索引错误:索引过多.1 行 2 列的 Numpy 数组 [英] IndexError: too many indices. Numpy Array with 1 row and 2 columns

问题描述

当我尝试像这样只获取数组的第一个元素时

When I try to get just the first element of an array like this

import numpy

a = numpy.array([1,2])

a[:,0]

我收到此错误

---------------------------------------------------------------------------
 IndexError                                Traceback (most recent call last)
<ipython-input-3-ed371621c46c> in <module>()
----> 1 a[:,0]

IndexError: too many indices

我想找到一种方法来做到这一点，同时仍然使用切片，因为完整的代码使用 numpy.loadtxt() 打开并读取许多不同的文件，所有文件都有两列，从 1 到一些不等N.

I would like to find a way to do this while still using slicing because the full code opens and reads many different files using numpy.loadtxt() all having two columns which vary from 1 to some N.

推荐答案

你的数组 a = numpy.array([1,2]) 只有一个维度:它的形状是(2,).但是，您的切片 a[:,0] 指定了 两个 维度的选择.这会导致 NumPy 引发错误.

Your array a = numpy.array([1,2]) only has one dimension: its shape is (2,). However, your slice a[:,0] specifies selections for two dimensions. This causes NumPy to raise the error.

要从 a 中获取第一个元素，您只需编写 a[0](此处仅选择一个维度).

To get the first element from a you only need to write a[0] (a selection for only one dimension is being made here).

查看您的其他问题，如果您想确保语法 a[:,0] 始终有效，您可以确保 a 始终具有两个维度.使用 np.loadtxt 加载数组时，请使用 ndmin 参数，例如:

Looking at your other question, if you want to ensure that the syntax a[:,0] always works, you could ensure that a always has two dimensions. When loading an array with np.loadtxt use the ndmin parameter, e.g.:

np.loadtxt(F, skiprows=0, ndmin=2)

这篇关于索引错误:索引过多.1 行 2 列的 Numpy 数组的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！