. So collaborating could be much 
more productive.
And, if you still want to create 100% your own code, what are tasks for 
students participating in GSoC? I want to estimate the complexity of 
jobs (am I able to finish them successfully till the deadlines or no for 
any reasons).

Thank you in advance for your answer, Dmitrey.





More information about the Numpy-discussion mailing list