[Numpy-discussion] numpy.arange() error?
Eric Firing
efiring@hawaii....
Thu Feb 9 13:47:51 CST 2012
On 02/09/2012 09:20 AM, Drew Frank wrote:
> Eric Firing<efiring<at> hawaii.edu> writes:
>
>>
>> On 02/08/2012 09:31 PM, teomat wrote:
>>>
>>> Hi,
>>>
>>> Am I wrong or the numpy.arange() function is not correct 100%?
>>>
>>> Try to do this:
>>>
>>> In [7]: len(np.arange(3.1, 4.9, 0.1))
>>> Out[7]: 18
>>>
>>> In [8]: len(np.arange(8.1, 9.9, 0.1))
>>> Out[8]: 19
>>>
>>> I would expect the same result for each command.
>>
>> Not after more experience with the wonders of floating point!
>> Nice-looking decimal numbers often have long, drawn-out, inexact
>> floating point (base 2) representations. That leads to exactly this
>> sort of problem.
>>
>> numpy.linspace is provided to help get around some of these surprises;
>> or you can use an integer sequence and then scale and shift it.
>>
>> Eric
>>
>>>
>>> All the best
>>>
>>>
>>
> I also found this surprising -- not because I lack experience with floating
> point, but because I do have experience with MATLAB. In MATLAB, the
> corresponding operation 3.1:0.1:4.9 has length 19 because of an explicit
> tolerance parameter used in the implmentation
> (http://www.mathworks.com/support/solutions/en/data/1-4FLI96/index.html?solution=1-4FLI96).
>
> Of course, NumPy is not MATLAB :). That said, I prefer the MATLAB behavior in
> this case -- even though it has a bit of a "magic" feel to it, I find it hard to
> imagine code that operates correctly given the Python semantics and incorrectly
> under MATLAB's. Thoughts?
You raise a good point. Neither arange nor linspace provides a close
equivalent to the nice behavior of the Matlab colon, even though that is
often what one really wants. Adding this, either via an arange kwarg, a
linspace kwarg, or a new function, seems like a good idea.
Eric
>
>
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion@scipy.org
> http://mail.scipy.org/mailman/listinfo/numpy-discussion
More information about the NumPy-Discussion
mailing list