如何从数组中有效地选择多个切片？ [英] how to efficiently select multiple slices from an array?

问题描述

给定一个数组

d = np.random.randn(100)

和一个索引数组

i = np.random.random_integers(low=3, high=d.size - 5, size=20)

我怎样才能有效地创建一个二维数组 r with

how can I efficiently create a 2d array r with

r.shape = (20, 8)

这样所有 j = 0 .. 19 ，

r[j] = d[i[j]-3:i[j]+5]

在我的情况下，阵列非常大（约200000而不是100和20） ），快速有用。

In my case, the arrays are quite large (~200000 instead of 100 and 20), so something quick would be useful.

推荐答案

您可以创建数据的窗口视图，即（93,8）数组，其中item [i，j] 是item [i + j] 原始数组，如：

You can create a windowed view of your data, i.e. a (93, 8) array, where item [i, j] is item [i+j] of your original array, as:

>>> from numpy.lib.stride_tricks import as_strided
>>> wd = as_strided(d, shape=(len(d)-8+1, 8), strides=d.strides*2)

您现在可以提取所需的切片：

You can now extract your desired slices as:

>>> r = wd[i-3]

请注意 wd 只是原始数据的视图，因此不需要额外的内存。在使用任意索引提取 r 的那一刻，数据将被复制。因此，根据您希望如何使用 r 数组，您可能希望尽可能地延迟它，或者甚至可以完全避免它：您可以随时访问它行 r [j] as wd [j-3] 而不触发副本。

Note that wd is simply a view of your original data, so it takes no extra memory. The moment you extract r with arbitrary indices, the data is copied. So depending on how you want to use your r array, you may want to delay that as much as possible, or maybe even avoid it altogether: you can always access what would be row r[j] as wd[j-3] without triggering a copy.

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