Strange output from arange()
Robert Kern
robert.kern at gmail.com
Mon Jul 25 15:45:00 EDT 2011
On 7/25/11 2:20 PM, Christopher Barrington-Leigh wrote:
> The following code:
>
> from pylab import arange
> nSegments=5.0
> print arange(0,1.0+1.0/nSegments,1.0/nSegments)
> nSegments=6.0
> print arange(0,1.0+1.0/nSegments,1.0/nSegments)
> nSegments=8.0
> print arange(0,1.0+1.0/nSegments,1.0/nSegments)
> nSegments=10.0
> print arange(0,1.0+1.0/nSegments,1.0/nSegments)
>
> gives an output of:
>
> [ 0. 0.2 0.4 0.6 0.8 1. ]
> [ 0. 0.16666667 0.33333333 0.5 0.66666667
> 0.83333333 1. 1.16666667]
> [ 0. 0.125 0.25 0.375 0.5 0.625 0.75 0.875 1. ]
> [ 0. 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1. ]
>
> These arrays have lengths, 6, 8, 9, and 11, in stead of 6, 7, 9, and
> 11.
> What is going on for the case of n=6?
Floating point computations are not always accurate, and when one tries to
compute "the same thing" two different ways, one may get inconsistent results.
This is what is happening with n=6. 1+1./6 happens to be slightly greater than
7*(1./6) while 1+1./5 happens to be slightly less than 6*(1./5), etc. The trick
of using 1.0+1.0/nSegments/2 tends to work better.
Nonetheless, if you want to get exactly nSegments segments with exact endpoints,
you should use numpy.linspace(0.0, 1.0, nSegments+1). That's a much better API
for what you want.
Also, you will want to ask numpy questions on the numpy-discussion mailing list,
not here.
http://www.scipy.org/Mailing_Lists
--
Robert Kern
"I have come to believe that the whole world is an enigma, a harmless enigma
that is made terrible by our own mad attempt to interpret it as though it had
an underlying truth."
-- Umberto Eco
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