如何将(mxn)尺寸的Numpy数组展开为单个向量 [英] How do you unroll a Numpy array of (mxn) dimentions into a single vector

问题描述

我只想知道将numpy数组展开为单个向量是否存在捷径.例如(将以下Matlab代码转换为python):

I just want to know if there is a short cut to unrolling numpy arrays into a single vector. For instance (convert the following Matlab code to python):

Matlab方式: A =零(10,10)％
A_unroll = A(:)％<-如何在python中做到这一点

Matlab way: A = zeros(10,10) %
A_unroll = A(:) % <- How can I do this in python

谢谢.

推荐答案

这是您要记住的吗?

正如Patrick指出的那样，在将A(:)转换为Python时必须要小心.

As Patrick points out, one has to be careful with translating A(:) to Python.

当然，如果您只想展平零的矩阵或二维数组，那就没关系了.

Of course if you just want to flatten out a matrix or 2-D array of zeros it does not matter.

因此，这是一种获得类似matlab行为的方法.

So here is a way to get behavior like matlab's.

>>> a = np.array([[1,2,3], [4,5,6]])
>>> a
array([[1, 2, 3],
       [4, 5, 6]])
>>> # one way to get Matlab behaivor
... (a.T).ravel()
array([1, 4, 2, 5, 3, 6])

numpy.ravel可以展平2D数组，但是不能像matlab的(:)一样进行.

numpy.ravel does flatten 2D array, but does not do it the same way matlab's (:) does.

>>> import numpy as np
>>> a = np.array([[1,2,3], [4,5,6]])
>>> a
array([[1, 2, 3],
       [4, 5, 6]])
>>> a.ravel()
array([1, 2, 3, 4, 5, 6])

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