On Sat, May 17, 2008 at 1:45 PM, Charles R Harris <[EMAIL PROTECTED]> wrote:
> > > On Sat, May 17, 2008 at 1:18 PM, Anne Archibald <[EMAIL PROTECTED]> > wrote: > >> 2008/5/17 Brian Blais <[EMAIL PROTECTED]>: >> >> > at least for me, that was the motivation. I am trying to build a >> simulation >> > framework for part of the brain, which requires connected layers of >> nodes. >> > A layer is either a 1D or 2D structure of nodes, with each node a >> > relatively complex beast. Rather than reinvent the indexing (1D, 2D, >> > slicing, etc...), I just inherited from ndarray. I thought, after the >> fact, >> > that some numpy functions on arrays would help speed up the code, which >> > consists mostly of calling an update function on all nodes, passing each >> > them an input vector. I wasn't sure if there would be any speed up for >> > this, compared to >> > for n in self.flat: >> > n.update(input_vector) >> > From the response, the answer seems to be no, and that I should stick >> with >> > the python loops for clarity. But also, the words of Anne Archibald, >> makes >> > me think that I have made a bad choice by inheriting from ndarray, >> although >> > I am not sure what a convenient alternative would be. >> >> Well, it doesn't exist yet, but a handy tool would be a factory >> function "ArrayOf"; you would pass it a class, and it would produce a >> subclass of ndarray designed to contain that class. > > > Subclasses should generally be avoided unless they satisfy the "is a" > criterion, which I don't think a matrix stack does. That is to say, a > subclass should behave as an ndarray in *all* ways except for added > functionality. All we want is an item type with dimensions. > Base classes also tend to have limited functionality that will be common to all derived types. The object type in Python has only a few methods and attributes: In [4]: dir(object) Out[4]: ['__class__', '__delattr__', '__doc__', '__getattribute__', '__hash__', '__init__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__str__'] And overloading any of these is likely to cause trouble. Chuck
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