用 2 个索引列表索引一个 2D Numpy 数组

我遇到了一个奇怪的情况.

I've got a strange situation.

我有一个 2D Numpy 数组，x:

I have a 2D Numpy array, x:

x = np.random.random_integers(0,5,(20,8))

我有 2 个索引器——一个带有行索引，一个带有列索引.为了索引 X，我必须执行以下操作:

And I have 2 indexers--one with indices for the rows, and one with indices for the column. In order to index X, I am having to do the following:

row_indices = [4,2,18,16,7,19,4]
col_indices = [1,2]
x_rows = x[row_indices,:]
x_indexed = x_rows[:,column_indices]

而不仅仅是:

x_new = x[row_indices,column_indices]

(失败:错误，不能用(2，)广播(20，))

(which fails with: error, cannot broadcast (20,) with (2,))

我希望能够使用广播在一行中进行索引，因为这样可以保持代码的清洁和可读性……此外，我对底层的 python 了解不多，但是据我了解，在一行中完成它应该更快(我将使用相当大的数组).

I'd like to be able to do the indexing in one line using the broadcasting, since that would keep the code clean and readable...also, I don't know all that much about python under the hood, but as I understand it, it should be faster to do it in one line (and I'll be working with pretty big arrays).

测试用例:

x = np.random.random_integers(0,5,(20,8))

row_indices = [4,2,18,16,7,19,4]
col_indices = [1,2]
x_rows = x[row_indices,:]
x_indexed = x_rows[:,col_indices]

x_doesnt_work = x[row_indices,col_indices]