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On 4/27/2011 2:15 PM, Mark Dickinson wrote:
<blockquote
cite="mid:BANLkTi=Podj_ntfprqrA=apm8kBcbmVZkw@mail.gmail.com"
type="cite">
<pre wrap="">On Wed, Apr 27, 2011 at 7:41 PM, Glenn Linderman <a class="moz-txt-link-rfc2396E" href="mailto:v+python@g.nevcal.com"><v+python@g.nevcal.com></a> wrote:
</pre>
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<pre wrap="">One issue that I don't fully understand: I know there is only one instance
of None in Python, but I'm not sure where to discover whether there is only
a single, or whether there can be multiple, instances of NaN or Inf. Â The
IEEE 754 spec is clear that there are multiple bit sequences that can be
used to represent these, so I would hope that there can be, in fact, more
than one value containing NaN (and Inf).
This would properly imply that a collection should correctly handle the case
of storing multiple, different items using different NaN (and Inf)
instances. Â A dict, for example, should be able to hold hundreds of items
with the index value of NaN.
The distinction between "is" and "==" would permit proper operation, and I
believe that Python's "rebinding" of names to values rather than the copying
of values to variables makes such a distinction possible to use in a correct
manner.
</pre>
</blockquote>
<pre wrap="">
For infinities, there's no issue: there are exactly two distinct
infinities (+inf and -inf), and they don't have any special properties
that affect membership tests. Your float-keyed dict can contain both
+inf and -inf keys, or just one, or neither, in exactly the same way
that it can contain both +5.0 and -5.0 as keys, or just one, or
neither.
For nans, you *can* put multiple nans into a dictionary as separate
keys, but under the current rules the test for 'sameness' of two nan
keys becomes a test of object identity, not of bitwise equality.
Python takes no notice of the sign bits and 'payload' bits of a float
nan, except in operations like struct.pack and struct.unpack. For
example:
</pre>
</blockquote>
Thanks, Mark, for the succinct description and demonstration. Yes,
only two Inf values, many possible NaNs. And this is what I would
expect.<br>
<br>
I would not, however expect the original case that was described:<br>
>>> nan = float('nan')
<br>
>>> nan == nan
<br>
False
<br>
>>> [nan] == [nan]
<br>
True                 # also True in tuples, dicts, etc.
<br>
<br>
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