如何制作具有不同行大小的多维numpy数组? [英] How to make a multidimension numpy array with a varying row size?

问题描述

我想创建一个二维 numpy 数组，每行具有不同数量的元素.

I would like to create a two dimensional numpy array of arrays that has a different number of elements on each row.

尝试

cells = numpy.array([[0,1,2,3], [2,3,4]])

报错

ValueError: setting an array element with a sequence.

推荐答案

虽然 Numpy 知道任意对象的数组，但它针对具有固定维度的同构数字数组进行了优化.如果您确实需要数组数组，最好使用嵌套列表.但是根据数据的预期用途，不同的数据结构可能会更好，例如如果您有一些无效的数据点，则使用屏蔽数组.

While Numpy knows about arrays of arbitrary objects, it's optimized for homogeneous arrays of numbers with fixed dimensions. If you really need arrays of arrays, better use a nested list. But depending on the intended use of your data, different data structures might be even better, e.g. a masked array if you have some invalid data points.

如果您真的想要灵活的 Numpy 数组，请使用以下内容:

If you really want flexible Numpy arrays, use something like this:

numpy.array([[0,1,2,3], [2,3,4]], dtype=object)

然而，这将创建一个存储对列表的引用的一维数组，这意味着您将失去 Numpy 的大部分优势(向量处理、局部性、切片等).

However this will create a one-dimensional array that stores references to lists, which means that you will lose most of the benefits of Numpy (vector processing, locality, slicing, etc.).

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