初始化一个 numpy 数组 [英] initialize a numpy array

问题描述

有没有办法初始化一个形状的 numpy 数组并添加到它?我将用一个列表示例来解释我需要什么.如果我想创建一个循环生成的对象列表，我可以这样做:

Is there way to initialize a numpy array of a shape and add to it? I will explain what I need with a list example. If I want to create a list of objects generated in a loop, I can do:

a = []
for i in range(5):
    a.append(i)

我想用 numpy 数组做类似的事情.我知道 vstack、concatenate 等.但是，这些似乎需要两个 numpy 数组作为输入.我需要的是:

I want to do something similar with a numpy array. I know about vstack, concatenate etc. However, it seems these require two numpy arrays as inputs. What I need is:

big_array # Initially empty. This is where I don't know what to specify
for i in range(5):
    array i of shape = (2,4) created.
    add to big_array

big_array 应该有一个形状 (10,4).如何做到这一点?

The big_array should have a shape (10,4). How to do this?

我想添加以下说明.我知道我可以定义 big_array = numpy.zeros((10,4)) 然后填充它.但是，这需要提前指定 big_array 的大小.我知道这种情况下的尺寸，但如果我不知道怎么办?当我们在python中使用.append函数扩展列表时，我们不需要提前知道它的最终大小.我想知道是否存在类似的东西，用于从较小的数组创建一个较大的数组，从一个空数组开始.

I want to add the following clarification. I am aware that I can define big_array = numpy.zeros((10,4)) and then fill it up. However, this requires specifying the size of big_array in advance. I know the size in this case, but what if I do not? When we use the .append function for extending the list in python, we don't need to know its final size in advance. I am wondering if something similar exists for creating a bigger array from smaller arrays, starting with an empty array.

推荐答案

numpy.zeros

返回给定形状的新数组并类型，用零填充.

Return a new array of given shape and type, filled with zeros.

或

numpy.ones

返回给定形状的新数组并类型，填充一个.

Return a new array of given shape and type, filled with ones.

或

numpy.empty

返回给定形状的新数组并类型，无需初始化条目.

Return a new array of given shape and type, without initializing entries.

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然而，通过将元素附加到列表来构造数组的心态在 numpy 中并没有得到太多使用，因为它的效率较低(numpy 数据类型更接近底层的 C 数组).相反，您应该将数组预先分配到您需要的大小，然后填充行.不过，如果必须，您可以使用 numpy.append.

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