Hi Amir
2008/7/18 Amir <[EMAIL PROTECTED]>:
> A very beginner question about indexing: let x be an array where n =
> len(x). I would like to create a view y of x such that:
>
> y[i] = x[i:i+m,...] for each i and a fixed m << n
>
> so I can do things like numpy.cov(y). With n large, allocating y is a
> problem for me. Currently, I either do for loops in cython or
> translate operations into correlate() but am hoping there is an easier
> way, maybe using fancy indexing or broadcasting. Memory usage is
> secondary to speed, though.
Robert Kern's recently added numpy.lib.stride_tricks should help:
In [84]: x = np.arange(100).reshape(10,-1)
In [85]: x
Out[85]:
array([[ 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]])
In [86]: x.stridesOut[86]: (40, 4)
In [87]: xx = np.lib.stride_tricks.as_strided(x, shape=(8, 3, 10),
strides=(40, 40, 4))
In [88]: xx
Out[88]:
array([[[ 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]],
[[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]],
[[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]],
[...]
Cheers
Stéfan
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