[Numpy-discussion] Changed attributes .dtypedescr, .dtypechar, .dtypestr and .dtype

[Travis O. <oli...@ie...>]

There was some cruft left over from the change to making data-type 
descriptors real Python objects.  This left lots of .dtype related 
attributes on the array object --- too many as Francesc Altet graciously 
pointed out.

In the latest SVN, I've cleaned things up (thanks to a nice patch from 
Francesc to get it started).   Basically, there is now only one 
attribute on the array object dealing with the data-type (arr.dtype).  
This attribute returns the data-type descriptor object for the array.  
This object itself has the attributes .char, .str, and .type (among 
others). 

I think this will lead to less confusion long term.  The cruft was due 
to the fact that my understanding of the data-type descriptor came in 
December while seriously looking at records module.

This will have some backward-compatibility issues (we are still pre-1.0 
and early enough that I hope this is not too difficult to deal with).

The compatibility to numpy-0.9.2 issues I can see are:

1) Replacing attributes that are now gone:

   .dtypechar --> .dtype.char
   .dtypestr --> .dtype.str
   .dtypedescr --> .dtype

2) Changing old .dtype -> .dtype.type

    This is only necessary if you were using a.dtype as a *typeobject* 
as in
    issubclass(a.dtype, <some scalar type>)

    If you were using .dtype as a parameter to dtype= then that usage 
will still work
    great (in fact a little faster) because now .dtype returns a 
"descriptor object"

3) The dtypedescr constructor is now called dtype.

This change should have gone into the 0.9.2 release, but things got too 
hectic with all the name changes.   I will quickly release 0.9.4 with 
these changes unless I hear strong disagreements within the next few days.

-Travis


P.S.

SciPy SVN has been updated and fixed with the changes.

Numeric compatibility now implies that .typecode() --> .dtype.char
although if .typecode() was used as an argument to a function, then 
.dtype will very likely work.

-Travis