When is min(a, b) != min(b, a)?

[Albert Hopkins]

This issue may have been referred to in
news:<ma******* *************** *************** **@python.orgbu t I didn't
entirely understand the explanation. Basically I have this:

>>a = float(6)
b = float('nan')
min(a, b)

6.0

>>min(b, a)

nan

>>max(a, b)

6.0

>>max(b, a)

nan

Before I did not know what to expect, but I certainly didn't expect
this. So my question is what is the min/max of a number and NaN or is it
not defined (for which I would have expected either an exception to be
raised or NaN returned in each case).

As a corrollary would I be able to rely on the above behavior or is it
subject to change (to fix a bug in min/max perhaps :-)?

[Bonjour]

'NaN' means "Not a number". according to Python semantics, if you try
to compare it with any other float numbers, it should return FALSE.
just like

>>>
1.0 'abc'

False

>>>

Since it always return FALSE, it is not a surprise for your question.

If you wish to get infinitive number, you'd use 'inf' or '-inf', from
IEEE 754 semantics:

>>>a=float(6)
b=float('inf ')
c=float('-inf')

Albert Hopkins wrote:

This issue may have been referred to in
news:<ma******* *************** *************** **@python.orgbu t I didn't
entirely understand the explanation. Basically I have this:

>>a = float(6)
>>b = float('nan')
>>min(a, b)

6.0

>>min(b, a)

nan

>>max(a, b)

6.0

>>max(b, a)

nan

Before I did not know what to expect, but I certainly didn't expect
this. So my question is what is the min/max of a number and NaN or is it
not defined (for which I would have expected either an exception to be
raised or NaN returned in each case).

As a corrollary would I be able to rely on the above behavior or is it
subject to change (to fix a bug in min/max perhaps :-)?

[Bonjour]

'NaN' means "Not a number". according to Python semantics, if you try
to compare it with any other float numbers, it should return FALSE.
just like:

>>>1.0 'abc'

False

Since it always return FALSE, it is not a surprise for your question.

If you wish to get infinitive number, you'd use 'inf' for positive
infinitive or '-inf' for negative infinitive, from
IEEE 754 semantics, just like:

>>>a=float(6)
b=float('inf ')
c=float('-inf')

For more information, PEP-0754 may be helpful.

[Paddy]

On Jan 21, 3:15 am, Albert Hopkins <mar...@python. invalidwrote:

This issue may have been referred to in
<news:ma******* *************** *************** **@python.orgbu t I didn't
entirely understand the explanation. Basically I have this:

>>a = float(6)
>>b = float('nan')
>>min(a, b)

6.0

>>min(b, a)

nan

>>max(a, b)

6.0

>>max(b, a)

nan

Before I did not know what to expect, but I certainly didn't expect
this. So my question is what is the min/max of a number and NaN or is it
not defined (for which I would have expected either an exception to be
raised or NaN returned in each case).

As a corrollary would I be able to rely on the above behavior or is it
subject to change (to fix a bug in min/max perhaps :-)?

I am definitely NOT a floating point expert, but I did find this:
http://en.wikipedia.org/wiki/IEEE_754r#min_and_max

P.S. What platform /Compiler are you using for Python?

- Paddy.

[Albert Hopkins]

On Sun, 20 Jan 2008 20:16:18 -0800, Paddy wrote:

I am definitely NOT a floating point expert, but I did find this:
http://en.wikipedia.org/wiki/IEEE_754r#min_and_max

P.S. What platform /Compiler are you using for Python?

Linux with GCC 4

-a

[Jason]

On Jan 21, 12:00 am, Albert Hopkins <mar...@python. invalidwrote:

On Sun, 20 Jan 2008 20:16:18 -0800, Paddy wrote:

I am definitely NOT a floating point expert, but I did find this:
http://en.wikipedia.org/wiki/IEEE_754r#min_and_max

P.S. What platform /Compiler are you using for Python?

Linux with GCC 4

-a

Please note that NaN's are very funky and platform dependent. They
depend on their underlying platform's C library for creation and
display. On windows, "float('nan ')" will cause an exception, as there
are no valid string representations of NAN that can be converted to
the special floating point value. Also, if you manage to create a nan
under Windows, it displays as "1.#QNAN".

Infinite values are also problematic. In almost all cases, it is far
better to avoid infinite and NaN values.

--Jason

[Mark Dickinson]

On Jan 21, 9:55*am, Jason <tenax.racc...@ gmail.comwrote:

display. *On windows, "float('nan ')" will cause an exception, as there
are no valid string representations of NAN that can be converted to
the special floating point value. *Also, if you manage to create a nan
under Windows, it displays as "1.#QNAN".

I believe this will be fixed in Python 2.6 :)

Mark

[Grant Edwards]

On 2008-01-21, Jason <te***********@ gmail.comwrote:

Infinite values are also problematic. In almost all cases, it is far
better to avoid infinite and NaN values.

In many applications (e.g. process control) propogating NaN
values are way too useful to avoid. Avoiding NaN would make a
lot of code far more complicated than would using them.

--
Grant Edwards grante Yow! How's the wife?
at Is she at home enjoying
visi.com capitalism?

[Christian Heimes]

Jason wrote:

Please note that NaN's are very funky and platform dependent. They
depend on their underlying platform's C library for creation and
display. On windows, "float('nan ')" will cause an exception, as there
are no valid string representations of NAN that can be converted to
the special floating point value. Also, if you manage to create a nan
under Windows, it displays as "1.#QNAN".

Infinite values are also problematic. In almost all cases, it is far
better to avoid infinite and NaN values.

CC to Python Dev

I've fixed that and enhanced the support for NaN and inf for 2.6 and
3.0. I'm working together with Mark on more NaN and inf related fixes
and he has fixed some numerical issues in the cmath module. We both hope
to get Python's math more sound and stable across platforms.

So far I got float('nan'), float('inf') and float('-inf') working on all
platforms. The math module got three new methods: isinf, isnan, copysign.

Additionally the trunk-math branch contains code for inverse hyberbolic
functions (acosh), log1p, Mark's fixes for complex math and more stuff.
For example operations on NaNs now return a NaN on all platforms (except
1**NAN which is defined as 1 and 0**NAN which is defined as 0). In 2.5
it depends on the platform whether a function raises an exception or
returns NaN.

Mark had the nice idea to introduce a thread local or global flag for
NaN support. Depending on a flag Python turns a NaN into an exception.
The feature needs a proper PEP. Maybe Mark has time to write a PEP in time.

Christian

[Christian Heimes]

Grant Edwards wrote:

In many applications (e.g. process control) propogating NaN
values are way too useful to avoid. Avoiding NaN would make a
lot of code far more complicated than would using them.

NaNs are very useful for experienced power users but they are very
confusing for newbies or developers without a numerical background.

It's very easy to create an inf or nan in Python:

inf = 1E+5000
ninf = -inf
nan = inf * 0.

1E5000 creates a nan because it is *much* bigger than DBL_MAX (around
1E+308). In fact it is even larger than LDBL_MAX (around 1E+4932).

Christian