有一些numpy.map吗? [英] Is there some numpy.map?

问题描述

我可能在这里缺少明显的东西，但是我缺少了函数numpy.map.那将与Python的map函数相同，但是会将输出收集在numpy数组中.例如，我可能有一个图像生成器genImage(i)，该图像生成器基于单个输入生成2D图像(大小为(m, n))，并且我想将range(k)输入到生成器函数中并获得一个(k, m, n)数组

I may be missing something obvious here, but I am missing a function numpy.map. What that would be is the same as Python's map function, but collect the output in a numpy array. For example, I could have an image generator genImage(i) that generates a 2D image (of size (m, n)) based on a single input, and I would like to input range(k) to my generator function and obtain a (k, m, n) array.

当前，我会使用numpy.array(list(map(genImage, range(k)))，但是我觉得这种转换成列表的效率很低(我的最终数组大小约为50 GB).因此，我正在寻找与numpy.fromiter类似的numpy.map(genImage, range(k))，但要查找迭代器的多维输出.

Currently, I would use numpy.array(list(map(genImage, range(k))), but I feel that this conversion into a list is rather inefficient (my final array is about 50 GB in size). I am thus looking for numpy.map(genImage, range(k)), which is similar to numpy.fromiter, but for multidimensional outputs of the iterator.

(我尝试过np.array(map(...))，但是它返回带有地图的一个元素数组，因为它是唯一的条目-这就是为什么:为什么需要将地图类型转换为列表以将其分配给熊猫系列?)

(I have tried np.array(map(...)), but that returns a one-element array with the map as it's only entry - here is why: Why is it required to typecast a map into a list to assign it to a pandas series?)

是否有更好的方法来实现我想要的?我正在寻找一种理想的方式，可以与joblib一起使用.

Is there a better way to achieve what I want? I am looking to a way that ideally, I could use with joblib.

推荐答案

如果我答对了，您需要

If I got you right you need column_stack that would work like this:

import numpy as np

a = np.array([[1, 2], [3, 4], [5, 6]])

a = np.column_stack((range(3), a))

a
[[0 1 2]
 [1 3 4]
 [2 5 6]]

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