On Wed, Apr 27, 2011 at 9:25 PM, Robert Kern <robert.k...@gmail.com> wrote:
> On 2011-04-27 23:01 , Guido van Rossum wrote:
>> And I wouldn't want to change that. It sounds like NumPy wouldn't be
>> much affected if we were to change this (which I'm not saying we
>> would).
>
> Well, I didn't say that. If Python changed its behavior for (float('nan') ==
> float('nan')), we'd have to seriously consider some changes.
Ah, but I'm not proposing anything of the sort! float('nan') returns a
new object each time and two NaNs that are not the same *object* will
still follow the IEEE std. It's just when comparing a NaN-valued
*object* to *itself* (i.e. the *same* object) that I would consider
following the lead of Python's collections.
> We do like to
> keep *some* amount of correspondence with Python semantics. In particular,
> we like our scalar types that match Python types to work as close to the
> Python type as possible. We have the np.float64 type, which represents a C
> double scalar and corresponds to a Python float. It is used when a single
> item is indexed out of a float64 array. We even subclass from the Python
> float type to help working with libraries that may not know about numpy:
>
> [~]
> |5> import numpy as np
>
> [~]
> |6> nan = np.array([1.0, 2.0, float('nan')])[2]
>
> [~]
> |7> nan == nan
> False
Yeah, this is where things might change, because it is the same
*object* left and right.
> [~]
> |8> type(nan)
> numpy.float64
>
> [~]
> |9> type(nan).mro()
> [numpy.float64,
> numpy.floating,
> numpy.inexact,
> numpy.number,
> numpy.generic,
> float,
> object]
>
>
> If the Python float type changes behavior, we'd have to consider whether to
> keep that for np.float64 or change it to match the usual C semantics used
> elsewhere. So there *would* be a dilemma. Not necessarily the most
> nerve-wracking one, but a dilemma nonetheless.
Given what I just said, would it still be a dilemma? Maybe a smaller one?
--
--Guido van Rossum (python.org/~guido)
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