On Friday 18 February 2005 06:04 pm, Travis Oliphant wrote:

From the current PEP:

Proposed Solution:

The solution proposed by this PEP is to fix the places in Python that could use rank-0 arrayobjects to allow for them before raising an exception (this will be in the core after-all).

A Python scalar will never be returned unless explicitly requested. I think this is the cleanest, easiest to understand and code for solution. It may require some explicity conversion to int here and there, but it seems like a case of "explicit is better than implicit"

Possible compromises: - a compromise could be made for OBJECT arrays and perhaps LONG arrays if needed.

- a special flag could be defined which is the default when an array of integers is constructed and which when set rank-0 array returns behave differently.

It is also proposed that slicing, indexing and len() do not work (i.e. they raise an error) for rank-0 arrays.

Comments:

I have one: The following script measures the time it takes for in-place array operations, comparing 0-D arrays with scalars. The results are 0.81 0D double 0.85 0D int 0.11 Scalar float 0.12 Scalar int Would Numeric3 address this issue? --- import Numeric as N import time a=N.zeros(100000,'d') one=N.array(1,'d') d=time.clock() for i in N.arange(100000): a[i]+=one d = time.clock()-d print d,'0D double' one=N.array(1) d=time.clock() for i in N.arange(100000): a[i]+=one d = time.clock()-d print d,'0D int' d=time.clock() for i in N.arange(100000): a[i]+=1. d = time.clock()-d print d,'Scalar float' d=time.clock() for i in N.arange(100000): a[i]+=1 d = time.clock()-d print d,'Scalar int' -- Darren