numpy slice: create view, not copy

[K. Jansma]

Hi,

given an array:

import numpy
a = numpy.arange(100).reshape((10,10))
print a

[[ 0  1  2  3  4  5  6  7  8  9]
 [10 11 12 13 14 15 16 17 18 19]
 [20 21 22 23 24 25 26 27 28 29]
 [30 31 32 33 34 35 36 37 38 39]
 [40 41 42 43 44 45 46 47 48 49]
 [50 51 52 53 54 55 56 57 58 59]
 [60 61 62 63 64 65 66 67 68 69]
 [70 71 72 73 74 75 76 77 78 79]
 [80 81 82 83 84 85 86 87 88 89]
 [90 91 92 93 94 95 96 97 98 99]]


I'd like to create a new array that is a view of a, i.e. it shares data. If
a is updated, this new array should be automatically 'updated'.

e.g. the array west should be a view of a that gives the element at the left
of location i,j in a.
a[i,j] = west[i,j+1]

west can be created using:

a[:,range(-1,a.shape[1]-1)]

As you can see, this also defines periodic boundaries (i.e. west[0,0] = 9)
but it seems that this returns a copy of a, not a view.
How can I change the slice definition in such a way it returns a view?

Thanks in advance,
Karel




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share function argument between subsequent calls but not between class instances!

[K. Jansma]

Hi,

given the following example class

class Test:
def f(self,a, L=[]):
L.append(a)
return L

and the following statements

a = Test()
a.f(0)
a.f(0)
a.f(0)
b = Test()
b.f(0)

this is the output I would like to have (i.e., expect)

>>> a = Test()
>>> a.f(0)
[0]
>>> a.f(0)
[0, 0]
>>> a.f(0)
[0, 0, 0]
>>> b = Test()
>>> b.f(0)
[0]

But this is what I get:

>>> a = Test()
>>> a.f(0)
[0]
>>> a.f(0)
[0, 0]
>>> a.f(0)
[0, 0, 0]
>>> b = Test()
>>> b.f(0)
[0, 0, 0, 0]


as you can see, the b.f method shares L with a.f.
How can I avoid this without using eg. self.L in an __init__?

Thanks in advance,
Karel.

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