[Edu-sig] design pattern with data

[kirby urner]

In the source code below, almost all that's special about subclasses is
their
respective data, which are initialized from globals.

Both the constructor and self representer (a VPython draw, not a __repr__
in this case) are inherited from a Tetrahedron superclass.

http://www.4dsolutions.net/ocn/python/quantamods.py

How might this be useful in a math learning context?

There's a quickie conversion going on, twixt two coordinate systems, with
one vector's .xyz attribute an argument to the next vector's initializer.

That'd be one thing to focus on (object translation).

Caveats:

I'm using arguments provided by a collaborator.  Although I've got a lot
of faith in 'em, I'm just taking 'em as given (assumed true).  The output
is visual (VPython) and to my eye the results were quite believable.

However, in pure Chakovians, with (1,0,0,0)(0,1,0,0)(0,0,1,0) and (0,0,0,1)
as my four vertices, I'd be sorely tempted to anchor my A modules (+/-)
as at least two of those 24.

On the other hand, I'm also quite focused on the Coupler as 8 MITEs
meeting at the origin (0,0,0,0) with As and Bs permuting accordingly
(lots of ways to go).

Sorry about all the jargon, for those not trained in slogging through this
namespace.  I call it "gnu math" and teach it with Python.

Kirby
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