[解決済み】cアンダースコア式`c_`は、具体的に何をするのですか？

質問

水平連結のようなものらしいのですが、ネットで調べてもドキュメントが見つかりませんでした。ここに最小限の動作例があります。

In [1]: from numpy import c_
In [2]: a = ones(4)
In [3]: b = zeros((4,10))    
In [4]: c_[a,b]
Out[4]: 
array([[ 1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.],
       [ 1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.],
       [ 1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.],
       [ 1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.]])

解決方法は？

IPythonの ? 構文を使用すると、より多くの情報を得ることができます。

In [2]: c_?
Type:       CClass
Base Class: <class 'numpy.lib.index_tricks.CClass'>
String Form:<numpy.lib.index_tricks.CClass object at 0x9a848cc>
Namespace:  Interactive
Length:     0
File:       /usr/lib/python2.7/dist-packages/numpy/lib/index_tricks.py
Docstring:
Translates slice objects to concatenation along the second axis.

This is short-hand for ``np.r_['-1,2,0', index expression]``, which is
useful because of its common occurrence. In particular, arrays will be
stacked along their last axis after being upgraded to at least 2-D with
1's post-pended to the shape (column vectors made out of 1-D arrays).

For detailed documentation, see `r_`.

Examples
--------
>>> np.c_[np.array([[1,2,3]]), 0, 0, np.array([[4,5,6]])]
array([[1, 2, 3, 0, 0, 4, 5, 6]])