Re: [Numpy-discussion] float64 / int comparison different from float / int comparison
On 10/31/11 6:38 PM, Stéfan van der Walt wrote:
On Mon, Oct 31, 2011 at 6:25 PM, Matthew Brettmatthew.br...@gmail.com
wrote:
Oh, dear, I'm suffering now:
In [12]: res 2**31-1
Out[12]: array([False], dtype=bool)
I'm seeing:
...
Your result seems very strange, because the numpy scalars should
perform exactly the same inside and outside an array.
I get what Stéfan gets:
In [32]: res = np.array((2**31,), dtype=np.float32)
In [33]: res 2**31-1
Out[33]: array([ True], dtype=bool)
In [34]: res[0] 2**31-1
Out[34]: True
In [35]: res[0].dtype
Out[35]: dtype('float32')
In [36]: np.__version__
Out[36]: '1.6.1'
(OS-X, Intel, Python2.7)
Something is very odd with your build!
-Chris
--
Christopher Barker, Ph.D.
Oceanographer
Emergency Response Division
NOAA/NOS/ORR(206) 526-6959 voice
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Re: [Numpy-discussion] float64 / int comparison different from float / int comparison
Hi,
On Tue, Nov 1, 2011 at 8:39 AM, Chris.Barker chris.bar...@noaa.gov wrote:
On 10/31/11 6:38 PM, Stéfan van der Walt wrote:
On Mon, Oct 31, 2011 at 6:25 PM, Matthew Brettmatthew.br...@gmail.com
wrote:
Oh, dear, I'm suffering now:
In [12]: res 2**31-1
Out[12]: array([False], dtype=bool)
I'm seeing:
...
Your result seems very strange, because the numpy scalars should
perform exactly the same inside and outside an array.
I get what Stéfan gets:
In [32]: res = np.array((2**31,), dtype=np.float32)
In [33]: res 2**31-1
Out[33]: array([ True], dtype=bool)
In [34]: res[0] 2**31-1
Out[34]: True
In [35]: res[0].dtype
Out[35]: dtype('float32')
In [36]: np.__version__
Out[36]: '1.6.1'
(OS-X, Intel, Python2.7)
Something is very odd with your build!
Well - numpy 1.4.1 on Debian squeeze. I get the same as you with
current numpy trunk.
Stefan and I explored the issue a bit further and concluded that, in
numpy trunk, the current behavior is explicable by upcasting to
float64 during the comparison:
In [86]: np.array(2**63, dtype=np.float) 2**63 - 1
Out[86]: False
In [87]: np.array(2**31, dtype=np.float) 2**31 - 1
Out[87]: True
because 2**31 and 2**31-1 are both exactly representable in float64,
but 2**31-1 is not exactly representable in float32.
Maybe this:
In [88]: np.promote_types('f4', int)
Out[88]: dtype('float64')
tells us this information. The command is not available for numpy 1.4.1.
I suppose it's possible that the upcasting rules were different in
1.4.1 and that is the cause of the different behavior.
Best,
Matthew
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Re: [Numpy-discussion] float64 / int comparison different from float / int comparison
On Mon, Oct 31, 2011 at 11:23 AM, Matthew Brett matthew.br...@gmail.com wrote: In [8]: np.float(2**63) == 2**63 Out[8]: True In [9]: np.float(2**63) 2**63-1 Out[9]: True In [10]: np.float64(2**63) == 2**63 Out[10]: True In [11]: np.float64(2**63) 2**63-1 Out[11]: False In [16]: np.float64(2**63-1) == np.float(2**63-1) Out[16]: True Interesting. Turns out that np.float(x) returns a Python float object. If you change the experiment to only use numpy array scalars, things are more consistent: In [36]: np.array(2**63, dtype=np.float) 2**63 - 1 Out[36]: False In [37]: np.array(2**63, dtype=np.float32) 2**63 - 1 Out[37]: False In [38]: np.array(2**63, dtype=np.float64) 2**63 - 1 Regards Stéfan ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] float64 / int comparison different from float / int comparison
Hi,
2011/10/31 Stéfan van der Walt ste...@sun.ac.za:
On Mon, Oct 31, 2011 at 11:23 AM, Matthew Brett matthew.br...@gmail.com
wrote:
In [8]: np.float(2**63) == 2**63
Out[8]: True
In [9]: np.float(2**63) 2**63-1
Out[9]: True
In [10]: np.float64(2**63) == 2**63
Out[10]: True
In [11]: np.float64(2**63) 2**63-1
Out[11]: False
In [16]: np.float64(2**63-1) == np.float(2**63-1)
Out[16]: True
Interesting. Turns out that np.float(x) returns a Python float
object. If you change the experiment to only use numpy array scalars,
things are more consistent:
In [36]: np.array(2**63, dtype=np.float) 2**63 - 1
Out[36]: False
In [37]: np.array(2**63, dtype=np.float32) 2**63 - 1
Out[37]: False
In [38]: np.array(2**63, dtype=np.float64) 2**63 - 1
Oh, dear, I'm suffering now:
In [11]: res = np.array((2**31,), dtype=np.float32)
In [12]: res 2**31-1
Out[12]: array([False], dtype=bool)
OK - that's what I was expecting from the above, but now:
In [13]: res[0] 2**31-1
Out[13]: True
In [14]: res[0].dtype
Out[14]: dtype('float32')
Sorry, maybe I'm not thinking straight, but I'm confused...
See you,
Matthew
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Re: [Numpy-discussion] float64 / int comparison different from float / int comparison
On Mon, Oct 31, 2011 at 6:25 PM, Matthew Brett matthew.br...@gmail.com wrote:
Oh, dear, I'm suffering now:
In [11]: res = np.array((2**31,), dtype=np.float32)
In [12]: res 2**31-1
Out[12]: array([False], dtype=bool)
OK - that's what I was expecting from the above, but now:
In [13]: res[0] 2**31-1
Out[13]: True
In [14]: res[0].dtype
Out[14]: dtype('float32')
I'm seeing:
In [7]: res = np.array((2**31,), dtype=np.float32)
In [9]: res (2**31-1)
Out[9]: array([ True], dtype=bool)
In [10]: res[0]
Out[10]: 2.1474836e+09
In [11]: res[0] (2**31-1)
Out[11]: True
Your result seems very strange, because the numpy scalars should
perform exactly the same inside and outside an array.
Stéfan
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