[Numpy-discussion] 3 comments on numarray documentation
Perry Greenfield
perry at stsci.edu
Fri Dec 13 08:30:05 EST 2002
Sorry it took so long to respond. We appreciate this feedback.
Edward C. Jones writes:
> To access UInt8, etc,
>
> from numerictypes import *
>
> Maybe mention this in 4.2.1.
>
Are you referring to text in another part of the manual or are you
suggesting that this be added to 4.2.1? If added I would reword it
somewhat since these type names are in the numarray namespace. If
one wants to do:
import numarray
and have the types as part of you namespace it would make sense to
import numarray
from numerictypes import *
(though if we go to a package system, this may become
from numarray.numerictypes import *)
We also need to add the fact that there are now
UInt32, UInt64 (not on windows), Int64 types.
> -------
>
> In 4.7
>
> Only one "..." is expanded in an index expression, so if one has a
> rank-5 array C, then C[...,0,...] is the same thing as
> C[:,:,:,0,:].
>
> So an unexpanded "..." is treated as a ':'?
>
yes
> ----------
>
> In 5.1.1,
>
> >>> a = arange(5, type=Float64)
> >>> print a[::-1] * 1.2
> [ 4.8 3.6 2.4 1.2 0. ]
> >>> multiply(a[::-1], 1.2, a)
> >>> a
> array([ 4.8 , 3.6 , 2.4 , 1.2, 0. ])
>
> doesn't make the desired point. Try:
>
> >>> a = arange(5, type=Int32)
> >>> a
> [0 1 2 3 4]
> >>> print a[::-1] * 1.2
> [ 4.8 3.6 2.4 1.2 0. ]
> >>> multiply(a[::-1], 1.2, a)
> >>> a
> array([4 3 2 1 0])
>
Yes, we will make this change
> Why does Python documentation always use the interpreter? I doubt if it
> is used much. Why not:
>
> a = arange(5, type=Int32)
> print a.type(), a
> b = a[::-1] * 1.2
> print b.type(), b
> numarray.multiply(a[::-1], 1.2, a)
> print a.type(), a
>
Actually many do use it in interpreter mode, at least here. But I think
you miss the main point which is to show the result of each command
for the purposes of instruction. Even if you never plan to use the
interpreter (which I think would be a mistake since it is a wonderful
way of verifying that things work the way you thought they did),
it serves to show examples in a very clear and concise way.
Perry
More information about the NumPy-Discussion
mailing list