Hello Andrew,
Hello all,
like Andrew, I had some strange experience with mgrid. Adrew writes:
Am Dienstag, den 27.02.2007, 19:43 -0600 schrieb Andrew Corrigan:
> I'm confused about the following:
>
> >>> print mgrid[2.45:2.6:0.05, 0:5:1]
> [[[ 2.45 2.45 2.45 2.45 2.45]
> [ 2.5 2.5 2.5 2.5 2.5 ]]
>
> [[ 0. 1. 2. 3. 4. ]
> [ 0. 1. 2. 3. 4. ]]]
> >>> print mgrid[2.45:2.6:0.05]
> [ 2.45 2.5 2.55]
>
> In the first case in the first dimension I get 2.45, 2.5. In the
> second case in the first dimension I get 2.45, 2.5, 2.55 In both
> cases
> I'm using 2.45:2.6:0.05 to specify the grid in the first dimension.
I think this is because for the one-dimensional case numpy.nd_grid
relies on numpy.arange. This is basically a good idea, but the
more-dimensional case behaves different, like Andrew states.
My problem is the following:
>>>mgrid[0.1:0.2:1, 0.2:0.3:1]
gives
array([], shape=(2, 0, 0), dtype=float64)
What I wanted to create was:
array([[[ 0.1]],
[[ 0.2]]])
which I finally got with
>>>mgrid[0.1:1.2:1, 0.2:1.3:1]
Since this behaviour is different from arange, I think it is not very
intentional. But maybe there is a good reason for this behaviour?
I am using numpy, version 1.0.1. Maybe the behaviour was already changed
in more recent versions?
Thank you for any comment
Lars Friedrich
--
Dipl.-Ing. Lars Friedrich
Optical Measurement Technology
Department of Microsystems Engineering -- IMTEK
University of Freiburg
Georges-Köhler-Allee 102
D-79110 Freiburg
Germany
phone: +49-761-203-7531
fax: +49-761-203-7537
room: 01 088
email: [EMAIL PROTECTED]
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